From Raw Sensor Data to Semantic Trajectories - Archive ouverte HAL
Communication Dans Un Congrès Année : 2019

From Raw Sensor Data to Semantic Trajectories

Résumé

GPS position are useful to analyse movements of mobile objects. Unfortunately , the outcome can be unsatisfactory due to imprecision and signal lost. Several sensors (generic or specific ones depending on the type of vehicle) are now included into mobile objects. This article describes a new generic model that enhances the semantic trajectory model and a process to extract semantic from GPS and other sensors. This process is based on the raw data from these sensors which help identify how, why and when mobile objects are moving, in order to add semantic information to the trajectories and then design new applications such as smart GPS, reporting systems or Remote Maintenance System. This process was successfully applied to the Indre et Loire fire department and its connected ambulances.
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Dates et versions

hal-02380444 , version 1 (26-11-2019)

Identifiants

Citer

Frédérick Bisone, Thomas Devogele, Laurent Etienne. From Raw Sensor Data to Semantic Trajectories. 5th ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management (EM-GIS 2019), Nov 2019, Chicago, United States. ⟨10.1145/3356998.3365777⟩. ⟨hal-02380444⟩
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