Frontiers in Engineering, Science and Technology
1st Edition
Will be published approx. on 11. August 2026
350 pages
E-Book
978-1-040-99835-9 (ISBN)
Description
This book presents a curated collection of peer-reviewed research contributions emerging from the International Conference on Frontiers in Engineering, Science, and Technology (ICONFEST 2025). It highlights contemporary innovations, interdisciplinary approaches, and transformative technologies that are shaping the future of engineering and applied sciences.
The volume brings together diverse research works spanning computer science, electrical and electronics engineering, mechanical and manufacturing systems, civil and environmental engineering, and materials science. It emphasizes the growing significance of interdisciplinary collaboration in addressing complex real-world challenges. Key themes include artificial intelligence and machine learning applications, intelligent infrastructure, renewable and sustainable energy systems, and advancements in smart manufacturing technologies. The book captures cutting-edge methodologies, experimental findings, and practical implementations, reflecting both theoretical advancements and industry-driven innovations. By integrating perspectives from academia and industry, it demonstrates how convergent research can foster sustainable development and technological progress across multiple domains.
This book is intended for researchers, academicians, industry professionals, and postgraduate students engaged in engineering, applied sciences, and emerging technologies. It serves as a valuable reference for those seeking insights into current research trends, interdisciplinary innovations, and practical solutions to contemporary engineering challenges.
The volume brings together diverse research works spanning computer science, electrical and electronics engineering, mechanical and manufacturing systems, civil and environmental engineering, and materials science. It emphasizes the growing significance of interdisciplinary collaboration in addressing complex real-world challenges. Key themes include artificial intelligence and machine learning applications, intelligent infrastructure, renewable and sustainable energy systems, and advancements in smart manufacturing technologies. The book captures cutting-edge methodologies, experimental findings, and practical implementations, reflecting both theoretical advancements and industry-driven innovations. By integrating perspectives from academia and industry, it demonstrates how convergent research can foster sustainable development and technological progress across multiple domains.
This book is intended for researchers, academicians, industry professionals, and postgraduate students engaged in engineering, applied sciences, and emerging technologies. It serves as a valuable reference for those seeking insights into current research trends, interdisciplinary innovations, and practical solutions to contemporary engineering challenges.
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Product notice
Reflowable
ISBN-13
978-1-040-99835-9 (9781040998359)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Sitanath Biswas | Sayan Chakraborty
Frontiers in Engineering, Science and Technology
Book
approx. 08/2026
1st Edition
CRC Press
€62.00
Not yet published
Sitanath Biswas | Sayan Chakraborty
Frontiers in Engineering, Science and Technology
Book
approx. 08/2026
1st Edition
CRC Press
€66.00
Not yet published
Persons
Sitanath Biswas is the Head of the Departments of CST and AIML at JIS College of Engineering, with over 20 years of experience in teaching, research, and academic administration. He holds a Ph.D. in Computer Science and Engineering and is a certified Change Management Professional (CMI). His expertise lies in Artificial Intelligence, Machine Learning, and Natural Language Processing (NLP). He has authored over 20 research publications, published 7 books, and holds around 20 Indian patents. A committed academic leader, Dr. Biswas is known for driving innovation, fostering research, and bridging theoretical knowledge with practical applications in emerging technologies.
Sayan Chakraborty is an Assistant Professor in the Department of Computer Science and Technology at JIS College of Engineering, Kalyani, West Bengal. He earned his Ph.D. in Image Registration from Sikkim Manipal University in 2023 and holds both M.Tech and B.Tech degrees from JIS College of Engineering. With over 11 years of academic experience, he also worked as a Visiting Engineer at Global Biomedical Technologies, California, USA. His research interests include medical image processing, nature-inspired algorithms, and machine learning. He has published over 65 research papers, served on editorial boards, and is a Senior Member of IEEE.
Sayan Chakraborty is an Assistant Professor in the Department of Computer Science and Technology at JIS College of Engineering, Kalyani, West Bengal. He earned his Ph.D. in Image Registration from Sikkim Manipal University in 2023 and holds both M.Tech and B.Tech degrees from JIS College of Engineering. With over 11 years of academic experience, he also worked as a Visiting Engineer at Global Biomedical Technologies, California, USA. His research interests include medical image processing, nature-inspired algorithms, and machine learning. He has published over 65 research papers, served on editorial boards, and is a Senior Member of IEEE.
