AWS Deep Lens implementation for drowsiness detection in drivers

Industries
Travel & Hospitality
Services
AI / AWS Deep Lens implementation
Tools We used
Python, AWS IoT, Node.js, Amazon RDS

Challenges We Faced

Developing a system to prevent drowsiness in drivers required innovative solutions. The goal was to leverage AWS DeepLens to continuously monitor drivers' facial expressions and detect signs of drowsiness. This MVP (Minimum Viable Product) required extensive R&D to:

  • Monitor users in real-time.
  • Detect drowsiness accurately.
  • Generate actionable alerts for user safety.
  • Integrate with cloud systems and voice assistants for immediate guidance to rest areas or coffee shops.

Using AWS DeepLens to monitor drivers' facial expressions and detect signs of drowsiness.

Whizzbridge's Solution

WhizzBridge developed and implemented an AI-powered solution using AWS DeepLens and integrated it with cloud-based services to enhance driver safety. Key features included:

  • Real-Time Monitoring:
    Continuous user monitoring through AWS DeepLens to detect drowsiness or sleepiness.
  • Cloud Integration:
    Events detected by DeepLens were sent to AWS Cloud for processing and further actions.
  • Voice Assistant Integration:
    Integrated with Alexa Skills to guide users to the nearest coffee shop or restaurant.
  • Navigation Support:
    System-enabled commands for Google or Alexa Maps to provide precise navigation.
View UI/UX Casestudy Here

Results We Achieved

  • Enhanced Driver Safety:
    The system helped prevent accidents by detecting drowsiness and guiding drivers to rest stops.
  • Scalable MVP:
    The research and development yielded a scalable MVP that can be enhanced for broader adoption.

WhizzBridge’s innovative implementation of AWS DeepLens and cloud integration is saving lives daily by providing real-time monitoring and proactive safety solutions for drivers.

AWS-powered solutions help WhizzBridge save lives with innovation.

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