Where is my Device? - Detecting the Smart Device's Wearing Location in the Context of Active Safety for Vulnerable Road Users
This work addresses safety for vulnerable road users by providing context information for algorithms like dead reckoning, but it appears incremental as it builds on existing sensor-based methods.
The paper tackled the problem of detecting where pedestrians and cyclists wear smart devices using only device sensors, achieving evaluation on a real-world dataset to improve safety for vulnerable road users.
This article describes an approach to detect the wearing location of smart devices worn by pedestrians and cyclists. The detection, which is based solely on the sensors of the smart devices, is important context-information which can be used to parametrize subsequent algorithms, e.g. for dead reckoning or intention detection to improve the safety of vulnerable road users. The wearing location recognition can in terms of Organic Computing (OC) be seen as a step towards self-awareness and self-adaptation. For the wearing location detection a two-stage process is presented. It is subdivided into moving detection followed by the wearing location classification. Finally, the approach is evaluated on a real world dataset consisting of pedestrians and cyclists.