Role of AI in wireless sensor network

Incorporating artificial intelligence (AI) into wireless sensor networks (WSNs) has become a pivotal strategy for improving their performance, scalability, and adaptability. WSNs, composed of spatially distributed sensor nodes, are extensively employed to monitor and gather data across diverse fields, including healthcare, agriculture, industrial systems, and smart urban infrastructures. Despite their potential, WSNs face several limitations such as constrained energy supply, dynamic network structures, redundant data, and the need for timely decision-making. AI methodologies including machine learning, deep learning, swarm intelligence, and data reduction, provide effective solutions to these challenges. By facilitating intelligent data processing, efficient routing, anomaly detection, and predictive maintenance, AI greatly enhances the intelligence and autonomy of WSNs. This chapter investigates the multifaceted roles of AI in optimizing WSN performance, highlights recent developments, and explores future directions and challenges in the integration of AI with WSN technologies.