For safer Gurugram roads, GMDA to adopt AI solutions

Tribune News Service

Kulwinder Sandhu

Gurugram, March 17

The Gurugram Metropolitan Development Authority (GMDA) has planned to transition from the conventional method of monitoring and maintenance to artificial intelligence (AI) solutions for the repairing and upkeep of roads.

The GMDA has invited tenders for the selection of an agency to conduct surveys, monitoring and maintenance of roads using AI solutions. The last date for inviting tenders is April 18, and the bids will be opened on April 19.

Gurugram has an extensive road network spanning 300 km managed traditionally through manual surveys and estimations, jointly by the MC and the PWD. However, the GMDA now intends to enhance its maintenance strategies by adopting AI-based solutions.

The main objectives of switching to AI solutions are to enhance efficiency and cost-effectiveness in road maintenance operations. Moreover, the proposed approach entails comprehensive automation, enabling automated surveys and validations, significantly reducing the need for extensive manpower. With AI at its core, GMDA looks forward to adopting modern-day technologies for streamlined and optimised road maintenance practices in Gurugram city.

A total of 12 surveys will be conducted by the selected agency every month. Each survey will cover the full length of roads so that road health data for the entire road network can be obtained on a monthly basis. This data may further be used in road maintenance, estimations, etc.

The system will also record videos with GPS coordination so that the system can capture road pavement anomalies, including potholes, cracks and patches. It will also record road furniture anomalies, including missing or faded lane markers, boundary markers, kerb paint, road signs, zebra crossings, speed breakers, missing median vegetation and streetlights. This will help generate area estimation for potholes and web cracks to aid detailed project report (DPR) preparations.

The AI system will be enabled for GPS correction of tunnels and underpasses. Besides, it will enable the identification of road defects, which will be marked on a centralised map and visualised by a special team of the engineering wing. These defects will be communicated to officials and contractors through an automated system for prompt repairs.

Advantages over traditional methods

• AI systems excel in detecting potholes and other road hazards swiftly and with greater accuracy compared to human inspectors.
• Moreover, they necessitate less human intervention, thereby potentially reducing costs associated with manual inspection processes.

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