A Cluster-Based Approach Using Smartphone Data for Bike-Sharing Docking Stations Identification: Lisbon Case Study

Urban mobility is a massive issue in the current century, being widely promoted need of adopting sustainable solutions regarding transportation within large urban centres. The evolution technologies has democratised smart cities to better plan and manage their solutions, without compromising social, economic, environmental impacts. Pursuing carbon neutrality climate agreement goals, soft one most popular emerging methods provide greener alternatives mobility. Among these modes are bicycle, which been used several public systems across world, them Lisbon. This article provides decision support system for bike-sharing docking stations three council parishes city, namely, Parque das Nações, Marvila, Beato. Taking advantage clustering GSM data from telecommunication operator, this study pretends highlight novel approach identify hotspots, specific stations, suited management Lisbon’s city centre.