International Journal of Engineering Research and Sustainable Technologies (IJERST)

SMART AGRICULTURE: ENHANCING PLANT DISEASE DETECTION WITH DRONE TECHNOLOGY

2025-10-06T10:17:56+00:00

This technology transforms farm management by optimizing resource consumption and improving crop health through the integration of AI-driven disease diagnosis and targeted watering. A quadcopter drone equipped with a GPS and high-resolution camera captures geo-referenced images for aerial surveys, which are processed in real-time by an onboard edge intelligence unit. Advanced AI technologies locate and map affected areas, instantly linking diseases to precise locations. Only the affected areas may receive precise water and nutrient supplies if this data is wirelessly transmitted to intelligent irrigation systems. The technique reduces unnecessary fertilizer and pesticide use, eliminates water waste, and boosts yields while promoting sustainability. Early disease diagnosis helps prevent large-scale epidemics and supports proactive management. This method combines drone-based remote sensing, AI-powered analysis, and precision irrigation to boost agricultural yield while conserving resources.

STOCK FORECASTING WEB APPLICATION WITH MACHINE LEARNING

2025-10-06T10:17:48+00:00

In this project we created a web application for stock forecasting that uses machine learning techniques to give users insights into stock prices in advance. The application integrates realtime stock data from financial APIs and uses Python for both machine learning and web development, making it easy to access the most recent information. The LSTM (Long ShortTerm Memory) algorithm is a kind of recurrent neural network and it is the main component of the application that analyses historical stocks data and projects future prices. Here we used Frontend technologies like HTML, CSS, and JavaScript (Angular) power the user-friendly single-page interface of the Flask or Django framework-built web interface. And here we use other model like SARIMA, Random Forest,Prophet Any appropriate database system,such as SQLite, can be used for data management. Using scikit-learn or TensorFlow libraries, machine learning functionalities are implemented, allowing the development of reliable forecasting models. The libraries Matplotlib, Plotly, or D3.js make it easier to visualise stock data, which improves user comprehension and decision-making.Alpha Vantage and other financial market APIs and yfinance library provide real-time stock data, guaranteeing the application's relevance and dependability in fluctuating market conditions. From this project users can easily understand and analyze the stock data with user-friendly interface and dynamic visualization. This project's ultimate objective is to democratize access to stock forecasting tools for all traders and they get better experience levels can confidently make an gameplay with financial market trends.

INNOVATIVE LIFI BASED VIDEO TRANSMISSION: A HIGH-SPEED OPTICAL WIRELESS COMMUNICATION APPROACH

2025-10-06T10:17:41+00:00

The increasing demand for high-speed data transmission has led to the exploration of alternative wireless communication technologies. Li-Fi (Light Fidelity) is a promising optical wireless communication system that leverages visible light for data transfer. Unlike traditional radio-frequency (RF) communication systems, Li-Fi offers significant advantages, including higher bandwidth, enhanced security, and minimal electromagnetic interference. This paper focuses on the implementation of video transmission using Li- Fi technology, a potential breakthrough in wireless communication. By modulating light intensity with high-speed variations, data can be transmitted effectively, achieving high bandwidth and secure communication. The study explores system architecture, challenges, and performance evaluations, highlighting the feasibility of Li-Fi for video streaming applications. Furthermore, the research evaluates different modulation techniques, signal processing methods, and real- world applications where Li-Fi can be effectively deployed for high-definition video streaming. The findings suggest that Li-Fi could be a game-changer in multimedia communication, with promising applications in smart homes, healthcare, and secure defense systems.

ANALYZING VULNERABILITIES MALFUNCTIONS AND SECURITY BREACHES IN ELECTRONIC VOTING MACHINES

2025-10-06T10:17:32+00:00

A project analyzing electronic voting machines (EVMs) identifies vulnerabilities, malfunctions, and security breaches that can compromise election integrity. While EVMs are valued for their efficiency, they are susceptible to security threats like software vulnerabilities, cryptographic failures, and physical tampering. The study examines hardware and software weaknesses, such as buffer overflow attacks and weak encryption, alongside malfunctions from power failures and hardware faults, assessing their impact on voting accuracy. Through simulations and testing, the project reveals risks of vote manipulation, data loss, and election disruption. Recommendations include stronger encryption, regular audits, intrusion detection, and robust error handling, emphasizing the need to secure EVMs, protect the electoral process, and maintain public trust.

SKILL GAP ANALYSIS USING MACHINE LEARNING

2025-10-08T10:39:49+00:00

The “Skill Gap Analysis Using Machine Learning” project aims to bridge the gap between user skillsets and industry requirements. It examines user resumes, finds skill gaps, and gives a path for skill improvement using Natural Language Processing (NLP) and machine learning techniques. Additionally, the system suggests resources for interview preparation based on the professional domains that the user has chosen. This platform supports firms in workforce development while providing users with practical insights for career growth.

Editorial Note

2025-10-08T09:18:52+00:00

International Journal of Engineering Research and Sustainable Technologies (IJERST)

Volume 3, No.3 Online ISSN: 2584-1394

Message from Editorial Desk 25th September 2025

Dear Readers, Researchers, and Contributors,

With great pleasure, we present the September issue of IJERST, offering a fresh collection of innovative research and thought leadership in engineering and sustainable technologies. This issue reflects our vision of fostering collaboration and sharing transformative scientific work that advances both theory and practical solutions.

Notably, we continue to see an encouraging trend of interdisciplinary submissions and international participation. Our growing community speaks to the rising relevance of sustainable and impactful engineering research in the present global context. We are currently in the final stages of our application for DOAJ indexing, and initiatives to further enhance peer review standards and accessibility are underway.

We express sincere gratitude to the authors, peer reviewers, and our editorial team for their tireless effort and commitment. Your contributions shape the progress and reputation of our journal.

Warm regards,

On behalf of Editorial Team

Dr.V.RameshBabu

Managing Editor

Dean-University Journal , Dr.M.G.R. Educational and Research Institute Chennai,Tamilnadu,India

dean-univ.journals@drmgrdu.ac.in / ijerst@drmgrjournals.org