Human localization and tracking using distributed motion sensors and an inertial measurement unit

The purpose of this research is to localize a resident in indoor environments by using distributed binary sensors and body activity information obtained from an inertial measurement unit (IMU). The hardware setup consists of two types of sensor nodes. The passive infrared (PIR) sensor node provides binary information about motion in its field of view, while the IMU sensor node collects motion data for body activity recognition, walking velocity and heading estimation. Basic human activities such as sitting, sleeping, standing and walking are recognized. We proposed a particle filter-based sensor fusion algorithm that considers a behavior-based map to increase the localization accuracy. Experiments were conducted in a mock apartment testbed. We used the ground truth data obtained from a motion capture system to evaluate the results.