Content
1. A Strategic Roadmap for Renewable Energy Integration in India's Competitive Electricity Market: Policy, Infrastructure, and Digital Resilience. 2. Comparative Analysis of AI Models for Proliferative Diabetic Retinopathy Diagnosis Using Fundus Images. 3. Quantum-Enhanced V2G Scheduling forLarge-Scale EV Fleets. 4. LANDEASE AERIAL & GROUND DETECTOR. 5. Automated Alzheimer's Patient Monitoring Using Geofencing and Real-Time Notifications. 6. A Transfer Learning Approach to the Analysis of Sentiment for the Kannada Language Based on Indic-BERT and XLM-RoBERTa-Base. 7. PTF-IDFLSVC: A TF-IDF and Linear SVC-Based Pipeline for Emotion Detection via Sentiment Analysis. 8. Accuracy and Gesture-based recognition system for Smart Automation. 9. COVID-19 Lockdown and Air Quality Improvement: A Case Study on NO? Reduction Across West Bengal. 10. Fingerprint Based Non-Invasive Blood Group Detection Using Deep Neural Nets. 11. Design and Development of a Low Cost IoT Based Real-Time Air Quality Monitoring System for Chemistry Labs. 12. Intelligent AIoT-Blockchain System for Enhancing Construction Supply Chain Transparency and Efficiency. 13. Study on Water Use Efficiency in SRI (System of Rice Intensification) Method under the Drip Irrigation System. 14. Boosting Water Efficiency and Banana Productivity Using Various Methods of Drip Irrigation in New Alluvial Zone of West Bengal. 15. AI in the Detection and Prevention of Chronic Non-Communicable Diseases. 16. Anomaly Detection using TinyML. 17. Computational Methods to Discover Endometriosis Therapeutics in Chamomile: A Network Pharmacology and Docking Study. 18. AI-Based Mental Health Support Systems: LSTM-Attention and BERT Chatbot Implementations. 19. Enhanced Suspicious Activity Detection in Cow Farm Using a CNN-Based Model. 20. CryptC: A Secure and Efficient Blockchain- Based Cryptocurrency Wallet Using React Native and Ethereum. 21. Securing IoT Networks Using Hybrid Machine Learning Model Against DDoS Attacks. 22. Encryption-Based Frameworks for Secure Web Development. 23. Sentiment Analysis of Amazon Product Reviews using NLP Machine Learning Techniques. 24. Eye Disease Classification Using Deep Learning on Fundus Images. 25. KG-DB: A Knowledge Graph-Based Database for Disorder Representation and Analysis. 26. Aware Melanoma Detection Using GANs: Enhancing Diagnostic Accuracy in Dermatology. 27. Enhancing Student Performance Prediction Using Deep Learning and Explainable AI: A Case Study on the Offee Dataset. 28. Chart Detection and Recognition in Document Image Analysis. 29. Optimization of Dynamic Credit Scoring Models for Financial Risk Assessment. 30. Metaverse Interoperability: Transferring NFT using Decentralized Oracle Network. 31. Exploring the Role of LZ77 to Deflate in Smart Computing and Information Security: A Comparative Approach. 32. Firefighting Drones: Pioneering Safety and Efficiency in Emergency Response. 33. Deep Learning Applications in Oil and Gas Production Optimization. 34. AI-Powered Gym Trainer: A Real-Time Exercise Monitoring System Using Pose Estimation and Machine Learning. 35. An IoT-Enabled Multi-Sensor Smart Helmet for Worker Safety and Tracking in Underground Mining. 36. Context-Aware Customer Segmentation Using Zipf-Weighted RFM Modeling. 37. A Review on Convolution Neural Network Based Classification Techniques for Efficient Detection of Plant Leaf Disease. 38. AutoMedAgent: A Novel Agentic AI Approach for Biomedical Research and Early Detection of Breast Cancer. 39. Proactive Budget Management Through AI-Powered Receipt Digitization. 40. Utilizing Agricultural and Industrial Waste for High-Performance Bio-Composites: A Study on Luffa-Cenosphere PMC. 41. Application of deep learning in developing smart cities. 42. A Systematic Review of Technology-Assisted Recruitment Practices and Their Impact on Modern Hiring. 43. Numerical study on the effectiveness of nanofluids in heat sink cooling application. 44. AI-Enhanced Assessment of Childhood Behavioural Deviations: Clinical Perspectives and Applications. 45. Explainable AI in Smart Health Attacks. 46. Analysis of heat and mass transfer of chemically reactive hybrid nanofluid flow over a stretching sheet in a porous medium with velocity slip. 47. AI Powered Stock Market Prediction Web Application - A Review. 48. A Critical Review on Generative Artificial Intelligence in Healthcare: Innovations, Applications and Challenges. 49. Study on the influence of heat treatment on the mechanical properties of low-carbon steel.
