Daily Archives: March 7, 2024

Wireless Bypass Charging System for E-Vehicle Using Darrieus
Authors:-Assistant Professor Dr. Pon Partheeban, Aarthi, Sreeba.S, Tamil.4, Uvashree.U.V

Abstract- This paper presents a comprehensive review of ex- isting charging technologies for Electric Vehicles (EVs), followed by a proposed solution based on distributed transmitter coils supplied by parallel resonant inverters. The system employs sequential energization of coils depending on the position of the receiver coil mounted on the vehicle, utilizing Inductive Power Transfer (IPT) technology. This ground-breaking tech- nique of magnetic induction wireless charging eliminates the requirement for physical connections between the vehicle and charging infrastructure. Power is wirelessly delivered from the charging station to the vehicle through electromagnetic fields, with both transmitter and receiver coils resonating at the same frequency. The growing interest in such technologies stems largely from the EU Air Quality Directive of 2008, which established strict CO2 footprint limitations that internal combustion ve- hicles struggle to meet. These regulations apply to both light vehicles and heavier transport options like trucks and buses, which are significant contributors to particulate matter (PM) and nitrogen oxide emissions in urban areas. While widespread EV adoption promises significant pollution reduction in cities, potential customers remain concerned about limited charging infrastructure and range anxiety. The proposed wireless charging solution offers users seamless experiences by enabling charging without the constraints of cords or plugs. This innovation has the potential to revolutionize the automotive sector by providing increased mobility, convenience, and efficiency in how EVs are powered, ultimately accelerating the transition to sustainable transportation.

DOI: 10.61137/ijsret.vol.10.issue2.309

Published by: Kajal Tripathi

Tribal Welfare Application Using Artificial Intelligence
Authors:-Associate Professor Dr. F R Shiny Malar, Albert.G, Denishlin Hersho.M, Girinath.R, Subitha.S.K

Abstract- Every day new technology is arriving and billions of people were connected to the Internet. Purchasing goods, groceries, clothes everything is online. He or She can able to place the order from their smart phone within a minute. But, Farmers are still lack of benefitting from the internet. As we all knew that Farmers are the backbone of our country and without them, we can’t complete a day. Well, this idea is completely dedicated to farmers and helps them in generating good profitable revenue by using our platform. This is an online e-Commerce platform that enables a farmer to buy or sell anything related to the agriculture and farming category by simply creating an account. Strictly all vendors are farmers since it is dedicated to them. The ultimate objective of the idea is to help a farmer with good revenue for their goods. Nowadays smart phone is like a coin in a pocket. So, it’s not a big question of thinking about smart phones with a farmer. Also, most of them are already familiar with social media accounts and it is quite easy to play with our online e-platform. Our project aims to revolutionize tribal welfare by creating a digital marketplace where farmers can easily sell their products and customers can seamlessly find what they need. Leveraging the power of Artificial Intelligence (AI), customers can use their smart phones to visually search for products without the need for typing detailed descriptions. This innovative approach not only streamlines the buying process but also empowers tribal farmers by providing them with a platform to showcase their goods to be a broad audience. Through this project, we envision bridging the gap between farmers and consumers, fostering economic growth, and promoting sustainable livelihoods within tribal communities.

DOI: 10.61137/ijsret.vol.10.issue2.308

Published by: Kajal Tripathi

Electronic Health Record Management with Two Factor Authentication Using Blockchain
Authors:-Associate Professor Dr. A Selva Reegan, Ashika.M, Minisha.P, Pridni.M, Rahini.I

Abstract- The “Secure Blockchain-Based Electronic Health Record Management with Two- Factor Authentication” project presents a practical and innovative solution to the challenges of medical data security. This project presents a solution by combining the power of blockchain technology with a sophisticated two-factor authentication (2FA) mechanism to create a comprehensive and secure environment for managing electronic health records. In this system, patients, doctors, and secure cloud server interact seamlessly, ensuring the privacy, security and transparency of electronic health information. The project begins with user registration and authorization, where patients and doctors undergo a robust authentication process facilitated by the cloud server. Two-Factor Authentication (2FA) enhances login security, providing a foundation for trust in the system. Patients can initiate key requests for data encryption, and the cloud server, acting as a key manager, securely generates encryption keys, fortifying the protection of healthcare records. The blockchain, with its decentralized and immutable ledger, ensures the integrity of patient records, offering transparency across the entire healthcare network.

DOI: 10.61137/ijsret.vol.10.issue2.307

Published by: Kajal Tripathi

Smart Navigation: Real-Time Traffic Sign Recognition Using CNNs
Authors:-Mr. R.V. Viswanathan, K. Ashik, M.Chandru, R. Gokulnath

Abstract- In today’s dynamic road environments, ensuring driver safety and efficient navigation is paramount. This paper introduces an innovative method to tackle the challenge by integrating Convolutional Neural Networks (CNNs) for real-time traffic sign identification and auditory notifications. The system provides comprehensive support for drivers in understanding traffic signs. Traffic signs are crucial for delivering vital information to drivers, but factors like poor weather conditions and driver distractions can hinder quick recognition. Our CNN-based solution addresses these issues by precisely detecting and categorizing different types of traffic signs, such as warning, prohibition, and informational signs, across various environmental settings. Furthermore, our system enhances driver awareness by providing auditory alerts alongside visual cues. When a TTS library is integrated, recognized signs can be translated into clear spoken alerts, providing drivers with timely and useful information. Our method has the potential to improve traffic safety, provide drivers with on-the-spot decision support, and further the development of intelligent transportation systems.

DOI: 10.61137/ijsret.vol.10.issue2.303

Published by: Kajal Tripathi

Enhancing Network Security through DIPS
Authors:-J. Sathishkumar, K. Dhanush, K. Aneesh, B. Vigneshwaran

Abstract- Network Intrusion Detection Systems (NIDS) play a crucial role in protecting computer networks from unauthorized access and harmful activities. This paper investigates the use of Machine Learning (ML) techniques to improve the effectiveness of NIDS in detecting network intrusions. The approach involves gathering a comprehensive dataset of both legitimate and malicious network traffic, extracting important features, and labeling data for supervised learning. Various machine learning models, such as Decision Trees, XGBoost, and Artificial Neural Networks, are assessed for their ability to differentiate between normal and malicious network behavior. The models are rigorously tested and fine-tuned to ensure precise and dependable intrusion detection. Additionally, the system notifies the user through reporting. For real-time operation, the ML-powered NIDS continuously monitors network traffic using a Denial of Intrusion Detection and Prevention System (DIPS), offering the capability to adjust to evolving conditions and new threats.

DOI: 10.61137/ijsret.vol.10.issue2.302

Published by: Kajal Tripathi