Greenhouse Monitoring and Controlling Using Iot and Machine Learning
Authors:-Shreya Patwadkar, Harshada Shete, Nirmala Shelke, Snehal Sabale

Abstract-This study presents an ESP8266-based greenhouse monitoring and controlling system that effectively regulates environmental parameters essential for plant growth. The system utilizes sensors such as the DHT11 for temperature and humidity, YL69 for soil moisture, and an LDR for light intensity. These sensors provide real-time data to the ESP8266 microcontroller, which not only processes the inputs but also enables wireless connectivity for remote monitoring and control. Through relay modules, the system controls devices such as water pumps, artificial lighting, and ventilation fans to maintain optimal growing conditions. A display panel can be included for on-site visualization, while data transmission via Wi-Fi facilitates integration with cloud platforms for data logging and analytics. This IoT-enabled approach supports automation, enhances sustainability, and minimizes manual intervention, making it a robust solution for modern greenhouse management.

DOI: 10.61137/ijsret.vol.11.issue2.369

Published by: Kajal Tripathi

Bail Reckoner
Authors:-Kutala Pravalika, Korimi Praveen

Abstract-The subjectivity and complexity of bail determinations in criminal justice systems have for a long time presented difficulties to fairness and consistency. In this paper, we suggest a software solution named Bail Reckoner that helps assess bail eligibility with the use of machine learning methodologies. Through processing of historical court data and determining useful features such as offense category, previous offenses, and socio-economic factors, the system produces a probabilistic bail outcome suggestion. Our method is designed to assist judges and legal practitioners by increasing transparency and minimizing bias. The system is tested using simulated legal datasets and shows encouraging accuracy in matching with real judicial decisions.

DOI: 10.61137/ijsret.vol.11.issue2.368

Published by: Kajal Tripathi

Copyright in the Digital Age: Addressing Issues on Online Piracy and Streaming Services
Authors:-Soumya Mishra, Dr. Taru Mishra

Abstract-Copyright laws are being developed along with technology. Today, digital advances such as the Internet and PC offer both opportunities and challenges for creative work stakeholders. The balance of these interests is complicated but reflects the continued adaptation of copyright to new developments. The advent of the Internet and the widespread adoption of HR computers have begun an era of unprecedented connectivity and accessibility for creative work. However, in addition to these transformative developments, there are various challenges faced by stakeholders in the production, distribution, and consumption of copyrighted content. This analysis examines various digital copyrights in the Internet age and uses literature review methods that address the complex interactions of technological advancements and legal frameworks. The rise of digital copyright infringement, the spread of user-generated content platforms, and the development of new distribution models provide traditional ideas for copyright tracking and intellectual property protection. Furthermore, the global features of the digital economy complicate regulatory efforts as the terms of the legal framework make it difficult to meet the infinite characteristics of online transactions and consumption of digital content. This review examines development strategies used by political decision-makers, industrial interest groups, and law to control these challenges, from legislative reforms to innovation in content management and digital rights management (DRM) systems. Through a comprehensive analysis of existing literature, this overview uncovers ongoing dialogue related to digital copyrights on the Internet, providing insight into the complexity of copyright in the digital age, debate, and future trajectories.

DOI: 10.61137/ijsret.vol.11.issue2.367

Published by: Kajal Tripathi

AI-Driven Real-Time Threat Detection System for Women’s Safety Using Deep Learning and Gesture Analytics
Authors:-Associate Professor Dr.S. Mohana, Preethi S, Sujay Charan P, Parthiban S, Sanjai Krishnan A, Pradiksha R J

Abstract-This paper presents a comprehensive AI-driven real-time threat detection framework designed to enhance women’s safety in urban environments. The system integrates advanced computer vision techniques including YOLOv8- based person detection, ResNet-50 gender classification, and LSTM-based gesture recognition to analyze live surveillance feeds. Through the execution of a multi-modal threat analysis algorithm, the system can recognize vital scenarios including SOS gestures (with 92.3% accuracy), isolated female detection in night hours (with 89.7% accuracy), and probable mob scenario situations. The system is integrated with a distributed architecture supporting low- connectivity location-based edge computing, real-time alert generation based on Twilio/Vonage APIs, and compatibility with police systems through an exclusive web dashboard. Experimental outcomes prove 86.4% threat detection accuracy at an average latency of 1.2 seconds on NVIDIA Jetson devices.

DOI: 10.61137/ijsret.vol.11.issue2.366

Published by: Kajal Tripathi

AI Chatbot
Authors:-Vipashyna Arun Sable, Professor Suresh Mestry

Abstract-AI chatbots can assist right away by answering questions, providing explanations, and pointing to more resources. Software applications like chatbots can aid teachers in many assignments and become excellent digital teaching assistants.Chatbots are software applications that respond to inputs in natural language. We can see that chatbots are now a part of our daily life. We use them every day to book a movie, reach the closest restaurant, or find an open ATMThese are chatbot software applications that have made life easy. But their uses are not restricted to this. They also entertain users who are bored, play a massive role in home automation projects, give business strategy suggestions, and aid in many other ways.The system was tested on various user inputs and usage scenarios and satisfactory results were observed for usability, accuracy, and responsiveness. The project brings highly evolved chatbot framework technologies like Rasa and chit-chat bots of the likes of facebook and wit.ai to beginner level with a responsive conversational chatbot which could be deployed with minimal coding efforts.The project shows how advanced AI could be used effectively with simple web technologies, and opens up the possibility of further development of using voice, multilingual support, and AI-powered customization.

