Driver Monitoring System
Redefining the driving experience
Moozt’s Driver Monitoring System, uses the latest deep learning methodologies to detect drivers’ alertness, stress and wellness level under diverse conditions. The algorithms are developed to obtain real time performance on various hardware platforms.
- Moozt DMS monitors driver behaviour and attentiveness thereby ensuring safe driving.
- Driver’s eye, face, head movements, emotions and behavior are continuously monitored to assess the overall driver performance.
- If a potential accident scenario is detected based on the driver’s attentiveness level, the system will warn the driver by flashing lights, warning sounds or even notifying the autonomous system to take control.
- With an optional real world perception module, the system can detect potential hazards on the road and alerts the driver.
Driver Monitoring System (DMS) - Features
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Distraction Detection
- Eye-Gaze Direction
- Head-Pose Estimation
- Phone Usage : Call
- Phone Usage : Texting
- Day-Dream Detection
- Pupil Dilation
- Blink Detection
- Yawn Detection
- Sleep Detection
- Heart Rate
- Fever Detection
- Visual perception based alerts
- Face Recognition
Platforms, Frameworks and Tools
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Platforms
- Embedded platforms encompassing ARM
- Digital Signal Processors (DSP)
- Vision Accelerators
- Custom SoCs and camera sensors
- Tensorflow
- PyTorch
- OpenCV
- Parallel Computation: CUDA
- Data Visualization: GTK & Matplotlib
- Stats Workbench : Python and C/C++
Typical Applications
Advanced Co-Pilot
- Recognises driver
- Monitors the Driver
- Engages the driver based on
- – Emotion
- – Wellness
- – Drowsiness
- Gives assistance to the driver
- Enables to monitor the driver and report in case of any incidents
