An Efficient Walking Safety Service for Distracted Mobile Users

There is a growing number of incidents related to using cell phones while walking on the street. To address this issue, this paper proposes a new system based on tactile paving detection on the sidewalk to alert distracted mobile users to avoid traffic hazard. Our system (namely Inspector) is deployed as an application on an off-the-shelf normal mobile phone equipped with back camera. Inspector plays as a third eye to alert users when they step out of the safe zones where no tactile paving is detected. In order to obtain reliable yet effective decision results, we exploit a lightweight image processing method, simple classifiers along with a smart sampling strategy. The main idea is that the application capture more images of the surrounding environments when we doubt that the result from one image is not sufficient. The sampling interval is adjusted dynamically so that we can save the energy and thus extend the working time of the system. Real-scenario tests show that Inspector can detect whether a mobile user is walking along a blind sidewalk with an accuracy of 92.72%, 98.78%, and 99.44% when the detection algorithm sample 2 times, 3 times, and 4 times continuous detection respectively. The reaction time, which is measured by the difference between the alert time and the time when a user steps out of a safety zone, is 0.52 seconds early with a sampling interval of 2 seconds.