Bengaluru Engineer Creates AI Tool That Detects Potholes and Files Complaints in 4 Seconds

Bengaluru techie turns car dashcam into AI tool that spots potholes and files a complaint in four seconds with photo and exact location

A Bengaluru engineer has used a car dashcam, GPS and AI to tackle a problem that has become part of everyday driving in the city: potholes. His system not only detects damaged roads but also records their location and prepares a complaint in seconds, while trying to identify who is responsible for fixing them. Also read: El Niño effect: Bengaluru bans drinking water for car washing, gardening amid monsoon disruption One bumpy commute led to an AI experimentFor Gaurav Sen, the idea started with a frustrating drive through Bengaluru. He encountered 12 potholes during one commute and decided to see if technology could make reporting them easier. Sen fitted his car with a dashcam, GPS and an accelerometer. The setup records the road as he drives, along with location and movement data that can help identify where a pothole was encountered. He then used Codex to build an app that processes the information and sends it to AI vision models. The result is a system that can scan the recorded footage, spot potholes and classify them by size, including small, medium and large defects. Sen shared the project on Instagram on August 5, describing it as his way of reporting potholes to the Brihanmumbai Municipal Corporation, or BBMP. He also pointed to the wider danger posed by damaged roads, saying more than 2,000 Indians die every year in accidents described as pothole-related. The app does more than spot a potholeDetecting a pothole is only the first step. A photograph of damaged road may show the problem, but a complaint still needs details such as where the pothole is located and which authority or contractor is responsible for that particular stretch of road. Sen's system attempts to solve that part too. The app searches through around 2,900 government road contracts to connect a detected pothole with the relevant road project. It can identify the tender number, the contractor associated with the work and the government office responsible for the road. That could be particularly useful for roads that are still covered by a maintenance or construction warranty. If a road is under warranty, the contractor may be responsible for repairing defects rather than the repair being treated as a fresh government expense. View this post on Instagram A post shared by Gaurav Sen (@gkcs__) A pothole can become a complaint in four secondsThe most striking part of the system is what happens after the pothole has been detected. Instead of leaving the user with a photograph and coordinates, the app puts the information together into a complaint record. It can include the pothole image, exact location, tender details and the relevant government office. Sen says the system can prepare this information in about four seconds. In other words, the process moves from spotting a pothole to having the basic material needed to report it without requiring the driver to manually record every detail. One Bengaluru drive found 12 potholesSen tested the system during his regular commute and the app detected 12 potholes along the route. Each detection could be tied to photographic and location information, creating a record of the road damage rather than simply relying on a driver's description of where the pothole was. The system also attempts to take the complaint one step further by connecting the road damage to the contract and authority responsible for that stretch. That is important because identifying a pothole and getting it repaired are two different problems. A civic complaint can only go so far if the person reporting the problem has no idea which agency or contractor is responsible. Why the idea has attracted attentionThe project has drawn attention because it applies AI to a problem that Bengaluru motorists encounter every day. The technology itself is relatively simple in terms of hardware. A dashcam captures the road, GPS provides the location and an accelerometer records vehicle movement. AI then processes the footage and helps identify the damaged sections. The more unusual part is the attempt to connect that road damage to government contracts. Instead of treating a pothole as an isolated defect, Sen's system tries to create a chain linking the pothole, photograph, location, road contract, contractor and responsible office. That turns an ordinary commute into a source of documented civic information. From detecting potholes to making someone responsibleSen's experiment is ultimately less about building another pothole detector and more about making the reporting process easier. A driver can spot a pothole, but documenting it, finding the right authority and preparing a complaint can take considerably more effort. His system attempts to compress those steps into a few seconds. The idea also raises a larger possibility for civic technology. If similar systems could collect road damage data at scale, cities could potentially build a much more detailed picture of where roads are deteriorating and which projects or contractors are linked to those stretches. For now, Sen's project remains an individual experiment built around his own commute. But the basic idea is straightforward: spot the pothole, record the evidence, find who is responsible and make the complaint ready to file.

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.

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.