arXiv:2605.23663v1 Announce Type: cross Abstract: Alcohol-impaired driving remains a major yet preventable cause of road traffic injury and death, with many drivers underestimating their level of intoxication. Compared to in-vehicle systems, mobile drunk-driving detection using consumer smartwatches offers a scalable way to trigger preventive interventions and increase awareness without additional in-vehicle hardware. We introduce a system that leverages wrist accelerometer data and heart rate variability-derived physiological signals to detect alcohol-related driving impairment. We collected
Miniaturization of sensors and advancements in AI/ML enable sophisticated biometric analysis from ubiquitous consumer devices, making such applications practical for immediate deployment.
This development transforms personal wearables into public safety tools, offering a scalable, non-invasive method for detecting impaired driving that bypasses traditional enforcement bottlenecks.
Individuals' personal devices can now serve as active, real-time monitors for dangerous behaviors, shifting some responsibility for public safety from institutions to personal tech.
- · Smartwatch manufacturers
- · Insurance companies
- · AI/ML developers
- · Public health organizations
- · Traditional in-vehicle safety systems
- · Alcohol industry (potential regulatory pressure)
Increased detection rates of drunk driving, leading to fewer accidents and fatalities.
New insurance models could emerge, offering lower premiums for drivers who voluntarily use and share data from such detection systems.
Societal norms around personal data privacy might shift as the benefits of pervasive health and safety monitoring become more apparent.
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Read at arXiv cs.LG