A system to query historical traffic events collected by Waze

• Marcos Vinicius Pontarolo Federal University of Parana (UFPR)
• Murilo Ferreira Federal University of Parana (UFPR)
• Rebeca Schroeder Santa Catarina State University (UDESC)
• Carmem S. Hara Federal University of Parana (UFPR)

DOI: https://doi.org/10.5753/sbbd_estendido.2022.21845

Abstract

This paper presents MIDET-IU (Method for Indexing Traffic Events - User Interface), a system that supports queries on traffic events collected by the Waze application. The implementation of the system uses the querying mechanism and storage model from MIDET, which has been proposed in SBBD 2021. The model is based on a grid spatial partitioning over an area of interest, generating geographic cells (GCs) of fixed size. Traffic events that occur in the same GC are stored together aiming at obtaining good performance in spatial queries. In this demo, Waze data from the city of Joinville is used. A graphical interface allows the user to select a region of interest, a time interval, as well as the types of events to be presented in the query result.

Keywords: Database engines, In-memory data management, Multidimensional and temporal databases, Spatiotemporal databases

References

Chaudhry, N., Yousaf, M. M., and Khan, M. T. (2020). Indexing of real time geospatial data by IoT enabled devices: Opportunities, challenges and design considerations. Journal of Ambient Intelligence and Smart Environments, 12:281-312.

Duarte, M. G., Pontarolo, M. V., Schroeder, R., and Hara, C. S. (2021). MIDET: A method for indexing traffic events. In Anais do XXXVI Simpósio Brasileiro de Banco de Dados, pages 1-12.

Goes, G. V. (2020). Entrada de meios alternativos de tranporte urbano: Histórico e perspectivas futuras. Technical Report 66, Instituto de Pesquisa Econômica Aplicada.

Mahmood, A. R., Punni, S., and Aref, W. G. (2019). Spatio-temporal access methods: a survey (2010-2017). Geoinformatica, 23:1-36.

Patel, J. M. and DeWitt, D. J. (1996). Partition based spatial-merge join. In Proc. of the 1996 ACM SIGMOD international conference on Management of data, pages 259-270.

Tsitsigkos, D., Bouros, P., Mamoulis, N., and Terrovitis, M. (2019). Parallel in-memory evaluation of spatial joins. In Proc. of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pages 516-519.