Ahmedabad, September 2026: Commuters travelling on Ahmedabad (AMTS) buses could soon see a major technology-driven change in how bus operations and road safety are monitored. The Ahmedabad Municipal Corporation (AMC) is deploying AI-enabled dashcams in public buses to detect traffic and safety-related violations in real time.
The initiative is part of Ahmedabad’s broader push towards AI-based traffic monitoring and smart city surveillance. The cameras installed in AMTS and BRTS buses are designed to turn moving public transport vehicles into mobile monitoring units across the city.
AI Cameras to Monitor Ahmedabad AMTS Buses Operations
Under the project, around 1,000 AMTS and BRTS buses and other municipal vehicles are planned to be equipped with high-definition AI-enabled dashcams.
Unlike fixed CCTV cameras, these cameras will move across different routes and collectively cover thousands of kilometres of Ahmedabad’s road network. The AI system will analyse footage and identify predefined traffic, civic and public-safety issues before transmitting relevant information to the municipal system for further action.
What Will the AI Cameras Detect?
The AI-powered system has been designed around approximately 20 predefined use cases, covering traffic violations, road conditions, civic problems and safety-related incidents.
Potential monitoring areas include:
- Traffic rule violations
- Road and infrastructure problems
- Potholes and damaged roads
- Accidents
- Illegal or unauthorised activities
- Stray cattle
- Improper parking
- Civic cleanliness-related issues
- Other public-safety concerns
The tender documents for the project specify AI-based automated detection for 20 use cases, divided into priority categories.
Driver Safety and Traffic Violations Under Watch
The technology is also expected to strengthen monitoring of bus-driver behaviour and road safety.
This comes after AMC took disciplinary action against drivers following surprise inspections. In July 2026, 13 contract drivers from AMTS and BRTS were suspended/removed after authorities identified issues including overspeeding, failure to stop at designated bus stops and inappropriate behaviour with passengers.
The AI-based monitoring system could provide authorities with an additional source of real-time information to identify unsafe driving patterns and traffic violations.
AMTS Buses Could Become Moving CCTV Units
One of the biggest advantages of the project is the mobility of the cameras. Fixed surveillance cameras can monitor only their immediate surroundings, whereas AI cameras mounted on buses can continuously collect information as buses travel through different neighbourhoods.
According to project details, the system is expected to cover more than 5,000 km of roads through buses operating on regular city routes.
How the System Could Work
| Stage | What Happens |
|---|---|
| 1 | AI camera installed on bus |
| 2 | Bus travels on its regular route |
| 3 | Camera captures road and traffic conditions |
| 4 | AI analyses predefined situations |
| 5 | Detected events are transmitted to AMC systems |
| 6 | Authorities can review and take appropriate action |
Ahmedabad Expands AI-Based Traffic Monitoring
The AMTS initiative is part of a wider technology upgrade planned for Ahmedabad.
The city’s proposed Traffic and Road Safety Policy includes expanding surveillance infrastructure and upgrading cameras with AI capabilities. The proposal also includes automatic e-challans for detected traffic violations and integration of traffic-management systems.
Ahmedabad already uses an Intelligent Traffic Management System to monitor AMTS and BRTS operations, while the city’s Integrated Command and Control Centre supports technology-based urban monitoring.
What It Means for Ahmedabad Commuters
For passengers, the primary objective is expected to be safer and more accountable public transport.
Continuous monitoring could help authorities identify unsafe driving, traffic violations and road problems more quickly. It may also help AMC understand recurring problems on busy routes and take action based on actual road-level data.
However, the effectiveness of the system will depend on accurate AI detection, timely response from authorities and proper implementation across the bus fleet.
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