Distracted Driver Detection System

A web application that detects and buzzes an alarm to alert the driver when he/she is distracted by the phone or other objects, not focusing on the road ahead or closing his eyes due to drowsiness.

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Inspiration

According to the latest report by the Road Safety Bureau, Texas is one of the top three states accounting for a major share of total traffic accidents in the States in the year 2020. All of us belong to Texas, US, and thought of designing a solution to curb this problem,

What it does

When the driver begins his journey and starts the web application, the app detects and buzzes an alarm when the driver is not focussed on the road ahead or closes his eyes due to drowsiness.

How we built it

We used a pre-trained cascade classifier and opencv library in python. To create the web app we used flask, html and css.

Challenges we ran into

  1. Classifier used is not very accurate
  2. No front end experience so it was difficult to build the web app

Accomplishments that we're proud of

  1. This was our first Hackathon and we used the following technologies for the first time: HTML, Flask, CSS, OpenCV library, Google Cloud
  2. We successfully achieved our goal of building a web app that deploys an object classifier to detect driver drowsiness and distraction

What we learned

  1. New technologies like CSS, Html, Flask
  2. Integrating the web app with our machine learning model

What's next for Distracted Driver Detection System

The web application can be upgraded further to incorporate the following features:

  1. A button to stop the application when the driving journey is finished.
  2. A points-based system that deducts points from the driver's account every time the driver is distracted or drowsy. These points can be tied to the driver's auto insurance.
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