USING Sensor: User-Smartphone Decoupling Detection as a Mobile-Based Virtual Sensor

In many disaster situations, the location of victims is the most important information for saving them. To provide such information, most studies simply use indoor positioning technologies of the victim’s mobile device. Nevertheless, their schemes have a large lack to point out the exact location of a victim because people sometimes drop off their mobile device or put it down some places, such as a desk and a table. In other words, it merely provides the location of mobile devices and not of victims. Hence, this paper proposes a novel virtual sensing mechanism, named the USING sensor (User-Smartphone-Decoupling Detection). The USING sensor relies on the user activity sensing and co-existence monitoring of users and smart mobile devices. It could track the continuous coupling state of the user-mobile device. However, continuous user activity detection is not trivial, since some actions, such as sitting, dropping, and so on, intermittently occur while some actions like walking are frequent and continuous. So, data acquisition methods from a mobile device for the detection of user actions should be designed and managed differently. In addition, for high sensing reliability, the USING sensor is based on machine learning (ML) analytics with multiple algorithms and the ensemble technique. Thus, it could achieve 95.0% of user activity recognition accuracy and 86.8% of sensing accuracy.