Smart Cities: Data-Driven Solutions to Understand Disruptive Problems in Transportation—The Lisbon Case Study

Transportation data in a smart city environment is increasingly becoming available. This availability allows building solutions that are viewed as meaningful by both residents and management authorities. Our research work was based on Lisbon mobility available through the local municipality, where we integrated cleaned different sources applied CRISP-DM approach using Python. We focused problems interdependence cascading-effect for of Lisbon. developed data-driven approaches artificial intelligence visualization methods to understand traffic accident problems, providing big picture competent authorities supporting being more prepared, adaptable, responsive, better able recover from such events.