The Pioneering Project for Road Asset Monitoring and Defect Detection in Indian Roads was conceived to address a critical need in India's road infrastructure management. Aligned with the guidelines set by the National Highways Authority of India (NHAI), this project employs cutting-edge machine learning techniques, with a focus on object detection using TensorFlow.
The primary objective of this project is to automate the identification and classification of various road assets such as street lights, sign boards, and delineators. Alongside asset detection, the project also detects and categorizes road defects like potholes, cracking, and road unraveling.
This project is a game-changer for road asset management and defect detection. By automating the process, it significantly increases efficiency and effectiveness, marking a clear departure from traditional manual monitoring systems. With TensorFlow and machine learning, this project holds the potential to revolutionize infrastructure management and contribute to safer roads across India, in line with NHAI's standards.
Watch our advanced machine learning system in action as it identifies and classifies road assets on Indian roads. This system automatically detects street lights, sign boards, and delineators, providing enhanced road safety and infrastructure management through automation.
Experience the future of road maintenance with our AI-powered system detecting road defects with precision. From potholes to cracks and road unraveling, this system enables early defect detection for safer, well-maintained roads in India.