Artificial Intelligence in Wireless Sensor Network

Artificial Intelligence in Wireless Sensor Networks provides a comprehensive examination of intelligent techniques applied to sensor-based communication systems. The book begins with foundational concepts of WSN architecture, communication protocols, sensor node design, and network topologies. It then systematically introduces AI methodologies relevant to WSN optimization and management.
Detailed chapters cover supervised and unsupervised learning for data aggregation, deep learning for pattern recognition, reinforcement learning for adaptive routing, swarm intelligence for network optimization, and predictive analytics for fault tolerance. The book also addresses cybersecurity enhancements through AI-based intrusion detection systems and blockchain-assisted secure communication frameworks.
Emerging themes such as edge computing, green AI for sustainable sensor deployments, and AI-enabled IoT integration are discussed with case studies from healthcare, agriculture, environmental monitoring, and industrial systems.
Designed for postgraduate students, doctoral scholars, researchers, and industry professionals in electronics, computer science, and communication engineering, this book serves as both a theoretical foundation and an applied guide for advancing intelligent wireless sensor network technologies.