Pluv-Web: A Data-Oriented Scientific Gateway for Rain Analysis and Monitoring in the City of Niterói
Abstract
A fundamental task to be carried out by the government is planning to prevent problems caused by weather events (e.g., landslides, floods, etc.). This planning can be supported by solutions involving areas of Computer Science such as Data Management, Visualization, and Machine Learning. In this demonstration article, we present the scientific gateway Pluv-Web to support the analysis and monitoring of rainfall and weather events in the city of Niterói. Pluv-Web allows for interactive visualization of historical and real-time rainfall data, as well as the identification of floods through camera images and the generation of optimized routes for handling incidents generated by weather events.
Keywords:
Data visualization, Rainfall monitoring
References
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de Souza, C. V. F., da Cunha Luz Barcellos, P., Crissaff, L., Cataldi, M., Miranda, F., and Lage, M. (2022). Visualizing simulation ensembles of extreme weather events. Computers & Graphics, 104:162–172.
Diehl, A., Pelorosso, L., Delrieux, C., Saulo, C., Ruiz, J., Gröller, M. E., and Bruckner, S. (2015). Visual analysis of spatio-temporal data: Applications in weather forecasting. In Computer Graphics Forum, number 3 in 34, pages 381–390.
Harby, A. A. and Zulkernine, F. H. (2022). From data warehouse to lakehouse: A comparative review. In Tsumoto, S., Ohsawa, Y., Chen, L., den Poel, D. V., Hu, X., Motomura, Y., Takagi, T., Wu, L., Xie, Y., Abe, A., and Raghavan, V., editors, IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, December 17-20, 2022, pages 389–395. IEEE.
Lage, M., Victorino, F., Moreira, G., Sá, B., Paes, A., Amorim, A., Cholodoysky, D., Pereira, K., Assis, G., Poustka, A., Alves, P., Nemirovsky, A., Moura, N., and de Oliveira, D. (2022). @weathernit: uma plataforma orientada a dados para monitoramento de chuvas e ocorrências de eventos climáticos. In Anais Estendidos do XXXVII Simpósio Brasileiro de Bancos de Dados, pages 209–214, Búzios, RJ. SBC.
Lu, G. Y. and Wong, D. W. (2008). An adaptive inverse-distance weighting spatial interpolation technique. Computers & geosciences, 34(9):1044–1055.
Pierce, M. E., Miller, M. A., Brookes, E. H., Wong, M., Liu, Y., Afgan, E., Gesing, S., Dahan, M., Marru, S., and Walker, T. (2018). Towards a science gateway reference architecture. In Atkinson, M. P. and Gesing, S., editors, Proceedings of the 10th International Workshop on Science Gateways, Edinburgh, Scotland, UK, 13-15 June, 2018, volume 2357 of CEUR Workshop Proceedings. CEUR-WS.org.
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., et al. (2022). Tackling climate change with machine learning. ACM Comput. Surv., 55(2).
Thorndahl, S. and Willems, P. (2008). Probabilistic modeling of overflow, surcharge and flooding in urban drainage using the first-order reliability method and parameterization of local rain series. Water Research, 42(1):455–466.
Published
2023-09-25
How to Cite
VICTORINO, Fabio et al.
Pluv-Web: A Data-Oriented Scientific Gateway for Rain Analysis and Monitoring in the City of Niterói. In: DEMOS AND APPLICATIONS - BRAZILIAN SYMPOSIUM ON DATABASES (SBBD), 38. , 2023, Belo Horizonte/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 108-113.
DOI: https://doi.org/10.5753/sbbd_estendido.2023.233224.
