Government Tests AI System to Detect Rural Road Defects Through Smartphone Videos
India is exploring a new technology-driven approach to rural road maintenance by testing an artificial intelligence system capable of identifying potholes, cracks and other visible road defects through videos recorded on smartphones. The initiative is being tested on roads constructed under the Pradhan Mantri Gram Sadak Yojana (PMGSY) and is part of a wider effort to make infrastructure monitoring more systematic and data-driven.
AI to Identify Road Problems Through Video
The system is being developed by the Centre for Development of Advanced Computing (C-DAC) in collaboration with the National Rural Infrastructure Development Agency (NRIDA). The Ministry of Rural Development has given in-principle approval for trials, while a nationwide field-validation exercise began on September 1, 2026.
The technology is being trained to identify seven categories of visible road defects, including potholes, longitudinal and transverse cracks, edge breaks, surface depressions, patches and vegetation-related obstructions. Road-condition videos are being recorded using mobile devices mounted on vehicles already available with Programme Implementation Units, meaning the initial system can be tested without creating a separate fleet of inspection vehicles.
Engineers Will Continue to Verify AI Findings
The AI system is intended to support engineers rather than replace physical inspections. At present, road maintenance under PMGSY involves field inspections and geo-tagged photographs uploaded through the eMARG mobile application. Under the proposed system, AI-generated assessments will provide additional information that engineers can compare with their own observations and measurements.
If the AI system and field assessment produce different results, those differences will be examined during the ongoing validation exercise. A formal verification and review protocol is expected to be finalised before wider implementation. The government is also examining whether technology-enabled road assessments could eventually be carried out every quarter, although the frequency has not yet been finalised.
Trials Across Different Parts of India
The technology has already undergone testing in several regions with different road and environmental conditions. Initial trials covered six roads in Pune, Lucknow district, Kamrup district in Assam and Ri-Bhoi district in Meghalaya. An improved version of the AI model was subsequently tested on seven roads in Kanpur district and Berasia block of Bhopal district.
The current nationwide validation exercise is expected to generate additional data that can help improve the accuracy and reliability of the system. Any wider deployment will depend on the results of this exercise, operational readiness and further approvals.
Strengthening Technology-Based Rural Infrastructure Monitoring
The initiative comes against the backdrop of the enormous scale of India's rural road network. According to government data released in July 2026, 1,85,651 roads covering nearly 7.97 lakh kilometres and 10,833 bridges had been constructed under different components of PMGSY since the programme's inception. During 2025–26 alone, 2,905 roads covering 15,647.78 kilometres and 1,042 bridges were completed.
For a network of this scale, technology-assisted monitoring can provide additional data for identifying maintenance requirements and tracking road conditions. The proposed smartphone-based approach also builds on existing digital monitoring mechanisms rather than creating an entirely separate infrastructure.
AI Expanding Across India's Road Management
The use of AI for road monitoring is also being explored beyond rural roads. In March 2026, the National Highways Authority of India announced an AI-powered Dashcam Analytics System for approximately 40,000 kilometres of the National Highway network. Specialised cameras mounted on Route Patrol Vehicles are intended to collect imagery and video data for road-condition assessment and operations and maintenance activities.
Together, these initiatives indicate how artificial intelligence, mobile devices, cameras and digital platforms are increasingly being incorporated into infrastructure management. For rural roads in particular, smartphone-based assessment could provide a practical way to gather road-condition information across large and geographically diverse areas.
The MGMM Outlook
The government’s initiative to test AI-based road monitoring through smartphone videos reflects the growing use of technology to strengthen rural infrastructure management. By enabling AI to identify potholes, cracks, surface depressions, edge breaks and other visible defects, the system could provide engineers with additional, timely information about road conditions across the extensive PMGSY network. Its integration with existing field-inspection and digital monitoring mechanisms can also help make road-condition assessment more systematic and data-driven.
The ongoing nationwide validation will be important in establishing the technology’s accuracy across different geographical and environmental conditions. Since engineers will continue to verify AI-generated findings, the system is being positioned as a supportive tool rather than a replacement for professional assessment. If the trials demonstrate reliable results, smartphone-based AI monitoring could become a practical addition to India’s infrastructure-management efforts, helping authorities identify maintenance requirements more efficiently across rural areas and strengthen the long-term monitoring of roads.
(Sources: India Today, Hindustan Times)
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