Design a Wearable IoT Devices using pressure Sensors for fall avoidance by Human Movement Monitoring system

Abstract

Seamless monitoring is one of the major challenge for human community because of increasing the strength of sixty years old people and occurrence of many accidents in falls-risk related works like construction, manufacture and others. Wearable IoT devices are useful for continuous health monitoring, analyzing the behaviors, and fall detection. Falls are one of the foremost causes for injuries and death in our life.  Present work proposes the human movement monitoring by using the pressure sensor for avoiding human falls and also the health report prepared from historical data’s uploaded in cloud by support-vector machine (SVM) algorithm. The proposed wearable IoT device for seamless monitoring system is proving 99% accuracy, less complex and compatible to use over other IoT wearable devices.

Keywords: wearable IoT devices, fall detection, SVM algorithm, machine learning.