Vertical Handoff Mechanism: Recent Challenges & Applications
Authors:-Research Scholar Ravneet Kaur, HOD. Ravi Malik
Abstract- The evolution of the next-generation wireless network has led to the increasing demand for handheld devices to enjoy mobility through “Always Best Connected” services. In the next-generation wireless network, seamless best-possible access to a network, which has a widely varying set of network characteristics, requires rigorous mobility management. The vertical handover facilitates users to roam across different networks with the seamless network connection. The vertical handover process that supports mobility can be initiated as mobile controlled handoff or as a network controlled handoff process. Associating the user with a suitable wireless network using a vertical handover process through wide network integration is a challenging and difficult problem that has drawn the attention of many researchers.
Design & Development of Electricity Generation by using Wave Energy
Authors:-Shriram Malwe, Shivam Shahu, Anaya Bansod, Amit Bele, Aniket Singh, Vaishnav Shende, Tushar Dhakhare, Bhavesh Sewatkar
Abstract- Waves are a huge, largely untapped energy recourse, and the potential for extracting energy from waves is considerable. Research in this area is driven by the need to meet renewable energy targets, but is relatively immature compared to other renewable energy technologies. This review introduces the general status of wave energy and evaluates the device type that represents current wave energy convertor (WEC) technologies. Here, our research paper focusing to eliminates the existing limitations of wave energy converter methods, and also helps the potential of this method for generating electricity and this could be common way to producing electricity in future.
IOT Based Seed Planting and Watering Rover
Authors:-G Nagarjuna Reddy, G Maheedhar Reddy, G Balaji, CH Muni Harish, CH Kethan
Abstract- Exploring Mars and other planets aids scientists in their understanding of severe climate swings that have potential to drastically affect the planets. Humans devised a strategy for colonizing Mars. As a result, before humans set foot on Mars, it’s a good idea to grow some plants on Mars and monitor them. This Automated Rover takes on the role of a human by planting and watering the plants on its own. This paper is focused on automated seed planting and monitoring using Internet of Things (IoT). Rover is a movable device that is powered by ESP8266 Node MCU controlled DC motors. Rover is equipped with a DHT11 sensor and a Wi-Fi module that continuously monitors and uploads data to Thingspeak. This rover is equipped with a plough that can be adjusted, a seed dropper, and automated water pouring equipment. An Arduino Nano can be used to control all of the actions. It estimates the distance between each seed after dropping the seed, so that it can water the seeds automatically after 12 or 24 hours. Depending on availability, the rover uses both DC battery and solar energy to power the entire setup. All the rover’s actions are fully automated, and no human intervention is required.
Air-Borne Disease Prevention System
Authors:- Ms. Sai Saru Nossam, Ms. Sandhya Nethibottu, Mr. Shaik Imran, Ms. Aparna Somala, Asst. Prof. Mr. Iliyaz Pasha M
Abstract- Mining continues to be a dangerous activity, whether large-scale industrial mining or small-scale artisanal mining. Not only exposure to dust and toxins, there are accidents along with stress from the working environment or managerial pressures, give rise to a range of diseases that affect miners. I look at mining and health from various personal perspectives and the risk of transmission is high. One of the best ways is to stay safe from getting infected is by wearing a face mask. In this project, we propose a method to detect human face masks by continuously monitoring the mining environment using TensorFlow and OpenCV. A bounding box drawn on a person’s face stored in a database, you can take precautions by determining the name of a person who is not wearing a mask and sending an email warning that person is not wearing a mask.Also this proposed system can also be used in Sand blasting and public areas where there is strict demand of face mask in situations like covid-19.
Authentication System for Global Roaming on Unlimited Resources in Mobility Networks
Authors:- Asst. Prof. Mohanapriya D, Sujith Kumar M, Kapilesh B, Rhakul P G
Abstract- With the improvement of the Internet, cyber-assaults are converting hastily and the cyber protection state of affairs isn’t always optimistic. Machine Learning (ML) and Deep Learning (DL) techniques for community evaluation of intrusion detection and presents a quick educational description of every ML/DL approach. Papers representing every approach had been indexed, read, and summarized primarily based totally on their temporal or thermal correlations. Because information is so essential in ML/DL techniques, they describe a number of the typically used community datasets utilized in ML/DL, talk about the demanding situations of the use of ML/DL for cyber protection and offer guidelines for studies directions. The KDD information set is a widely recognized benchmark in the studies of Intrusion Detection techniques. A lot of labor goes on for the development of intrusion detection techniques even as the studies at the information used for schooling and checking out the detection version is similarly of top problem due to the fact higher information nice can enhance offline intrusion detection. This assignment provides the evaluation of the KDD information set with recognition of 4 lessons that are Basic, Content, Traffic and Host wherein all information attributes may be categorized by the use of MODIFIED RANDOM FOREST(MRF). The evaluation is finished with recognizing of 2 outstanding assessment metrics, Detection Rate (DR) and False Alarm Rate (FAR) for an Intrusion Detection System (IDS). As a result of this empirical evaluation of the information set, the contribution of every of 4 lessons of attributes on DR and FAR is proven that may assist beautify the suitability of the information set to obtain most DR with minimal FAR.
Prediction on Patient Treatment Time Scheduling Based on Machine Learning Approach
Authors:- Asst. Prof. Javed Ahamed B M S, Saravanan M, Srikanth A, Thamizhselvam S, Vijayaravind S
Abstract- Clinical decision-production in medical care is now being impacted by expectations or proposals made by information driven machines. Various AI applications have showed up in the most recent clinical writing, particularly for result forecast models, with results going from mortality and heart failure to intense. In this undertaking, we sum up the best in class in related works covering information handling, derivation, and model assessment, with regards to result expectation models created utilizing information removed from electronic wellbeing records. We likewise examine impediments of conspicuous demonstrating suspicions and feature valuable open doors for future examination.
Post-Operative Rotator Cuff Repair using IoT
Authors:- Asst. Prof. Padmanaban K, Grisey E, Janitha J, Leena B, Manju A
Abstract- This paper shows the design of a low-cost upper limb rehabilitation robot that can be applied to various symptoms of shoulder disorders. The 3-dimensional shoulder tracking mechanism was implemented to allow the translational movement of the shoulder joint. With improvements in surgical techniques and increased knowledge of rotator cuff healing, there was a need to identify a safe progression after rotator cuff repair. During rehabilitation after rotator cuff repair, there should be constant communication with the surgical team.Awareness of complication management, healing potential of the repaired tendon, and anatomies of the shoulder complex are critical. During the early stages, reducing pain and inflammation should be prioritized followed by progressive restoration of range of motion. When advancing range of motion, progression from passive, active assisted, and active movements allow for gradual introduction of stress to the healing construct. Even though time frames are not used for progression, it is important not to place excessive stress on the shoulder for up to 12 weeks to allow for proper tendon-to-bone healing. As exercises are progressed, scapular muscle activation is initiated, followed by isometric and lastly isotonic rotator cuff exercises. This system uses micro controller and EMG, TILT, ACCELEROMETER sensors in order to find the muscle activity along with the position & angle of the hand while they performing movement during rehabilitation recovery time. The system can able to give the muscle rehabilitation details time to time using the micro controller. Thus, we can predict how soon the patient can recover from the rotator cuff problem and also the current muscle activity details are shown using cayenne app using IOT (ESP 8266-12E) NODE MCU and cayenne server.
Super Cool Workspace using Deep Learning
Authors:- Asst. Prof. Sudhakar R, Ebinezar M, Varun Kumar M, Saran R, Siva C
Abstract- To capture the emotions of employees during various times automatically without having to manually key in the ratings. To analyze the movements of happiness index with various factors .To map the captured emotions into a graph or chart during the real time. Face discovery assumes an essential job in feeling acknowledgment. These days face acknowledgment is increasingly effective and utilized for some constant applications because of security purposes. Face recognition in real time using photo manipulation and artificial intelligence (AI) techniques a challenging task for a PC vision to interpret the world in the same way as people do using AI. Organizations have been exploring various avenues for combining refined calculations with picture preparation methods that have risen in the last ten years to see progressively about what a picture or video of a person’s face teaches us about how he or she is feeling, as well as indicating the probabilities of blended feelings a face could have. We distinguish feeling by examining (static) pictures or with the (dynamic) recording. Highlights extricating should be possible like eyes, nose, and mouth for face identification. The convolutional neural system (CNN) calculation follows ventures as max-pooling (greatest component extraction) and leveling.
Plant Leaf Disease Detection & Fertilizer Suggestion using CNN
Authors:- Akash V. Bhambere, Aniket K. Sawale, Suvarna I. Patil, Manali B. Kapadnis,Mrs. Poonam Y. Pawar
Abstract- Every country’s primary need is Agricultural products. If plants are infected by diseases, this impacts the country’s agricultural production and its economic resources. In agriculture for an efficient crop yield early detection of diseases is important. Automatic methods for classification of plant diseases also help taking action after detecting the symptoms of leaf diseases. In the agricultural sector, identification of plant diseases is extremely crucial as they hamper robustness and health of the plant which play a vital role in agricultural productivity. These problems are common in plants, if proper prevention methods are not taken it might seriously affect the cultivation. The current method of detecting disease is done by an expert’s opinion and physical analysis, which is time-consuming and costly in the real world. We are introducing the artificial intelligence based automatic plant leaf disease detection and classification for quick and easy detection of disease and then classifying it. This main aim of ours system is towards increasing the productivity of crops in agriculture. In this approach we have follow several steps i.e. image collection, image preprocessing, segmentation and classification.
A Review of Intrusion Detection Systems
Authors:- Udit Narayan Pushpad, Prof. Lokendra Singh Songare
Abstract- A network security system that detects, identifies, and tracks an intruder or invader in a network is known as an intrusion detection system (IDS). As our society’s use of the internet grows by the day, intrusion detection systems (IDS) are becoming an integral component of the network security system. As a result, adequate IDS research and implementation are essential. Many ways for creating intrusion detection systems have been discovered nowadays, thanks to enhanced technology at our disposal. However, with so many alternatives available, it might be tough to choose the best one. As a result of the need for a better security system, this article gives a study of many published solutions that have been created and/or studied on the issue of intrusion detection methods from 2000 to 2019, including the accuracy of the output. An all-inclusive perspective of the various papers will be available with the aid of this survey.
Law Enforcement Managemenent System
Authors:- Adem Omer Adem, Asst. Prof. Sulthana A.S.R, MCA., M.Phil., Ph.D.
Abstract- To deliver next generation police and law enforcement reporting tools, and setting up intelligence platforms that agencies use to take incoming incident reports, lessen employee resources and allow these enforcement agencies to reallocate resources to much needed community areas.
Domestic Water Supply Monitoring andTheft Identification System
Authors:- Asst. Prof. Ragavi P, Keerthana G, Arthi T, Dharaneesh Kumar D, Gogula Varsini S.
Abstract- In urban areas the water supply to residence and commercial establishments are provided at a fixed flow rate. There are incidents of excess water drawn by certain consumers/users by connecting the motor pump or Suction pump to suck the water directly from the home street pipeline which is consider as water theft. In this project it is proposed to develop an IoT based water supply monitoring and theft identification system by recording the flow rates at the consumer/user end. In order to implement the proposed water supply system, each consumer can be provided with an Arduino based microcontroller kit to record the flow rate using a flow sensor. It is also provided with an electrically operated solenoid valve to supply water to the consumers. When there is theft occurred in water supply pipeline, the excess flow rate and corresponding charge will be sent to consumer Id. The valve is tuned off using IoT to stop the water supply, when the consumer fails to pay or uses excessive water. LCD is connected with a NodeMCU to display data locally. The proposed automated framework is completely programmed thus no human power is required.
comparison and Extension of Approximate 4:2 Compressors for Low-Power Approximate Multipliers
Authors:- Asst. Abinaya.D
Abstract- The existing research, which suggests numerous circuits built with approximate 4:2 compressors, is quite interested in approximate multipliers. Because of the enormous variety of offered solutions, the designer who desires to employ approximate 4:2 compressors faces the difficulty of picking the appropriate topology. In this study, we give a complete analysis and comparison of previously suggested approximate 4:2 compressors in the literature. We also introduce a fresh approximate compressor, bringing the total number of approximate 4:2 compressors studied to twelve. The circuits studied are used to create 8*8 multipliers.
An Automatic Security System in ATM and Vulnerability Reduction Based on IoT
Authors:- Asst. Prof. Elamathi K, Su.Harinyvidhya, Keerthana R, Arthi S, Vaishnavi R
Abstract- Our adventure proposes a made sure about ATM (Automated Teller Machine) frame exercising a card filtering frame alongside LINK frame for advanced security. Common ATM fabrics do not contain the LINK highlight for cash pullout. On the off chance that an raider figures out how to get hold of ATM card and the leg number, he may effectively use it to pull back cash deceitful. So our proposed frame bolsters the ATM card filtering frame alongside a LINK frame. This customer may filter his card and login to the frame. In any case, after customer is through with this evidence he may see craft yet is approached to enter LINK when he clicks cash pullout volition. At this stage the frame produces and sends a LINK to the enrolled movable number to that specific customer. The secret expression is produced announcement transferred to the customer cell phone. He now needs to enter the LINK in the frame so as to pull back cash. In this way our frame gives an absolutely secure approach to perform ATM exchanges with two position security structure.
Digital Guide Assisstant
Authors:- Abdalrahman Farag Ali , Asst. Prof..Sulthana A.S.R, Mca, M.Phil
Abstract- The Project “Digital Guide Assistant” is designed by Frontend as PHP and Backend as MY SQL. This Project is about the tourist guide may expose toursits to fraud because they know that they don’t know anything. This project is based on website. This website helps to detect the fraud and it can helps the tourist in any country. This website will shows the places in every country that can add by Admin. It shows the correct time of closing and ending for the tourists. It will shows the correct price for entering. It shows the details of each thing there so can read or listen to a voice in the language.The uses can collect all the details of the statue in the place that users are in. The users can post the photos and it can be uploaded in the Gallery.
Safety Enhanced Location Tracking Device for Logistics Container using Raspberry PI
Authors:- Asst. Prof. Dinesh Kumar B, Arvisa SR, Balaji S, Gokul P, Illakiya P
Abstract- The Internet of Things (IoT) interconnects physical devices and objects that offer to enrich the user experience. For instance, empowering traditional transport systems with IoT ensures greater visibility Internet of Things (IoT) interconnects physical devices and objects that offer services to enrich the user experience. In traditional shipping and freight systems, containers carrying donated organs should be sealed carefully, kept below a certain temperature, and placed in a physically safe place to minimize the chances of damage due to jerking and accidental falling. During the shipping process, the IoT-enabled container provides continuous monitoring and readings related to temperature, humidity, location, vibration, and open/close conditions. Additionally, automatic push alerts and notifications are sent to stakeholders when certain conditions or violations occur.
Hybrid Accident Prevention Using Eye Blinking
Authors:- Ali Moallin Mao, Dr. K. Juliana Gnanaselvi
Abstract- Transportation safety is important for detection of Driver’s Drowsiness. Drowsy driving is an important reason of traffic accidents. Driver Fatigue is one of the major reasons causing most fatal road accidents around the world. This shows that in the transportation industry specially, where a heavy vehicle driver is often open to hours of monotonous driving which causes fatigue without frequent rest period. Hence it is very essential to design a road accidents prevention system for detecting driver’s drowsiness, which determines the level of driver inattention and give a warning when an impending hazard exists. The SMS or mail alert sends to the emergency helpline numbers about the drowsiness of a driver with the vehicle details and the contact details to the nearest police station and the help line numbers. This project provides Eye Blink Monitoring System that will alert the driver in drowsiness. A system for monitoring eye movements would be useful in warning drivers when they fall asleep. The driver’s eye is continuously monitored using a web camera. To monitor the number of eye blink, threshold limit is been set. Webcam keeps monitoring the eye blinks based on this threshold. When the blink gets fluctuated from the threshold limit then the system automatically plays a song and helps the driver to get rid of drowsiness. Two algorithms are implemented one is based on edge detection that helps in monitoring the brightness of video and the other algorithm is based on counting the dark pixels to monitor the driver accurately. This in general avoids road accident due to fatigue of drivers if this system is implemented in every vehicle. The purpose of such a model is to advance a system to detect fatigue symptoms in drivers and to alert the drivers to avoid accidents. This is developed as a windows application using Python language. MySQL backend is used to store the vehicle information such as vehicle number, driver contact details and the helpline numbers.
