Pune Launches AI Cameras to Tackle Traffic Violations

Pune has introduced an AI-based traffic surveillance system to monitor and penalize common traffic violations, aiming to improve road safety and reduce congestion.

Ai CamerasTraffic ViolationsRoad SafetySmart CityPuneReal Estate PuneMay 29, 2025

Pune Launches AI Cameras to Tackle Traffic Violations
Real Estate Pune:Pune has launched an artificial intelligence-based traffic surveillance system to automatically detect and penalize traffic violations. Introduced on a trial basis, the system is being tested along Fergusson College Road, one of the city’s busiest stretches known for chronic congestion and habitual infractions. The pilot initiative, backed by a smart city vision for sustainable and equitable mobility, marks the first such deployment in Pune.

The system harnesses live footage from AI-powered closed-circuit television cameras to monitor common violations such as illegal parking, wrong-lane driving, overspeeding, and signal jumping. According to officials, the system analyses real-time video feeds and alerts the traffic command centre about any breach of road rules. Once verified, digital penalties including e-challans are swiftly issued. Vehicles found parked in no-parking zones or obstructing traffic for more than three minutes are flagged automatically, eliminating the need for manual patrolling.

The automation is expected to not only reduce the burden on traffic personnel but also increase the consistency and speed of enforcement. Officials explained that four high-definition AI cameras have been installed along the Fergusson College Road corridor for a 90-day pilot run. Data from the trial period will be critically analysed to evaluate the system’s efficacy, user compliance, and potential scalability across other parts of Pune. Depending on the success of the trial, the traffic department may consider a citywide rollout of the system.

Experts associated with the initiative stated that such intelligent enforcement mechanisms represent a transformative shift in urban traffic management. While traditional methods often rely on physical deployment and manual review, AI introduces precision and speed that manual systems can seldom match. In the broader context, the adoption of AI in public infrastructure contributes to smarter and more sustainable cities. By promoting stricter enforcement of traffic norms, the initiative aims to reduce emissions caused by congestion and idling vehicles, contributing to Pune’s long-term goals of becoming a net-zero carbon city. Sustainable urban mobility, officials argue, cannot be achieved without instilling road discipline among citizens.

Civic observers noted that this AI-driven system could play a pivotal role in ensuring traffic order, especially in fast-growing metropolitan regions where manual policing is neither efficient nor scalable. In a city like Pune—grappling with rising vehicular populations and limited road infrastructure—technology-driven interventions could reduce accidents, curb lawlessness, and enhance public safety. Officials emphasised that this system is not intended as a punitive measure alone, but as a behavioural nudge to foster safer road habits among commuters. By using real-time detection, the authorities aim to build a culture of compliance and discourage recurring offences. “The certainty of being monitored,” they suggested, “often has a stronger deterrent effect than the severity of punishment.”

The move also aligns with the broader push for digital governance and data-driven decision-making in Indian cities. Automation in enforcement, especially when coupled with public transparency and accountability, could contribute to building trust between citizens and authorities. A data-rich environment also enables targeted infrastructural improvements and policy corrections where violations are most frequent. While the current deployment is limited in scope, early feedback from citizens has been mixed. Some residents have welcomed the initiative for its potential to restore order on undisciplined city roads. Others have voiced concerns over privacy, fairness in enforcement, and potential glitches in AI recognition systems. Officials, however, have assured that all privacy norms are being adhered to, and each flagged offence is subject to secondary review before penalisation.

As Pune positions itself among India’s leading smart cities, the introduction of AI in traffic regulation is more than a tech upgrade—it is a cultural reset that demands collaboration between authorities, citizens, and innovators. The next 90 days will prove critical in understanding whether AI-powered governance can balance enforcement with empathy and create safer, more sustainable public spaces. If successful, the model could inspire similar interventions in other rapidly urbanising Indian cities where road safety remains a pressing concern.

Frequently Asked Questions

What is the new traffic surveillance system in Pune?

Pune has launched an AI-based traffic surveillance system to automatically detect and penalize traffic violations such as illegal parking, wrong-lane driving, overspeeding, and signal jumping.

Where is the system being tested?

The system is being tested along Fergusson College Road, one of the city’s busiest stretches known for chronic congestion and habitual infractions.

How does the system work?

The system uses AI-powered CCTV cameras to monitor real-time video feeds and alerts the traffic command centre about any breaches of road rules. Once verified, digital penalties including e-challans are swiftly issued.

What are the benefits of this system?

The system aims to reduce the burden on traffic personnel, increase the consistency and speed of enforcement, and promote stricter enforcement of traffic norms, contributing to safer and more sustainable urban mobility.

What are the concerns raised by residents?

Some residents have voiced concerns over privacy, fairness in enforcement, and potential glitches in AI recognition systems, although officials have assured that all privacy norms are being adhered to and each flagged offence is subject to secondary review.

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