Adaptive AI in Sensor Informatics
Methods, Applications, and Implications
- 1st Edition - January 13, 2026
- Latest edition
- Editors: Karthik Ramamurthy, Suganthi Kulanthaivelu, S. Sountharrajan, S. B. Goyal, Seifedine Kadry
- Language: English
Adaptive AI in Sensor Informatics: Methods, Applications, and Implications explores the growing need for efficient, interpretable, and reliable adaptive AI systems tailored to wir… Read more
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Description
Description
The book also examines the unique challenges and opportunities that arise when deploying adaptive AI in real-world sensor environments. It offers actionable advice for designing AI models that comply with regulations and support user confidence, especially in areas such as healthcare, environmental monitoring, smart cities, and industrial automation.
Key features
Key features
• 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
Readership
Readership
Table of contents
Table of contents
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
Product details
Product details
- Edition: 1
- Latest edition
- Published: January 15, 2026
- Language: English
About the editors
About the editors
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.
SK
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.
SS
S. Sountharrajan
SG
S. B. Goyal
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.
SK
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.