Fall Detection and Observation System over Linux Environment with IOT

An enhanced fall detection system is proposed for elderly person monitoring that is based on-body sensor operating through consumer home networks and Internet of things(IoT). The on-body sensor which consists of accelerometer and cardio tachometer is used in this model. In this proposed system accelerometer measures overall vibration by means of using Signal Magnitude Vector and trunk angle. Here Signal Magnitude Vector is used to calculate the acceleration caused due to movement of the body with respect to xyz axis and trunk angle is used to calculate the posture of the elderly person during fall event, also these values will be updated over the web for caretaker view. Cardio tachometer is used to measure the pulse rate. A typical fall event ends with the person lying on the ground or leaning on walls, or furniture that will cause a significant change in trunk angle. In this case, it is desirable to consider changes on the trunk angle to detect whether the detected acceleration was due to a fall event. The set values of acceleration and pulse provides accuracy to the system avoiding false detection. This system is connected to GPS to measure the latitude and longitude values and GSM for communication purpose which is unique.