As India’s urban centres expand rapidly amid a digital revolution, city administrations are increasingly leaning on artificial intelligence (AI) to combat long-standing civic challenges—from managing stray cattle and illegal constructions to detecting water loss and sanitation violations. This shift underscores a broader ambition to transform Indian cities into more sustainable, efficient, and responsive spaces through tech-enabled governance.
In Surat, one of the country’s leading smart cities, AI is being deployed to monitor stray cattle, a problem that continues to disrupt traffic and cause accidents. The Surat Municipal Corporation (SMC), in partnership with the National Institute of Technology, has integrated an AI-driven video surveillance system to detect unattended cattle using real-time feeds from cameras placed at major city junctions. Alerts are generated only when cattle are unaccompanied by herders, enabling rapid response by on-ground municipal teams. This initiative stems from the Gujarat High Court’s directive, following which the city also implemented RFID tagging for cattle to trace ownership and penalise repeat offenders. With 1,545 incidents detected so far, the city has already collected ₹18.4 lakh in fines, reinforcing how data-backed enforcement can yield meaningful results.
Beyond traffic and street safety, Surat is also harnessing AI for sanitation. The same system identifies littering and spitting offences, capturing evidence through Automatic Number Plate Recognition (ANPR). According to civic officials, over 47,000 violations were detected, leading to more than ₹25 lakh in collected fines. This blend of surveillance, automation, and enforcement has notably contributed to Surat’s high ranking in the Swachh Survekshan initiative. In Pune, AI has taken on the more invisible but financially draining issue of non-revenue water (NRW), primarily caused by pipe leakages and unauthorised consumption. A pilot project using digital twin technology in Panchawati successfully brought NRW down to 25%, with further reductions expected. The technology, which creates a virtual replica of the city’s water infrastructure, uses AI and machine learning models to detect anomalies based on sensor data, enabling targeted interventions and improved efficiency. This system is now being expanded to 15 more zones in the city.
The Pune Municipal Corporation is also using AI to detect illegal constructions by comparing GIS data with property tax records, thereby recovering lost municipal revenue and improving land-use accountability. Chhatrapati Sambhajinagar (formerly Aurangabad) has deployed an AI-powered chatbot in Marathi and English to assist residents with civic queries. The system covers a wide range of services including birth certificates, property tax payments, and grievance redressal. Complaints unresolved within two weeks are automatically escalated to the city commissioner—closing the loop between citizens and authorities.
Elsewhere, Jabalpur in Madhya Pradesh is leveraging drone surveys and 3D modelling to detect building expansions, leading to an additional ₹30 crore in property tax collections. The comparison between updated aerial imagery and past models has provided a data-backed method to check unregistered development. These local innovations are being supported by central government programmes such as the Smart Cities Mission and the Safe City Project, which have embedded AI into traffic management systems across several Tier 1 and Tier 2 cities. These tools monitor red-light violations, helmetless riders, and triple riding while identifying offenders through ANPR. The Safe City initiative is also deploying facial recognition systems to identify suspects and strengthen urban security.
However, this digital transformation is not without gaps. Recent incidents in Delhi highlighted concerns over the maintenance of AI-integrated camera infrastructure, with several units found defunct or uninstalled. These lapses raise questions about the consistency of implementation and the need for ongoing oversight. Experts from national urban think tanks suggest that the next wave of AI integration should focus on predictive analytics for climate resilience. Under the CITIIS 2.0 programme, 21 climate observatories are being set up to combine live pollution, weather, and urban data with AI tools for localised disaster mitigation planning.
As Indian cities stride into a new era of data-driven governance, the integration of AI not only signals a leap in operational efficiency but also offers hope for building equitable and resilient urban ecosystems.
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