AI-Enhanced Optimization Algorithm for Body Area Networks in Intelligent Wearable Patches for Elderly Women's Safety

Abstract

IoT-enabled sensor nodes gather real-time data and employ machine learning techniques to enable remote monitoring and rapid response. To overcome these challenges, the proposed solution employs the opportunistic power best routine algorithm (OPA), a heuristic algorithm designed to extend the lifespan of sensor nodes in the wearable patches for women's safety. This algorithm eliminates redundant data loops between network patches, ultimately increasing the efficiency of the system. The effectiveness of this approach is evaluated based on metrics such as network lifespan, latency in data sensing, throughput, and error rates. Maximizing power usage through algorithms like OP2A and employing predictive analytics, the system can enhance network efficiency, reduce response times, and ultimately contribute to a safer environment for women.