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

Bengaluru Engineer Transforms Dashcam Into AI-Powered Pothole Detection System

Gaurav Sen, a Bengaluru engineer, has developed an AI tool that converts a car dashcam into an automated pothole detection and reporting system.1

1

The AI-powered system combines hardware components including a car dashcam, GPS, and an accelerometer to identify damaged roads while driving through Bengaluru's streets. Sen's motivation stemmed from a frustrating commute where he encountered 12 potholes, prompting him to explore whether technology could simplify the reporting process.1

1

The system addresses a critical safety concern, as more than 2,000 Indians die annually in pothole-related accidents.1

1

How the AI-Powered System Detects Damaged Roads

Sen built the application using Codex and connected it to OpenAI for processing the collected data.2

2

As he drives, the dashcam records road footage while GPS tracks location and the accelerometer captures vehicle movement patterns that indicate road irregularities.1

1

AI vision models then analyze the recorded footage to spot potholes and classify them by size into small, medium, and large categories.1

1

The technology also handles a common challenge on Indian roads: distinguishing potholes from speed breakers when viewed from a distance.2

2

System Identifies Responsible Contractors Through Government Contracts

The AI tool goes beyond simple pothole detection by searching through approximately 2,900 government contracts to connect each detected pothole with the relevant road project.1

1

The system identifies responsible contractors, tender numbers, and the government office associated with that particular road stretch.1

1

This feature proves particularly valuable for roads still under warranty, where contractors remain legally responsible for fixing defects without additional government expense.2

2

By linking road damage to government contracts, the system establishes clear road maintenance accountability rather than treating potholes as isolated defects.1

1

Automatic Complaint Generation in Four Seconds

The most striking aspect of Sen's AI-powered system is its automatic complaint generation capability. Within approximately four seconds of detecting a pothole, the system compiles a comprehensive complaint record.1

1

Each record includes the pothole photograph, exact location coordinates, relevant tender numbers, contractor details, and the officer responsible for that road section.3

3

This automated civic reporting process eliminates the manual effort typically required to document road damage, find the appropriate authority, and prepare a formal complaint.1

1

Sen shared the project on Instagram on August 5, describing it as his method for reporting potholes to the Brihanmumbai Municipal Corporation (BBMP).1

1

Real-World Testing Reveals Scope of Road Damage

During his regular commute, Sen tested the system and detected 12 potholes along his route.2

2

Each detection generated photographic and location-based evidence, creating a documented record rather than relying solely on driver descriptions.1

1

The system prepared 12 ready-to-file complaints linked to respective road authorities and contractors.2

2

This test demonstrated how ordinary commutes can generate valuable civic infrastructure management data when everyday hardware combines with AI vision models.2

2

Implications for Civic Infrastructure Management

Sen's project demonstrates a practical application of AI tool technology beyond conventional apps and chatbots.3

3

The video demonstration, shared in collaboration with ChatGPT India, gained significant attention on social media platforms including X.2

2

Users praised the innovative approach, with reactions describing it as "fixing real-life bugs" and expressing hope that similar systems could improve road repairs across Bengaluru and other Indian cities.3

3

If deployed at scale, such AI-powered systems could help cities build comprehensive maps of deteriorating roads and track which projects require immediate attention. The technology transforms routine drives into sources of documented civic information, potentially accelerating response times from authorities when presented with precise location data and contractor accountability. Watch for civic agencies exploring similar automated detection systems to complement traditional complaint mechanisms and improve road maintenance workflows across urban areas.