This mining-grade Driver Monitoring System (DMS) uses AI enhanced for helmets, masks,and constant movement. It delivers reliable fatigue and distraction detection even when drivers wear PPE, works fully offline with in-cab audio and seat-vibration alerts, and can integrate with wearable devices to build a more accurate picture of driver fatigue in harsh mining conditions.
Product features
AI vision model enhanced for helmets, masks, reflective lenses and body movement, more robust than standard DMS systems
Mining-optimized tuning for drivers wearing reflective clothing, hard hats, respirators or face shields to ensure reliable detection in real-world conditions
Extended safety through integration with wearable devices for more accurate fatigue detection, especially when sunglasses or visors block direct eye tracking
Edge AI on the vehicle so the system keeps working with no network, with strong in-cab audio and seat-vibration alerts that cut through noisy mining environments
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Streamax is committed to the responsible and ethical deployment of technology. Our solutions are developed with a privacy-by-design and security-first architecture. All data processing occurs locally on the edge device, ensuring that personally identifiable information, including biometric data, is neither stored nor transmitted to the cloud, thereby adhering to global data sovereignty regulations.
The AI features and performance metrics referenced in our materials are based on data from extensive internal testing and validation under controlled, laboratory-style scenarios. These results are provided to demonstrate our technological capabilities and direction; however, actual performance may vary in real-world operating environments and should be validated by the end-user.
Our AI models are trained on diverse, legally sourced datasets and are designed to function strictly as decision-support tools for human operators, not as autonomous systems. We actively mitigate algorithmic bias and our development process aligns with emerging global standards for AI ethics and functional safety.
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