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We’ve developed an AI-powered Road Repair Cost Estimator designed to assess road conditions, estimate repair costs, and empower decision-makers with actionable data for efficient infrastructure management.

🛠 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 𝗮𝗻𝗱 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻𝘀:

𝟭. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗣𝗼𝘁𝗵𝗼𝗹𝗲 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 & 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻:
Leveraging YOLOv8 by Ultralytics, our model accurately identifies and segments potholes in road images, offering precise data on road damage that can drive impactful maintenance decisions. With high accuracy and speed, YOLOv8 ensures our system can reliably detect even subtle road wear and tear.

𝟮. 𝗔𝗰𝗰𝘂𝗿𝗮𝘁𝗲 𝗖𝗼𝘀𝘁 𝗘𝘀𝘁𝗶𝗺𝗮𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗠𝗮𝗶𝗻𝘁𝗲𝗻𝗮𝗻𝗰𝗲 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴:
Our estimator takes pothole and damage data to provide real-time, cost-effective repair estimates. This functionality supports road maintenance planning by helping stakeholders quickly prioritize repairs based on both severity and budget constraints.

𝟯. 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝘃𝗲, 𝗨𝘀𝗲𝗿-𝗙𝗿𝗶𝗲𝗻𝗱𝗹𝘆 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝘄𝗶𝘁𝗵 Streamlit:
Deployed on Streamlit, our project delivers a highly accessible, easy-to-navigate interface for a seamless user experience. This interface allows users to visualize road conditions, access estimated repair costs and make informed maintenance decisions with real-time insights.

𝗪𝗵𝘆 𝗜𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀:
With roads being critical to daily life and commerce, effective maintenance is essential for safety and economic productivity. By integrating advanced AI models like Ultralytics' YOLOv8 and a streamlined UI, this tool bridges the gap between complex analysis and actionable insights, helping optimize infrastructure resources.
Check out the working video below to see our project in action, and let us know how this innovation could contribute to smarter infrastructure management!