Human Motion Recognition Based on Integrate Interval Grey Association Degree With Pyroelectric Sensors Node

Human intrusion has always been one of the risks of port management. Pyroelectric infrared (PIR) sensor has been widely used in high-precision tracking of moving human body, which provides an effective method to monitor human intrusion. However, radial distance is still an important factor affecting PIR detection of the human body. In order to effectively detect the radial distance of the human body, this article proposes a reliable, simple, and easy-to-implement new method for detecting human radial distance based on the integrate interval grey association degree (IIGAD) algorithm. The method fuses multiple pyroelectric feature information of the human body, and integrates the subjective and objective weights into the interval grey correlation coefficient matrix composed of the human body feature information, so as to obtain the correlation degree of the radial distance between the human body and the pyroelectric sensor nodes. The accurate identification of the radial distance between the moving human target and the pyroelectric sensor node is further achieved through the correlation degree. The experimental results show that the greater the grey correlation degree of the comprehensive interval, the stronger the recognition reliability of the distance, and the correct recognition rate can reach more than 82%. In a private, concealed or high-level security area, that is not suitable for deploying cameras, pyroelectric sensors can replace them to enhance security monitoring. The proposed method provides a strong theoretical support for the realization of high-precision tracking of moving human body by pyroelectric sensors.