Analysis of Friction Stir Spot Weldments Using EN19TAPER Square & Diamond Profile Tools on Similar Metals
Authors:- Associate. Prof. Dr. B Srinivasulu, Abdul Saud Khan, Mohammed Uzair, Salman Hussain
Abstract- The process uses a non-consumable tool comprised of two rotating components – probe and shoulder. Although one continuous process, RFSSW occurs over four stages: the first of which sees the tool move to the surface of the top sheet, where it rotates to produce the initial frictional pre-heating. Once the pre-heating stage is complete, the material is sufficiently soft, allowing the shoulder to plunge to a pre-determined depth in the base material while the probe retracts to create a gap into which the displaced material can flow. The third stage of the process involves the rotating components returning to the top surface, consolidating the weld material. EN 19 Diamond and Taper Square profile tool. Al-6061 to Brass-IS319 and Brass-IS319 to Al-6061 specimens, in lap-joint configuration. Test samples showed a Brass-IS319 to Brass-IS319 and Al-6061 to Al-6061.
Smart Energy Meter with Wi-Fi Module
Authors:- Asst. Prof. Sravanthi Gottipati, Ganesh. N, Jathin. M, Srilatha. A, Mahesh babu. P
Abstract- Efficient energy utilization plays a very vital role for the development of smart meters in power system. So, proper monitoring and controlling of energy consumption is a chief priority of this project. The existing energy meter system has few problems associated to it and one of the key problems is there is no full duplex communication for the suppliers. To solve this problem, a smart energy meter is proposed based on Internet of Things (loT). The proposed smart energy meter controls and calculates the energy consumption using ESP 8266 12E, a Wi-Fi module and uploads it to the cloud from where the consumer and producer can view the reading. Therefore, energy analyzation by the consumer becomes much easier and controllable. This system also helps in detecting power theft. Thus, this smart meter helps in close monitoring of the energy utilization using IoT and enabling wireless communication for consumers and suppliers.
Wallpaper App with Firebase Server
Authors:- Prof. Reshma R. Owhal, Pooja D. Salave, Sakshi S. Waghmare, Ritika S. Kothawade, Prithviraj S. Thorat
Abstract- We are going to build a wallpaper application in which we will be adding functionality to filter wallpapers based on various categories. Along with that we will be also adding a search bar to search wallpapers based on the user search query. We are going to implement this project using the kotlin language. Basically the project is divided into two modules. First Moduleis home screen in which different types of wallpaper are available like Aesthetic Wallpaper, Animal Wallpaper, BlackWallpaper, Colorful Wallpaper, Flower Wallpaper, Landscape Wallpaper, Anime wallpaper, Natural Scenery, Simple Wallpaper, Solid Color Wallpaper, etc.second module is for downloading wallpaper in which all the free downloadedwallpapers are available offline which are used to set homescreen and lockscreen wallpaper.
An Efficient Spam Detection Technique for IoT Devices using Machine Learning
Authors:- Asst. Prof. Sulthana A.S. R, Ilyas Abdi Mohamed
Abstract- The Internet of Things (IoT) is a group of millions of devices having sensors and actuators linked over wired or wireless channel for data transmission. IoT has grown rapidly over the past decade with more than 25 billion devices are expected to be connected by 2020. The volume of data released from these devices will increase many-fold in the years to come. In addition to an increased volume, the IoT devices produces a large amount of data with a number of different modalities having varying data quality defined by its speed in terms of time and position dependency. In such an environment, machine learning algorithms can play an important role in ensuring security and authorization based on biotechnology, anomalous detection to improve the usability and security of IoT systems. Motivated from these, in this paper, we propose the security of the IoT devices by detecting spam using machine learning. To achieve this objective, Spam Detection in IoT using Machine Learning framework is proposed. In this framework, five machine learning models are evaluated using various metrics with a large collection of inputs features sets. Each model computes a spam score by considering the refined input features. This score depicts the trustworthiness of IoT device under various parameters. REFIT Smart Home dataset is used for the validation of proposed technique. The results obtained proves the effectiveness of the proposed scheme in comparison to the other existing schemes.
A Localization and Traffic Density Short Term Forcasting in Non Motorised Vehicle Comprehensive Case Analysis
Authors:- Mohammad Hashim Khan, HOD Mr. Vinay Deulkar
Abstract- Non-motorized transport (NMT) is the use of a bicycle or walking to travel from one place to another. It is gaining popularity especially in the developed countries due to low transport externalities such as emissions and traffic congestion alongside its benefits to physical and mental health. The built environment, geography and weather, and socioeconomic factors significantly affect the use of NMT as a travel mode. This study reviewed some unique characteristics of NMT especially in developing countries to provide a clear understanding of the dynamics of NMT.
Energy Management Strategies of Hybrid Energy Storage System Using LSTM Technique
Authors:- M. Tech. Scholar Neetu Singh, HOD Ashwani Kumar, Assistant Professor Shilpi
Abstract- The commercial penetration and expansion of EV are restricted by various barriers such as Energy Storage System (ESS), driving range, Power Electronic Interface (PEI), charging station and high initial cost. Research related to ESS helps in solving the various research challenges associated with it. Since last decade, researchers are aiming at hybridizing different energy storage technologies. In fact, hybridization of different energy storage systems has proved to be the promising solution in improving the driving range, extending the battery life span by mitigating the stress, increasing the power train efficiency, lowering the cost and weight of ESS. A fuel cell model was developed and then to get the required energy level, a module was made using this fuel cell. The sharing of power between Ultracapacitor and fuel cell was again analysed and checked for optimal sharing of energy which will allow the Ultracapacitor to share more during the acceleration when peak current is in demand by EV. To get the optimal energy management of the HESS, a Hybrid Optimization Algorithm was developed which consists of a novel control strategy and optimization technique to analyse for efficient energy management of HESS for maximum energy utilization by electric vehicle. The MATLAB/SIMULINK software was used to validate the implementation. The complete energy management scheme which utilizes the proposed novel LSTM management scheme making it an efficient management scheme and at the same time the life of the primary energy source of Electric Vehicle is protected from easy damage and fuel starvation.
Attendance System Using face Detection with Deep Learning
Authors:- Ayushi Verma, Ashwani Shankar Amist
Abstract- The attendance management could be much hectic for teachers if it is taken manually by hand. To get rid of this problem smartly automatic attendance system has been developed but authentication of this system becomes an issue. In general, the smart attendance system has been accomplished with the help of biometrics. Face recognition is one of the effective forms of biometric to get improvement in security and authentication. Being a key feature of biometric verification, facial recognition is used in various applications like video monitoring, CCTV footage system and enables interaction between computer and humans. By using this method, the problem of proxies and students marked present when they are not present physically can be easily removed. This article has been proposed to implement automated attendance management system for students by using face recognition, with the help of eigenface values, Principal component analysis (PCA) and Convolutional neural network (CNN). After that the connection has been recognized by comparing these faces with the student’s faces stored in database. This model could manage records of students for attendance purpose successfully [1]. Human face recognition is one of the evolutions in machine vision. Attendance System is one of the main implementations of human face recognition. In Attendance System faces are used as objects which need to be detected and recognized to identify a person’s identity and that is stored in face database. In this process the faces captured by camera has been matched with the face images stored in face database to identify the object faces captured by camera. In this study this attendance system based on face recognition uses hybrid feature extraction method using CNN-PCA. This kind of collaboration of methods will deliberate to produce more precise and accurate feature extraction method. This method of attendance system based on face recognition system using this camera has very accurate data processing resulting it would be more effective, powerful and reliable to identify faces in real-time [2].
“Study on Diferent Techniques of Retrofitting”
Authors:- Ganesh Mali, Omakr Kailas Tambe, Kunal Shrinath Babar, Adesh Dattatray Modak,Lecturer Nishchay R More sir
Abstract- Now-a-days retrofitting is becoming popular around the world, as most of the important structures like historical building or some other old structures which becomes weak over the time. Retrofitting is the best method to make safe the existing structures from the future earthquake and other environmental factors. Retrofitting diminishes the helplessness of harm to a current structure amid future seismic movement It plans to reinforce a structure to fulfil the necessities of the present codes for seismic outline. With respect to conventional repair and rehabilitation, retrofit is much better and convenient. Retrofitting helps to enhance the strength, resistivity and overall lifespan of the structure.
Study of Incorporation of Waste Plastic in Road Construction
Authors:- Abhishek Kamble, Harish Kokani, Abhishek Tapkir, Akshay Bodhale, Lecturer M.A. Dhatunde
Abstract- Plastic use in road construction is not new. Waste plastic is ground and made into powder; 3 to 4 % plastic is mixed with the bitumen. The durability of the roads laid out with shredded plastic waste is much more compared with roads with asphalt with the ordinary mix. Worldwide, sustainability is the pressing need of the hour in the construction industry and towards this end use of waste material in road construction is being increasingly encouraged so as to reduce environmental impact. In the highway infrastructure, a large number of originate materials and technologies have been invented to determine their suitability for the design, construction and maintenance of these pavements. Plastics and rubbers are one of them. Also considering the environmental approach, due to excessive use of polythene in day-to-day business, the pollution to the environment is enormous. The use of plastic materials such as carry bags, cups, etc. is constantly increasing day by day. Since the polythene are not biodegradable, the need of the current hour is to use the waste polythene in some beneficial purposes. the main aim of this study is to focus on using the available waste/recycled plastic materials and waste rubber tires present in abundant which can be used economically and conveniently. The use of these materials as a road construction proves ecofriendly, economical and use of plastic will also give strength in the sub-base course of the pavement. Keywords-abundant, recycled, biodegradable, economical.
Low-Cost Housing
Authors:-Soham Katkol, Suyash Dhaygude, Abhishek Tugaonkar, Gaurav Tupe, Lecturer Samiksha R. Gaikwad
Abstract- The objective of our project is to develop low, economical and efficient housing material especially bricks which we covered in this project. Construction materials made of renewable resources have promising potential given their low cost, availability, and environmental friendliness. Although hemp fibres are the most extensively used fibre in the eco-friendly building sector, their unavailability hinders their application in Iraq. This study aimed to overcome the absence of hemp fibre in Iraq and develop a new sustainable construction material, straw create, by using wheat straw and traditional lime as the base binder. A comparable method of developing hempcrete was established. The experimental program adopted novel Mixing Sequence Techniques (MSTs), which depended on changing the sequence of mixed material with fixed proportions. The orientation of the applied load and the specimen’s aspect ratio were also studied. The mixing proportion was 4:1:1 (fibre/binder/water) by volume. Results showed that the developed straw create had a dry unit weight ranging from 645 kg/m3 to 734 kg/m3 and a compressive strength ranging from 1.8 MPa to 3.8 MPa. The enhanced physical and strength properties varied with the MST and loading orientation. The properties of the developed hempcrete were compared with those of straw create.
Tiles From Recycled Tyre Rubber: The Future
Authors:- Sakshi S. Kande, Komal R. Tambare, Nita N. Kolekar, Sayali K. Gopnar Lecturer Thorat M.D.
Abstract- This research present a case study of producing flexible tiles from rubber crumb obtain from automobile tyre waste using a polyrethene resin asa binder matrix. The process was made in collaboration with a company located in colombia, where the manufacturing of this materials has been optimized. The material is green solution to an increasing worldwide problem,rubbertyres ,mostly put in landfills or burn to extrat their reinforced steel wires instead of properly recycled. Several rubber contents and particle size disrtibution were investigated and tested.Tension, density scanning electron microscopy,and thermo-gravimetric analysis characterization were used to evalute the composites.Result shows that the amount of rubber usedis quite large in comparision with the binder, maximizing the rubber in the formulations, and composites to be used in multiple application. The tensile test showed the composites can work very well for structural application of low solicitations , asuch as well cover soft floors and barriers.The project is sucessful example of a small-medium entreprise company that contributes to the circular economy of these highly pollutant materials.
A Review of Nano Refrigerant R134a+Al2O3 based Vapour Compression Refrigeration System
Authors:- Ibrahim Hussain Shah
Abstract- This research paper is deals about the today’s world refrigeration systems which play a significant role to meet the human desires and never-ending analysis is being dole out by several researchers so as to boost the performance of those systems. Here, an endeavour has been created to boost the performance of the system. Our, gift study on experimental investigations into the performance of nano refrigerant (R134a + Al2O3) based mostly cooling. it absolutely was ascertained that there’s additional temperature drop across the condenser for the nano refrigerant (12.37% — 10.88%) compared to refrigerant R134a. Similarly, a gain of five.52% and 9.24% was obtained for evaporator temperature. Associate in nursing improvement in COP was additionally ascertained throughout the investigations (1.17% — 9.14%). This was achieved underneath 25–26 oC evaporator temperature load. The results indicate that constant of performance will increase with the usage of nano Al2O3. So mistreatment Al2O3 nano refrigerant in cooling is found to be possible.
Study on Effect of Admixtures on Self Compacting Concrete
Authors:- Saurabh Satav, Omkar Dhere, Shubham Dunghav, Prof. Jayram Shivaji Shendge, Prof. Manoj Dilip Thorat, Prof. Sayali Akshay Wadkar
Abstract- The concrete today can take care of any specific requirements under most critical exposure conditions. The concrete in modern days has to satisfy various performance criteria’s. As a result, concrete is required to have properties like high fluidity, self compactability, high strength, high durability, better serviceability and long service life. In order to address these requirements, self-compacting concrete (SCC) was developed. Self compacting concrete is a mix that can be compacted into every corner of formwork, by means of its own weight and without the need for vibrating compaction. In spite of its high flowability, the coarse aggregate is not segregated. At the same time there is no entrapped air.
Nanotechnology towards the Next Revolution
Authors:- Dr.Diwakar Nath Jha
Abstract- The Nano world is full of surprise and potential. In this field, the disciplinary boundaries between chemistry, molecular Biology, materials science and condensed matter physics dissolve as scientists struggle to understand new and sometimes unexpected properties. Atoms are the most basic units matter. They can be combined to form more complex structures such as molecules, crystals and compounds nanomaterial also are arrangements of matter in length scale of approximately 1 to 100nanometers that exhibit unique characteristics due to their size. Fabrication, or the making, of nanomaterial falls into one of two categories top-down or bottom-up. Top-down method involves carving nanomaterial out of bulk materials. Approaches in this category are referred to as different forms of lithography. Lithography can be understood through the concepts of writing and replication. Writing involves designing a pattern on a negative and replication involves transferring the pattern on the negative to a functional materials. One nanometer is equal to one billionth of a matter, spans approximately 10 atoms. Even scientists in the field maintain that it “depends on whom you ask”. Biophysicist Steven M. Block notes that some researchers “reserve the world to mean whatever it is they do as opposed to whatever it is anyone else does” Scientists reserve the term for research involving sizes between 1 and 100nanometers. There is also debate over whatever naturally occurring nano- particles, such as carbon soot, fall under the rubric of nanotechnology. One nano meter is equal to the width of three to five atoms. Type of Applications:-there are three general classes of nanotechnology applications based on the degree of control over the synthesis, characterization, first, we use the term simple nanotechnology to describe applications involving mass production of nanomaterial’s commercial products based on simple nanotechnology do not involve precise fabrication and positioning of nanostructures. We describe the second class of nanotechnology applications as building small. This category refers to the use of nanomaterials to build advanced materials devices and systems within the next 5 to 15 years, “building small” nanotechnology could have a major impact on a number of different products in a range of different industries the final class of nanotechnology applications “building large” describes the unrealized vision of self –replicating nanorobots.
Diabetes Detection Using Image Processing Algorithm
Authors:- Ms. Reshma.R.Owhal, ShubhamVaghasiya, AtharvaTenkale, AkshayPokale
Abstract- Diabetes is a metabolic disease that causes high blood sugar and an untreated high blood sugar can damage your nerves, eyes, kidneys and other organs and to detect the diabetes disease, we propose this methodology to machine learning technique which will be painless to detect diabetes. We’re using thermal imaging scans of an eye to illustrate the effect of temperature variation of anomalies in the ocular architecture as a diagnostic imaging modality that can help optometrists make clinical diagnoses. We’re using thermo graphy images of an eye to actually prove the caused by thermal variation of abnormalities in the eye structure as a mammography type of therapy that can help optometrists make clinical reasoning. A method through which a computational system understands the characteristics of input information is known as machine learning. Several methodologies have previously been shown to be sensitive enough to detect diabetes. Countless optimization algorithms, with the exception of guided, uncontrolled, and reinforcement instructional strategies, have been developed. Machine learning techniques are powered by data, so this is obviously practical. Our system is using SVM, machine learning algorithm and histogram array values to find the diabetes disease, in data. This project that we have created takes less time and detects diabetes from the entered values.
