IoT based Smart Fall Detection Device for Elderly People

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Abstract
Instances of falls, especially among the elderly, pose notable health concerns, prompting the need for innovative interventions. This paper presents an inventive approach to fall detection via the development of a wearable smart device. By harnessing Internet of Things technology and an advanced sensor array, our system aims to improve the precision and efficiency of fall detection while prioritizing user comfort. The proposed device seamlessly integrates into daily life, providing non-intrusive monitoring. Through the utilization of accelerometers, gyroscopes, and various sensor technologies, the system captures and assesses pertinent data related to human movement patterns. This data is then processed using an Internet of Things framework, enabling real-time communication and alert generation in the event of a fall. To validate the efficacy of our wearable smart fall detection device, extensive testing and evaluation have been carried out. The research focus includes assessing the device's sensitivity, specificity, and overall accuracy in distinguishing authentic falls from routine activities. The results illustrate the system's potential to deliver swift and precise fall detection, thereby facilitating timely assistance and minimizing the repercussions of falls.

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