About this ebook
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.
