Person tracking using Kalman Filter in Wireless Sensor Network

Wireless Sensor Network (WSN) is an emerging technology for person detection and tracking. This paper proposes a scheme for detecting and tracking a person using WSN. In an organization where employees possess unique Radio Frequency Identification (RFID) tags, a WSN node detects the presence of a person using a PIR sensor and the identity of the person is obtained from the RFID tag. The accuracy of tracking a person in a WSN is limited due to the sensor´s detection capabilities. Also, the sensor packets may be lost in the wireless medium. Moreover, the location information in the sensor is not accurate indoors. This paper proposes a multi-sensor and Kalman Filter (KF) based tracking scheme in a WSN oblivious to localization errors, errors due to missing events caused by failure of nodes etc. The accuracy of the proposed tracking has been validated for different scenarios.