Real-time Driver Monitoring Systems on Edge AI Device

Jyothi Hariharan; Rahul Rama Varior; Sunil Karunakaran

Real-time Driver Monitoring Systems on Edge AI Device

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arxiv 2304.01555 v1 pith:H6IOC3YS submitted 2023-04-04 cs.CV cs.AIcs.ARcs.LG

Jyothi Hariharan , Rahul Rama Varior , Sunil Karunakaran This is my paper · ORCID

classification cs.CVcs.AIcs.ARcs.LG

keywords deviceedgedriversystemmonitoringreal-timesystemsaccelerators

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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.

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