Anomaly Stop Detection by Smartphone
Viet Chau Dang, Masao Kubo, Hiroshi Satō, Tomohiro Shirakawa, Akira Namatame · Journal of Robotics Networking and Artificial Life · 2014
This paper proposes a method for detecting anomaly stop events from GPS logs of a vehicle recorded by smartphone.Despite of many researches of strong braking event detection are proposed, they cannot discriminate between a normal and an abnormal braking event.Our proposal includes an IMAC model for GPS based map generation and an algorithm for anomaly stops detection based on the acquired map.The real world experiment shows our map generation method and its anomaly stop detection rule works well.