International Journal of Engineering Research and Sustainable Technologies (IJERST)

DETECTION OF CHEST DISEASES IN RADIO GRAPHS USING DEEP LEARNING

Roselin Sahana Roy — 2024-12-25

One of the most widely used and easily accessible diagnostic methods for identifying a variety of pulmonary disorders is still chest radiography. However, interpreting chest radiographs accurately requires significant experience and time, which can lead to delays in diagnosis and treatment. To enhance the precision and efficiency of diagnosis, we present a deep learning-based method for the automated identification of chest disorders in radiographs. Our approach analyzes chest radiographs and detects anomalies indicative of various pulmonary diseases using convolutional neural networks (CNNs), a type of deep learning model well-suited for image recognition tasks. We utilize a large collection of annotated chest radiographs covering a wide range of pathological conditions, including pulmonary edema, lung cancer, pneumonia, and tuberculosis.

ENHANCING E-COMMERCE COMPETITIVENESS: CNN-BASED PRICE COMPSRISON APPLICATION

Shaik Aslam Basha — 2024-12-25

This paper introduces an innovative method for price comparison on e-commerce websites using Convolutional Neural Networks (CNNs). We discuss the importance of price comparison, highlight the flaws in manual methods, and examine the limitations of existing systems. Our CNN-based solution automates price extraction and analysis from various online retailers, streamlining cross-platform comparisons. By processing both textual and visual data, such as product descriptions and images, our approach improves accuracy. Real-time data updates enhance the user experience. Through rigorous testing, we demonstrate the effectiveness of our CNN-based solution, promising a superior shopping experience for e-commerce consumers.

OPTIMIZED COOPERATIVE ROUTING ALGORITHM FOR AUTONOMOUS VEHICLE IN SWARM NETWORKS

R.Sreenithi — 2024-12-25

Transportation is integral to human life, driving continuous advancements in vehicle speed and safety. However, car accidents remain a persistent challenge. To address this, research is increasingly focused on autonomous systems. This paper explores the integration of dynamic cooperative routing algorithms based on swarm intelligence into autonomous vehicles. By leveraging swarm intelligence principles, these vehicles can navigate dynamically, proactively avoiding collisions and fostering cooperative driving. This approach enhances safety, reduces accident rates, and paves the way for a new era of intelligent, collaborative autonomous transportation.

SECURING THE VOTE: LEVERAGING ANOMALY DETECTION IN BLOCKCHAIN SYSTEMS

Vignesh Poornachandran — 2024-12-25

E-voting with blockchain technology presents a promising solution to enhance the security, transparency, and efficiency of traditional voting systems. This paper explores the key components and functionalities of blockchain-based e-voting, emphasizing benefits such as decentralized consensus, immutability, and auditability. The process involves voter authentication, encrypted vote submission, blockchain consensus, and transparent record-keeping. However, challenges such as scalability, privacy concerns, and regulatory frameworks must be addressed for widespread adoption. Blockchain-based e-voting has emerged as an innovative approach to transforming electoral systems worldwide. This paper examines its fundamental principles and mechanics, highlighting its potential to resolve long-standing issues like fraud, coercion, and inefficiency in traditional voting methods. Through decentralized architecture and cryptographic techniques, blockchain ensures the integrity, transparency, and security of the voting process. The key stages include voter authentication, encrypted ballot submission, blockchain consensus, and immutable record-keeping. Despite its significant advantages, challenges remain, including scalability, privacy preservation, and regulatory compliance. By overcoming these obstacles, blockchain-based e-voting has the potential to redefine democracy, fostering trust, inclusivity, and integrity in electoral processes worldwide.

A REAL TIME INDIAN SIGN LANGUAGE RECOGNITION USING TENSORFLOW

Sanjusaran K — 2024-12-25

Communication is the exchange of information, ideas, or emotions, typically through spoken or written language. However, for individuals who are deaf or mute, traditional communication methods may not be effective. Instead, they rely on sign language—a visual form of communication using gestures and movements. Unfortunately, many people are unfamiliar with sign language, creating a barrier between those who use it and those who do not. Machine learning offers a promising solution to this challenge. By training a model to recognize and translate sign language gestures into spoken or written language, we can bridge this communication gap. This study proposes a real-time Sign Language Recognition (SLR) system using transfer learning with TensorFlow. Our approach involves capturing Indian Sign Language (ISL) gestures via a webcam and continuously training a deep learning model for accurate, real-time recognition. To enhance usability, we integrate a text-to-audio translation feature, converting recognized gestures into spoken language. This functionality allows individuals proficient in sign language to communicate seamlessly with those who are not, fostering inclusivity and accessibility. By leveraging machine learning, our system aims to break communication barriers and create a more inclusive society.

Editorial Message

Dr.V.RameshBabu — 2024-12-25

Message from Editorial Desk 25th December 2024

Dear Readers, Researchers, and Contributors,

We are pleased to present the latest edition of the International Journal of Engineering Research and Sustainable Technologies (IJERST), Volume 2, No. 4, 2024. This issue continues our mission of highlighting pioneering research and innovative solutions in engineering and sustainability from distinguished scholars worldwide.

Our Patron, Er. A. C. S. Arun Kumar, has been the driving force behind this journal and the many others launched under Pen2Mind Publishing. We sincerely thank him for his vision, guidance, and unwavering support—both in resources and expertise—that have enabled us to reach new heights.

Exciting developments are underway as we move toward becoming a Crossref member. With continued support from our management and editorial team, we are making significant progress. Future editions will feature DOI assignments for all past and forthcoming articles, enhancing their accessibility and citation impact.

This edition showcases a diverse range of research contributions that not only advance engineering knowledge but also emphasize the urgency of sustainable practices in an ever-evolving technological landscape. We remain committed to academic excellence, and to further this commitment, we are actively working on expanding the journal’s presence through partnerships with leading academic databases and platforms.

Looking ahead, we plan to introduce thematic special issues, interactive online forums, and collaborative projects with esteemed universities and research institutions. These initiatives aim to foster interdisciplinary dialogue and drive impactful real-world solutions.

We extend our sincere appreciation to all our authors, reviewers, and editorial board members for their continuous dedication and support. Your contributions are vital to shaping a strong and dynamic research community.

Thank you for your readership, and we encourage you to submit your valuable research for future issues. Together, we can continue to push the boundaries of engineering innovation and sustainability.

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