Abstract Manager

Manually acquiring and mapping transportation data is a time-intensive, error-prone process that struggles to keep pace with the rapidly evolving needs of Canadian cities. Traditional methods often lack accuracy and scalability, resulting in incomplete or outdated datasets that hinder effective transportation planning. As cities focus further on complete street goals and active transportation, granular information on key assets within the public right-of-way becomes critical.

AI-powered systems can process large volumes of aerial and satellite imagery to generate precise, real-time maps of road networks and analyze traffic bottlenecks in key infrastructure segments such as crosswalks, road signage, parking availability, etc. Leveraging this high-quality data improves transportation planning, enabling urban planners to design more efficient roadways, optimize traffic flow, and enhance public transit systems.

GeoMate uses aerial imagery with vision mapping to identify assets that are either too granular or too time-consuming to be mapped traditionally. This allows municipalities to open new pathways for innovation and gain a deeper understanding of the transportation network for efficient planning and creating safer streets for all.