Points of interest idintification: A case study in Beijing metropolitian area

Recent advances in navigation have generated an extensive amount of georeferenced trajectories which contain information about citizen's movement and their behavior. The objective of this article is to explore georeferenced satellite-based trajectories to identify points of interest, like university, restaurant and gym. We proposed a three-step approach, the first step is cleaning the georeferenced satellite-based data, the second step is to identify stay points by checking the distance and time between the points of each trajectory, and finally we cluster these stay points to extract points of interest. We evaluate the proposed method with a real-world dataset recorded over three years by 62 users in Beijing. We worked with trajectories where the users were walking, riding a bike and driving a car. Our approach was able to extract 138 points of interest, in which 40% were extracted from walking trajectories 33% from biking and 26% from driving. Our results have demonstrated that taking into consideration, the transportation mode for points of interest identification is an important aspect specially for the parameters estimation

Advanced Smartphone-Based Identification of Transport Modes: Resilience under GNSS-Based Attacks

One of the main challenges for ticketing in Mobility as a Service is the integration of the public and individual transport modes into a unified ticketing service. To realize this concept, a trustworthy identification of transport modes that is resilient to possible attacks is required. In this work, we propose two smartphone-based methods to seamlessly identify the use of trams, buses, subways, walking and bicycles, which are able to detect GNSS-based attacks and continue to provide a trustworthy identification of transport modes. We have recorded real-world measurements with commercial smartphones using the transport network in Munich and Paris. Our results show that it is possible to provide trustworthy identification of transport modes even when the system is under attack. In conclusion, in this work we demonstrate the vulnerability of smartphone-based ticketing to GNSS-based attacks, propose two methods to overcome this vulnerability and demonstrate the validity of our methods with real-world measurements