Real-time Driver Monitoring Systems on Edge AI Device
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 4 of its 7 references that are in the map. First posted on arXiv 4 Apr 2023.
Builds on
4 of 7 references.
References · 4
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
- 2019BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUscited by 74
- 2019Real-time Facial Surface Geometry from Monocular Video on Mobile GPUscited by 72
- 2019PFLD: A Practical Facial Landmark Detectorcited by 25
Built on by
Citing papers per year: 2025: 1; 2026: 1.
2 papers.