With the dataset in hand, Ellington turned resident reports into an actionable, neighborhood-by-neighborhood maintenance and paving program that focused resources where they would help people fastest.
Ellington’s residents were reporting potholes, cracking, and rough pavement across town, but the Public Works team lacked current, system-wide data to act quickly and confidently. Traditional pavement inventories relied on slow, manual windshield surveys and spreadsheets, which delayed planning and pushed construction into the next season. Without a trusted condition map across all roads, budget hearings were harder, projects stalled for months, and taxpayers felt the impact in flat tires, detours, and safety concerns near schools and businesses.
Ellington chose Cyvl to rapidly survey every street using vehicle-mounted LiDAR and sensors, capturing precise pavement distress across 103.5 roadway miles. Cyvl’s Infrastructure Intelligence platform transformed those scans into detailed, actionable pavement condition data with segment-level ratings, recommended treatments, and costed capital plans—delivered to the Town on 2023-11-13. With clear maps, dashboards, and exportable worklists, Ellington aligned budget, engineering, and operations so projects could move from data to design in weeks, not months, accelerating resident benefits.
With the dataset in hand, Ellington turned resident reports into an actionable, neighborhood-by-neighborhood maintenance and paving program that focused resources where they would help people fastest. Engineering finalized treatment selections faster, procurement prepared bid packages sooner, and crews scheduled work while the weather still allowed safe construction. Because more projects can start within weeks of receiving Cyvl’s data, Ellington can maintain or repave 5x the number of roads compared to traditional methods and make the overall network safer for everyone as new safety standards are applied.