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Methods and Tools for Monitoring Driver's Behavior
Muhammad Tanveer Jan1, Sonia Moshfeghi1, Joshua Conniff2
1College of Engg and Computer Science Florida Atlantic University, Boca Raton, USA.
Proceedings. International Conference on Computational Science and Computational Intelligence
|March 15, 2024
Summary
We developed unobtrusive in-vehicle sensors to monitor driver behavior. This technology aids in identifying early dementia in older drivers, enhancing road safety.
Area of Science:
- Automotive Engineering
- Gerontology
- Medical Informatics
Background:
- In-vehicle sensing technology is crucial for connected and autonomous vehicles.
- In-vehicle data are vital for traffic management systems.
- Monitoring driver behavior is essential for road safety and health assessments.
Purpose of the Study:
- To propose an innovative architecture for unobtrusive in-vehicle sensors.
- To present methods and tools for measuring driver behavior.
- To apply this technology in an NIH project for early dementia detection in older drivers.
Main Methods:
- Development of an innovative in-vehicle sensor architecture.
- Implementation of novel methods and tools for driver behavior analysis.
- Utilizing sensor data for monitoring and identification of specific health conditions.
Main Results:
- Successful proposal of an unobtrusive in-vehicle sensor architecture.
- Development of effective methods and tools for driver behavior measurement.
- Demonstrated application in an NIH project for identifying older drivers with early dementia.
Conclusions:
- The proposed in-vehicle sensing architecture and methods are effective for monitoring driver behavior.
- This technology shows promise for early detection of cognitive decline, such as dementia, in older adults.
- In-vehicle sensing offers a valuable, non-intrusive approach to health monitoring and traffic safety.
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