Driver/pilot awareness monitoring
AI-powered, non-invasive, and privacy-first technology

On roads, in the air, or at sea, as mobility becomes increasingly automated, the focus is on enhanced safety, user experience, and comfort
At CSEM, we engineer in-cabin and in-cockpit monitoring systems that combine human-centric design, biomedical signal intelligence, through embedded artificial intelligence to support operator safety and well-being in real time.
Our solution delivers continuous, real-time insights into fatigue, distraction, stress, and cardiovascular state, using only facial video and AI. Built on advanced facial behavior analysis, remote photoplethysmography (rPPG), and privacy-first deep learning, it operates entirely without wearables, biometric storage, or cloud infrastructure. This contactless technology is validated, embedded-ready, and fully compliant with data protection standards, making it ideal for integration into automotive, aviation, and other mobility systems.

The challenge: Monitoring human readiness in mobility systems
Not only fatigue and inattention but also stress or medical emergency
Today’s systems – where available - focus on steering input and/or gaze. But human readiness is more than eye movement — it’s also stress levels, fatigue signals, and vital signs. With automation and driver handover scenarios increasing, understanding both behavioral and physiological states is now essential.
DriverCheck extends vision-based DMS with physiological sensing, anchoring state estimation in vital signs. This reduces false positives and explains the why behind behavior (fatigue, stress, or sudden medical incapacity).
Our platform is designed to meet this challenge with:
- Facial behavior analysis under real-world conditions
- Camera-based vital sign monitoring comparable to wearable solutions
- AI trained to prevent intrusive biometric learning while improving monitoring accuracy, and fully privacy-compliant by design.
Together, these technologies deliver actionable insights to driver assistance (ADAS) and human-machine interface (HMI) systems, helping OEMs improve safety across diverse mobility platforms, including automotive, rail, and aircraft human-machine interaction in the cockpit to improve safety.

Our solution: Multi-modal, camera-based driver state monitoring
DriverCheck fuses high-precision behavioral tracking with physiological sensing — heart rate, breathing rate, stress markers — all extracted from facial video. Built on privacy-first AI, it delivers deep insights without identity capture, biometric storage, or cloud dependency. The result is a unified platform designed for real-world deployment in vehicles, aircraft, and other mobility platforms.
Key technical advantages
What sets our real-time in-cabin monitoring technology apart?
- Automotive-grade, camera hardware with real-time behavioral and physiological output
- Compact, eye-safe 940 nm near-infrared (NIR) illumination with thermal-efficient design
- Privacy-preserving, embedded AI architecture trained on synthetic data coupled with adversarial training methods.
- Modular software SDK for integration into ADAS or cockpit systems
- Validated through simulator trials and clinical studies (100+ participants)
- Designed for scalability across vehicles, fleets, and operator-centric environments
Why partner with CSEM?
At CSEM, we collaborate with industry partners to co-develop intelligent in-cabin monitoring systems. Our platform is the result of decades of research in embedded AI, vision systems, and biomedical signal sensing, tailored primarily for automotive and operator-centric mobility environments.
- Complete driver insight: Combines behavioral and physiological indicators for accurate, contextual understanding
- Non-invasive experience: No wearables or intrusive sensors needed
- Privacy built in: Zero biometric retention, fully regulation-ready
- Fast & responsive: Real-time analysis on embedded hardware
- Flexible integration: Scalable architecture for passenger cars, fleets, or autonomous platforms
- Proven accuracy: Validated in simulator and clinical testing environments
