Optimizing Healthcare Patient Monitoring Through an Energy-Efficient Forward Greedy Algorithm (EEFGA) in WSN

Wireless sensor networks (WSNs) have become a game-changing technology for healthcare patient monitoring, providing continuous and non-invasive monitoring in clinical and remote settings. However, a major obstacle still exists in the effective selection of sensor nodes in a WSN for patient monitoring while taking energy consumption into account. We offer an Energy-Efficient Forward Greedy Algorithm (EEFGA) for Sensor Node Selection in response to this problem. This algorithm aims to maximize patient coverage while minimizing energy use in order to carefully balance resource management and healthcare quality. The procedure involves a step-by-step selection of sensor nodes that, while remaining below predefined energy restrictions, deliver the most significant coverage increases. We investigate the mathematical foundations of the method, investigate its practical applicability in healthcare contexts, and demonstrate through comprehensive simulations that EEFGA extends network lifetime by 32% compared to HEED, reduces end-to-end delay to 2.3±0.3ms, and achieves 96.2% patient coverage while maintaining energy efficiency of 0.045 J/packet in 150-node healthcare monitoring networks.