SVM for Diabetic Detection System
Authors:-Ms. Reshma.R.Owhal, Shubham Vaghasiya, Atharva Tenkale, Akshay Pokale
Abstract- Diabetic Diagnosis Using Retinopathy Diabetic retinopathy is a T2dm retinal detachments resulted in the degradation of neurotransmitters in the vascular system of the eye. High blood glucose levels could indeed significantly raise a patient’s risk of developing diabetes. Diabetic Retinopathy is indeed an infection that affects once diabetes propagates to a patient’s photoreceptors. This condition can cause inaccurate blood vessels to form in the retina, as well as blood vessel rupture and hypertension. Blurred vision, undulating vision, reduced colour perception, and spots or dusky filaments are all symptoms of diabetic retinopathy. The primary goal of this experiment is to determine whether the patients have eye diseases.
Deep Learning Techniques to Classify the Aerial Images with Gabor Filter
Authors:- PG Scholar Prakruthi D P, Asst. Prof. P Sumathi
Abstract- Aerial Images are a valuable data source for earth observation, can help us to measure and observe detailed structures on the Earth’s surface. Aerial images are drastically growing. This has given particular urgency to the quest for how to make full use of ever-increasing Aerial images for intelligent earth observation. Hence, it is extremely important to understand huge and complex Aerial images. Aerial image classification, which aims at labeling Aerial images with a set of semantic categories based on their contents, has broad applications in a range of fields. Propelled by the powerful feature learning capabilities of deep neural networks, Aerial image scene classification driven by deep learning has drawn remarkable attention and achieved significant breakthroughs. However, recent achievements regarding deep learning for scene classification of Aerial images is still lacking..
Decision on Cryptocurrency
Authors:- Miss. Priyanka Ramchandra Gupta
Abstract- A cryptocurrency is a digital currency that relies on networking for every transaction. It follows peer to peer version of electronic cash that can allow online payments to be sent directly from one party to another without any involvement of financial institutions or any other centralized authority. To prevent any fraudulent activities a decentralized system relies to record and oversee transactions. The thesis shows a present situations and the regulation of digital currencies in India. Despite gaining worldwide popularity and various other legal restrictions, it is regularized and gains its momentum. All circulars, challenges, and circumstances are being highlighted below on the matter of digital currencies.
Power Generation Using Speed Bumps
Authors:- Associate. Prof. Dr. B Srinivasulu, Mohd Faisal Farooq Malik, Mohammed Safdar Ullah, Mohammed Suleimaan
Abstract- In the following article, we will learn how speed breakers can be used as power generators. Adding a rack-and-pinion gear with a generator attached to a combination of the gears mentioned above can accomplish this. The electricity can also be stored in various cells or other storage sections. The following paper includes a sample calculation for which energy calculations have been conducted.
Face Mask Recognition Using RCNN
Authors:- Aishwarya M P, Sowmiya S
Abstract- Corona Virus is the latest pandemic that forced an international health emergency. It spreads mainly from person to person through airborne transmission. Many countries have imposed compulsory face mask policies in public areas as a preventive action. However, some people still do not wear masks in public areas, which might lead to infection of themselves or others. Manual observation of the face mask in crowded places is a tedious task. Therefore, automatic detection of the wearing of face masks may help global society, but research related to this is limited.In this paper, we propose a Mask-RCNN use two novel methods to achieve this. First, to detect mask region from the face using RPN and to extract rich context features and focus on crutial face mask related regions, we propose a novel residual residual context attention module (RCAM). Second, to learn more discriminating features for face with and without masks. This technique is capable of recognizing masked and unmasked faces to help monitor safety breaches, facilitate the use of face masks, and maintain a secure working atmosphere.
Survey on Existing Accident Alert Systems
Authors:- Divya K S, P J Roshan, Srivathsan, Vishnu S Nath, V Krishnadev
Abstract- Road accidents are a common sight nowadays. The main reasons are overspeeding, a lapse of concentration, drunk
and drive, etc. Moreover, victims do not get the required aid in time which results in serious problems such as injury or even
death. Thus, there arises the need for an accident alert system that detects accidents and delivers the aid in time by transmitting information to the right destination. There are many existing systems. In this paper, we focus on some of the existing accident alert systems and review their features. Studying these features will help in finding any bugs and faults in them.
Face Recognition Using Python and Deep Learning
Authors:- Jemi Mariya Jose, Maris Baby, Meenakshi P D, Assoc. Prof. T Sobha
Abstract- In their daily lives, people who work in the chemical sector come into contact with hazardous or caustic compounds. They also come across a variety of substances and particles that, when inhaled, cause a variety of negative effects. Some of the gases used in these industries are so toxic that they can make a worker dizzy and cause a temporary loss of concentration. When working with chemicals, it is therefore suggested that you use a breathing mask. These masks shield you from hazardous particles and gases in the air. They remove contaminants from the air that might cause injuries, infections, or death. As a result, respirators are required to protect you from gas and other toxic chemicals. In this research, we offer a method for detecting face mask.Abounding box drawn across the person’s face indicates whether or not the person is wearing a face mask. If a person’s face is recorded in the database, the name of the person who is not wearing a face mask is spotted, and an email is sent to the authority informing them that the worker is not wearing a mask so that precautions can be taken.subhumans using TensorFlow andOpenCV.
Agricultural Crop Recommendations System Based on Soil Fertility Using Machine Learning Techniques
Authors:- Sneha A.S, Nikila A, M. Dharun Gandhi Supervisor, Mr.P.Boopathirajan
Abstract- Agriculture plays a major role in everyday life, without proper agriculture techniques production of quality crops will be affected. This may lead to economic crisis or downfall. Agriculture gives a significant hand in country’s economic development. It is mandatory to administer new farming techniques and include technological advancements for better crop yield and production. Machine Learning techniques have greatly shaped agriculture throughout time. Machine Learning techniques greatly help in recommendation and prediction systems. Soil techniques greatly help in recommendation and prediction systems. Soil fertility is vital for healthy and increased crop yield. Soil fertility is determined based on several factors. Some of the features used in this approach are Nitrogen (N), Phosphorus (P), Potassium (K), humidity, temperature, rainfall and ph value of the soil. In our approach we use the technique of Multilayer Perceptron Classifier and Stochastic Gradient Descent to predict the best crop yielded based on the soil fertility.
Automatic Irrigation System
Authors:- Shaikh M Shahnawaz Aalam, Rahul Boga
Abstract- India is an agricultural-based country. Agriculture is the main source of livelihood for most Indians and contributes significantly to the country’s economy. In dry areas or when there is insufficient rainfall, irrigation becomes difficult. Therefore, it needs to be done automatically to get the right yield and remotely managed for the safety of the farmers. If the farmer is far from the agricultural land he will not be able to pay attention to the currentsituation.Therefore, good water management plays an important role in agricultural irrigation schemes. This study investigates the design of an Arduino-based automated irrigation system. This Embedded project is to design and develop a low-cost feature based on the fixed location of the irrigation system. This research uses soil moisture sensor to determine the amount of water availabilitysee the sensor value for the dry condition. in agriculture. The project uses a small Arduino controller to process information. The purpose of this was to show that automatic irrigation can be used to reduce water use.
Industrial Robotic Arm Based on IR Sensor and ARDUINO
Authors:- Prof. Komal Wanzare, Chetan Tamgadge, Pratiksha Suryavanshi, Sanket Gaurav, Sumedh Khillare
Abstract- This Paper outlines the various stages of operations involved in the pick and place robotic arm. It is an automated material handling system is synchronizing the movement of robotic arm to pick the object moving on a conveyor belt. Nowadays various advanced robots are used in industries but still controlling is done manually or using processors likewise Adriano, microcontroller. But microprocessors have several disadvantages so these disadvantages can be overcome by Arduino. Here Arduino uno is used for controlling and operating robotic arm. All the various problems of this process have been analyzed properly and have been taken into consideration while programming and designing the pick and place robotic arm.
Design of Area-Efficient Carry Skip adder
Authors:- M.Kousalya
Abstract- The design of area-efficient logic systems is an essential component and one of the most active areas of study in the field of VLSI Design. The most fundamental mathematical operation is addition. An area-efficient Carry Skip adder is suggested in this Project. CSA is a rapid adder that is used in data processing systems to execute quick arithmetic operations. Second, the Carry Skip adder’s construction allows for the reduction of space and power usage. Third, there is potential to lower the area by using an add-on plan. As a result, a Modified Carry Skip Adder (MCSA) is developed using a single Ripple Carry Adder (RCA) and a Binary to Excess-1 Converter (BEC) instead of twin RCAs to save size while sacrificing speed.
Survey on Crowdfunding Platforms Using Smart Contracts
Authors:- Namitha Sabin, Niranj U, Srinidhi D Pai, Sneha T U, Asst. Prof. Gripsy Paul Mannickathan
Abstract- In a normal banking system, the transactions are prone to hacks, double spending, high rates etc. The concept of blockchain puts a stop to these drawbacks. Blockchain is a distributed, unchangeable ledger that makes recording transactions and managing assets in a corporate network much easier. Crowd funding is a method of raising funds that runs independently of any government and is used by individuals, corporations, and charities. It is a method of raising funds by asking a huge number of people for a modest amount of money from each of them. Crowd funding has many advantages, but it also has a significant danger of fraud, as well as several other possible risks, such as money loss, investment lock-in and lack of transparency. In this paper we discuss various crowdfunding platforms that run for charity purposes.
Automatic Bush Trimming Machine
Authors:- Braj Bhushan Yadav, Meet Chandrakant Patel, Shubham Ahire, Associate Prof. Durgesh Borse
Abstract- This paper presents a literature review and development of Bush Trimming Machine use for trimming the plants of road side. Maintenance of private and public premises is becoming necessary and involves high cost. In general manually operated trimmers were used just like simple and most common type is shearing of scissors. This project focuses on development of bush trimming machine in societal view with low cost system. The manually operated trimmers involve more effort & time consuming, where the operator required more efforts to lift the trimmer at suitable height and it is having very heavy weight. The uniformity of cutting varies from one operator to another. Different operator will cut in different way. The time also be saved using this trimming machine.
Effect of Filler Rod on Microstructure and Mechanical Properties of Bimetallic Weld Joint
Authors:- M. Tech. Scholar Lokesh, Asst. Prof. Manoj Kumar
Abstract- Bimetallic weld joint is used in boiler reactor and pressurized water reactor design, where low carbon steel alloy components are welded to stainless steel piping system. There are various problems which need to be addressed while welding the bimetallic metals due to the variation in the properties of the base metal.The analysis confirms the well mixing of stainless steel and mild steel with filler rods inside the weld pool. The mechanical properties in terms of ultimate tensile strength found to be high as 467.54 N/mm2 with filler rod SS316L and micro hardness value at the center of the welded zone was found maximum (294 HV) with filler material SS316L, the fracture of the tensile test specimen were obtained outside the weld zone.
A Review Article to Voltage Sag and Swell Power Compensation with Power Stabilization Using SAF
Authors:- Gurpreet Kaur, Professor Arun Pachori
Abstract- The parameters of electrical energy, such as supply voltage amplitude, are very important, especially from the viewpoint of the final consumer with respect to sensitive loads connected to the grid. Dynamic states in the power grid?voltage sags and swells?might cause faults and defects to develop in sensitive loads. To mitigate unwanted effects, many topologies of ac/ac converters are implemented as voltage compensators. This article presents a review of hybrid ac/ac converters designed to compensate voltage sags and swells with the aim of protecting sensitive loads against sudden and severe changes in supply voltage amplitude. In this article, only solutions without galvanic separation between source and load are described. To assess the properties and to compare different topologies of voltage compensators, some common parameters, such as range of voltage sag and swell compensation, reliability, quantity of switches and transformers, and required power ratings of power electronic units in relation to power of load, are introduced. In addition, we discuss possibilities for compensation of voltage interruption, time of compensation, the efficiency, and the effect on the supply network of the described circuits. The results of the analysis have been collected and compared in tabular form and represented in graphical form. Furthermore, we show potential areas of application for particular solutions of ac voltage compensators.
Grid Connected Maximum Power Utilization Using Isolated AC- DC Converter
Authors:- Ballabh Chaudhary, Professor Arun Pachori
Abstract- An ever-increasing interest on integrating solar power to utility grid exists due to wide use of renewable energy sources and distributed generation. The grid-connected solar inverters that are the key devices interfacing solar power plant with utility play crucial role in this situation. Although three-phase inverters were industry standard in large photovoltaic (PV) power plant applications, the microgrid regulations increased the use of single-phase inverters in residential power plants and grid interconnection. This paper presents a detailed review on single-phase grid-connected solar inverters in terms of their improvements in circuit topologies and control methods. Even though there are many reviews have been proposed in the current literature, this study provides a differentiating approach by focusing on novel circuit topologies and control methods of string and micro inverters. The single and multi-stage solar inverters are reviewed in terms of emerging DC-DC converter and unfolding inverter topologies while the novel control methods of both stages have been surveyed in a comprehensive manner. The isolated and transformerless circuit topologies have been investigated by reviewing experimental and commercial devices. The soft computing, evolutionary and swarm intelligence based algorithms have been summarized in MPPT methods section while current injection and grid-connection control methods of unfolding inverters stage have been presented with and without PLL architecture. There are many papers have been compared and listed in each section to provide further outcomes which is followed by a summarizing discussion section and conclusion.
Smart Blind Stick Using Arduino UNO
Authors:- Prof. Sushma Patwardhan, Miss. Divyata Karivadekar, Miss. Pratiksha Phadtare, Miss. Komal More, Miss. Swapnali Rabade
Abstract- In the era of technology where each and every person strives to be independent in order to survive in this competitive world, being an independent is the at most priority to almost all the people. Our project is designed to provide this independence to the visually challenged people. This project gives them helping end to commute safely and securely. This act as a Third Eye for the visually challenged people and make their difficult life little bit simple and safe. The project consists of Ultrasonic sensor used for detection of obstacles like staircase, wall and other objects. After the detection of an obstacle, it alerts the user by beep sound of the buzzer.
Alphaneumeric Hand Gesture recognition System
Authors:- Prof. Megha Beedkar, Mr.Barve Saurabh, Mr.Jadhav Rajan, Mr.Raibole Vinay, Ms.Sonawane Pooja
Abstract- The project introduces an application using computer vision for Hand gesture recognition. A camera records alive video stream, from which a snapshot is taken with the help of interface. The system is trained for each type of count hand gestures (one, two, three, four, and five) OR Alphabets (A, B and C) at least once. After that a test gesture is given to it and the system tries to recognize it.
Review of Human Face Mask Identification using Deep learning with Open CV Techniques
Authors:- M.Tech. Scholar Rahul Baghel , Associate Professor Dr. Pallavi Pahadiya, Dr.Akhilesh Upadhyay
Abstract- The 2019 coronavirus illness outbreak has become a significant threat to public health. Because of the way it behaves when in touch with other substances, it is rapidly disseminating. Therefore, the World Health Organization recommended that people in crowded settings use masks as a form of preventive. In some of these regions, the illnesses have grown quite widespread as a direct result of the incorrect use of face masks. Therefore, in order to solve this issue, we needed a mask monitoring system that was effective. By means of the development of machine learning and analytical techniques using image processing, present methods for mask detection. Image processing analysis and the approach of machine learning are both used in the process of finding out mask detection. There are a few different approaches that may be used to identify face masks. The convolutional neural network approach is the one that is utilised most often nowadays. In comparison to other organisations, CNN has a very high level of both accuracy and decision making. In this article, we will talk about a variety of deep learning approaches that may be used to recognise face masks.
Food and Medicine Serving Robot
Authors:- Asst. Prof.A. Rama Krishna Prasad, P. Sukumar, A. Narayana Teja, AA. Jagadish
Abstract- His project describes the design and development of a Serving Robot which is considered as a possible solution to address the lack of human resource and to introduce Automation. The role of robotics in healthcare and allied areas with special concerns relating to the management and control of the spread of the hazardous diseases like corona virus disease 2019 (COVID-19). The pandemic covid-19 have brought a vast change to the world and made us distant socializing rather than social distancing. The medical sectors are facing a crucial stich on this. Moreover a Bluetooth based remote controlled robot for navigating ,delivering food and Medicines can limit the interactions of medical professionals to patients. Ensuring the safety and low expansion of covid-19, the robot can be controlled anywhere from the hospital.
