Within weeks from data collection, Brownsburg had current condition scores for every street segment and a verified inventory of 5,628 signs, giving staff immediate clarity on needs, risk, and safety gaps.
Brownsburg is growing fast, and its mix of neighborhood streets and busy corridors made it hard to decide where to direct limited paving funds. The public works team was working from outdated or inconsistent data, which meant they didn’t know which roads to fix or when and struggled with no accurate paving budgets. In council and town-hall settings, leaders found it hard to defend budgets and couldn’t justify actions in town meetings, fueling a reactive cycle to complaints.
The City of Brownsburg selected Cyvl to rapidly survey its entire network, scanning 165 roadway miles with vehicle-mounted LiDAR and sensors and delivering results in weeks, with final delivery on May 25, 2024. Cyvl’s Infrastructure Intelligence platform used AI to convert the scans into detailed, actionable pavement condition data and a complete inventory of 5,628 signs, all presented in clear, map-based reports and dashboards. With objective condition scores, prioritized repair lists, and defensible plans, the city gained the tools to make better decisions faster and communicate them clearly to residents.
Within weeks of fieldwork, Brownsburg had current condition scores for every street segment and a verified inventory of 5,628 signs, giving staff immediate clarity on needs, risk, and safety gaps. Delivery by May 25, 2024 enabled the city to schedule maintenance and resurfacing in the same construction season, reducing the time between data collection and project implementation for residents. With trustworthy data for all 165 miles, leaders can justify investments, allocate crews efficiently, and explain project choices in a way residents understand and trust.