TY - GEN
T1 - UrbanGen
T2 - 23rd IEEE International Conference on Mobile Data Management, MDM 2022
AU - Sun, Yunkai
AU - Nielsen, Nichlas
AU - Xie, Xike
AU - Pedersen, Torben Bach
AU - Simonsen, Ulf
AU - Lu, Hua
AU - Ainciburu, Maite
PY - 2022
Y1 - 2022
N2 - The prevalence of mobile devices and positioning techniques has enabled so-called traffic-aware urban computing. In urban daily life, people's activities consist of indoor and outdoor parts whose transitions have important impacts on traffic behavior. For example, outdoor traffic events (e.g., jams) can be triggered by indoor events (e.g., the ending of exhibitions, tour-naments, or working hours). In turn, indoor events (e.g., subway jams) can also be affected by outdoor events (e.g., snowy weather or other bad outdoor traffic conditions). For a wide range of applications like traffic monitoring and emergency response, it is thus interesting to develop techniques for analyzing data in an integrated indoor and outdoor space. Since real datasets of this kind are still scarce and small, a suitable data generator is needed for both functional and scalability testing. In this work, we present UrbanGen, which follows the constraints of road networks for the outdoor space and the constraints of topologies for the indoor space. The system provides the functionalities including: 1) integrating a model of indoor topologies with the state-of-art road networks; 2) parameterizing the movement of objects in the integrated model; 3) serializing and visualizing the generated trajectories.
AB - The prevalence of mobile devices and positioning techniques has enabled so-called traffic-aware urban computing. In urban daily life, people's activities consist of indoor and outdoor parts whose transitions have important impacts on traffic behavior. For example, outdoor traffic events (e.g., jams) can be triggered by indoor events (e.g., the ending of exhibitions, tour-naments, or working hours). In turn, indoor events (e.g., subway jams) can also be affected by outdoor events (e.g., snowy weather or other bad outdoor traffic conditions). For a wide range of applications like traffic monitoring and emergency response, it is thus interesting to develop techniques for analyzing data in an integrated indoor and outdoor space. Since real datasets of this kind are still scarce and small, a suitable data generator is needed for both functional and scalability testing. In this work, we present UrbanGen, which follows the constraints of road networks for the outdoor space and the constraints of topologies for the indoor space. The system provides the functionalities including: 1) integrating a model of indoor topologies with the state-of-art road networks; 2) parameterizing the movement of objects in the integrated model; 3) serializing and visualizing the generated trajectories.
KW - in- and outdoor spaces
KW - moving objects
KW - trajectories
KW - visualization
KW - in- and outdoor spaces
KW - moving objects
U2 - 10.1109/MDM55031.2022.00057
DO - 10.1109/MDM55031.2022.00057
M3 - Article in proceedings
AN - SCOPUS:85137584707
T3 - Proceedings - IEEE International Conference on Mobile Data Management
SP - 270
EP - 273
BT - Proceedings - 2022 23rd IEEE International Conference on Mobile Data Management, MDM 2022
PB - IEEE Computer Society Press
Y2 - 6 June 2022 through 9 June 2022
ER -