Interactive and Smart Refrigerator using IOT
Authors:- Raashi Taneja, Rushit Shah, Shradha Narwadkar, Manisha Kumawat
Abstract- In the modern era of technology and with increasing dependency on smart techniques like mobile phones, there is a requirement of solving daily life tasks in quick and easy ways. Smart technology is becoming the need of the hour to take control over the different tasks at home and in industries. The system proposed is based on detection and recognition algorithms. The main function of the algorithms is to automatically detect the smell and generate a message to the user that the food is spoiled. The key feature of computer vision is Arduino for reasons like marketability & law-abiding apps. Secondly, after a lot of research on the accessibility of realistic technologies, this area of research finds an important place among different types of researchers and scientists like computers, food & different organizations. The microcontroller panel can perform functions that include interpreting inputs and outputs and making the sensor activated. Generally, food is stored in the refrigerator which lowers the bacteria rate of production. Certain items which are perishable or not used for long-term storage are to be detected and informed to the user. This project is based to solve the food spoilage through sensors by continuously sensing the signals from the food and sending the alert message to the registered mobile phone.
Design & Analysis of LPG Kit for Two Wheeler
Authors:- Manish Krishna Prasad Singh, Taufik Sikandar Maniyar, MD Ghayas Alam, Associate Prof. Amol D Lokhande
Abstract- In metropolitan regions like Mumbai, Pune, and many other cities. In India, two-wheeler act a very major role in transportation. Most of the vehicles (four-stroke engines) are majorly run by petrol. In recent days petrol prices have increased and the availability of crude oil decreases. Petrol and diesel contribute a major role in global warming because it emits harmful gases and partials like carbon monoxide (CO), hydrocarbon (HC), nitrogen oxide (NOx). These gases are harmful to human health and also affect the environment. We have seen a three-wheeler (auto-rickshaw) that is also run-on LPG. In this paper, we all attempted to use alternative fuel for a single-cylinder four-stroke engine to increase efficiency and decrease the running cost. Our aim in selecting this paper is to use non-conventional fuel against conventional fuel. We have done the required modification. LPG is cheaper than petrol and it is clean gas. Gasoline/petrol has less value of octane compared to LPG and emitted less exhaust emission hence it is less harmful to global warming and human health. In this paper, the single-cylinder four-stroke engine is run on both fuels’ petrol and LPG.
A Cyber Security of IOT in 6G Era
Authors:- Mr. R Vignesh, Asst. Prof. Ms. Sumaiya M
Abstract- With the deployment of more 5g networks, the limitations of 5g networks have been found, which undoubtedly promotes the exploratory research of 6G networks as the next generation solutions. These investigations include the fundamental security and privacy problems associated with 6G technologies. Therefore, to combine and solidify this foundational research as a basis for future investigations, we have prepared a survey on the status quo of 6G security and privacy.
Cloud Computing Distinctiveness In The Real-Time Environment
Authors:- Dr.V.Mathivanan , Dr. Vimal Kumar Stephen ,Mr Mohamed Ruknudeen Raf, Mr.Senthil Jayapal , Dr. Ramesh Palanisamy i.
Abstract-Information can be shared via cloud computing on systems such as computers, tablets, laptops, or smartphones. Software and resources can be provided based on user demand for devices such as computers, tablets, laptops, and smartphones [1]. The advent of cloud computing has distorted the general notion of Infrastructure, software delivery services, and development models. In this paper, we investigate the revenue from Cloud service modes such as Infrastructure as a service (IaaS), Platform as a service (PaaS) and Software as a service (SaaS) through vertical transmission from mainframe computers to client/server deployment models. This finally leads to cloud computing, combining distributed computing, utility computing and autonomic computing into an evolving deployment architecture[2].
A Review on Maximum Power Point Tracking Using Renewable Energy Resources
Authors:- Research Scholar Rahul Kumar, Asst. Prof. Aashutosh Khasdeo
Abstract- Both the AC and DC power systems need to be updated so that they can meet the needs of the public. When DC microgrids are connected to DC renewable and storage sources, their performance is admirable because it is so efficient, consistent, and reliable, and it allows for load sharing. The main goal of any DC Microgrid’s control strategy should be to make sure that the load and power are balanced well with the Distributed Generator (DG) sources. Because renewable energy sources come and go, batteries are an important part of a DC microgrid’s load–power balancing system. There’s a chance that the plan for managing energy that’s already in place can handle the extra load. The power distribution networks that serve rural areas, on the other hand, are not made to work with this method. The results of this study give an energy management strategy, or EMS, for a DC Microgrid that can use solar, wind, super capacitors, and batteries as input sources to power remote areas. In the modelling and overall design of controllers, the rated voltage of the super capacitor is usually taken into account. The usual way to make a controller could cause the system to become unstable or cause the DC link voltage to ring when the super capacitor voltage is low. In this, the effect of changes in the voltage of supercapacitors on the stability of DC micro grids is studied, and a control design method is suggested to make sure that DC micro grids are stable in all modes of operation. The design and stability analysis of a direct current (DC) microgrid with a battery-super capacitor energy storage system that works with a variable super capacitor operating voltage.
Review on Air Pollution Detection and Purification using Air filter
Authors:- J.Jenitta, Praveen N, Vaibhav P, Shashank S Shetty, Yogesh H S
Abstract- As on today Pollution is a major problem which all the countries are trying hard to reduce it. Air pollution is a major harmful pollution. Pollution leads to severe health issues. Major reason for air pollution is the release of harmful substances from the vehicles. This paper aims to give a detailed review about methods used to detect the pollutants from the vehicle emission and various ways to purify the same.
Diabetes Prediction By Frog Jumping Algorithm and Artificial Neural Network
Authors:- Roopa Shrivastava, Prof. Rajesh Ku. Nigam, Prof. Rakesh Ku. Tiwari
Abstract- Diabetes is a disease that is continuously increasing in developed and developing countries. The efficient solution to deal with this disease is need of the time. This work has reduced the input dataset size by use of frog leaping genetic algorithm that give high effective features. Selected features will be further used for the training of neural network that give more accurate results. Use of less feature for training and testing directly reduces the evaluation complexity. Experiment was done on real dataset of users feature who might have chance of diabetes. Comparison of proposed model is done with existing techniques on different evaluation parameters. Result shows that proposed model has improved precision, recall, and accuracy of diabetes prediction.
Family Searching Assisstant
Authors:- Ms. Areej Bakdash, Dr. K. Juliana Gnanaselvi
Abstract- The Project “Family Search Assistant” is designed by Frontend as PHP and Backend as MY SQL. We will make a site that can help the people to find some boys or girls who can take care of our kids or old people in some places near from you or we also can choose the location that where we need them and then we will find them also with their details, photos experiments. This site will be very useful for families to find someone who can help them with a good price and we can get all their info.
Security with CCTV Camera and Deep Learning with Python
Authors:- Durgesh Rao
Abstract- The Corona Virus Disease known as COVID- 19; An Acute Respiratory Syndrome Coronavirus-2 Disease called SARS-CoV-2. As, this virus is genetically related to the SARS outbreak of 2003. This deadly and unstoppable disease, which all started in Wuhan, China in Dec 2019, was declared as the World Pandemic on 11 March, 2020 by WHO World Health Organization. Face Mask and Social Distancing are the Best Precautions for staying safe. These Research Papers focuses on implementing Real Time Face Mask Detection using CCTV Closed- Circuit Television Camera and Deep Learning, to Catch the Real Culprit of Virus Spread and Report him or her Immediately.
Design of Kalman Adaptive Filter Thresholding and EMD based De-noising Method for ECG Signals
Authors:- Monisha Lodhi , Silky Pariyani
Abstract- An ECG signal is usually corrupted by various types of noises. Some of these noises are power line interface, baseline drift, muscle contraction, motion artifacts, electrosurgical noise, instrumentation noise and electromyography noises. It is highly required to develop a method which can filter ECG signal noises significantly. In this work, an EMD along with adaptive switching mean filter based new method for de-noising of ECG signal has been proposed. Unlike, conventional EMD based de-noising approaches, where only lower orders IMFs are denoised in this work, along with EMD, ASMF operation has been employed for further signal quality improvement. The lower order IMFs are filtered through wavelet de-noising technique to reduce high-frequency artifacts and retain the QRS complexes. Then, considering the effectiveness of ASMF, for further enhancement of signal quality adaptive switching mean filtering is performed. The validity of the performance of the described technique is evaluated on standard MIT-BIH arrhythmia database. Gaussian noise at different signal to noise ratio (SNR) levels are added to the original signals.
Performance of Energy Consumption and Communication Overhead in WSN Using Clustering Techniques
Authors:- Himani Pidi Paras, Rajat Saxena
Abstract- During the past few years, Wireless Sensor Networks (WSNs) have become widely used due to their large amount of applications. The use of WSNs is an imperative necessity for future revolutionary areas like ecological fields or smart cities in which more than hundreds or thousands of sensor nodes are deployed. In those large scale WSNs, hierarchical approaches improve the performance of the network and increase its lifetime.In this paper, we are using self-organizing map (SOM) based clustering methods. The Simulation a result indicates that a cluster based protocol has low communication overheads compared with the velocity in m/s based protocol.
Plant Leaf Disease Detection Using Image Processing
Authors:- C Manikanta Reddy, Golla Lakshmi Prasanna, Gonuthala Sreevidya, Maddha Siva Kishore,Associate Prof. Iliyaz Pasha M
Abstract- The major cause for decrease in the quality and quantity of agricultural production in plant diseases. A farmer faces very high difficulties in identifying and controlling plant diseases. So, a very huge importance for leafs in order to diagnose the plant diseases at early stages so that the accurate and the suitable action can be done by the farmers to avoid further losses. The project focuses on the approach based on image processing using machine learning for identification of plant diseases. In this project we use machine learning algorithms to test and train the data. The data set contains both healthy and unhealthy leaf images. At last by comparing the input image and trained image we can detect the disease. By this we can control the loss of the crops.
Thermal Analysis of Vapour Compression Refrigeration System with R22, 4404A, R407C and R410A Refrigerants
Authors:- Amit Kumar, Prof. Abhishek Bhandari
Abstract- Refrigeration and air conditioning (RAC) play a very important role in modern human life for cooling and heating requirements. This area covers a wide range of applications starting from food preservation to improving the thermal and hence living standards of people. The utilization of these equipment’s in homes, buildings, vehicles and industries provides for thermal comfort in living/working environment and hence plays a very important in increased industrial production of any country. On the basis of comparison of COP with different refrigerant, VCRS with R22 has max. COP as compared to others. Max. Compressor work with R407C is achieved i.e. 28.57 KJ/Kg. Max. Heat rejected from evaporator and condenser is achieved with 22 i.e. 147.9 KJ/Kg. Therefore, R22 can be used for achieving maximum COP with VCRS.
Hearing aid using Reverse Piezoelectric Effect
Authors:- M Prithvi Raj, Nikhil V, Prashanth Manoj, Tushanth L, Ms Manasa S
Abstract- The hearing device described in this study uses reverse piezoelectric technology and differs from conventional hearing aids in a number of ways. Sound waves are transmitted to the three major bones by bone conduction (Malleus, Incus, Stapes). Electrical pulses are converted into mechanical stress using piezoelectric transducers (vibrations). The goal is to create a low-cost gadget that does not require implants. We concentrate on talking about the construction and operation of hearing aids.
Design Optimization of B- Pillar of Car
Authors:- M.Tech. Scholar Ankur Kumar Rathore, Dr. Pankaj Agarwal, Dr. Ashish Manoria
Abstract- For protection of passengers in accidental scenarios, the B-pillar design and manufacturing must be in line with existing standards and techniques to enhance resistance to impact which may depend on a number of factors including material and welding techniques. Therefore, in order to validate the efficiency of a B-pillar for proper design and reinforcement, it is necessary for the design to be analysed by Finite Element Analysis (FEA) using appropriate Computer Aided Engineering (CAE) software. FEA is a numerically analysis techniques for structural engineering designs. This involves design with the aid of complex software and FEA solvers, which can be used in analysing the effect impacts, vibration stress, heat transfer etc. It functions as a mechanism of linked points referred to as nodes which combined arrangements make up an element often referred to as a mesh (Roymech, 2016). Therefore, this study attempts to analyse and optimize the design of B-pillar using Taguchi method.
Productivity Improvement in Manufacturing Industry Using Industrial Engineering Tools
Authors:- M.Tech. Scholar Rupesh Mahajan, Prof. Nitesh Mishra
Abstract- This study presents a novel analysis for the control of manufacturing flaws. This investigation focuses on the tube bending process. The chosen component was generally rejected due to defects in a cross section of the tube flatness. Six Sigma, the zero-defect approach, is used in this research. A strategy for increasing productivity is a method for increasing the production of brake shoes. The collection of data is intended to provide an analytical foundation, that is, to turn data into information that decision makers and value may use. However, before data can be collected, a data collection plan must be developed. Data is obtained in order to identify, analyse, and eliminate the manufacturing facility’s bottleneck station. The collected data is viewed immediately on the shop floor through continuous assessment of each machine using a stop-watch.
Deep Learning Techniques Based Plant Leaf Disease and Prediction
Authors:- Mayur Kumar Bundela, Assistant professor Ms. Priya sen
Abstract- The latest advances in deep learning indicate that repeated image appreciation organization using convolutional neural network (CNN) models can be very beneficial in such troubles. Since the plant leaf disease imaging dataset is not readily accessible, we used transfer learning to enlarge our deep learning model. Accurate or timely recognition of diseases in plants leaf can help farmers to deal with plants in time, which can greatly reduce economic losses. The latest development of the deep learning-based convolutional neural network (CNN) has vastly enhanced accuracy of image classification. Driven by CNN’s success in image classification, this paper developed a deep learning-based method for detecting infection from images of plants leaf. The contribution of this work has two aspects: The most advanced deep learning architecture, such as ResNet50, DenseNet, used for recognition of the plant leaf disease .Training, testing and experimental results show that proposed architecture can realize and higher ResNet50 model getting is 95%.accuracy as compare to other model.
Stock Market Prediction Using Machine Learning Algorithm
Authors:- Diviesh Chaudhari, Pranay Bafna, Shubham Jadhav, Jay Chaudhari, Prof. V.T. Patil, Prof. V.O.Patil
Abstract- Stock Market is one of the Important thing in any Country’s Economic Point Of View, people need to understand the way of stock changes and how can a stock behave in next Period of Time where it is Pretty Much Interesting that to Predict a Stocks. Prediction of Stocks are very much Interesting not for trading community as well as it also for Computer Enthusiastic Public Also. When we think About Prediction that it can be happen in two ways that prediction can be happen because of previous data values and the other way is look and understand the News and Data in the Digital Media. In Previous data there is problem is Unavailability of the data or some data which is available which might get bad prediction because some point their accuracy is less because of changing patterns. Some of stocks have the valuable parameter Like “Return Rate”, but at some point Due to Unavailability of Data, but the other side return rate need to find out Opening and closing Price of the Parameters we are here to focus on predicting long term value of the stock is relatively easy than predicting on day-to-day basis as the stocks fluctuate rapidly every hour based on world events. Our system will predict the stock prices for the next trading day and for the specific date. The prediction model will notify the up or down of the stock price movement for the next trading day and investors can act upon it so as to maximize their chances of gaining a profit. The accuracy of the prediction is evaluated and gives a percentage of accurate result. Combining the accuracy and the prediction, recommendation can be given to the user to acknowledge them the trend of the target stock with known accuracy.
Blockchain Enabled E-Voting
Authors:- Ali Saeed Mohamed, Asst. Prof. Mrs. Sulthana A.S.R, Mca. M. Phil
Abstract- In addition in block chain enabled e-voting computing technology there is a group of critical political issues which include the issues of privacy security and anonymity and the ability to communication and government control reliability responsibility and others But most of them are Security and how cloud provider confirms this Overall block chain enabled e-voting has many customers like ordinary users academia and corporations who have different motivations to move to the cloud Overall block chain enabled e-voting has many customers like ordinary users academia and corporations who have different motivations to move to the cloud Overall block chain enabled e-voting has many customers like ordinary users academia and corporations who hava different motivations to move to the cloud Security issues in block chain enabled e-voting such as the availability of the service.
