Understanding human mobility: A multi-modal and intelligent moving objects database

Jianqiu Xu, Hua Lu, Ralf Hartmut Güting

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

Abstract

The research field of moving objects has been quite active in the past 20 years. The recording of position data becomes easy and huge amounts of mobile data are collected. Moving objects databases represent time-dependent objects and support queries with spatial and temporal constraints. In this paper we provide the vision of a multi-model and intelligent moving objects database. The goal is to enhance the data management of moving objects by providing extensive data models for different applications and fusing artificial intelligence techniques. Toward this goal, we propose how to develop corresponding modules and integrate them into the system to achieve the next-generation moving objects database.
OriginalsprogEngelsk
TitelProceedings of the 16th International Symposium on Spatial and Temporal Databases, SSTD 2019
RedaktørerWalid G. Aref, Michela Bertolotto, Panagiotis Bouros, Christian S. Jensen, Ahmed Mahmood, Kjetil Nørvåg, Dimitris Sacharidis, Mohamed Sarwat
Antal sider4
Udgivelses stedNew York
ForlagAssociation for Computing Machinery
Publikationsdato2019
Sider222-225
ISBN (Trykt)978-1-4503-6280-1
DOI
StatusUdgivet - 2019
Udgivet eksterntJa
Begivenhed16th International Symposium on Spatial and Temporal Databases - Vienna, Østrig
Varighed: 19 aug. 201921 aug. 2019
http://sstd2019.org/

Konference

Konference16th International Symposium on Spatial and Temporal Databases
LandØstrig
ByVienna
Periode19/08/201921/08/2019
Internetadresse

Citer dette

Xu, J., Lu, H., & Güting, R. H. (2019). Understanding human mobility: A multi-modal and intelligent moving objects database. I W. G. Aref, M. Bertolotto, P. Bouros, C. S. Jensen, A. Mahmood, K. Nørvåg, D. Sacharidis, & M. Sarwat (red.), Proceedings of the 16th International Symposium on Spatial and Temporal Databases, SSTD 2019 (s. 222-225). Association for Computing Machinery. https://doi.org/10.1145/3340964.3340975