Predicting Demand for Smart Parking Systems
The rapid development of information technologies has enabled to create accurate machine learning models that could learn from the existing data without the need of an expert in the field. Applying these models in the field of urban design problems could help to create better living conditions in large cities. This research focuses on creating a neural network that could predict parking area occupancy. Integrating the model to a parking guidance platform would produce a valuable product that could help to reduce the traffic congestions and the cruising time for a parking spot.
Graduation Thesis language
Graduation Thesis type
Bachelor - Computer Science