Utilisation With Forecasting Of Demolish And Construction Waste In Environment Management
Authors:- Vianjal Badjatiya, Pallavi Gupta
Abstract- Construction is an important aspect of infrastructure and growth in developing countries. In this process the construction industry produced a large quantity of waste which is harmful environmentally and costly for budgeting the project. So waste management is important for construction industry. Construction waste management defines as reduction recycling and utilize of waste by proper management of resources. In this paper, we are going to review on the major sources and factors of generating construction waste by critical literature review. At last, developed framework for the future research in this area.
A Review Article Novel Approach Ofdm 5g Communication and Papr Minimization Using Modified Clipping Method
Authors:- Preeti Tembhurne, Swati Nigam
Abstract-To improvement of voice signal quality and reducing its noise level to implementation of various type method like filter and Compression etc. Hence observation of various article obtained maximum methods is not compatible of real time speech signal. So our proposed implementation gives a topological method to formulation of noise problem and real time speech signal processing. Its numerical technique are called of thresholding based DWT (Discrete wavelet Transform). This approach available of multiple decomposition and Composition to reduce of noise level in terms of db.
Strength evaluation of Geopolymer Concrete with C&D Waste
Authors:- Ilamugilan.C, Jerold Gnanaseelan.J, Asst. Prof. Nithyapriya.K, Subash Chandra Bose.S, Suryavarman.R.
Abstract- Global warming and climate change are increasingly threatening issues nowadays and cement industries alone emits 0.8-2 tonne of carbon dioxideper tons annually and the cement production alone estimated to be 1.35 billiontons annually by equating to approximately 5 percent of global total greenhouse emissions. This requires for the alternative construction materials to lessen the carbon emission, and to carry a sustainable development. One such is thegeopolymer concrete, it is the useful invention in the world of concrete and this paper presents the overview of recent advances of geopolymer concrete, a concreteformed organic/inorganic materials using alkaline solution. Which means thecement is totally replaced by pozzolanic material that is rich in silica and alumina that may be natural or artificial, and the alkaline liquid is activated to act as binder in concrete by means of polymerchains. In addition to that C&D waste (Construction and demolition waste) is usedas a partial replacement of coarse aggregate. The studies states that geopolymerconcrete posses the advantages of rapid strength gain, elimination of water curing,good mechanical and durability properties, eco-friendly and sustainable. In the present study C&D waste is used as partial replacement of natural coarse aggregate in geopolymer concrete at 0%, 5%, 10%, 15%, and 20% by weight. The flyash is used as the source material for geopolymer and 16M sodium hydroxide and sodium silicate alkali activators are used to synthesize the flyash geopolymerconcrete. This study is to compare the rapid strength gain of the geopolymer concrete without replacement of coarse aggregate and the geopolymer concrete with the partial replacement of coarse aggregate.
System Dynamic Simulation Modeling for Enhancing Green Environment through Energy Savings
Authors:- Doctoral Research Scholar Rathiga. J, Prof. Dr. Umadevi. G
Abstract- The fundamental stream characteristics are speed, flow, and density. Traffic density it is an important characteristic that engineers can use in assessing traffic performance from the point of view of users and system operators. Speed and travel time are fundamental measurements of a highway’s traffic performance and speed is a key variable in the design of roadway facilities. Some models use speed or travel time as an input for the estimation of fuel consumption, vehicle emissions, and traffic noise. Theoretical model relating fuel consumption, emission, modal split, v/c ratio, LOS, and speed is then developed, using STELLA 9.0.1. The results shows that in desirable scenario, as the percentage of public transport increases, the level of service, V/C ratio and Speed improves. The emission levels have decreased in desirable scenario, when compared to do minimum scenario. This is because, the public (Bus & Auto’s) share is increased, and the private (TW’s & Cars) share is decreased. As well as diesel cars are replaced with CNG cars and diesel bus with CNG bus.
Experimental Study of Strength and Behaviour of Gypsum with Sugarcane Bagasse Ash in Polymer Impregnated Mortar
Authors:- Anto Moses Mukilan A, Arumugam Essaki S, Akash Aravind S
Abstract-The industrial wastes due to their high performance when blended with the building materials generated great impact in the field of structural engineering. Many industries are looking for the cos effective use of their industrial waste. This paper represents the result of an experimental investigation carried out to study the gypsum with sugarcane bag asses’ ash in polymer impregnated mortar. Gypsum and sugarcane bag asses ash are waste materials from various industry. In this report gypsum was partially replaced with three percentages (10%, 20%, and 30%) of bag asses’ ash weight. Gypsum mortar was prepared by in the mix ratio 1:2 control mix mortar. After the initial test is carried out the specimens are casted and cured for 28 days at room temperature. The specimens are immersed in PVA solution for 5 minutes. After that this specimen are dried out and the compressive strength test as well as split tensile strength test is determined.
Application of Big Data in LegalCase Investigation
Authors:- Rahul Dhanji Gupta
Abstract-According to the 2020 report of the National Judicial Data Grid, over the last decade, 3.7 million cases were pending across various courts in India, including district, taluka courts and High courts.With the rapidemergence of information Technologyanddevelopmentin recent years. Many criminal cases have become sophisticated and secret. The Conventional investigation method has been very difficult to cater the demands of the times. With the continuous development of big data, it has been used in multiple domains. The fallowing paper reviews the pros of big data and application in legal context.
Live Video Emotion Detection Using Convolutional Neural Network
Authors:- Bibithamol Baby, Christy Jojy
Abstract-The human face plays an important role in the field of Human Computer Interaction (HCI) for real time applications like driver state surveillance, personalized learning, health monitoring etc. While communicating, only 7% of message is conveyed by spoken words, whereas 38% by tone of voice and 55% effect of the speaker’s message is contributed by facial expressions. Although humans possess various emotions, modern psychology defines seven basic facial expressions: Happiness, Sadness, Surprise, and Fear, Disgust, neutral and Anger as “Universal Emotions”. Most reported facial emotion recognition systems, however, are not fully considered subject-independent dynamic features. So, they are not robust enough for real life recognition tasks with subject (human face) variation, head movement and illumination change. Most of the existing systems use SVM’s and Clustering techniques to train the machine learning model. But these models have a less accuracy as they can’t adapt to live videos. Therefore, we propose to build a model which identifies the human emotions from a real time live video using CNN (convolutional neural networks) which gives more accurate results.
VLSI Architecture of Filter for Image Denoising: A Review
Authors:- Research Scholar Aarti Sharma, Asst. Prof. Shweta Garde
Abstract-Image processing has many of the application in current scenario. During the image capturing or processing, some noise mix with the original image. Due to the noise issue the overall performance down or sometimes it failure. The images pixels mix with these types of the noise signal. There is various filters design which avoids or removes the noise signal. The advancement of the technology is going with the advance ICs processing. The VLSI architecture of filter design is useful in the FPGA ICs for the image processing applications. This paper reviews about the low-cost VLSI architecture of the filter for image denoising.
Survey on Existing Student Management System
Authors:- Prof. Sumesh M.S, Jayanth Ramavarma, Sagar Saji, Sreehari Jeevan, Vinayak Sivaprasad
Abstract- Student Management System is software which is helpful for the students as well as the school authorities. In the current system, all the activities are done manually. So it is very time consuming and costly. In this paper, our main focus is to design a unique Student Management System that will improve Data Management in Institutes experience for both Students and the Administration authorities. The whole system will run on the internet. Users will have the ability to log in from any place with an internet connection. After that they will be able to do various tasks that are designed for them. This design mainly deals with the various activities related to the students.
Research on Image Activity Transformation into Readable Caption Using Deep Learning Algorithm
Authors:- Himaniadiga, Mallikarjunav.R, Mandarab, Mangala S, Prof. Dr. Praveenkumar KV
Abstract- In Recent years, with the rapid development of artificial intelligence, image captionhas graduallyattracted the attention of many researchers in the field of artificial intelligence and has become an interesting and arduous task. Image caption, automatically generating natural language descriptions according to the content observed in an image, is an important part of scene understanding, whichcombines the knowledge of computer vision and natural language processing. the application of image caption is extensive and significant, for example the realization of human computer interaction. This paper summarizes the related methods and focuses on the attention mechanism which plays an important role in computer vision and is recently widely used in image caption generation tasks. Furthermore, the advantages and the shortcomings of these methods are discussed providing the commonly used datasets and evaluation criteria in this field. Finally, this paper highlights some open challenges in the image caption task for a computer to generate context describing the image given as input takes a lot of effort in terms of computation memory usage and processing minute details present in the image. All the great progress has been made in ML, artificial intelligence, deep learning image processing it is always a challenging task for a computer to generate a text describing an image accurately with semantically and grammatically correctsentence.
Analysis of Fake News in a Twitter Data Set for a Food Review
Authors:- M. Tech. Scholar Rema Varma, Asst.Prof. Megha Gupta Jat
Abstract- The current day and age of the internet is characterised by the widespread dissemination of ideas and opinions among users through various forms of social media, including microblogging sites, personal blogs, and reviews. The reviews come from a variety of individuals and include topics such as a particular product, business, brand, person, forums, companies, brands, movies, etc. An important component of text mining is known as sentiment analysis. people’s opinions were analysed and the resulting tweets were categorised as either positive, negative, or neutral. In this paper, work data will be collected from Twitter’s API, and the sentiment of tweets and reviews of published papers will be identified by searching for particular keywords. After that, the polarity of tweets will be evaluated based on the percentage of tweets that are classified as being positive. Negative. Having done so, the data were then input into a supervised model for the purpose of evaluating additional data sets. Methods and technologies related to machine learning are used. Machine learning classifiers such as Naive Bayes (NB), Maximum Entropy, Random Forest (RF), and Support vector machine SVM classifiers are used for testing and training of the data sets, as well as evaluating the Polarity of sentiment of each tweet based on this analysis. These classifiers are used for testing and training of the data sets. Demonstrate that the end product gives us a performance of classifiers that has the maximum accuracy by evaluating the parameters. Utilizing machine learning classifiers such as RF, DTs, and SVM, as well as increasing the amount of tweets, accuracy of feature evaluation will be performed. Using the same process in subsequent studies may allow for the addition of more characteristics that may be used to improve the accuracy of the prediction.
A Look at Some Different Methods of Image Processing That Can Detect Glaucoma
Authors:- M.Tech. Scholar Akanksha Kumayu, Asst. Prof. Lokendra Jat, Asst. Prof. Megha Gupta Jat
Abstract- This review article discusses the use of a variety of image processing methods with the purpose of providing an automated diagnosis of glaucoma. Glaucoma is a neurological illness that affects the optic nerve and may lead to a loss of some of one’s eyesight. Eye problems affect a significant number of individuals in the world’s rural and semi-urban regions, and this is true in every region. The examination of a picture of the retinal fundus using image processing is now the gold standard for diagnosing retinal diseases. Image registration, image fusion, image segmentation, feature extraction, image enhancement, morphology, pattern matching, image classification, analysis, and statistical measures are some of the essential image processing methods for detecting eye illnesses.
Review of E-Mail Spam Filtring Using Machine Learning Classification Technique
Authors:- M.Tech. Scholar Neetu Ahirwar, Reshma Shivhare (HOD)
Abstract- One of the safest methods for online communication and sending data or messages over the internet is email. Along with an excessive rise in popularity, the amount of unwanted information has significantly expanded. There are many methods for filtering data that automatically identify and eliminate these undesirable signals. There are several methods for detecting spam in email, including knowledge-based methods, clustering methods, learning-based methods, heuristic procedures, and others. This study provides an overview of several machine learning techniques (MLTs) for email spam filtering, including Naive Bayes, SVM, K-Nearest Neighbor, Bayes Additive Regression, KNN Tree, and rules. However, in this article, we classify, assess, and compare various email spam filtering systems and provide a summary of the general situation with relation to the accuracy rate of various currently used methods.
A theoretical Model to make the Effective and Novelty Approach to Use the Solar Energy to Generate Electricity and Water Treatment towards the Optimization of Non-Renewable Energies Utilization by Using Magnifying Glass Tetragonal Dipyramid Shape System
Authors:- M.Muthuganesh, S.Baghavathi Babu
Abstract- The effective utilization of renewable energies is not yet achieved to optimize the utilization of non-renewable energy sources because of various difficulties and hurdles to get easy practicable approach systems. By considering the needs of modern techniques to solve this problems and meet the above challenge, we identifying one of the practically applicable novelty approach system to reduce the non-renewable energy utilization with effective utilization of the solar energy to treat the water and produce the electric power by introducing tetragonal Dipyramid magnifying glass dome system. This novelty approach of these duel system of treating water and generating electric power as a combined unit will leads to the technological development in the renewable energy resource utilization.
Review on Utilization and Management of Scrap Steel in Form Construction Fiber Concrete
Authors:- M.Tech. Scholar Aditya Srivastava, Associate Prof. Mr Satish Parihar
Abstract- In the construction of any industry or structure there is a common material used as concrete. And concrete is is used in very huge amount in the construction and industries. Many property of the the concrete like brittleness sometimes fails to bear tensile load which is the cause of brittle failure. Since the fibre have the property to increase the toughness of the concrete. In many experiments it is found that, steel fibre reinforced concrete have high resistance to cracking so the reason behind the increasing uses of steel fibre reinforced concrete to increase the hardness or toughness and to reduce the crack deformation characteristics. So I present this paper for theoretical discussion on the subject of of steel fibre reinforced concrete. And here we discuss use terms and models of behaviour that form ambitious for understanding material performance without mathematical details. Here we shown that flexural strength of steel fibre reinforced concrete is directly proportional to the the steel fibre content and inversely proportional to the water cement ratio. Why the different references from early and old authors are included as a means of tying the subject together along a timeline. In the current time by the historical review to build a background for what is currently understood about steel fibre reinforced concrete.
Performance Analysis of Different Routing Protocols In Mobile Ad-Hoc Networks
Authors:- Ripusudan Vishwakarma , Rajat Saxena
Abstract- MANET stands for Mobile Adhoc Network also called a wireless Adhoc network or Adhoc wireless network that usually has a routable networking environment on top of a Link Layer ad hoc network. A MANET can be defined as an autonomous system of nodes or MSs(also serving as routers) connected by wireless links, the union of which forms a communication network modeled in the form of an arbitrary communication graph. The characteristics of an ad-hoc network can be explored on the base of routing protocols. The dynamic topology is the vital characteristic in which nodes frequently change their position. In the ad-hoc networks, there are mobile nodes such as personal digital assistance (PDA), smart phone and laptops; they have limited operational resources like battery power and bandwidth. We have performs in this paper different routing protocols in mobile ad-hoc networks.
A Review on Utilization of Plastic Waste with Polymer Improvement of Soil Strength Using Geosynthetic Pavement
Authors:-M. Tech. Scholar Shubham Nigam, Associate Prof. Mr. Satish Parihar
Abstract- Geopolymer concrete (GPC) is a new material in the construction industry, with different chemical compositions and reactions involved in a binding material. The pozzolanic materials (industrial waste like fly ash, ground granulated blast furnace slag (GGBFS), and rice husk ash), which contain high silica and alumina, work as binding materials in the mix. Geopolymer concrete is economical, low energy consumption, thermally stable, easily workable, eco-friendly, cementless, and durable. GPC reduces carbon footprints by using industrial solid waste like slag, fly ash, and rice husk ash. Around one tonne of carbon dioxide emissions produced one tonne of cement that directly polluted the environment and increased the world’s temperature by increasing greenhouse gas production. For sustainable construction, GPC reduces the use of cement and finds the alternative of cement for the material’s binding property. So, the geopolymer concrete is an alternative to Portland cement concrete and it is a potential material having large commercial value and for sustainable development in Indian construction industries. The comprehensive survey of the literature shows that geopolymer concrete is a perfect alternative to Portland cement concrete because it has better physical, mechanical, and durable properties. Geopolymer concrete is highly resistant to acid, sulphate, and salt attack. Geopolymer concrete plays a vital role in the construction industry through its use in bridge construction, high-rise buildings, highways, tunnels, dams, and hydraulic structures, because of its high performance. It can be concluded from the review that sustainable development is achieved by employing geopolymers in Indian construction industries, because it results in lower CO2 emissions, optimum utilization of natural resources, utilization of waste materials, is more cost-effective in long life infrastructure construction, and, socially, in financial benefits and employment generation.
