Blog · By Avinash Verma · 2026-04-25 · Updated 2026-10-11

Improving road safety in India with AI-based pothole detection

Potholes cause crashes, damage vehicles and slow traffic across India's roads. Better engineering and maintenance are the long-term answer, but software and sensors can help right now by finding potholes quickly and warning drivers before they reach them. This post explains how AI-based pothole detection works, what it is good at and where it still struggles.

The road safety picture

Indian roads carry a large and growing volume of traffic. Heat, heavy monsoon rain, overloaded vehicles and uneven maintenance mean potholes are common on highways, city roads and village lanes alike. They cause sudden braking, swerving and falls, and two-wheeler riders are the most exposed.

Road safety depends on many things: driver behaviour, enforcement, vehicle condition and road design among them. Pothole detection addresses one part of the problem, but it is a part where better information makes a direct difference.

What AI adds

Automatic identification

Manual inspection is slow and depends on someone noticing the damage. Automated systems analyse data from vehicle sensors or cameras and flag likely potholes without anyone needing to look.

Fast processing

Sensor readings can be processed as they arrive, so a pothole can be recorded within moments of a vehicle hitting it. The shorter the gap between detection and warning, the more useful the warning is.

Fewer false alarms over time

Models can be tuned with more data so that they get better at separating real potholes from ordinary bumps. Repeated detections at the same place from different vehicles also add confidence.

What good road monitoring can do

With enough data from enough vehicles, a monitoring system can:

• tell normal road roughness apart from a genuine pothole
• estimate how severe a hazard is
• place each hazard accurately on a map
• rank road sections by how urgently they need repair

That ranking helps road agencies decide where to send crews first.

Detection methods

Ultrasonic and vibration sensors

An ultrasonic sensor under a vehicle measures the distance to the road surface, so a sudden increase signals a dip. Vibration sensors, including the accelerometer in a phone, record jolts. Both feed data into software that decides whether a pothole was hit.

Camera-based detection

Object-detection models such as YOLO can find potholes in video frames. A camera can spot a pothole before a vehicle reaches it, but performance drops in poor light, heavy rain or when a pothole is full of water.

Combining methods

Using sensors and cameras together can make detection more reliable, because each covers some of the other's weak points. The trade-off is cost and complexity.

Who uses this

Researchers and road agencies in India have experimented with sensor-equipped buses and official vehicles, camera surveys and citizen reporting apps. Fleet operators also have a clear interest, because fewer pothole hits mean lower repair bills. Road condition data can also be used to check how well new roads and repairs hold up over time.

The challenges

Connectivity

Sharing detections needs a data connection. Coverage is patchy on some highways and in hilly or remote areas, which can delay reports.

Cost

Dedicated sensors, cameras, servers and software cost money, and many local bodies have tight budgets. Using phones that drivers already own lowers the cost considerably.

Accuracy and upkeep

Models need regular checking and tuning. Phones, vehicles and mounts vary, and roads change with the seasons. A system that worked well last year may need adjustment this year.

Privacy

Location data and road imagery can be sensitive. A responsible system collects only what it needs, keeps raw data on the device where possible and is clear about what is shared.

Bringing detection into navigation apps

Warnings while you drive

Detection is most useful when the warning reaches the driver in time. A navigation app already knows your route, so it can warn you as you approach a known hazard.

Driver reports

Sensors miss things: a pothole a driver steered around, an open manhole or a waterlogged stretch. Letting drivers report hazards in the app adds this information, and multiple reports at one spot help confirm what sensors detect.

Route choices

When road damage data is available, drivers can compare routes with more information and decide which way to go.

The longer view

• Sensor-equipped roads that report traffic and surface condition.
• Roadside displays that show current hazards and speed limits.
• Drone inspections combined with data from vehicles.
• Prediction of which stretches are likely to fail, based on traffic, weather and road history.

These ideas will only help if agencies act on the data and fund repairs.

How IndiaRoad Map helps

IndiaRoad Map is a free Android navigation app (with ads) that uses your phone's accelerometer and gyroscope to detect potholes, speed breakers and rough road. The raw sensor data stays on your phone; only the detected hazard and its location are shared. You can also report hazards in a tap. During navigation, the app warns you about 10 seconds before a known hazard, never closer than 100 m, by voice and on screen, in English or Hindi, on your phone or through Android Auto.