2 Sources
[1]
Tired of potholes? Bengaluru techie builds AI-powered app that detects damaged roads and identifies contractors
A Bengaluru techie has developed an AI-powered app that can detect potholes using a dashcam, GPS and an accelerometer, then identify the contractor responsible for the affected road by checking government contracts. The system detected 12 potholes during one of his daily commutes. A Bengaluru engineer has turned his daily frustration with potholes into an AI-powered system that can detect damaged roads, locate them precisely and identify the contractor responsible for the road. The system combines a dashcam, GPS, an accelerometer and AI vision models, while also checking 2,900 government contracts to connect each pothole with the relevant road project. From bumpy roads to an AI solutionFor many motorists, hitting a pothole means a rough ride, possible vehicle damage and another complaint to the civic authorities. For Bengaluru-based engineer Gaurav Sen, it became a problem that could be tackled with technology. Sen demonstrated his system in a video shared on Instagram in collaboration with ChatGPT India. The video later reached X, where it drew attention for its unusual approach to a familiar problem on Indian roads. Instead of simply recording potholes, Sen's system attempts to build a complete record of each road defect. How the pothole detection system worksSen installed a dashcam, GPS and an accelerometer in his car. As he drives, the equipment collects road-related information along his route. The recorded footage is then examined using AI vision models. The system can identify potholes and classify them according to their size. The technology is also designed to deal with a common problem on Indian roads: potholes that can resemble speed breakers when viewed from a distance. Sen said he used Codex to develop an app that collects the relevant information and sends it to OpenAI for processing. AI goes beyond finding potholesFinding a pothole is only part of the problem. The bigger question is often who should repair it. Sen's system tackles that by searching through 2,900 government contracts. It attempts to identify the contractor responsible for the particular stretch of road where the pothole has been detected. This can be especially useful when a road remains under warranty. In such cases, the contractor may be responsible for fixing defects without the government having to bear an additional repair cost. Four seconds to create a complaint recordThe app can compile several pieces of information into a structured record within about four seconds. The record includes the pothole photograph, its exact location, the relevant tender number and the officer responsible for the road. That turns a simple drive into a collection of documented evidence that can potentially be used while raising a complaint with civic authorities. One commute found 12 potholesSen also tested the system during one of his regular drives to work. The app detected 12 potholes on the route, providing photographic and location-based evidence for each one. The system could then be used to prepare complaints linked to the respective road authorities or contractors. The experiment showed how AI can potentially reduce the effort involved in documenting everyday civic problems. Social media users take noticeThe project gained wider attention after the video reached X. Users praised the idea of applying AI to a problem that affects motorists in Bengaluru and many other Indian cities. The social media post explained the system this way: "An Indian engineer in Bengaluru got tired of potholes destroying his car. So he built an app with Codex that detects them, finds who is responsible, and files a complaint. Here is how it works. He installed a dashcam with GPS and an accelerometer. The app records everything while he drives. A vision model classifies every pothole by size. Small, medium, large. But here is the clever part. Most Indian roads are under warranty. The contractor who built them is legally responsible for fixing potholes for free. His app searches through 2,900 government contracts, finds the exact tender number, identifies the officer responsible, attaches the photo and geolocation, and generates a ready-to-file complaint. One drive to work. 12 potholes detected. 12 complaints ready." Some users also suggested that civic agencies could adopt similar technology to identify damaged roads and act on complaints more quickly. A different way to report civic problemsSen's experiment shows how a routine commute can generate useful civic data when everyday hardware is combined with AI. Instead of stopping at identifying potholes, the system attempts to connect each road defect with the contract, contractor and official associated with that stretch. What started as an attempt to make one Bengaluru commute less bumpy has turned into a broader experiment in making road complaints more detailed and easier to act on.
[2]
Bengaluru Engineer Builds AI Tool to Spot Potholes, Track Responsible Contractors