Research On Image Activity Transformation Into Readable Caption Using Deep Learning Algorithm
Authors:- Himaniadiga, Mallikarjunav.R, Mandarab, Mangala S, Dr. Praveenkumar Kv
Abstract- In Recent years, with the rapid development of artificial intelligence, image caption has gradually attracted the attention of many researchers in the field of artificial intelligence and has become an interesting and arduous task. Image caption, automatically generating natural language descriptions according to the content observed in an image, is an important part of scene understanding, whichcombines the knowledge of computer vision and natural language processing. the application of image caption is extensive and significant, for example the realization of human computer interaction. This paper summarizes the related methods and focuses on the attention mechanism which plays an important role in computer vision and is recently widely used in image caption generation tasks. Furthermore, the advantages and the shortcomings of these methods are discussed providing the commonly used datasets and evaluation criteria in this field. Finally, this paper highlights some open challenges in the image caption task for a computer to generate context describing the image given as input takes a lot of effort in terms of computation memory usage and processing minute details present in the image. All the great progress has been made in ML, artificial intelligence, deep learning image processing it is always a challenging task for a computer to generate a text describing an image accurately with semantically and grammatically correctsentence.
An Experimental Study on Self Compacting Concrete with Recycled Concrete Aggregate
Authors:- PG Scholar Seethal T M, Asst. Prof. Mr.M.Sadhasivam
Abstract- The usage of natural aggregate is becoming more intense with the advanced development in construction. Recycled aggregate can be used as a suitable replacement for natural aggregate. Recycling of aggregate material from construction and demolition waste may reduce the demand – supply gap and reduce consumption of natural resources. The advance in the pre stressed concrete and multistoried structures has given impetus for making high performance concrete. When the general performance of concrete is substantially higher than that of normal type concrete, such concrete is regarded as high performance concrete (HPC). High- performance concrete (HPC) exceeds the properties and constructability of normal concrete.HPC is usually more brittle when compared with normal strength concrete, especially when high strength is the main focus of the performance. These deficiencies can be overcome by adding fibres. Fibre reinforced concrete has become popular due to its crack arresting mechanism, strengthening property, high energy absorption properties, ductile behavior and post-cracking tensile strength. The aim of this thesis is to study the flexural as well as shear behaviour of fibrere in forced high performance recycled aggregate concrete in beams under monotonic for optimum percentages of fibres.
Smart Pesticide Spraying Robot
Authors:- Prof. Sushma Patwardhan, Mr.Adinath Kadam, Mr.Sourabh kothawale, Ms.Jagruti Kotkar, Mr.Tejas Ghodke
Abstract- pesticide spraying ramble is the device for exact pesticide spraying equipped nebulous shapes and variable article targets. the gadget incorporates a solitary splash siphon engine with a consequently separate flexible spraying utilizing ultrasonic sensors, all mounted on a pan tilt unit. the site-explicit spraying gadget plans to splash explicit targets while diminishing the utilization ofpesticides. the proposed framework includes the advancement of an article explicit sprayer arrangement. Created gadget intends to diminish pesticide application by spraying singular targets explicitly by setting the item separation of the spraying as per the objective. the spraying device is equipped for decreasing the measure of pesticides connected. real reserve funds rely upon the spraying lengths, target size, and appropriation. we trust that such a device can be utilized in present day farming and can be joined with an automated sprayer exploring independently along yield fields. such a gadget will add to decreased pesticide application. the aim of this paper is to create an intelligent spraying robot that will decrease pesticide use andhuman health damage, allowing farmers to be protected and labor intensity can be reduced. the robot will have full route planning and navigation systems, as well as driving control, spraying mechanism and system construction and obstacle avoidance with multi- sensor module integration.
Agriculture Protection from Animals Using Smart Scarecrow System
Authors:- Prof. Harshalata Mahajan, Mr. Jaydeep Farate, Mr. Vishnu Sankpal , Mr. Dhananjay Choudhari, Mr. Purvesh Bokade
Abstract- Subsistence farmers of our country repeatedly encroaching wild habitats so interaction between farmer and wildlife increases resulting into the conflicts. We studied how the pattern of raiding changes according to different seasons, farm land and crop types. A smart scarecrow system is constructed to minimize crop raiding and man animal conflict from wild animals and birds. The scaring system works in three parts: time delay, servo control with flash light and automatic sound system. Depending upon seasonal cropping pattern sound of the system get automatically adjusted using mp3 module. In our study we take samples from different farms combined and observed how object detection vary at day and night in three seasons which gives monthly efficiency of the system. It is more convenient and cost effective than traditional scaring strategies like trapping, hunting and wood fencing. No manpower is required for scaring. The present system is made up of metal body so it can work in worst climate conditions.
Power Grid Failure Detection System using Arduino
Authors:- Dr.B. Durai Babu, Samera Salim Sulaiman Al-Saadi, Badour Majid Salim Mohammed Al-Azri
Abstract- Recent advancement in power system made possible to deliver electrical energy from the power station to the consumer through big network of transmission and distribution. To supply power there are several power units connected to the grids. For the proper operation we must provide consumers with constant voltage and frequency. In this project we have designed a system to sense abnormalities in voltage and frequency in order to detect the synchronization failure in power grids. To maintain the power quality and frequency of the grid voltage synchronization technique plays a vital role. In our project we used PLL (Phase Locked Loop) synchronization technique for grid integration. In this project, we have designed and developed a system for monitoring and measuring voltage and frequency so that these parameters are maintained within limits. If any deviation from the acceptable limit feeder should be disconnected from the grid so that black out of power can be avoided. So, we developed a system which warn the grid in advance so that alternative arrangement can be done to avoid complete grid failure. Arduino monitors the under/over voltage received from the comparators and lamp load is used to predict the blackout incase voltage/frequency going out of acceptable range.
Online Car Parking Application Using GPS Mapping
Authors:- Tanishq A. Injal,Shweta V. Jadhav,Ankita A. Madakari,Shivani N. Nimbalkar, Asst. Prof. Mrs. P. G. Sanmane
Abstract- Online Car Parking application using GPS mapping is an application built to book parking slots by allotting free parking slots. This application is to reduce the traffic in parking slots.In the multiplexes, cinema halls, large industries, shopping-malls, and function halls there is problem, that people have to go and search for free space to park the vehicle. Hence for parking, man power is required for parking vehicles in correct slot and its money consuming process. Also, when people park their vehicles in no parking zones their vehicles are taken away by towing vans and they have to pay the penalty. This problem can be solved by providing people a platform to easily book their parking slots before going on roads with this online parking slots booking application.
Wavelet Compression Techniques for Video Data Using Bit-Plane Complexity Segmentation
Authors:- Ismail Hassan Farah, Dr. K. Juliana Gnanaselvi
Abstract-This project presents a steganography method using lossy compressed video which provides a natural way to send a large amount of secret data. The proposed method is based on wavelet compression for video data and bit-plane complexity segmentation (BPCS) steganography. In wavelet based video compression methods such as 3-D set partitioning in hierarchical trees (SPIHT) algorithm and Motion-JPEG2000, wavelet coefficients in discrete wavelet transformed video are quantized into a bit-plane structure and therefore BPCS steganography can be applied in the wavelet domain. 3-D SPIHT-BPCS steganography and Motion-JPEG2000-BPCS steganography are presented and tested, which are the integration of 3-D SPIHT video coding and BPCS steganography, and that of Motion-JPEG2000 and BPCS, respectively. Experimental results show that 3-D SPIHT-BPCS is superior to Motion-JPEG2000-BPCS with regard to embedding performance. Steganography is the art and science of communicating in a way which hides the the existence of the secret message communication. It aims to hide information/covered writing. Information to be protected is hidden in another data known as cover or carrier. Data containing hidden message are called as Stefano’s or Stegos. Steganos look like cover data and it is difficult to differentiate between them. Steganography based communication over easily accessible platforms to prevent leakage of information.
Influence of Wood Fiber On The Performance Of Stone Matrix Asphalt Using Slag As Aggregate Replacement
Authors:- Pusapatri Venu , K.Sreekar Chand
Abstract-Stone grid black-top , was most importantly evolved in 1960 in Germany which currently generally assists in giving a more noteworthy long-lasting twisting obstruction, strength to surfacing materials, longer help life, worked on maturing ,high opposition in breaking, weakness, wear, better pallet opposition and like in diminishing with noising. It is a hole evaluated combination of totals which helps by boosting the black-top concrete substance and parts of coarse total . It is a steady, groove safe blend and extreme which depends on total contact for giving strength . Alongside rich mortar cover it gives better strength. The SMA test is ready by blending coarse total, fine total , filler according to the degree diagram given by the standard code while utilizing stabilizer and without stabilizers. . A fiber that is promptly accessible in nature. less practical contrasting with other non regular filaments has been utilized as stabilizer. It is Bamboo fiber, which is cellulose fiber separated from normally accessible Bamboo stem. It has high strength in fiber heading, more prominent pliable, flexural and influence strength. Slenderness level of fiber can without much of a stretch be gotten from it. It is sturdy in nature, has relentlessness and great soundness esteem. An endeavor has been made to figure out its appropriateness in expanding the steadiness and stream esteem in the combination of Stone Matrix Asphalt Mixes. For this undertaking, we have arranged SMA blends involving stone as coarse total, slag in halfway substitution of coarse total and utilized various stabilizers and have attempted to look at the outcomes at a differing bitumen content of 4,5,5.5,6,7 % bitumen. The stabilizers were utilized at an ideal of 0.3% of the heaviness of test.
Review of Under Water Communication
Authors:-Babita Suryavanshi, Er. Lokendra Jat, Er. Megha Gupta Jat
Abstract- This essay offers a clear and comprehensive overview of the directions that our research on the topic of underwater sensor networks will go in the future. In this article, we explore the potential applications of underwater robotics, equipment monitoring, and seismic monitoring in offshore oil fields. In this paper, we examine the future opportunities for research in the fields of MAC, short-range acoustic communications, localization protocols and time synchronisation for high-latency acoustic networks, application-level time scheduling, and long-duration network sleeping.
Developing Autonomous Luggage System Using Arduino
Authors:- Pradeep Saroj, Rahul Varma
Abstract- People in the world today use many modes of transport to travel from A to B in the shortest amount of time. Traveling with luggage is always important.Each piece of luggage has its own meaning, function and practicality. We all experienced frustration with carrying luggage while traveling. It is a time-consuming process that contributes to our fatigue and road difficulties. The idea of the Autonomous Baggage project is to prevent the suitcase from being pushed away. To do this, we will create an autonomous baggage system that can successfully track users by bypassing obstacles and sending coordinates from mobile phones. Baggage will track you. Arduino UNO is used to integrate all the electronic components used in the project. In addition, we will introduce a new luggage function that is easier and more convenient to use.
Design and Fabrication Of Semi Automated Areca Nut Collecting Machine
Authors:- Priya S, Shubham S Naik, Sneha E S, Sushma G, Dr.Usha Rani, Dr.Swetha Rani
Abstract- The Indian economy most desperately needs the field of agriculture. The areca palm, which grows in Coorg, Shivmoga, and some locations in Karnataka, produces the areca nut as its seed. Areca nut automatically falls to the ground as a result of wind and heavy rain. The main issue encountered when collecting areca nuts from the ground is that it takes a lot of labour and takes a long time. We put in place a machine for digging up areca nuts to solve this issue. For identifying areca nuts, the Raspberry Pi can be used with openCV. The areca nut is extracted from the ground using a robotic arm. There are numerous machines available for drying, separating, and scraping areca nuts. This essay investigates the notion of gathering areca nuts.
Intelligent Traffic Controlling and Assisting Road Divider
Authors:- Yaseen B S, Syed Saif, Shyam Sunder Tiwari, Sufiya Kouser, Asst.Prof. Victor Jeyaseelan D
Abstract- Road Divider is generically used for dividing the road for ongoing and incoming traffic. This helps in easy flow of traffic; generally, there is equal number of lanes for both ongoing and incoming traffic. The problem with Fixed Road Dividers is that the number of lanes on either side of the road is fixed. Since the resources are limited and population as well as number of vehicles increasing day by day, there is significant increase in number of vehicles on roads. This calls for better utilization of existing resources like number of lanes available. For example, in any city, there is industrial area or shopping area where the peak traffic generally flows in one direction in the morning or evening hours. The other side of Road divider is mostly either empty or much underutilized. This is true for peak rush hours. These results in loss of time for the vehicle owners, traffic jams, time consuming as well as underutilization of available resources. Our aim is to create a mechanism of automatic road divider that can shift lanes, so that we can have desirable number of lanes in the direction of the rush. The collective impact of the time and fuel that can be saved by adding even one extra lane to the direction of the rush will be significant. And also detecting traffic rules violations and giving priority to emergency vehicles with speed breaker deactivation if any so that the whole roadway system is utilized efficiently and effectively .
To Provide Security for Database Using Encryption and Decryption
Authors:- Asst. Prof. M.Thangamani M.Sc, M.Phil, B.Ed
Abstract- Encryption is the process of transforming information from an unsecured form or Plain Text into coded information or Cipher Text, which cannot be easily real by strangers. An algorithm and key. control the entire transformation process. This process may be reversible, so that the intended recipient can return the information to its original readable form. But reversing the process, without the appropriate encryption information is not possible. This means that the details of the key must also be kept secret. The use of cryptography in daily life is growing immensely. This is due to the necessity for hiding the content from unauthorized person. As the days pass by the old algorithms used in crypiography may not remain as strong as it was before Hence, the cryptanalysts suggest new algorithms for the same. Currently the computers are faster and in future its speed will also increase rapidly Brute force attacks are made to bereak the encryption and are emerging faster. These attacks are the main drawbacks for the older algorithms. In future these algorithms will be replaced by new algorithms that will enhance a better protection. In this investigation, a new encryption technique is proposed, which is more faster, better immune to attacks more complex, easy to encrypt and many more advanced security features are comprised. Encryption can also provide strong security for data, but developing a database encryption strategy will take many factors into consideration “Combination of encryption and decryption for secure communication” is an application which combines both encryption and decryption techniques, to make the communication more secure. It is concerned with embedding information in a secure and robust manner. Providing security speedily is the aim of this investigation, Relational databases are very important in satisfying today’s infirmation needs. This investigation provides a method to provide security by using encryption algorithm which is alone sufficient to protect the same.
Object Detection Deep Learning Using Yolo, Darknet
Authors:-Dharun Kumar, Premnath. S
Abstract- Picture characterisation stands out enough in the field of computer vision to be noticed. Over the last few years, there has been a lot of research done on picture characterisation using traditional AI and deep learning techniques. Deep learning-based techniques have yielded astounding results thus far. Despite the fact that various deep learning-based methods have demonstrated excellent picture sorting performance, deep learning methods are unable to separate all significant data from the image due to a variety of difficulties. As a result, characterization precision was significantly reduced. The goal of the current study is to improve image classification performance by combining deep features extracted using the popular YOLO deep convolutional neural network. From the experiment, we achieved an accuracy of 94.51 percent.
Dense Graph Sequences and Its Limits
Authors:- Asst. Prof. R. Sujatha
Abstract- We show that if a sequence of dense graphs Gn has the property that for every fixed graph F , the density of copies of F in Gn tends to a limit, then there is a natural “limit object,” namely a symmetric measurable function 𝑊 = [0,1]2 → [0,1] . This limit object determines all the limits of subgraph densities. We discuss about weighted graphs and homomorphisms. We restrict our attention to positive real weights between 0 and 1. An edge with weight 0 will play the same roles as no edge between those nodes, so we could assume that we only consider weighted graph is obtained by replacing the 1’s in the adjacency matrix by the weights of the edges. We consider graph sequence we need not assume that the number of nodes tends to infinity. We could always achieve this without changing the limit. We also characterize graph parameters that are obtained as limits of subgraph densities by the “reflection positivity” property, along the way we introduce W-random graphs and some simple properties and lemma.
Movie Recommendation Using Machine Learning
Authors:- Shivani Chowdhary, B. Kalyan, V. Gnanavathi, U.V.Rambai
Abstract- The recommendation system plays an essential role in the modern era and used by many prestigious applications. The recommendation system has made the collection of apps, creating a global village, and growth for abundant information. This paper represents the overview of Approaches and techniques generated in the Collaborative Filtering based recommendation system [1]. The recommendation system derived into Collaborative Filtering, Content-based, and hybridbased approaches. This paper classifies collaborative filtering using various approaches like userbased recommendation, item-based recommendation. This survey also tells the road map for research in this area. We extract aspect-based specific ratings from reviews and also recommend reviews to users depends on user similarity and their rating patterns. Finally, validating the proposed movie recommendation system for various evaluation criteria, and also the proposed system shows better result than conventional systems.
