Real-time Driver Monitoring Systems on Edge AI Device
This work addresses road safety by enabling real-time monitoring of drivers using edge computing, though it appears incremental as it focuses on optimizing existing models for specific hardware.
The authors tackled the problem of driver inattention by developing a real-time driver monitoring system that runs on an edge AI device, achieving 63 frames per second on a TI-TDA4VM edge device.
As road accident cases are increasing due to the inattention of the driver, automated driver monitoring systems (DMS) have gained an increase in acceptance. In this report, we present a real-time DMS system that runs on a hardware-accelerator-based edge device. The system consists of an InfraRed camera to record the driver footage and an edge device to process the data. To successfully port the deep learning models to run on the edge device taking full advantage of the hardware accelerators, model surgery was performed. The final DMS system achieves 63 frames per second (FPS) on the TI-TDA4VM edge device.