Recent Advances in Wireless Rechargeable Sensor Networks: A Comprehensive Review of Energy Management and Charging Strategies

Wireless Rechargeable Sensor Networks (WRSNs) have emerged as a sustainable solution to the energy limitations of traditional Wireless Sensor Networks (WSNs). By integrating Wireless Power Transfer (WPT) technologies, WRSNs enable continuous energy replenishment, enhancing operational longevity and efficiency. However, challenges in energy management, charging strategies, and scalability persist. This review systematically examines recent advancements in WRSN energy management, focusing on state-of-the-art methodologies such as Deep Reinforcement Learning (DRL), Fuzzy Logic, metaheuristic optimisation, and UAV-assisted charging. A novel taxonomy is proposed to categorise charging strategies based on mechanisms, optimisation techniques, energy sources, and application domains. The review highlights key trends, including multi-agent UAV coordination, hybrid charging schemes, and decentralised energy optimisation. A comparative analysis evaluates the trade-offs in efficiency, scalability, and feasibility of existing approaches. Critical challenges such as computational overhead, real-world deployment feasibility, and scalability constraints are identified. The study underscores the need for adaptive scheduling mechanisms, intelligent energy management frameworks, and empirical validation to bridge the gap between simulations and practical implementation. Future research directions include sustainable charging solutions, enhanced scalability, and robust optimisation techniques to improve network reliability and efficiency in large-scale WRSN deployments.