Grid to Vehicle and Vehicle to Grid Energy Transfer Using Three -Phase Bidirectional AC-DC Converter
Authors:- Lokesh Kumar Sharma, Bhanu Pratap Soni, Ankit Kumar Sharma
Abstract- Chargers must be efficient so that electric cars (EVs) and plug-in hybrid electric vehicles (PHEVs) can be charged at the right rate as they become more popular. It would also make charging more expensive, because more people would use the traditional power grid. It’s because of this that more people are going to use local, renewable sources of energy instead. PV panels, which convert sunlight into electricity, can be added to the traditional power grid. As well wind converter designed to convert the energy of wind movement into mechanical power this could make the traditional grid more efficient. A place to recharge in this thesis, PV and the grid are used to power EV loads. However, Because of the PV’s intermittent nature, which is very dependent on where you live and the weather, it is well-known that it isn’t very stable Conditions. To make up for the PV’s inconsistency, a battery storage system is used. An electric car charging station powered by solar panels and wind that are part of a system that is connected to the grid. Most of the time, hybrid charging stations are supposed to be, efficient, and safe to use. The needs of electric vehicles in a variety of situations by giving them more options. This thesis talks about how to be more efficient at the top. PV power generation on site is planned and implemented to meet the needs of the project. Using BSS, electric cars can have a more varied load, which lessens the strain on the grid. This method works. Improves overall performance, reliability, and cost by a lot. Efficiency in converting power in both directions interleaved buck-boost converters are added to BSS to make sure it works. By using BSS, conversion losses can be kept to a minimum. This structure could help to reduce the waves that are already there. Electricity will be better if you improve its quality to get the most out of a PV system while keeping it as environmentally friendly as possible. MPPT and an interleaved boost converter are used when the weather isn’t always clear. This way, the output stays the same. PV power will always be available. In the same way, to deal with the changing power needs of car chargers, Converters should be put together in a way that meets the needs of electric cars while also keeping the balance between the levels of power that can be generated.
Experimental Investigation on Mechanical Behaviour of Rice Straw- Jute – Coconut-Palm Fibres – Reinforced Epoxy Natural Composite Material
Authors:- Asst. Prof. Gosula Suresh, Research Scholar Manda Ranjith Kumar, M. Keshav Prasad, M. Shiva Kumar, M. Nagesh, Ch. Ranjith Kumar
Abstract- Rice-Straw-jute-Coconut-palm-Fibres is being used as a reinforcement material in the development of reinforced plastics for various engineering applications. Its biodegradability, low cost, and moderate mechanical properties make it a preferable reinforcement material in the development of polymer matrix composites. Therefore, Rice-Straw-jute-Coconut-palm-Fibres reinforced composites have replaced the most widely used synthetic fibre (glass, kevlar) reinforced composites in many applications. In the present experimental endeavor, Natural fibre reinforced composites were prepared using Vacuum bagging process. The effect of the weight percentage of the trio fibre reinforcement was investigated experimentally on the mechanical properties of the developed composites. The mechanical properties were tested using computerized UTM machine as per the ASTM standards. Scanning Electron Microscope (SEM) have been utilized to fully understand the mechanical behaviour of developed composites. The results reveal that, the mechanical properties of Rice-Straw-jute-Coconut-palm-Fibres based composites are substantially improved on account of the addition of the Jute fibre reinforcement. It has also been observed that the significance of the enhancement of the mechanical properties increased as the weight percentage of the Jute fibre reinforcement increased.
A Semantic Knowledge for Distributed Smart Environment
Authors:- Yeduguri Himani, Pathakota Akhila Sai, Nayuni Guna Eswar Prakash, Poojari Sai Ashmith
Abstract- Intelligent functionality is provided to every objects with the help of wireless sensors by the internet. Since the past few years, all are facing some problems to develop effective and intelligent protocols to integrate a large number of smart objects in distributed computation environments. However, the main difficulty for smart and distributed system designers lies in the combination of a huge number of heterogeneous components for rapid, low cost, and effective functionalities. In this article, we are going to propose semiology and intelligent based framework on the Garbage bins to provide the perfect service by connecting the sensors to the garbage bin, from these sensors collect the information from the bins within less time.
Developing A Master Plan For Tribal Hamlet
Authors:- PG Student Hanna , Prof. A. Kumar
Abstract- The project is concerned with developing a master plan for an “Adivasi” hamlet. The hamlet under consideration is Vellakulam ooru in Attappady in Mannarkad taluk, Palakkad district. A socio- economic survey was conducted to collect the necessary data for assessment and planning. The topographical details and details of existing buildings were collected through relevant surveys. On the basis of collected data site plan of the hamlet was prepared. A complete master plan of hamlet for the development of hamlet is proposed, which encompasses the provision of well-designed habitats, water supply, sanitation, transportation and other public amenities. A rough estimate of all the proposed works is also presented.
An Experimental Study on Self Compacting Concrete with Recycled Concrete Aggregate
Authors:- PG Scholar Seethal T M, Asst. Prof. Mr.M.Sadhasivam
Abstract- The usage of natural aggregate is becoming more intense with the advanced development in construction. Recycled aggregate can be used as a suitable replacement for natural aggregate. Recycling of aggregate material from construction and demolition waste may reduce the demand – supply gap and reduce consumption of natural resources. The advance in the pre stressed concrete and multistoried structures has given impetus for making high performance concrete. When the general performance of concrete is substantially higher than that of normal type concrete, such concrete is regarded as high performance concrete (HPC). High- performance concrete (HPC) exceeds the properties and constructability of normal concrete.HPC is usually more brittle when compared with normal strength concrete, especially when high strength is the main focus of the performance. These deficiencies can be overcome by adding fibres. Fibre reinforced concrete has become popular due to its crack arresting mechanism, strengthening property, high energy absorption properties, ductile behavior and post-cracking tensile strength. The aim of this thesis is to study the flexural as well as shear behaviour of fibrere in forced high performance recycled aggregate concrete in beams under monotonic for optimum percentages of fibres.
Rings in Which Elements Are Sums of, Tripotents and Its Idempotents
Authors:- Asst. Prof. S. Bhuvaneswari
Abstract- we completely determine the rings for which every element is a sum of a tripotent, and a idempotent that commutative with one another, and the rings for which every element is a sum of a tripotents and two idempotent that commutative with one another. Here are all the possible meanings and translations of the word tripotent. Relating to or being a mathematical quantity which when applied to itself under a given binary operation (such as multiplication) equals itself also: relating to or being an operation under which a mathematical quantity is idempotent. We study the class of rings R with the property that for x ∈ R at least one of the elements x and 1 + x are tripotent. We prove that a commutative ring has this property if and only if it is a subring of a direct product R0 × R1 × R2 such that R0/J(R0) =∼ Z2, for every x ∈ J(R0) we have x2 = 2x, R1 is a Boolean ring, and R3 is a subring of a direct product of copies of Z3.
Experimental Study on Underground Water Quality in Coimbatore Dump Yard Area
Authors:- J Akash, L Sivanesh, R Sriram
Abstract- Underground water is a precious natural water resource considered as a readily available and safe source of water for domestic, agriculture and industrial uses. In Coimbatore, underground water is being contaminated because of numerous human activities. Improper solid waste management is one amongst the major sources of environmental pollution deteriorating underground water quality around landfill sites. In this view, the current study was conducted to determine the impact of the existing landfill site on the quality of subsurface water in Vellalore. So as to realize this nine underground and one pool water samples from various distances around the dump site were analyzed. Parameters analyzed are color, odour, turbidity, pH, TDS, BOD, COD, DO, total hardness, nitrate, chloride, alkalinity. Results revealed that concentration of all the parameters apart from pH scale, are unit moderate than acceptable limits for safe drink. The distance from the dump site has an impact on the quality of subsurface water. Overall, underground water is imprinted contaminated because of existing landfill site in this study area. Therefore, the municipal solid waste in this space is nice in method. As a result, there are no consequences in groundwater.
Hybrid Power Systems Energy Management Based on Artificial Intelligence Using ANN Controller
Authors:- Sachin Verma, Asst. Prof. Mrs. Namrata Nebhnani, (HOD) Dr. Manish Sahajwani
Abstract- Due to the fact that solar and wind power is intermittent and unpredictable in nature, higher penetration of their types in existing power system could cause and create high technical challenges especially to weak grids or stand-alone systems without proper and enough storage capacity. By integrating the two renewable resources into an optimum combination, the impact of the variable nature of solar and wind resources can be partially resolved and the overall system becomes more reliable and economical to run. This paper provides a review of challenges and opportunities / solutions of hybrid solar PV and wind energy integration systems. Voltage and frequency fluctuation, and harmonics are major power quality issues for both grid-connected and stand-alone systems with bigger impact in case of weak grid. This can be resolved to a large extent by having proper design, advanced fast response control facilities, and good optimization of the hybrid systems. The paper gives a review of the main research work reported in the literature with regard to optimal sizing design, power electronics topologies and control. The paper presents a review of the state of the art of both grid-connected and stand-alone hybrid solar and wind systems.
Experimental Investigation On Behavior Of Box Girder Bridge
Authors:- Sachin Verma, Asst. Prof. Mrs. Namrata Nebhnani, (HOD) Dr. Manish Sahajwani
Abstract- Bangalore metropolis, the silicon valley of India, has experienced phenomenal growth in population in the last two decades. So, to meet the traffic demands, Metro Rail Transport started. Bangalore Metro Rail Corporation; is constructing some phase of Metro Rail to be of elevated one. There are different structural elements for a typical box girder bridge. The present study focus on the parametric study of single cell box girder bridges curved in plan. For the purpose of the parametric study, five box girder bridge models with constant span length and varying curvature. In order to validate the finite element modeling method, an example of box girder bridge is selected from literature to conduct a validation study. The example box girder is modeled and analyzed in SAP 2000 and the responses are found to be fairly matching with the results reported in literature. For the purpose of the parametric study, the five box girder bridges are modeled in SAP2000. The span length , cross-section and material property remains unchanged. The only parameter that changes is the radius of curvature. The cross section of the superstructure of the box girder bridge consists of single cell box. The curvature of the bridges varies only in horizontal direction. All the models are subjected to self weight and moving load of IRC class A tracked vehicle. A static analysis for dead load and moving load, and a modal analysis are performed. The longitudinal stress at top and bottom of cross sections, bending moment, torsion, deflection and fundamental frequency are recorded. The responses of a box girder bridge curved in plan are compared with that of a straight bridge. The ratio of responses is expressed in terms of a parameter. From the responses it is found that; the parameters like torsion, bending moment, and deflection is increasing as curvature of the bridges increase.
A Review on Automatic Fruit Plucking and Sorting Using Image Processing
Authors:- Soumya Tummaraguddi, Prakruthi R T, Tejaswini Anand, Sharathchandra C, Mr shivayogappa H J
Abstract- An emerging area of research that combines ma chine intelligence and computer vision is automated or robot assisted harvesting. This study can be applied to the picking and sorting of fruits to provide a more rapid production chain. This essay will examine common fruit classification and auto harvesting techniques. Sorting is the action of placing objects in a methodical order. In the wholesale market and food processing industries, manual fruit sorting is favoured depending on several factors like size, shape, quality, etc. However, it is a laborious, ineffective, and erratic approach. The market’s current methods can sort a single fruit based on one or more criteria. The pro posed system offers an automatic fruit sorting mechanism using an image processing methodology to replace this conventional method of sorting.
A Review on IOT Based Wheel Chair Fall Detection
Authors:- M. Tech. Scholar Teena Sachdeva , Asst. Prof. Ms. Rachna
Abstract- The purpose of this article “IOT BASED WHEEL CHAIR FALL DETECTION” is to discuss that we know that people with disabilities and older people need a wheelchair and elderly people are more prone to fall than we usually anticipate. These falls often lead to injuries and sometimes even lead to death. As elders are more vulnerable, it is important to monitor their old ones for their health and safety. Due to weakness and weak joints, they have a great risk of falling down. Now it is important to know if an old person has fallen so that they can be helped on time. So, it has become an urgent need to devise a system to alert the people nearby and attract the help that is directly needed in situations like these. The purpose of this project is to provide the necessary help through a device that would detect the fall through a series of sensors and send an alert message to a mobile device without any delay.
Genetic Algorithm Based Routing of IOT Network
Authors:- Research Scholar Shailendra Kumar Tiwari, Asscoiate Prof. Dr.Ravindra kumar Tiwari
Abstract- Smart devices in human life brings Internet of Things in day to day uses. Routing in such network should be efficient and energy effective, as devices depends on battery. Such network are optimized by various approaches, out of different methods routing based IOT network is an effective solution. This paper has proposed a genetic algorithm that finds the path based on Biogeography genetic algorithm. Paths were filter by estimating the fitness on the basis of node spectrum utilization. Such nodes are filter by into two class real and other is malicious. Malicious nodes are identified by the Adamic Adar function. Experiment was done on different environment and results shows that proposed model has increases the work performace.
Performance of PAPR Reduction in OFDM Based Wireless Communication using OICF system
Authors:- Mr. Pankaj Anare, Prof. K. K. Sharma
Abstract- Orthogonal frequency division multiplexing has emerged as a leading candidate for a key technology in a variety of wireless communication systems in recent years. In particular, OFDM has been accepted as a standard for a variety of wireless communication systems, including DAB and DVB, wireless local area networks, wireless metropolitan area networks, and wireless local area networks. In this article, we have covered a variety of topics concerning PAPR, including reduction approaches and a discussion of PAPR concerns. The power amplification product ratio, or PAPR, is defined as the relation between the maximum powers of a sample in a particular OFDM transmits symbol and the average power of that OFDM symbol. PAPR is triggered if a multi-carrier system has sub-carriers that are out of phase with one another. The simulation results show that our proposed power reduction technique OICF was proposed to reduce the high Peak to Average Power Ratio values. The Simulations are performed using the OICF technique with modulation technique under both Additive White Gaussian Noise channels. The simulation result shows the relationship between Complementary Cumulative Distribution Function versus PAPR. The simulation is performed by MATLAB R2013a.
Detection of Plant-Leaf Diseases with the Application of Deep Learning Techniques: A Review
Authors:- M. Tech. Scholar Punam Solanki, Asst. Prof. Ramiz Sheikh
Abstract- In India, a considerable proportion of the population relies on agriculture as their primary source of income, as well as meeting one of the fundamental requirements for human survival. Agriculture is an essential component in the economic development of many nations. The harvest is contaminated with a wide variety of diseases due to the varied weather and environmental conditions that exist there. In the early phase of the disease, it is possible to see the majority of symptoms on the plant’s leaves; nevertheless, the disease will ultimately affect the whole plant, which may result in less crop yield. The diagnosis of diseases in plants is an essential step in reducing production losses in the agricultural sector and improving the overall quality of food and other products derived from agriculture. When there are a large number of plants in a field, it may be challenging to recognise illness and to identify specific plant breakdowns from natural eye observation in agricultural settings. It is essential to do checks on all crops in order to prevent the illness from spreading over a vast area. It is essential to have precise sickness diagnosis and control measures in order to prevent disease in its early stages in order to maintain superior product quality while simultaneously increasing production levels. This recommended model will be AI-based software for the detection of crop leaf infections, which will make the diagnostic process more expedient and straightforward. Subsequently, it will evaluate this information and generate solutions that are foreseeable with the goal of preventing enormous crop cultivation loss. This strategy seeks to increase the profitability of farming by increasing the value of the crops produced. In this model, we are required to perform a number of operations, including the collecting of image data sets, the pre-preparation of the data, the selection of features from the leaf image, the evaluation, and the categorization of diseases.
