Which ideas and use cases could be imagined if the private car is as well collection health data or
mood data from the driver or even passengers ? What could we or IOMT with AI do then ? Which support or livesaving could be provided ?
The integration of health and mood data collection in private cars opens up numerous innovative
possibilities across safety, wellness, entertainment, and personalized experiences.
Here potential ideas and use cases and some picture from our PoCs for ADAS enhaced driver monitoring for insurance purpose:
Safety Enhancements
Health Crisis Management: Systems like Hyundai Mobis’ Smart Cabin Controller could
detect emergencies such as cardiac arrest or carbon monoxide poisoning and autonomously
drive the car to an emergency room .
Driver Vigilance Monitoring: Sensors could assess heart rate variability, eyelid closure, and
other metrics to predict drowsiness or distraction, triggering alerts or taking control of the
vehicle to prevent accidents .
Drunk Driving Prevention: Advanced monitoring systems could block vehicle operation if
signs of intoxication are detected .
Wellness and Health Monitoring
Real-Time Health Checkups: Cars could act as mobile health stations, monitoring vital signs
like blood pressure, heart rate, and temperature to provide real-time feedback on physical
well-being.
Stress Management: Emotional AI systems could adjust cabin settings such as lighting,
temperature, or music to reduce stress during traffic jams or long drives .
Carsickness Prevention: Technologies could detect early signs of motion sickness and
adjust air circulation or seat positioning accordingly .
Personalized Experiences
Mood-Based Entertainment: Emotional AI systems like Affectiva Automotive AI could tailor
entertainment options (music playlists or video content) based on passengers’ moods .
Adaptive Cabin Settings: The car could change seat ergonomics, air conditioning, or
lighting based on detected emotional states to enhance comfort .
Passenger Safety
Child and Pet Monitoring: Systems like Toyota’s cabin monitors could detect unattended
children or pets in vehicles and alert nearby individuals or authorities .
Passenger Emotional Recognition: Cameras and sensors could monitor passengers’ facial
expressions to identify distress or discomfort and adjust settings accordingly .
Data Collection for Research
Driver Emotion Recognition Studies: Multimodal data collection systems can gather real
world data on emotions during driving for improving AI algorithms and understanding human
behavior behind the wheel .
Personalized Health Insights: Continuous collection of health data could be used to build
personalized health profiles for drivers and passengers, potentially integrating with external
healthcare systems .
Autonomous Vehicle Applications
Control Transition in Autonomous Cars: Health monitoring systems could determine
whether a driver is fit to retake control from an autonomous vehicle or continue driving
autonomously during emergencies .
Passenger Well-being in Shared Mobility: In ride-sharing scenarios, these systems can
ensure passenger comfort and safety by dynamically adapting the cabin environment
based on individual needs.
CONCLUSION
The convergence of health monitoring and emotional AI in vehicles has transformative potential
for enhancing safety, comfort, and personalization while paving the way for smarter mobility
solutions.
SOURCES
https://pmc.ncbi.nlm.nih.gov/articles/PMC5375895/
https://www.designnews.com/motion-control/emotional-ai-makes-your-car-really-know-how-you-feel
