Energy Efficient Internet of Things-Based Wireless Sensor Network

Tackle the critical challenge of sustainability in modern technology with this essential book, which provides a comprehensive, expert-led exploration of energy-aware methodologies and machine learning strategies for optimizing IoT-based wireless sensor networks.

With the rapid expansion of IoT applications in diverse domains such as smart cities, agriculture, healthcare, and industry, energy constraints pose significant challenges to maintaining sustainable operations. This book addresses these challenges by presenting a comprehensive exploration of methodologies, technologies, and strategies aimed at optimizing energy usage in IoT-based wireless sensor networks. Authored by experts from academia and industry, the book covers topics such as energy-aware routing protocols, edge computing, energy harvesting technologies, machine learning applications, and blockchain-based energy management frameworks. Each chapter provides cutting-edge insights and practical approaches to fostering energy efficiency while ensuring robust and scalable IoT solutions. This book serves as a valuable resource for researchers, professionals, and policymakers, offering actionable knowledge to navigate the evolving landscape of IoT and wireless sensor network technologies.

Readers will find the volume:

• Explores the intersection of Internet of Things, wireless sensor networks, and energy efficiency across fundamental concepts, protocols, applications, and advanced solutions;
• Features chapters by leading researchers and industry professionals, providing authoritative perspectives;
• Offers actionable insights for implementing sustainable and energy-efficient IoT solutions in diverse fields like healthcare, agriculture, and smart cities;
• Highlights emerging trends, including AI, machine learning, and blockchain integration in wireless sensor networks.

Audience

Researchers, academics, engineers, system architects, technology developers, and policymakers specializing in IoT, wireless communications, and energy-efficient systems.

Arvind Panwar, PhD is an Associate Professor in the School of Computing Science and Engineering at Galgotias University, India with more than ten years of teaching experience. He has published more than 20 research papers in international journals and conferences and five Indian patents, one of which has been granted. His areas of interest include blockchain technology, distributed ledger technology, data science, machine learning, data mining, and network security.

Vishal Jain, PhD is a Professor in the Department of Computer Science and Engineering in the School of Engineering and Technology at Vivekananda Institute of Professional Studies’ Technical Campus, India. He has published more than 250 research papers in professional journals and conferences and more than 70 books and edited ten book series. His research areas include machine learning, information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, sensor networks, and network security.

Urvashi Sugandh, PhD is an Assistant Professor at Galgotias University and a Professor at Chitkara University, India with more than 12 years of research and teaching experience. She has published seven journal articles, ten conference papers, 11 book chapters, edited two books, and 11 patents, six of which have been granted. Her expertise spans blockchain technology, cybersecurity, and Internet of Things applications.

Vinay Kukreja, PhD is a Professor and the Director of Research in the Office of Research Publications at Chitkara University, India with more than 18 years of experience. He has published more than 600 articles, three books, four edited volumes, and 50 patents. His research interests encompass machine learning, deep learning, agile software development, image processing, data analysis, and structural equation modeling.