Road Pavement Analysis

An innovative road infrastructure analysis tool that combines computer vision with modern web technologies. This application helps civil engineers and transportation departments assess pavement conditions and prioritize maintenance efforts.

The system uses machine learning models to analyze road surface images and detect various types of damage including cracks, potholes, and surface degradation. Results are visualized on an interactive map with severity ratings.

My contribution to the project: I was responsible for implementing the automatic road segmentation feature, which allows dividing roads into segments with configurable lengths, automatically processing sensor data for each segment, and visualizing segmented results directly on the interactive map, classified by pavement quality. This feature significantly improved analysis efficiency and consistency, reducing manual effort and enabling standardized evaluations.