Potholes are a common problem for motorists, often leading to uncomfortable rides, vehicle damage and repeated complaints. For Bengaluru-based engineer Gaurav Sen, the problem became an opportunity to build a system that could detect potholes and identify who may be responsible for fixing them.
Sen demonstrated the system in a video shared on Instagram in collaboration with ChatGPT India.
The system designed by Sen uses a dashcam, GPS, and an accelerometer fitted in his car to collect information while he drives.
Watch Video Here:
The footage is then processed using AI vision models to identify potholes of different sizes.
Sen said he used Codex to build an app that records the relevant data and sends it to OpenAI. The system can also identify potholes that may be difficult to spot from a distance because they can look like speed breakers.
However, detecting a pothole is only the first step. Sen wanted the system to also identify who was responsible for fixing a particular pothole.
To do this, he modified the app to go through 2,900 government contracts and identify the contractor responsible for a particular stretch of road.
Sen explained that this can be particularly useful when a road is still under warranty, as the contractor may be required to repair defects without additional cost to the government.
The app can produce a structured record within four seconds, including the photograph, exact location, tender number, and the officer responsible for the road.
Sen also tested the system during one of his drives to work. It detected 12 potholes along the route, giving him documented evidence that could be used to raise complaints with civic authorities.
The idea later travelled beyond Bengaluru after the video reached X.
Social Media Reaction
Social media users praised Sen for building a system around a problem that affects motorists across the country.
One user commented, "Great idea and execution."
Another user noted, "Good job. Hope it helps."
"Fixing real life bugs," added a third user.
A fourth user noted, "Hope this works."
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