Adaptive AI in Sensor Informatics
Methods, Applications, and Implications
- 1st Edition - January 1, 2026
- Imprint: Elsevier
- Editors: Karthik Ramamurthy, Suganthi Kulanthaivelu, S. Sountharrajan, S. B. Goyal, Seifedine Kadry
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 6 4 1 2 - 9
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 6 4 1 3 - 6
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… Read more
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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. 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.
- Draws on the latest research and methods to provide valuable insight into the efficiency of AI-based systems, particularly within the realm of wireless sensors and related domains
- Explores and explains the critical role played by adaptive AI and sensor informatics in healthcare, finance, and autonomous vehicles, where the synergy of AI and sensor data plays a pivotal role
- Presents relevant case studies, practical demonstrations, and empirical evidence to substantiate the efficacy of AI-enabled sensor systems
Researchers, graduate students, and professionals in the fields of sensors, artificial intelligence, machine learning, adaptive systems, and sensor networks
1. AI in Sensor Technology
Integration of AI in sensor technology
Advancements in sensor design and development with AI
Applications of AI-enabled sensors in various domains
2. AI for Sensor Data Analysis
AI-driven techniques for sensor data analysis
Machine learning algorithms for sensor data interpretation
Real-time insights and decision-making using AI in sensor data analysis
3. Role of AI in Wireless Sensor Network (WSN)
Integration of AI in WSN
Challenges and advantages of AI in WSN
Emerging trends in AI and WSN Integration
4. AI driven-Smart data processing in WSN
Adaptive Data Fusion and Aggregation
Context-aware Data Processing Techniques
5. Energy Efficient communication with adaptive AI models
Energy aware transmission
Cognitive Radio Networks for Spectrum Management
Adaptive Routing protocols
6. Adaptive AI techniques for the deployment of WSN
Dynamic node deployment strategies for WSN
Dynamic optimization techniques for sensor placement
Smart Trajectory panning in UAV assisted WSN
7. AI in Smart Sensing and Things
AI based smart IoT system
Smart data storage and data processing
IoT data analytics Models
8. AI in Sensor Cloud
Data Processing in Sensor Cloud
AI-based Optimizations.
9. AI powered Edge computing for IoT
AI Models for Real-Time Data Processing and Decision-Making at the Edge
Edge-Based Machine Learning Inference and Model Deployment
Adaptive AI Algorithms for Resource-Constrained Edge Devices
10. Adaptive AI in techniques for Industrial Internet of Things
Adaptive AI-Driven Predictive Maintenance in Manufacturing
Smart Energy Management Systems for Industrial
Adaptive Robotics and Automation in Industrial Settings
Safety-Critical Applications with Adaptive AI in Industrial IoT
11. AI in Urban Infrastructure Monitoring
AI applications in urban infrastructure monitoring
Smart city initiatives and AI integration
Challenges and opportunities in urban infrastructure monitoring with AI
12. Real-World Applications
Healthcare Monitoring and Telemedicine
Smart Agriculture and Precision Farming
Energy Management and Smart Grids
AI in Environmental Monitoring and Sustainability
13. Future Directions and Emerging Trends of Adaptive AI in WSN, IoT, IIoT
Emerging Trends in Adaptive AI in WSN, IoT, IIoT
Challenges and Open Research Questions in Adaptive AI in WSN, IoT, IIoT
Integration of AI in sensor technology
Advancements in sensor design and development with AI
Applications of AI-enabled sensors in various domains
2. AI for Sensor Data Analysis
AI-driven techniques for sensor data analysis
Machine learning algorithms for sensor data interpretation
Real-time insights and decision-making using AI in sensor data analysis
3. Role of AI in Wireless Sensor Network (WSN)
Integration of AI in WSN
Challenges and advantages of AI in WSN
Emerging trends in AI and WSN Integration
4. AI driven-Smart data processing in WSN
Adaptive Data Fusion and Aggregation
Context-aware Data Processing Techniques
5. Energy Efficient communication with adaptive AI models
Energy aware transmission
Cognitive Radio Networks for Spectrum Management
Adaptive Routing protocols
6. Adaptive AI techniques for the deployment of WSN
Dynamic node deployment strategies for WSN
Dynamic optimization techniques for sensor placement
Smart Trajectory panning in UAV assisted WSN
7. AI in Smart Sensing and Things
AI based smart IoT system
Smart data storage and data processing
IoT data analytics Models
8. AI in Sensor Cloud
Data Processing in Sensor Cloud
AI-based Optimizations.
9. AI powered Edge computing for IoT
AI Models for Real-Time Data Processing and Decision-Making at the Edge
Edge-Based Machine Learning Inference and Model Deployment
Adaptive AI Algorithms for Resource-Constrained Edge Devices
10. Adaptive AI in techniques for Industrial Internet of Things
Adaptive AI-Driven Predictive Maintenance in Manufacturing
Smart Energy Management Systems for Industrial
Adaptive Robotics and Automation in Industrial Settings
Safety-Critical Applications with Adaptive AI in Industrial IoT
11. AI in Urban Infrastructure Monitoring
AI applications in urban infrastructure monitoring
Smart city initiatives and AI integration
Challenges and opportunities in urban infrastructure monitoring with AI
12. Real-World Applications
Healthcare Monitoring and Telemedicine
Smart Agriculture and Precision Farming
Energy Management and Smart Grids
AI in Environmental Monitoring and Sustainability
13. Future Directions and Emerging Trends of Adaptive AI in WSN, IoT, IIoT
Emerging Trends in Adaptive AI in WSN, IoT, IIoT
Challenges and Open Research Questions in Adaptive AI in WSN, IoT, IIoT
- Edition: 1
- Published: January 1, 2026
- Imprint: Elsevier
- Language: English
KR
Karthik Ramamurthy
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.
Affiliations and expertise
Vellore Institute of Technology, Chennai, IndiaSK
Suganthi Kulanthaivelu
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.
Affiliations and expertise
Vellore Institute of Technology, Chennai, IndiaSS
S. Sountharrajan
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.
Affiliations and expertise
Department of Computer Science and Engineering , School of Computing, Amrita Vishwa Vidyapeetham, Chennai, IndiaSG
S. B. Goyal
Dr. S. B. GOYAL received aPh.D. degree in computer science and engineering from Banasthali University, Rajasthan, India, in 2012. He is currently the Director of the Faculty of Information Technology, City University Malaysia. He has more than 22+ years of work experience at national and international levels and introduced IR 4.0, including blockchain technology into the academic curriculum in Malaysian universities. He holds more than ten international patents/copyrights from Australia, Germany, and India. His current research interests include blockchain, artificial intelligence, cloud computing, cyber security, the Internet of Things, data mining and warehousing, and method engineering. He has contributed as editor and co-editor for may books, and serves as a reviewer or guest editor in many international journals published by IEEE, Inderscience, IGI Global, and Springer. He was a Speaker in the Bloconomic 2019 Event on Blockchain and World AI Show 2021 Event on AI.
Affiliations and expertise
City University, Petaling Jaya, MalaysiaSK
Seifedine Kadry
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.
Affiliations and expertise
Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon; Department of Applied Data Science, Noroff University College, Kristiansand, Norway