Emerging Trends in Smart Computing, Communication and Automation

1. Auflage 2026
ISBN: 978-1-041-40699-0
Verlag: Taylor & Francis Ltd

Buch, Englisch, 292 Seiten, Format (B × H): 210 mm x 280 mm

Reihe: Conference Proceedings Series on Futuristic Intelligent and Smart Technologies

The book explores important application areas like healthcare, smart cities, agriculture, education, and energy systems, offering workable solutions and creative use cases. It highlights how AI, ML, and IoT may boost data management, upgrade infrastructure, and open up new avenues for research and development.

The book examines the transformative potential of AI, ML, and IoT in addressing practical issues. It takes a multidisciplinary approach, combining viewpoints from government, business, and academia to show how these technologies may promote sustainable development—a pressing issue of our day. This book, which features contributions from eminent academics, researchers, and business professionals, is an invaluable tool for comprehending how new technologies can promote social justice, economic advancement, and environmental sustainability, especially in light of India's developing digital ecosystem.

The book will serve as a comprehensive resource for academics, researchers and professionals in the fields of computer science, education, environmental sustainability.

Zielgruppe

Academic and Undergraduate Core

Autoren/Hrsg.

Biswas, Himadri

Banerjee, Jyoti Sekhar

Bhattacharyya, Siddhartha

De, Debashis

Sarigiannidis, Panagiotis

Platoš, Jan

Asad, Muhammad Mujtaba

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik Quantencomputer, DNA-Computing
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1. Design and implementation of a compute-in-memory sram with on chip mac for low-power edge computing 2. Review on estimation of soc and soh parameters of battery in energy storage system  3. A fermatean fuzzy mcdm approach to select ideal plastic material for food packaging with topsis method using novel distance measure.  4. Ai-driven stress detection for enhancing student well-being and academic performance using wearable smart-watch data  5. Seeing through the noise: self-supervised reconstruction for adversarially robust perception in autonomous vehicles  6. Optimization of transactions and energy consumption in blockchain technology for future prospective  7. Sentiment analysis on social media using bert model  8. Utilizing naïve bayes with fuzzy logic and wrapper feature selection to improve cyberbullying detection in terms of noisy textual data in social media context  9. A comprehensive review on handwritten medical prescription recognition using deep learning techniques  10. A hybrid ensemble framework for emotion detection using tf-idf through sentiment analysis: CoRNL  11. From fasttext to GPT-4o and deepseek: architecture-aware benchmarking for multimodal and scientific reasoning  12. Performance analysis of a CTO based-localization algorithm for smart grid  13. Enhancing interpretability in chronic kidney disease prediction: a comparative analysis of shap, lime and permutation feature importance  14. Quantum relay nodes: enhancing security and scalability in quantum key distribution networks  15. Scanning pattern optimization for wall-mounted ultrasonic sensor array in fall detection system  16. Ai based ingredient and freshness analyzer  17. Student feedback analysis using machine learning and natural language processing: a real-time web-based system  18. Integration of quantum error correction in the BB84 protocol: a comprehensive analysis and simulation using IBM quantum experience  19. A comprehensive survey on an integrated smart home security and health monitoring system using machine learning and IOT  20. Investigating the optical response of SPR sensors for cancerous cell detection 21. Dual image based reversible data hiding schemes for healthcare system utilizing weighted matrix  22. Parametric analysis and enhancement of uwb microstrip patch antenna for wireless application.  23. Hate speech detection using LSTM(long short-term memory)  24. A graph-theoretical study of vertex identification and its impact on domination parameters in network models  25. Application of discontinuous mathematical functions to engineering problems through integral transforms: some case studies  26. Design and evaluation of an RF energy harvester for low power applications operating in the 2.4ghz (wi-fi) frequency band  27. Error mitigation for a 2-bit quantum comparator on IBM quantum hardware  28. Implementation of AR in engineering projection  29. Economic sustainability of metal recovery from e-waste: a green AI-assisted modelling for sustainable smart cities  30. Auditing QOS of public cloud server using blockchain  31. Explainable AI-driven sentiment-aware market dynamics forecasting in decentralized finance (DEFI) ecosystems using XGBOOST  32. Dual image based reversible watermarking scheme using MPVD and MQVD  33. U-net-based deep learning framework for robust brain tumor segmentation and classification using multimodal MRI  34. Quizmania: a real-time web platform for enhancing teaching, learning and self-assessment for students  35. Leveraging structured and sequential learning for dynamic flight fare prediction  36. Feature-rich deep learning architecture for breast cancer detection: from image analysis to real-time app deployment 37. Estimations of weather parameters with modern tools-a survey  38. Dragon fruit maturity detection using transfer learning with densenet121: a high-accuracy deep learning approach for agricultural automation  39. Comparative optimization of combined heat and power economic dispatch and hydro-thermal scheduling with solar, wind using advanced metaheuristic techniques 40.

Über Autor(innen)

Himadri Biswas is presently working as a Dean & Professor in the department of Computer Science and Engineering, and is a past HoD & Professor in the Department of Information Technology of Budge Budge Institute of Technology, Kolkata. He has 22 years of teaching experience and served at several institutions as a HoD & Professor. His research interests include cloud computing, mobile computing, mobile cloud computing, data science, machine learning and deep learning.

Jyoti Sekhar Banerjee is currently serving as the Associate Professor & Head of the Computer Science and Engineering (AI & ML) Department at the Techno Bengal Institute of Technology, Kolkata, India. He is also the Professor-in-Charge of the R&D and Consultancy Cell & Nodal Officer of the IPR Cell at Techno BIT.

Siddhartha Bhattacharyya [FIET(UK), FIEI, FIETE, LFOSI, FSCRS, SMIEEE, SMACM, SMAAIA, SMIETI, LMCSI, LMISTE] is currently serving as a Senior Researcher in the Faculty of Electrical Engineering and Computer Science of VSB Technical University of Ostrava, Czech Republic. He also serves as the Scientific Advisor of Algebra University College, Zagreb, Croatia.

Debashis De is a professor in the Department of Computer Science and Engineering at the Maulana Abul Kalam Azad University of Technology, West Bengal, India. He received an M.Tech. degree from the University of Calcutta, in 2002. and a Ph.D. from Jadavpur University in 2005.

Panagiotis Sarigiannidis is the Director of the ITHACA lab, co-founder of the 1st spin-off of the University of Western Macedonia: MetaMind Innovations P.C., and Full Professor in the Department of Electrical and Computer Engineering in the University of Western Macedonia, Kozani, Greece. His research interests include telecommunication networks, internet of things and network security. He is an IEEE member and participates in the Editorial Boards of various journals.

Jan Platoš is a professor at the Department of Computer Science and the Dean of the Faculty of Electrical Engineering and Computer Science, VSB-TUO, Czech Republic. His primary fields of interest are machine learning, artificial intelligence, industrial data processing, text processing, data compression, bioinspired algorithms, information retrieval, data mining, data structures, and data prediction.

Muhammad Mujtaba Asad is serving as an Assistant Professor and Lead Researcher of Educational Technologies and TVET Research at Department of Education, Sukkur IBA University, Pakistan. He is also serving as an honorary international faculty at the American University of Nigeria.