CePEX - São Paulo Data integration Center for Monitoring Extreme Events

• Grant number: 25/07171-2
• Support Opportunities: Research Grants - Science Centers for Development
• Start date: November 01, 2025
• End date: October 31, 2030
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: João Paulo Papa
• Grantee: João Paulo Papa
• Host Institution: INST ESTUDOS AVANCADOS MAR PROF DR PETER CHRISTIAN HACKSPACHER/UNESP
• Principal investigators: Ana Maria Heuminski de Avila ; Daniel Carlos Guimarães Pedronette ; Enner Herenio de Alcântara ; Erivaldo Antonio da Silva ; Regina Célia dos Santos Alvalá ; Rogério Galante Negri
• Associated researchers: Antonio Carlos Varela Saraiva ; Carlos de Oliveira Affonso ; Carlos Frederico de Angelis ; David Montenegro Lapola ; Demerval Soares Moreira ; Douglas Rodrigues ; EDINÉIA APARECIDA DOS SANTOS GALVANIN ; Fábio Augusto Gomes Vieira Reis ; Fernando Luiz de Campos Carvalho ; Gabriela Ramos Hurtado ; Gisele dos Santos Zepka Saraiva ; Guilherme Henrique Barros de Souza ; Guilherme Pina Cardim ; Helber Custódio de Freitas ; Jose Remo Ferreira Brega ; Jurandir Zullo Junior ; Kelton Augusto Pontara da Costa ; Klécia Gili Massi ; Leandro Aparecido Passos Junior ; Luana Albertani Pampuch Bortolozo ; Lucilia do Carmo Giordano ; Luiz Felippe Gozzo ; Marcos Roberto de Mattos Fontes ; Maria de Souza Custodio ; Maria Rita Donalisio Cordeiro ; Marilaine Colnago ; Maurício Araújo Dias ; Murilo Cesar Lucas ; Ney Lemke ; Patrícia Soares Santiago ; Priscila Pereira Coltri ; Priscilla Teles de Oliveira ; Renata Ribeiro Do Valle Gonçalves ; Roberto Donato da Silva Júnior ; Roberto Luiz Do Carmo ; Roberto Vicente Calheiros ; Rodrigo Fiorentini ; Simone das Graças Domingues Prado ; Tatiana Sussel Gonçalves Mendes ; VANDERLEI BRAGA ; Vera Lucia Messias Fialho Capellini ; Wallace Correa de Oliveira Casaca

Abstract

The proposal presents CePEX - São Paulo Center for Data Integration for Monitoring Extreme Events, which aims to develop integrated research on monitoring, forecasting, and decision support for disaster events in São Paulo. The proposal seeks to use analytical models consolidated in the literature, advanced Artificial Intelligence techniques, and multiple data sources, which include a diverse network of meteorological radars installed in different strategic regions of the state, in turn, complemented by an extensive network of data collection platforms, in addition to a network of lightning sensors to be installed in the region. These data sources will be complemented by images made available in public remote sensing databases. Initially, the project will address the organization and availability of these data by creating a computational architecture that allows efficient integration and recovery of information, considering its different spatial and temporal resolutions and natures/formats. Once the integrated database is consolidated, the project will apply physical concepts and advanced Artificial Intelligence methodologies, especially deep learning techniques, using convolutional and recurrent neural networks to develop predictive models capable of anticipating and mapping hydrological extremes, landslides, floods, and forest fires. As an essential part of the project, information visualization techniques will be researched and applied, facilitating the interpretation of the results obtained by the models. These results will be available through an integrated spatial visualization and analysis platform, which will allow queries, overlay of data layers, and download of specific information by analysts and public managers. This platform is expected to evolve progressively throughout the project, gradually incorporating results and functionalities, enhancing its contribution to public management and mitigation of environmental risks. (AU)