Defining Routes for Emergency Response from Climate Events: a Data-oriented Approach

Authors

Keywords:

Emergency Events, Emergency Response, E-events, Routing, Optimization, Smart Cities

Abstract

Extreme Events have recently become a topic of interest mainly due to the impacts of climate change worldwide over the last years. Such events commonly have a severe impact on major cities. Especially in Brazilian cities, the combination of climate change and unplanned urban growth on steep slopes has led to floods and landslides that killed thousands of people over the past decade. Once an extreme event impacts a city, a series of emergency events (henceforth named e-events) are registered by the citizens (by calling the local emergency telephone number). These e-events may vary from a small flood to a large-scale landslide. Thus, it is a top priority for governments to respond to these e-events as fast and as efficiently as possible. The problem is that the number of e-events is usually larger than the number of people (and vehicles) to respond to them. Another challenge is that these vehicles have to cross an impacted city with major traffic jams. The routes have to consider real-time traffic data to avoid streets with heavy traffic. This article proposes an approach named IRONSTONE, which aims at collecting the topology of the city and real-time traffic data to generate optimized routes for teams to respond to e-events. The proposed approach was evaluated with real scenarios of the city of Niterói and the results are promising.

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Author Biographies

Luis Felipe Oliveira, Universidade Federal Fluminense (UFF), Niteroi

Luis Felipe Oliveira is a master's student at the Institute of Computing at Universidade Federal Fluminense (UFF). He graduated in Engineering from CEFET in 2006 and obtained an M.S. degree in Engineering from UFF (2016). His research interests include optimization problems and machine learning.

Daniel Oliveira, Universidade Federal Fluminense (UFF), Niteroi.

Daniel de Oliveira is an associate professor of computer science at Universidade Federal Fluminense in Niterói, Brazil since 2013. His current research interests include scientific workflows, provenance, cloud computing, data scalable and intensive computing, high-performance computing, and distributed and parallel databases. He serves or served on the program committee of major international and national conferences (VLDB, IPAW, IEEE eScience, SBBD, etc). He has published many technical papers and is a co-author of the book "Data-Intensive Workflow Management For Clouds and Data-Intensive and Scalable Computing Environments'' published by Morgan and Claypool (now Springer) in 2019.

Yuri Frota, Universidade Federal Fluminense (UFF), Niteroi.

Yuri Frota is an associate professor in the Department of Computer Science at Universidade Federal Fluminense, where he has been since 2010. He graduated in Computer Science from UECE (1999), obtained an M.S. in Computer Science from UFC (2002), and a Ph.D. also in Computer Science from UFRJ (2008). He has experience in computer science, focusing on algorithms, and is engaged in the following subjects: combinatorial optimization and integer programming.

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Published

2023-08-18

How to Cite

Oliveira, L. F., Oliveira, D., & Frota, Y. (2023). Defining Routes for Emergency Response from Climate Events: a Data-oriented Approach. IEEE Latin America Transactions, 21(10), 1064–1072. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/8150