Perspectives on Artificial Intelligence and Internet of Things for Sustainable Environment

· ·
· Elsevier
Sách điện tử
450
Trang
Đủ điều kiện
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Giới thiệu về sách điện tử này

Perspectives on Artificial Intelligence and Internet of Things for Sustainable Environment addresses urgent environmental issues stemming from urbanization, deforestation, and pollution by harnessing the power of artificial intelligence and the Internet of Things. This book offers readers crucial insights into how AI can be integrated with IoT, providing the knowledge necessary for leveraging these technologies to foster a sustainable future. In addition to theoretical knowledge, this book serves as a practical guide, offering tailored practices for AI and IoT integration. Case studies provide hands-on experience, empowering readers to make informed decisions on selecting and applying various AI and IoT frameworks for environmental sustainability. - Explores emerging trends in AI and IOT and their applications for environmental sustainability - Provides step-by-step guidance by showcasing the successful applications of AI and IOT in environmental monitoring and assessment - Includes actionable guidelines for deploying AI and IOT-based solutions

Giới thiệu tác giả

Gwanggil Jeon, PhD, is currently a Full Professor at Incheon National University, Incheon, Korea. He was previously a Visiting Professor at Sichuan University, China, Universitat Pompeu Fabra, Barcelona, Spain, Xinjiang University, China, King Mongkut's Institute of Technology, Ladkrabang, Bangkok, Thailand, and University of Burgundy, Dijon, France. Dr. Jeon is an IEEE Senior Member, an Associate Editor of Sustainable Cities and Society, IEEE Access, Real-Time Image Processing, Journal of System Architecture, and MDPI Remote Sensing. Dr. Jeon was a recipient of the IEEE Chester Sall Award in 2007, the ETRI Journal Paper Award in 2008, and Industry-Academic Merit Award by Ministry of SMEs and Startups of Korea Minister in 2020.

Dr. Bhisham Sharma received a Ph.D. in Computer Science & Engineering from the PEC University of Technology (Formerly Punjab Engineering College), Chandigarh, India. He is currently working as an Associate Professor in the Centre of Research Impact and Outcome (CRIO), Chitkara University, Punjab, India. He is having 14 years of teaching and research experience at various reputed Universities in India. He has received the Excellence Award for publishing research papers with the highest H-index is given by Chitkara University in 2020, 2021 & 2023. He is currently serving as an associate editor for the Computers & Electrical Engineering (Elsevier), International Journal of Communication Systems (Wiley), Human-centric Computing and Information Sciences (HCIS), PLOS ONE, and Technical Editor of Computer Communication (Elsevier). He is Guest Editor (GE) in Q1 journals CEE Elsevier, Sensors MDPI, Security and Communication Networks (Hindawi), Current Medical Imaging (Bentham Science) & Environmental Science and Pollution Research (Springer). He is also a reviewer for more than 40 journals such as Future Generation Computing Systems, IEEE Access, Computer Networks, Frontier of Computer Science, International Journal of Communication Systems, IEEE Transactions on Reliability, and so on. His research interests include Mobile Computing, Cloud Computing, Quantum Computing, Wireless Communication, Wireless Sensor Networks, Wireless Mesh Networks, Next Generation Networking, Network Security, Internet of Things, UAV, Medical Image Processing, AI, DL, ML and Edge/Fog Computing in which he has published over 100 research papers in reputed SCI and Scopus indexed journals, international conferences, and book chapters.

Dr. Nitish Katal is currently working as Assistant Professor in School of Electronics and Communication Engineering at Vellore Institute of Technology Chennai. He has received his PhD degree in Electrical Engineering from Punjab Engineering College (Deemed to be University), Chandigarh. His research interests include robust and optimal control systems, soft computing, multi-objective optimization, and deep learning.

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