With comprehensive pavement condition data and a complete drainage asset inventory, Moorestown moved from guesswork to a transparent, defensible program residents can see on the ground.
Without current, consistent pavement data, Moorestown struggled to know which roads to fix or when, and lacked an up-to-date asset inventory to guide budgeting. As a result, staff were stuck playing defense to resident complaints—constantly asked “Why not my road?” and unable to justify choices in meetings. The absence of reliable, comparable data left the team uncertain, reactive, and under fire, with projects delayed and taxpayer dollars stretched thin.
Moorestown chose Cyvl to rapidly survey the entire network using vehicle-mounted LiDAR and sensors, scanning 106 roadway miles in weeks instead of months. Through Cyvl’s Infrastructure Intelligence platform, AI converted the raw data into detailed, actionable pavement condition scores, prioritized repair lists, and defensible multi-year plans and reports. Delivered by July 29, 2025, the city received trustworthy, up-to-date pavement condition data for all 106 miles plus a mapped inventory of 2,247 catch basins, enabling faster decisions, clearer budgeting, and quick action for residents.
With comprehensive pavement condition data and a complete drainage asset inventory, Moorestown moved from guesswork to a transparent, defensible program residents can see on the ground. The city now sequences repairs and preservation work based on objective scores and risk, accelerating visible fixes and reducing time between data collection and construction. Faster data delivery by July 29, 2025 meant plans, budgets, and communications were ready in weeks, helping leadership secure support and schedule work before another season of wear.