DOI: 10.61137/ijsret.vol.11.issue2.365

Published by: Kajal Tripathi

E-Commerce Price Comparison System
Authors:-Assistant Professor Vimmi Malhotra, Kanchan Panwar, Jaya

Abstract-In recent years, mobile apps have become increasingly useful for everyday use. The objective of this project is to provide users with a convenient method to compare product availability and prices across different e-commerce platforms. By inputting the product details into the program, users can effortlessly compare prices from various sources. To compare the product details discovered on multiple websites simultaneously, the application’s databases are searched. To guarantee that they never overlook a fantastic deal, customers can also receive push notifications when items become available or go on sale.

DOI: 10.61137/ijsret.vol.11.issue2.364

Published by: Kajal Tripathi

A Novel IDS Framework Combining PCA and Random Forest
Authors:-Roshan Kumar S, Mageshwaran S D, Krithik S R, Dr. U. Surendar

Abstract-The aim of this project is to develop an application capable of identifying the type of attack on a system and detecting intruders using an intrusion detection system. [1] [6] Various machine learning techniques have been previously applied to IDS to enhance intrusion detection accuracy. This research introduces a novel approach by integrating principal component analysis and the random forest classification algorithm to build a more efficient IDS. PCA helps refine the dataset by reducing its dimensionality, simplifying data processing, while the random forest algorithm ensures precise classification of network activities. Experimental results indicate that this method outperforms traditional techniques such as support vector machine, naïve bayes and decision tree, delivering high accuracy. IDS functions as a network security measure, identifying threats, malicious activities, and attack types. A key limitation in conventional IDS is that if the primary detector fails, intrusions remain undetected. To address this, the proposed system implements multiple detection mechanisms, ensuring that if one detector fails, other continue monitoring and identifying threats, thereby, strengthening system security.

DOI: 10.61137/ijsret.vol.11.issue2.363

Published by: Kajal Tripathi

Complaint Management System for Migrant Workers in Tamil Nadu
Authors:-MS.B.Manjubashini, Ranjithkumar S, Sevvelkaran Palani Vetrivel, Srikanth S, Jahan V

Abstract- The proposed Complaint Management System for Migrant Workers in Tamil Nadu is a digital platform designed to empower migrant laborers by providing a streamlined, accessible, and multilingual interface for registering and tracking workplace grievances. Recognizing the diverse linguistic backgrounds and socio- economic challenges faced by migrant workers, the system incorporates features such as real- time complaint tracking and automatic translation of the app interface and complaint content into the worker’s native language (e.g., Hindi, Bengali, Odia, Telugu) This user-centric platform allows workers to easily lodge complaints related to: wage disputes, unsafe working conditions, harassment, poor living standards, and other labor rights violations. Each complaint is assigned a unique tracking ID, enabling real-time status updates through a simple dashboard. The translation feature ensures inclusivity, bridging the communication gap between workers, government authorities, and employers.

DOI: 10.61137/ijsret.vol.11.issue2.362

Published by: Kajal Tripathi

Smart Monitoring of Water Absorption in Roads Using Sensor Technology – A Review
Authors:- Mr. Jeshurun Wakdey, MS Amarja Pawar, Mr. Sahil Dolas

Abstract-Roads are lifeline of our country as it is the best suitable method for all type of vehicles and most used by common people. The development of any country largely depends on the efficiency of its transportation system, because the transportation of a chain of activities related to economic development Human wants are satisfied by the production of good and its distribution. The road is ordinary type i.e. concrete road, WBM road or bituminous road. If we replace these roads by water absorbing road (WAR) we can save large quantity of water. Ordinary road constructed in cities majorly face the problem of flooding of road and because its top layer is impervious. In urban areas larger amount of rainwater ends up falling on impervious surfaces such as parking lots, driveways, sidewalks, and streets rather than soaking into the soil and becomes storm water.

DOI: 10.61137/ijsret.vol.11.issue2.361

Published by: Kajal Tripathi

E-Commerce Price Comparison System
Authors:-Prof.Vimmi Malhotra, Kanchan Panwar,Jaya

Abstract-In recent years, mobile apps have become increasingly useful for everyday use. The objective of this project is to provide users with a convenient method to compare product availability and prices across different e-commerce platforms. By inputting the product details into the program, users can effortlessly compare prices from various sources. To compare the product details discovered on multiple websites simultaneously, the application’s databases are searched. To guarantee that they never overlook a fantastic deal, customers can also receive push notifications when items become available or go on sale.

DOI: 10.61137/ijsret.vol.11.issue2.360

Published by: Kajal Tripathi