Machine learning solutions for matching of vehicle exit to unmatched entry events

Abstract

An edge device generates an exit event for a vehicle exiting a parking facility. The edge device determines whether the exit event matches with an entry event. Responsive to determining that the exit event does not match to an entry event, the edge device inputs images of the vehicle into a supervised machine learning model and receives, as output from the model, an exit feature vector. The edge device retrieves entry feature vectors corresponding to hanging entry events. A hanging entry event is an entry event for a vehicle with an unknown vehicle identifier. Edge device inputs the exit feature vector and the entry feature vectors into an unsupervised machine learning model and receives, as output from the model, matching scores for each entry feature vector. Edge device matches the exit event to one of the hanging entry events based on the matching scores.