Adaptive AI in Sensor Informatics: Methods, Applications, and Implications - Brossura

Brossura

ISBN 10: 0443364125 ISBN 13: 9780443364129

Casa editrice: Elsevier, 2026

Riassunto

Adaptive AI in wireless sensor networks is crucial for ensuring user understanding and confidence in AI outputs across fields such as healthcare, environmental monitoring, smart cities, and industrial automation. It enables compliance with regulations specific to these domains and encourages the design of user-centric AI systems that align with human values and operational requirements. Adaptive AI in Sensor Informatics delves into the need for efficiency, interpretability, and reliability in Adaptive AI systems that are designed specifically for wireless sensor networks and related domains. It sheds light on how Adaptive AI can provide decisions made by AI models, facilitating effective collaboration between humans and AI within the context of wireless sensor networks. The book serves as a comprehensive guide for academics, professionals, and students interested in the intersection of adaptive AI and wireless sensor networks. It examines the challenges and opportunities inherent in deploying Adaptive AI in these contexts and offers practical insights into methods, approaches, and best practices for developing and deploying AI models that are both understandable and reliable within wireless sensor networks.

Su questo libro

Informazioni sugli autori

Dr. Karthik Ramamurthy obtained his Doctoral degree from Vellore Institute of Technology, India and Master’s degree from Anna University, India. Currently, He serves as Associate Professor in the Research Centre for Cyber Physical Systems, Vellore Institute of Technology, Chennai. His research interest includes Artificial Intelligence, Deep Learning, Computer Vision, Digital Image Processing, and Medical Image Analysis. He has published around 80 papers in peer reviewed journals and conferences. He is an active reviewer for journals published by Elsevier, IEEE Springer and Nature.

Dr. Suganthi Kulanthaivelu is working as an Associate professor in the School of Electronics Engineering, Vellore Institute of Technology, Chennai, India. She has completed her PhD from Anna University in wireless sensor networks. She has approximately 15 years of teaching and research experience. Her area of research interest includes wireless sensor networks and its Internet of Things applications, Image processing, Artificial intelligence and Industrial IoT. She has published more than 20 research papers in journals and conferences.

S. Sountharrajan completed his PhD from Anna University in Information and Communication Engineering in the year 2017 and is currently working as Associate Professor in the School of Computing (SOC) at Amrita Vishwa Vidyapeetham, Chennai Campus. He is Program Head, B. Tech Computer Science and Engineering. He was sanctioned an amount of Rs. 38,00,000 from the funding agencies like DST, AICTE and ICMR. He has also published papers in 10 International / 6 National Conferences. He was published 35 International journals including 50 Scopus index and 12 SCI. He has been certified from reputed companies of India like the IBM, DELL EMC Corporation. He has delivered 33 Guest Lectures in reputed universities and Institutions in India. He has worked on Big Data, cloud computing show the importance of cloud deployed applications.

Dr. S. B. Goyal received his Ph.D. in Computer Science and Engineering from Banasthali University, Rajasthan, India, in 2012. He is currently working as Professor and Dean–CSE at Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India. He has over 22 years of national and international academic and research experience and has contributed to integrating Industry 4.0 technologies, including blockchain and artificial intelligence, into academic curricula.

Dr. Goyal holds more than ten international patents and copyrights from Australia, Germany, and India. His research interests include blockchain, artificial intelligence, cloud computing, cybersecurity, the Internet of Things, and data mining. He has served as editor or co-editor for several academic books and as a reviewer or guest editor for journals published by IEEE, Inderscience, IGI Global, and Springer. He has also been an invited speaker at international events such as Bloconomic 2019 and the World AI Show 2021.

Seifedine Kadry is a Professor in the Department of Mathematics and Computer Science, at Norrof University College, in Norway. He has a Bachelor’s degree in 1999 from Lebanese University, MS degree in 2002 from Reims University (France) and EPFL (Lausanne), PhD in 2007 from Blaise Pascal University (France), HDR degree in 2017 from Rouen University. At present, his research focuses on data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing, and ABET program evaluator for Engineering Tech. He is a Fellow of IET, Fellow of IETE, and Fellow of IACSIT. He is a distinguished speaker of IEEE Computer Society.

Dalla quarta di copertina

Adaptive AI in wireless sensor networks is crucial for ensuring user understanding and confidence in AI outputs across fields such as healthcare, environmental monitoring, smart cities, and industrial automation. It enables compliance with regulations specific to these domains and encourages the design of user-centric AI systems that align with human values and operational requirements. Adaptive AI in Sensor Informatics: Methods, Applications, and Implications delves into the need for efficiency, interpretability, and reliability in Adaptive AI systems that are designed specifically for wireless sensor networks and related domains. It sheds light on how Adaptive AI can provide decisions made by AI models, facilitating effective collaboration between humans and AI within the context of wireless sensor networks. This book serves as a comprehensive guide for academics, professionals, and students interested in the intersection of adaptive AI and wireless sensor networks. It examines the challenges and opportunities inherent in deploying Adaptive AI in these contexts and offers practical insights into methods, approaches, and best practices for developing and deploying AI models that are both understandable and reliable within wireless sensor networks.

Dettagli dell'edizione

• Editore: Elsevier
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 0443364125
• ISBN 13: 9780443364129
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 338
• Redattore: Ramamurthy
• Contatto del produttore: non disponibile
• Persona responsabile: LSWR Group; b.criscuolo@lswr.it; ; Via Spadolini, 7; Milano; Italia