One of the most common, yet most dangerous, events that people face every day is driving. But what if city planning and safety departments could predict and see where traffic accidents were going to happen?
In this episode of HxGN TV, we sat down with Austin Harris from the University of Tennessee Chattanooga and Michael Baker from Hexagon’s Safety, Infrastructure & Geospatial division to talk about the university’s new research project that uses a machine learning-based model to predict where roadway accidents will take place at any given time of the day. We’ll also discuss how the project fuses video, multi-sensor data and HxGN Connect to visualise and analyse historical and predicted traffic accident data.
To learn more, please visit www.reimaginecollaboration.com.
