The fully-automated system is trained using AI-powered object detection to identify street signs in the freely available images.
Municipal authorities currently spend large amounts of time and money monitoring and recording the geolocation of traffic infrastructure manually, a task which also exposes workers to unnecessary traffic risks.
Results just published in the journal of Computers, Environment and Urban Systems show the system detects signs with near 96% accuracy, identifies their type with near 98% accuracy and can record their precise geolocation from the 2D images.
