Smart AI-Based FRP Cover Damage Tracker Rolled Out in Chennai

Chennai is fast becoming a leader in AI-driven civic innovation, and its latest development targets one of the most overlooked but critical areas of infrastructure — manhole cover health monitoring. In partnership with IIT Madras and a private AI startup, the Greater Chennai Corporation has deployed a machine-learning-based FRP cover damage detection system, powered by on-ground image data.

The Problem

Chennai's coastal climate, which is characterized by severe monsoons, salty air, and flooding in urban areas, puts a lot of strain on manhole covers. While FRP covers outperform concrete and cast iron in corrosion resistance, physical damage from vehicular impact or installation faults still occurs.

The AI Solution

Chennai’s pilot uses computer vision and AI models trained on thousands of street-level images. Municipal vehicles and field officers are equipped with cameras that capture real-time images of roads and footpaths. These images are fed into a centralized server, where an algorithm automatically flags:

• Cracks

• Surface delamination

• Displacement

• Unauthorized replacement

If an anomaly is detected, an alert is triggered on the municipal dashboard, prompting pre-emptive inspection or replacement.

The FRP coverings themselves, which are provided by regional producers, are now enhanced with reflective markings or QR codes to increase the precision of image identification in low light. The AI models improve with each dataset, thanks to reinforcement learning techniques developed in collaboration with the IIT research team.

Advantages

• Reduces manpower burden for manual inspections

• Supports preventive maintenance rather than reactive repair

Detection accuracy has now surpassed 88% in early deployment throughout Adyar and T. Nagar, greatly reducing false negatives. GCC officials plan to integrate this AI model with existing GIS maps and eventually enable automated complaint tickets via WhatsApp or public apps.

This AI-FRP collaboration demonstrates how technology and materials science may collaborate to prolong infrastructure life and enhance urban safety in light of Chennai's quest for smart governance.