Analysis, design and implementation of a parking recommendation system applying machine learning techniques

Nowadays, smart city and urban mobility topics are focusing growing interest for business and R\&D purposes both, and one of its trendy application regards the study and the realization of parking recommendation systems. In our case, a parking recommendation system is going to be developed for the city of Bologna. After a brief revision of similar proposed solutions and their approaches and findings, a first data analysis phase is going to be executed to explore the data and to mine any useful information about the parking behavior. Then, once the adopted forecasting model has been exposed, the design and the development of the system are going to be described. In the end, the performances of the system are going to be evaluated under multiple points of view, considering some project-specific constraints too.