Early warning system for drivers’ phone usage with deep learning network

Dangerous driving, e.g., using mobile phone while driving, can result in serious traffic problem and threat to safely. To efficiently alleviate such problem, in this paper, we design a intelligent monitoring system to detect the dangerous behavior in driving. The monitoring system is combined by camera, terminal server, target detection algorithm and voice reminder. Furthermore, we applied an efficiently deep learning model, namely mobilenet combined with single shot multi-box detector (mobilenet-SSD), to identify the behavior of driver. To evaluate the performance of proposed system, we construct a dangerous driving dataset which consists of 6796 images. The experimental results show that the proposed system can achieve accuracy of 99% in 100 testing images. It can be used for real-time monitoring of the driver’s status.