Proposal and Initial Evaluation of Human Identification Based on Door Opening/Closing Operations

In recent years, sensing in various situations becomes possible due to the advances in wireless networking, computing, and sensing technologies. For human sensing, wearable devices and cameras installed in the environment are widely utilized, which is though stressful for the sensing target people. In this paper, we present a human identification method based on door opening/closing operations. Door opening and closing operations such as door knob turning operations and speed of door movement are dependent on people. We analyze the acceleration and angular velocity data derived by accelerometer and angular velocity sensor attached to a door knob to identify people who opens/closes the door. We develop a machine learning based human identifier utilizing features extracted from the acceleration and angular velocity data. Experimental evaluations revealed that our human identifier successfully identified human in a small group with an accuracy of 0.79 on average.