Road infrastructure is the backbone of a country’s economy, facilitating trade, transportation, and connectivity. However, maintaining and monitoring road conditions is a complex task due to various challenges such as wear and tear, weather conditions, increasing vehicular load, and lack of real-time data. Traditional road monitoring methods often rely on manual inspections, which are time-consuming, expensive, and prone to errors. The integration of Geographic Information Systems (GIS) into road infrastructure monitoring provides a more efficient, accurate, and cost-effective solution. AI-based Road Condition Monitoring Systems leverage advanced machine learning algorithms and computer vision to detect road damages such as potholes, cracks, and surface degradation in real-time. These systems enhance efficiency by automating…