Every year at CTIA Super Mobility, the largest wireless event in America, the world’s most cutting-edge mobile products and services are honored for excellence in transforming networks, businesses, smart cities and connected consumers.
We’re thrilled to announce that HARMAN's Pupil-Based Driver Monitoring System, our industry-first advanced safety technology released early this year at CES, has been selected as a finalist in the prestigious CTIA Emerging Technology (E-Tech) Awards in the Connected Life category.
A panel of 35 industry experts, reporters and analysts judged submissions in 15 different award categories. Winners will be announced at the Super Mobility conference in Las Vegas on September 8 but there’s still time to help HARMAN take home an additional award for “Crowd Favorite”! If you’re on board with the idea of a safe, highly intelligent connected car experience, please take a brief moment to show your support and cast your vote here.
About the solution:
HARMAN’s Pupil-Based Driver Monitoring System measures increases in pupil dilation as an indication of a driver’s mental workload. HARMAN’s new proprietary eye and pupil tracking system detects high cognitive load and mental multitasking in the driver’s seat, and signals the car’s other safety systems to adapt to the driver’s state. The technology represents a major step forward in the domain of Advanced Safety and Driver Monitoring Systems (DMS) for vehicles.
Adoption of in-cabin cameras is growing rapidly, enabling features such as occupant detection and driver drowsiness monitoring. With the introduction of high cognitive load detection, HARMAN’s eye and pupil tracking technology brings additional value to the driver-facing camera. The technology eliminates the need for complex sensors built into seats and steering wheels, or biometric sensors that require physical contact with the driver. This camera continually captures the driver’s pupil dilation, and a proprietary software algorithm analyzes the pupil reflex using advanced filtering and signal processing. The filter isolates and identifies responses triggered by high cognitive load. The calculated outputs are used to intuitively adjust user interfaces, like placing mobile devices in do-not-disturb mode or adjusting ADAS system intervention thresholds to minimize physical and mental distraction to the driver. To learn more about the solution, view this video demonstration here.