Intelligent Wireless Sensor Networks and the Internet of Things
Algorithms, Methodologies, and Applications
1st Edition
Published on 25. December 2025
Book
Paperback/Softback
348 pages
978-1-032-76497-9 (ISBN)
Description
The edited book Intelligent Wireless Sensor Networks and Internet of Things: Algorithms, Methodologies and Applications is intended to discuss the progression of recent as well as future generation technologies for WSNs and IoTs applications through Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). In general, computing time is obviously increased when the massive data is required from sensor nodes in WSN's. the novel technologies such as 5G and 6G provides enough bandwidth for large data transmissions, however, unbalanced links faces the novel constraints on the geographical topology of the sensor networks. Above and beyond, data transmission congestion and data queue still happen in the WSNs.
This book:
Addresses the complete functional framework workflow in WSN and IoT domains using AI, ML, and DL models
Explores basic and high-level concepts of WSN security, and routing protocols, thus serving as a manual for those in the research field as the beginners to understand both basic and advanced aspects sensors, IoT with ML & DL applications in real-world related technology
Based on the latest technologies such as 5G, 6G and covering the major challenges, issues, and advances of protocols, and applications in wireless system
Explores intelligent route discovering, identification of research problems and its implications to the real world
Explains concepts of IoT communication protocols, intelligent sensors, statistics and exploratory data analytics, computational intelligence, machine learning, and Deep learning algorithms for betterment of the smarter humanity
Explores intelligent data processing, deep learning frameworks, and multi-agent systems in IoT-enabled WSN system
This book demonstrates and discovers the objectives, goals, challenges, and related solutions in advanced AI, ML, and DL approaches
This book is for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
This book:
Addresses the complete functional framework workflow in WSN and IoT domains using AI, ML, and DL models
Explores basic and high-level concepts of WSN security, and routing protocols, thus serving as a manual for those in the research field as the beginners to understand both basic and advanced aspects sensors, IoT with ML & DL applications in real-world related technology
Based on the latest technologies such as 5G, 6G and covering the major challenges, issues, and advances of protocols, and applications in wireless system
Explores intelligent route discovering, identification of research problems and its implications to the real world
Explains concepts of IoT communication protocols, intelligent sensors, statistics and exploratory data analytics, computational intelligence, machine learning, and Deep learning algorithms for betterment of the smarter humanity
Explores intelligent data processing, deep learning frameworks, and multi-agent systems in IoT-enabled WSN system
This book demonstrates and discovers the objectives, goals, challenges, and related solutions in advanced AI, ML, and DL approaches
This book is for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Postgraduate, Professional Reference, and Undergraduate Advanced
Illustrations
70 s/w Zeichnungen, 20 s/w Tabellen, 84 s/w Abbildungen, 14 s/w Photographien bzw. Rasterbilder
20 Tables, black and white; 70 Line drawings, black and white; 14 Halftones, black and white; 84 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 20 mm
Weight
559 gr
ISBN-13
978-1-032-76497-9 (9781032764979)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Bhanu Chander | Anoop Benet Nirmala | Koppala Guravaiah
Intelligent Wireless Sensor Networks and the Internet of Things
Algorithms, Methodologies, and Applications
E-Book
06/2024
1st Edition
CRC Press
€90.99
Available for download
Bhanu Chander | Anoop Benet Nirmala | Koppala Guravaiah
Intelligent Wireless Sensor Networks and the Internet of Things
Algorithms, Methodologies, and Applications
E-Book
06/2024
1st Edition
CRC Press
€90.99
Available for download
Bhanu Chander | Anoop Benet Nirmala | Koppala Guravaiah
Intelligent Wireless Sensor Networks and the Internet of Things
Algorithms, Methodologies, and Applications
Book
06/2024
1st Edition
CRC Press
€242.70
Shipment within 10-20 days
Persons
Dr. Bhanu Chander
Assistant Professor, Department of Computer Science and Engineering, Indian Institute of Information Technology (IIIT-K)
Dr. Bhanu Chander, working as Assistant Professor at Indian Institute of Information Technology (IIIT-K), Pala, Kerala, India. Graduated from Acharya Nagarjuna University, A.P, in the year 2013. A post-graduate degree from the Central University of Rajasthan, Rajasthan in 2016. Ph.D. on Machine Learning in Wireless Sensor Networks for sensor data classification from Pondicherry University in 2022. He published 6 articles in peer-reviewed journals, 5 international conferences, and 8 book chapters (Elsevier, Wiley, CRC and Springer). Presently his main interesting areas include Wireless Sensor Networks, IoT and Healthcare, Cryptography, Machine Learning, Deep Learning.
Dr. Anoop B
Postdoctoral Research Fellow, University of Texas Health Science Centre.
Dr. Anoop working as Postdoctoral Research Fellow at Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Centre, US. He received Ph.D. degree on Development of Automated Methods for Retinal Optical Coherence Tomography Image Analysis from National Institute of Technology, Surathkal in 2021. MTech on Signal Processing from National Institute of Technology, Calicut, 2013. He published 6 articles in peer-reviewed journals, and 2 book chapters. Presently his main interesting areas include Medical Image processing, Deep Learning, GANs and Auto-encoders.