Automatic Fertigation System
Authors:- Prof. Yayati Shinde, Saurabh Parhyad, Aditya Lohakare, Ditij Nandgaonkar, Sanyukta Bankar, Dr. Sandhya D. Jadhav
Abstract- Fertigation is that the strategy of delivering plants nutrients beside water to supply a high-grade crop with higher yields. victimization associate degree automatic fertigation system can facilitate farmers by significantly rising water and nutrient usage. the target is to automatically maintain the condition level at intervals the soil and to mix totally different nutrients to urge the desired NPK quantitative relation and provides it to plants beside irrigation. This work is assigned in a pair of components. One is maintaining the optimum level of condition at intervals the soil. A soil condition detector that senses the condition content at intervals the soil is used. The detector output is given to the controller, which decides if further water should be tense up or not. Then an effect system for the chemical combination and delivery 0.5 is meant. The user can give the input in terms of what amount of N, P and K is needed in kg. The user conjointly can input the concentrations of NPK chemical solutions used. Taking of those parameters into thought, the system will prepare a chemical mixture that contains the required amount of nutrients needed by the plant. it’ll then deliver the mixture beside irrigation water. The preparation of chemical mixture area unit finished specific intervals of some time which is ready to be set by the user. The system is connected to web by exploitation Wi-Fi and conjointly the user can enter the parameters in an exceedingly} very mobile application that is ready to transmit the data to the system over net.
Students Activities and Behavior Prediction in Online Exams Using Resnet50 Deep Learning Model
Authors:- Amit Shukla, Aditi Khemariya(HOD)
Abstract- This research focuses on current issues in online assessments, which are especially relevant during the Covid-19 pandemic. Our focus is on academic dishonesty associated with online assessments. We investigated the prevalence of potential e-cheating using a case study and propose preventive measures that could be implemented. We have utilized an e-cheating mechanism for detecting the practices of online cheating, which is composed ResNet50 deep learning technique. The behavior of the students and has the ability to prevent and detect any malicious practices. It can be used to assign randomized multiple-choice questions in a course examination and be integrated with online learning programs to monitor the behaviour of the students. The proposed method was tested on various data sets confirming its effectiveness. The deep neural network ResNet50 model achieved accuracy of 95.12 percent.
A Review on Optimization Of Process Parameters In Extrusion Of aluminium Alloy
Authors:- M.Tech. Scholar Atul Kumar, Prof. Mayank Mishra
Abstract- Recently, extrusion processes have been used to make a wide range of metal products, including bars and tubes and strips and solid and hollow profiles, that are usually long, straight, semi-finished metal products. In order to govern the extrusion parameters, it is also critical to understand the history of the process reactions. Prior to the experimentation, a finite element analysis of extrusion was used to predict the performance.Friction between the die and the blank can have a significant impact on numerous process parameters during extrusion. It is preferable to run the lathe at a modest pace to avoid overheating the blank owing to friction and distortion. It causes the blank to heat up too quickly. Inefficient use of memory resources results in higher operating costs and a longer time to complete tasks. A review has been done on optimization of process parameters in extrusion of aluminium alloy.
Leveraging AI to Optimize Oracle EM Ops Center Operations
Authors: Lakshmi Menon, Aravind Krishnan, Ramya K, Vineeth Das
Abstract: Modern IT environments, characterized by hybrid infrastructure, rapid virtualization, and regulatory constraints, demand sophisticated systems management platforms that go beyond manual operations. Oracle Enterprise Manager Ops Center (OEMOC) has long served as a unified platform for provisioning, patching, asset discovery, and monitoring in Oracle Solaris and Linux-based data centers. However, as operational complexity scales, traditional rules-based workflows face limitations in managing configuration drift, correlating events, and predicting performance degradation. This has prompted a shift toward integrating artificial intelligence into Ops Center’s telemetry and operational lifecycle. This review explores the application of AI and machine learning techniques to optimize various facets of OEMOC. From predictive asset discovery and patch prioritization to real-time anomaly detection and resource planning, AI offers the potential to transform the platform into a proactive, self-optimizing system. The review evaluates supervised, unsupervised, and reinforcement learning models that can be trained on logs, asset data, and historical events collected across Enterprise Controllers and Agent Controllers. Specific emphasis is placed on using time series forecasting for utilization prediction, clustering techniques for configuration drift detection, and NLP algorithms for intelligent alert triage. Additionally, the review delves into the architectural integration of AI pipelines with OEMOC components, the use of SNMP, syslog, and ITSM APIs for external telemetry fusion, and case studies from financial, government, and telecom deployments. The article also addresses challenges related to model explainability, data governance, and integration within legacy environments. In doing so, it outlines a roadmap for enhancing Ops Center with intelligent automation, turning it from a monitoring tool into a closed-loop operations platform capable of dynamic remediation and resource optimization.
DOI: https://doi.org/10.5281/zenodo.15846496
Reimagining Personalized Healthcare With AI-Driven Diagnostics, Monitoring, And Treatment Planning
Authors: Raghavendra Duvvuri
Abstract: The convergence of wearable technology and artificial intelligence is transforming the landscape of physical and mental wellness. Modern wearables collect a wide range of biometric data—such as heart rate, sleep quality, and stress indicators—while AI systems analyze this data to generate real-time, personalized insights. These intelligent feedback loops help users make informed decisions about their activity levels, recovery needs, sleep hygiene, and emotional well-being. By continuously adapting to the user’s habits and physiological trends, AI enhances behavior change, supports mental resilience, and promotes preventive self-care. While challenges such as data privacy, sensor accuracy, and user dependency remain, the long-term potential for AI-driven wellness systems is vast. As wearable tech becomes more advanced and integrated with broader healthcare ecosystems, it paves the way for predictive, adaptive, and personalized health management that is proactive rather than reactive. This article explores how AI-enhanced wearables empower individuals to take control of their health through data-driven, sustainable lifestyle changes.
DOI: http://doi.org/10.5281/zenodo.16742346
Reinventing Retail Through AI-Driven Personalization, Demand Forecasting, And Inventory Optimization
Authors: Priya Gopalakrishnan
Abstract: This article explores how artificial intelligence (AI) is revolutionizing the retail industry by enhancing personalization, demand forecasting, and inventory optimization. It discusses the limitations of traditional retail approaches and illustrates how AI enables data-driven strategies that improve customer engagement, operational efficiency, and profitability. By leveraging technologies such as machine learning, natural language processing, and predictive analytics, retailers can deliver customized experiences, anticipate market demand with greater accuracy, and optimize stock levels across supply chains. The article also outlines practical implementation strategies, highlights measurable business impacts, and offers a forward-looking perspective on the future of AI in retail.
DOI: http://doi.org/10.5281/zenodo.16742080
Revolutionizing Decision-Making In Enterprises With AI-Augmented Analytics And Real-Time Dashboards
Authors: Harish Kumaran
Abstract: This article explores how AI-augmented analytics and real-time dashboards are transforming enterprise decision-making. As businesses face increasing complexity, data overload, and the need for instant responsiveness, traditional analytics methods fall short. AI-driven analytics enhances decision-making by automatically uncovering patterns, generating forecasts, and offering prescriptive recommendations, while real-time dashboards provide live visibility into key metrics and operations. Together, these technologies empower organizations to act with speed, precision, and agility. The article covers their core capabilities, integration strategies, implementation challenges, and the evolving role they play in modern business environments. It also looks ahead to the future of enterprise intelligence—where decisions are increasingly autonomous, collaborative, and insight-driven.
DOI: http://doi.org/10.5281/zenodo.16742123
Scaling Your Side Hustle With No-Code AI: From Passion Project To Intelligent Business
Authors: Revathi Bommakanti
Abstract: In today’s creator economy, side hustles are evolving into scalable, revenue-generating ventures. However, many solo entrepreneurs struggle to grow due to limited time, resources, and technical skills. This article explores how no-code AI tools empower side hustlers to automate repetitive tasks, analyze business data, and optimize performance—without needing to write a single line of code. From content generation and customer engagement to sales forecasting and financial tracking, no-code platforms are transforming how small businesses operate. Through practical tools, real-world examples, and common pitfalls to avoid, this guide offers a blueprint for turning passion projects into intelligent, self-sustaining businesses. By strategically integrating AI from the start, side hustlers can build smarter systems, make data-driven decisions, and free up time to focus on creativity, growth, and impact.
DOI: http://doi.org/10.5281/zenodo.16742147
A Review Of Big Data Frameworks In Healthcare IT
Authors: Tanira Poddar
Abstract: The exponential growth of healthcare data, driven by electronic health records (EHRs), medical imaging, wearable sensors, genomic sequencing, and real-time monitoring systems, has resulted in unprecedented opportunities for transforming medical care. Big data frameworks provide the computational backbone to store, process, analyze, and visualize these massive, heterogeneous datasets. Their applications extend from early disease prediction and personalized medicine to hospital workflow optimization, fraud detection, and population health management. However, integrating big data solutions in healthcare presents challenges such as data privacy, fragmented systems, interoperability issues, and resource-intensive infrastructure requirements. This review comprehensively explores the evolution and impact of big data frameworks in healthcare IT, evaluating critical technologies, architectures, applications, and implementation strategies. It also highlights the barriers and future directions for leveraging big data to improve clinical practice, research, and administration. Insights are drawn from recent studies, practical use cases, and emerging trends in artificial intelligence, predictive analytics, and real-time decision support. The review ultimately provides a roadmap for stakeholders—clinicians, technologists, administrators, and researchers—to harness big data for better outcomes, operational efficiency, and patient-centric care.
DOI: http://doi.org/10.5281/zenodo.16982564
The influence of AI in optimizing workload balancing across multi-cloud infrastructures
Authors: Aditya Bhandari
Abstract: Artificial Intelligence (AI) has emerged as a transformative force in IT infrastructure management, particularly in optimizing workload balancing across multi-cloud environments. Multi-cloud infrastructures, which involve the utilization of multiple cloud services from different providers, present a complex landscape for businesses seeking high availability, scalability, and cost efficiency. The dynamic nature of workloads, variability in service level agreements (SLAs), and diverse cloud resource characteristics necessitate intelligent automation to optimize performance. AI-driven approaches leverage machine learning algorithms, predictive analytics, and autonomous decision-making to manage workload distribution effectively, ensuring optimal utilization of resources while minimizing latency and operational costs. This article delves into the integration of AI in multi-cloud workload balancing, exploring how it addresses challenges such as resource heterogeneity, network latency, and fluctuating demand patterns. We discuss various AI techniques, including reinforcement learning, neural networks, and evolutionary algorithms, that are employed to predict workload behavior and automate deployment decisions. Additionally, the article examines real-world case studies highlighting successful AI implementations and outlines the future trajectory of this synergy. By adopting AI-driven workload optimization, organizations can enhance resilience, improve user experience, and achieve sustainable cloud operations amid the rapidly evolving digital ecosystem.
DOI: https://doi.org/10.5281/zenodo.17708834
The influence of AI on achieving sustainable energy consumption in data centers
Authors: Sanjana Rao
Abstract: Sustainable energy consumption in data centers has emerged as an urgent global priority as digital transformation accelerates and the demand for cloud computing, data storage, and processing escalates dramatically. Data centers, pivotal infrastructure for the digital economy, are also substantial consumers of electricity and significant sources of greenhouse gas emissions. The integration of artificial intelligence (AI) technologies introduces promising avenues to enhance energy efficiency, optimize resource management, and ultimately contribute to sustainability goals. AI-driven systems can analyze vast amounts of operational data in real-time, enabling predictive maintenance, smart cooling, dynamic workload management, and energy-aware orchestration of resources. These capabilities reduce energy waste and minimize carbon footprints while ensuring robust performance. This article explores the multitude of ways AI influences energy consumption patterns in data centers, including machine learning techniques for demand forecasting, innovative cooling solutions, renewable energy integration, and automated control systems. It also examines challenges such as the energy demands of AI itself and the need for transparent, ethical AI governance. Through the lens of case studies and emerging technologies, this synthesis underlines the transformational potential of AI in promoting sustainable data center operations, offering insights valuable for industry stakeholders, researchers, and policymakers. Ultimately, embracing AI as a core component of data center management aligns with broader objectives of climate responsibility and operational resilience in the digital age.
DOI: https://doi.org/10.5281/zenodo.17708969
Engineering Resilience In Multi-Cloud Java Microservices: Architectural Patterns Across AWS And Google Cloud
Authors: Sriram Ghanta
Abstract: As enterprises increasingly adopt multi-cloud strategies to mitigate vendor lock-in, meet regulatory requirements, and improve service availability, ensuring resilience across heterogeneous cloud platforms has emerged as a fundamental architectural challenge. Java microservices ubiquitous in large-scale enterprise systems must be engineered to tolerate partial service failures, regional outages, transient network partitions, and uneven performance characteristics inherent to distributed cloud environments, all while preserving end-user experience and meeting strict service-level objectives. This article presents a systematic study of multi-cloud resilience patterns for Java microservices deployed across Amazon Web Services (AWS) and Google Cloud Platform (GCP), synthesizing established distributed-systems principles with cloud-native fault-tolerance techniques and industry best practices published prior to 2022. We examine core architectural patterns including asynchronous messaging for decoupling and buffering, circuit breakers and bulkheads for failure containment, and saga-based coordination for maintaining data consistency without global transactions, highlighting their practical applicability in real-world enterprise deployments. Leveraging publicly available architectural diagrams and insights from prior empirical studies, the paper demonstrates how these patterns can be implemented in a cloud-agnostic manner while mapping effectively to provider-specific services, enabling fault isolation, graceful degradation, operational stability, and predictable recovery behavior in complex multi-cloud Java microservice ecosystems.
DOI: http://doi.org/10.5281/zenodo.18081618
Architecting High-Throughput Transaction Processing In Distributed Microservices Systems: Principles, Coordination Mechanisms, And Performance Optimization
Authors: Shekar Vollem
Abstract: Modern digital applications demand the ability to process massive numbers of transactions while maintaining reliability, scalability, and responsiveness across geographically distributed infrastructures. Traditional monolithic architectures often struggle to support the throughput requirements of large-scale distributed systems due to tight coupling between components, limited horizontal scalability, and the difficulty of isolating failures within a single codebase. As workloads grow and user bases expand globally, these limitations become increasingly evident in areas such as transaction latency, system availability, and deployment agility. Distributed microservices architectures offer a viable alternative by decomposing applications into smaller, independently deployable services that communicate through lightweight APIs or event-driven messaging systems. This architectural paradigm enables organizations to scale services horizontally, optimize resource utilization, and process transactions concurrently across distributed environments. In such systems, each microservice typically manages its own data store and business logic, allowing for flexible scaling and improved resilience. This paper examines the architectural principles, distributed transaction models, and performance optimization strategies that enable high-throughput transaction processing in microservices environments. The study reviews existing research on distributed transaction processing systems, including distributed OLTP platforms and main-memory databases that reduce I/O bottlenecks and improve transaction latency. It also analyzes microservice orchestration patterns and coordination mechanisms that enable reliable transaction management across multiple services. Particular attention is given to techniques such as data partitioning, asynchronous messaging, event-driven communication, and Saga-based transaction coordination, which collectively help maintain data consistency without sacrificing system performance. Through the analysis of existing systems, architectural patterns, and prior research studies, the paper highlights approaches that significantly improve transaction throughput while preserving fault tolerance, service autonomy, and data consistency in complex distributed computing environments.
DOI: https://doi.org/10.5281/zenodo.19219630
Performance And Environmental Assessment Of A Waste-to-Energy Thermal Power Plant Under Variable Load Conditions”
Authors: Mr. Parth Kohli, Prof. Neha Singh
Abstract: Waste-to-Energy (WtE) thermal power plants offer a sustainable solution for simultaneous municipal solid waste (MSW) management and electricity generation. This study presents a detailed performance and environmental assessment of a WtE thermal power plant operating under varying load conditions. Key performance indicators, including thermal efficiency, heat rate, and specific carbon dioxide (CO₂) emissions, were analyzed to evaluate the influence of operating load on plant performance. The results demonstrate a clear improvement at higher loads, with increased thermal efficiency, reduced heat rate, and lower specific CO₂ emissions per unit of electricity generated. These enhancements are attributed to improved combustion stability, effective utilization of the calorific value of MSW, and lower relative auxiliary power consumption. The analysis confirms that operation near rated capacity maximizes energy recovery and minimizes environmental impact, highlighting the importance of consistent waste supply and optimized load management. Beyond technical performance, the study underscores the role of WtE plants in sustainable urban infrastructure by reducing landfill dependence, recovering energy, and mitigating greenhouse gas emissions. The findings provide practical insights for policymakers, urban planners, and plant operators, supporting the integration of WtE systems into modern energy strategies and environmentally responsible waste management frameworks.
DOI: https://doi.org/10.5281/zenodo.19449403
Published by: vikaspatanker