Bengaluru engineer Gaurav Sen has built an AI tool that detects potholes through dashcam footage during daily drives. He demonstrated the on August 16, 2026, to tackle Bengaluru's road problems using AI, GPS and vehicle sensors. The system also finds contractors responsible for damaged roads by checking government contracts. Sen built the app with and connected it with vision models to study road footage. A dashcam, GPS and accelerometer collect data while the car moves through Bengaluru streets. The AI can spot potholes that may look like speed breakers from a distance. The system goes beyond simply finding damaged roads and also checks who should repair them. Sen added data from 2,900 government contracts to identify contractors linked with specific road stretches. This feature could help with roads still covered under warranty, where contractors may need to fix defects. The system can create a detailed record within four seconds after finding a pothole. Each record includes a photograph, exact location, tender number and responsible road officer. Sen tested the tool during a drive to work and found 12 potholes along his route. The results could provide stronger evidence for complaints sent to civic authorities. The project also gained attention after the video reached X and other . A social media reaction described the project as 'Fixing real-life bugs.' Another user wrote, "Great idea and execution." Users also hoped the system could help improve road repairs across Bengaluru and other cities. Sen's project gives a practical use to AI beyond regular apps and chatbots. It connects road damage with location data and contractor details, creating a simpler way to report potholes.
Share
Copy Link
Gaurav Sen built an AI tool that combines dashcam footage, GPS and accelerometer data to detect potholes on Bengaluru roads. The system searches through 2,900 government contracts to identify contractors responsible for damaged road stretches and generates complaint records within four seconds.
Gaurav Sen, a Bengaluru engineer, has developed an AI-powered app that addresses one of India's most persistent civic infrastructure issues: potholes. The system combines hardware and AI vision models to detect damaged roads during regular drives, then identifies which contractor should repair them by cross-referencing government contracts
1
. Sen demonstrated the technology on August 16, 2026, through a video shared on Instagram in collaboration with ChatGPT India, which later gained attention on social media platforms2
.The pothole detection system relies on three hardware components installed in Sen's vehicle: a dashcam, GPS and accelerometer. As he drives through Bengaluru streets, these devices continuously collect road-related data. The recorded footage is then processed using AI vision models that can identify and classify potholes according to size—small, medium or large
1
. Sen built the application using Codex and connected it with OpenAI for processing the collected information2
. The technology also tackles a common challenge on Indian roads: distinguishing potholes from speed breakers when viewed from a distance.What sets this AI-powered app apart is its ability to connect each detected pothole with accountability. The system searches through 2,900 government contracts to identify the contractor responsible for the specific road stretch where damage has been found
1
. This feature proves especially useful for roads still under warranty, where contractors remain legally obligated to fix defects without additional government expenditure. The app compiles a complete record within approximately four seconds, including the pothole photograph, exact location via GPS, relevant tender numbers and the officer responsible for that road section1
.Related Stories
During a test drive to work, Sen's system detected 12 potholes along his regular route, generating photographic and location-based evidence for each one
1
. The experiment demonstrated how AI can reduce the effort required to document civic infrastructure issues. Each detected pothole resulted in a ready-to-file complaint that could be submitted to civic authorities or contractors with all necessary documentation already prepared. This approach transforms a routine commute into a systematic data collection exercise that builds evidence for action on damaged roads.The project gained widespread attention after reaching X, where users praised the practical application of AI to everyday civic problems affecting motorists across Indian cities. One social media reaction described the initiative as "Fixing real-life bugs," while another user wrote, "Great idea and execution"
2
. Some users suggested that civic agencies could adopt similar technology to identify damaged roads and respond to complaints more quickly. The system shows how combining everyday hardware like dashcam and accelerometer with AI vision models can generate actionable civic data. Watch for potential adoption by municipal authorities seeking to improve road maintenance accountability and whether this approach spreads to other cities facing similar infrastructure challenges.Summarized by
Navi
[2]
15 Nov 2025•Technology

25 Oct 2024•Policy and Regulation

04 Feb 2025•Science and Research

1
Technology

2
Technology

3
Policy and Regulation