Dr. Koppala Guravaiah
Assistant Professor, Department of Computer Science and Engineering, Indian Institute of Information Technology
Dr. Koppala Guravaiah, working as Assistant Professor at Indian Institute of Information Technology (IIIT-K), Pala, Kerala, India. Completed Ph.D. on the topic performance of Routing protocols in Wireless Sensor Networks using River formation dynamics from National Institute of Technology Tiruchirappalli, India. His research interests include the Internet of Things (IoT), Software Defined Networks, Wireless Ad hoc, and Sensor network routing protocols and their applications. He published 5 Journals, 8 conferences, 2 book chapters in the areas mentioned above by his name.
Dr. G. Kumaravelan
Assistant Professor & Head (i/c), Department of Computer Science, School of Engineering & Technology, Pondicherry University
Dr. G. Kumaravelan, working as Assistant professor in the Department of Computer Science and Engineering at Pondicherry University, Karaikal Campus, Pondicherry, India - 609605. He received a Ph.D. degree in Communications and Information Systems from Bharathidasan University in 2008. He has more than 12 years of teaching and research experience, published 20 articles in peer-reviewed journals and international conferences. He is an active reviewer in various international conferences and peer-reviewed journals. His research interests include the internet of things, cloud computing, big data analytics, wireless communications, and networking.
Assistant Professor, Department of Computer Science and Engineering, Indian Institute of Information Technology (IIIT-K)
Dr. Bhanu Chander, working as Assistant Professor at Indian Institute of Information Technology (IIIT-K), Pala, Kerala, India. Graduated from Acharya Nagarjuna University, A.P, in the year 2013. A post-graduate degree from the Central University of Rajasthan, Rajasthan in 2016. Ph.D. on Machine Learning in Wireless Sensor Networks for sensor data classification from Pondicherry University in 2022. He published 6 articles in peer-reviewed journals, 5 international conferences, and 8 book chapters (Elsevier, Wiley, CRC and Springer). Presently his main interesting areas include Wireless Sensor Networks, IoT and Healthcare, Cryptography, Machine Learning, Deep Learning.
Dr. Anoop B
Postdoctoral Research Fellow, University of Texas Health Science Centre.
Dr. Anoop working as Postdoctoral Research Fellow at Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Centre, US. He received Ph.D. degree on Development of Automated Methods for Retinal Optical Coherence Tomography Image Analysis from National Institute of Technology, Surathkal in 2021. MTech on Signal Processing from National Institute of Technology, Calicut, 2013. He published 6 articles in peer-reviewed journals, and 2 book chapters. Presently his main interesting areas include Medical Image processing, Deep Learning, GANs and Auto-encoders.
Dr. Koppala Guravaiah
Assistant Professor, Department of Computer Science and Engineering, Indian Institute of Information Technology
Dr. Koppala Guravaiah, working as Assistant Professor at Indian Institute of Information Technology (IIIT-K), Pala, Kerala, India. Completed Ph.D. on the topic performance of Routing protocols in Wireless Sensor Networks using River formation dynamics from National Institute of Technology Tiruchirappalli, India. His research interests include the Internet of Things (IoT), Software Defined Networks, Wireless Ad hoc, and Sensor network routing protocols and their applications. He published 5 Journals, 8 conferences, 2 book chapters in the areas mentioned above by his name.
Dr. G. Kumaravelan
Assistant Professor & Head (i/c), Department of Computer Science, School of Engineering & Technology, Pondicherry University
Dr. G. Kumaravelan, working as Assistant professor in the Department of Computer Science and Engineering at Pondicherry University, Karaikal Campus, Pondicherry, India - 609605. He received a Ph.D. degree in Communications and Information Systems from Bharathidasan University in 2008. He has more than 12 years of teaching and research experience, published 20 articles in peer-reviewed journals and international conferences. He is an active reviewer in various international conferences and peer-reviewed journals. His research interests include the internet of things, cloud computing, big data analytics, wireless communications, and networking.
Content
1. Energy Efficient WSN With Deep Learning Using Dispersed Data Mining Strategy Based LSTM. 2. Learning-based Intelligent Energy Efficient Routing Protocols in WSN for Industry 5.0. 3. Optimizing Secure Routing For Mobile Ad-Hoc and WSN In IoT Through Dynamic Adaption And Energy Efficiency. 4. Energy Efficient In-Network Data Aggregation in Internet-of-Things. 5. Future 6g Approaches: Integrating Intelligent Security, Sensing, And Communication Into A Green Network's Architecture. 6. Energy Efficient Wireless Sensors Architecture With LSTM Based On Machine Learning Technique. 7. Healthcare 4.0: Blockchain Technology Application in Healthcare Ecosystem. 8. Inventory Tracking Via IoT in the Pharmaceutical Industry. 9. A Decentralized File Sharing System Based On IPFS And Blockchain. 10. FAWT Based Advanced Multiboost Learning Algorithm For Driver Fatigue Detection Using Brain EEG Signals. 11. Feature Fusion based learning algorithm using Multi-Domain Signal Features For Wearable Healthcare Devices. 12. The Intelligent of WSNs. 13. Applications of Wireless Sensor Networks in IoT. 14. Security considerations in IoT using Machine Learning and Deep Learning. 15. Block chain-Energized Smart Healthcare Monitoring System