By June 30, 2025, Lebanon had a current, citywide baseline of pavement and roadside assets it could trust.
Lebanon’s rapid growth exposed the limits of outdated and inconsistent street data, making it hard to know which roads to fix and when and leaving paving budgets built on guesswork. Without defensible, current information, staff often played defense in public meetings—fielding 311 calls, answering “Why not my road?,” and appearing reactive instead of strategic. The lack of a clear, data-backed prioritization method delayed projects, fueled frustration, and made it difficult to justify spending taxpayer dollars with confidence.
To move from reactive to proactive, Lebanon chose Cyvl to quickly measure its network with vehicle-mounted LiDAR and sensors, scanning 850 roadway miles and capturing 10,550 signs and 610 guardrails. Within weeks, Cyvl’s Infrastructure Intelligence platform applied AI to produce detailed, actionable pavement condition data for all 850 miles—complete with segment-level condition scores, mapped distresses, and geolocated imagery—alongside a comprehensive sign and guardrail inventory. With these insights, the city built prioritized repair lists and defensible multi-year plans, supported by clear, ready-to-share reports that accelerate decisions and align staff, leadership, and residents.
By June 30, 2025, Lebanon had a current, citywide baseline of pavement and roadside assets it could trust. With 850 miles scanned, 10,550 signs inventoried, and 610 guardrails mapped, the city targeted safety and pavement improvements where they matter most for residents. The speed of delivery—weeks instead of months—translated into earlier scheduling, faster construction starts, and a shorter gap between data collection and visible results on the street.