Automatic Accident Detection and Alarm System

Abstract

Accident and system is very important to detect possible accidents or dangers for the peoples using their mobile devices while walking, i.e., distracted walking. In this paper, we introduce an automatic and system, called AutoADAS, which is fully implemented and tested on the real mobile devices. The proposed system can be activated either manually or automatically when walks. Under the manual mode, activates the system before distracted walking while under the automatic mode, a user behaviour profiling module is used to recognize (distracted) walking behaviours and an object detection module is activated. Using image processing and camera field of view (FOV), the distance and angle between the and detected objects are estimated and then applied to identify whether any potential accidents can happen. The accident analysis and prediction module includes: temporal that inputs the user's walking speed and distance with respect to the detected objects and outputs temporal prediction; spatial that inputs the user's walking direction and angle with respect to the detected objects and outputs spatial prediction. Once the proposed system positively predicts a potential accident, the alarm and suggestion module alerts the with text, sound or vibration.