RoadSight360 analyzes 360° road imagery, automatically detects features such as lanes, barriers, and pedestrian crossings, and produces a safety rating for every road segment.
Traditional field audits rely on manual processes; slow and inconsistent at scale.
Data captured by vehicle-mounted 360° cameras is analyzed with AI to generate a safety rating for each segment.
Processes road imagery.
Identifies safety features.
Generates segment score.
Delivers up-to-date network data.
Produces a safety score per segment.
Analyzes wide road networks on drive-by basis.
Extracts lanes, barriers, and edge elements.
Sequences maintenance work by risk score.
Feeds data into agency infrastructure decisions.
Highlights high crash-risk zones.
Imagery captured by vehicle-mounted 360° cameras is processed; lanes, edges, and environmental elements are digitally modeled.
Lane count, width, barriers, crosswalks, and roadside elements are labeled automatically; output is delivered as a data layer to engineering and planning teams.
Road attributes and environmental risk factors are combined into a single safety score per segment; comparison speeds investment prioritization.
Results appear on maps as risk layers and on dashboards as KPIs and trends; field and leadership work from the same screen.
Road network is shown on a color-coded regional heatmap; high-risk corridors stand out instantly.
Output data layers integrate with GIS, infrastructure data platforms, and enterprise systems via standard connectors.
Vehicle-mounted 360° cameras record the road network while driving.
AI algorithms normalize and analyze the captured imagery.
Lanes, barriers, and other infrastructure features are auto-labeled.
A score is produced for each segment and a risk class is assigned.
Results are delivered as visual maps and analytic reports.
Analyze your road networks with AI; spot risky segments fast with RoadSight360.
