Integration of Mobility Data with Weather Information
| Main Authors: | Nikolaos Koutroumanis, Georgios M. Santipantakis, Apostolos Glenis, Christos Doulkeridis, George A. Vouros |
|---|---|
| Format: | Proceeding eJournal |
| Terbitan: |
, 2019
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| Online Access: |
https://zenodo.org/record/3697706 |
Daftar Isi:
- Nowadays, the vast amount of produced mobility data (by sen- sors, GPS-equipped devices, surveillance networks, radars, etc.) poses new challenges related to mobility analytics. In several ap- plication, such as maritime or air-traffic data management, data analysis of mobility data requires weather information related to the movement of objects, as this has significant effect on various characteristics of its trajectory (route, speed, and fuel consump- tion). Unfortunately, mobility databases do not contain weather information, thus hindering the joint analysis of mobility and weather data. Motivated by this evident need of many real-life applications, in this paper, we develop a system for integrating mobility data with external weather sources. Our system is de- signed to operate at the level of a spatio-temporal position, and can be used to efficiently produce weather integrated data sets from raw positions of moving objects. Salient features of our approach include operating in an online manner and being re- usable across diverse mobility data (urban, maritime, air-traffic). Further, we extend our approach: (a) to handle more complex geometries than simple positions (e.g., associating weather with a 3D sector), and (b) to produce output in RDF, thus generating linked data. We demonstrate the efficiency of our system using experiments on large, real-life data sets.