2019/02/08 by Amnir Hadachi, Hadachi, Amnir, Artjom Lind +1
Computer Science · Engineering · Social Sciences · #FOS: Computer and information sciences #Human Mobility and Location-Based Analysis #Indoor and Outdoor Localization Technologies #Networking and Internet Architecture (cs.NI) #Opportunistic and Delay-Tolerant Networks
paper · pdf · doi:10.48550/arxiv.1902.09399
openalex publication_date 2019/02/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The emerging technologies related to mobile data especially CDR data has great potential for mobility and transportation applications. However, it presents some challenges due to its spatio-temporal characteristics and sparseness. Therefore, in this article, we introduced a new model to refine the positioning accuracy of mobile devices using only CDR data and coverage areas locations. The adopted method has three steps: first, we discovered which model of movement (Move, Stay) is associated with the coverage areas where the mobile device was connected using a Kalman filter. Then, simultaneously we estimated the location or the position of the device. Finally, we applied map-matching to bring the positioning to the right road segment. The results are very encouraging; nevertheless, there is some enhancement that can be done at the level of movement models and map matching. For example by introducing more sophisticated movement model based on data-driven modeling and a map matching that uses the movement model type detected by matching "Stay" location to buildings and "Move" model to roads.