Wireless Body Area Networks: A Promising Technology for Fall Detection – A Review

Abstract

Falling is a major risk factor for the senior population, who may suffer significant injuries, loss of independence, or even death. Various fall detection devices, including wearable and environment-based sensors that employ IoT and AI to detect falls and monitor everyday activities, have been created to solve this issue. However, the utilization of cutting-edge AI methods like machine and deep learning models and the availability of high- quality data are both necessary for these systems to function effectively. Recent research has demonstrated that CNN-based models are the most accurate in detecting falls, but it is still necessary to construct lightweight deep models for older people. Overall, there is potential for intelligent IoT-enabled fall detection and monitoring systems to improve the safety and well-being of the elderly population.