A Robust Home Alone Faint Detection Based on Wireless Sensor Networks

Abstract

Target detection and tracking are one of the fundamental problems for wireless sensor networks and play an important role in the safety field. Faint detection is an important problem for the elderly people or patients or even pregnant women. It has wide application in current society. This paper proposed a method to collect information about the behavior and position of faint event in the sensing environment. This method detects and tracks faint person by combining Kalman filter and Camshift tracking algorithm. Experiments showed that the method yields good detection and tracking performance in complex environments.