Driving can be exhausting for anyone, but the stakes are exceptionally high for semi-truck drivers. The inspiration behind our project stems from the understanding that drowsiness behind the wheel can lead to fatal consequences. Here are some compelling fast facts that highlight the urgency of this issue:

  • In the United States alone, there are approximately 3.5 million professional truck drivers.
  • In the year 2020, there were a staggering 415,000 accidents involving large trucks.
  • Of these accidents, 24 percent resulted in injuries.
  • Shockingly, out of every 100,000 crashes caused by drowsy driving, a significant 8,000 involve truck drivers.

These statistics underscore the critical need for a solution to tackle drowsy driving among truck drivers and reduce the associated risks.

What it Does

Our project serves as a robust administrative tool tailored for trucking companies. Leveraging cutting-edge AI and videography technology, it's designed to address the problem of drowsy driving head-on. Here's a detailed overview of its functionalities:

  • Drowsiness Detection: The heart of our system lies in its ability to detect drowsiness indicators in real-time. It monitors drivers for eyelid drooping and yawning, key signs of fatigue.

  • Geographical Tracking: To provide valuable context, each detected yawn is attributed to a specific point on a map. This geographical component is crucial for understanding where and when drowsy incidents occur.

  • Real-time Monitoring: Our system allows administrators to monitor the condition of truckers in real-time. This capability ensures that proactive measures can be taken promptly.

How We Built It

During the development of our project, we encountered several challenges that tested our problem-solving skills and creativity. The major hurdles included:

  • Determining Drowsiness Thresholds: One of the key challenges was defining the precise level of eye droopiness that should be considered as the threshold for closed eyes.

  • Video Integration: Integrating the video feed with the user interface posed technical challenges, requiring innovative solutions.

  • Real-time Truck Tracking: Achieving real-time tracking of trucks via a web interface demanded intricate technical solutions, ensuring accurate and up-to-date information.

Accomplishments that We'rre Proud of

Throughout the journey of creating this project, we achieved several significant milestones that fill us with pride. Among these accomplishments are:

  • Machine Learning Implementation: Successfully incorporating machine learning and AI into our project to detect drowsy driving, showcasing our technical proficiency.

  • Linear Algebra We had to learn some linear algebra in order to calculate eye gaze, head tilt, mouth aspect ratio, and eye aspect ratio.

What We Learned

This project was a tremendous learning experience for our team. Some key takeaways include:

  • Machine Learning Expertise: We gained in-depth knowledge of implementing machine learning algorithms for practical applications, especially in the realm of driver safety.

  • Real-time Web Development: We acquired valuable skills in real-time web development, which are transferable to various other projects.

  • Safety Innovation: This journey reinforced our commitment to using technology for enhancing safety in critical areas of our daily lives.

In summary, our project is a testament to our dedication to addressing a pressing issue – drowsy driving among truckers. It combines technology, data analysis, and a commitment to safety, providing a potential solution that can save lives on the road. Our journey was filled with challenges and achievements, leaving us with a wealth of knowledge and skills to apply to future endeavors.

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