Disaster Detection Using SVDD Group Learning for Emergency Rescue Evacuation Support System

抄録

Many people have got injured and died by sudden disasters such as fires and terrorisms. We have proposed an Emergency Rescue Support System (ERESS) for reducing victims at the time of disaster. ERESS operates under mobile ad-hoc networks (MANET) composed of handheld terminals such as smartphones and tablets. ERESS terminals have disaster detection algorithm and plural sensors such as acceleration, angular velocity, and geomagnetism. ERESS detects the disaster from the behavior analysis of people by the sensors. In this paper, we propose a new disaster detection method by performing the machine learning in the group using a support vector domain description (SVDD). We are able to detect the abnormal behavior of people by using this method. The results of disaster simulation experiments show the validity of the proposed method.