Viso.ai

GoodRoads offers a system that performs automated inspections of asphalt and concrete roads using device-mounted sensors to capture imaging and ride-quality data. The system computes standard condition scores (such as the Pavement Condition Index per ASTM D6433 and PASER) from the collected data. It also provides software tools to generate multi-year maintenance plans and manage roads and roadside assets through a desktop interface.

NCTech offers a service that collects high-resolution 360° street-level imagery and LiDAR data to document infrastructure assets in the field. It uses geospatial capture techniques to map the exact location, orientation, and status of items like signs, poles, utility boxes, sidewalks and more. The data collection process replaces many site visits by enabling desktop review of assets, and feeds into updating inventories and condition assessments with minimal manual input. The captured imagery and 3D data can be regularly refreshed so agencies can monitor change over time and integrate the outputs into GIS or asset-management systems.

RoadAI uses a smartphone to survey road networks, capturing video while driving and applying computer vision to automatically identify surface distresses such as alligator cracks, potholes, settlement, and edge deterioration. It also detects roadside assets including traffic signs, line markings, guard rails, street lights, manholes, and drains. The system provides interactive maps and exportable data formats such as Excel, CSV, GeoJSON, and Shapefile for integration with asset management workflows.