Capture of variables for early warning of forest fires and their storage for integration into prediction systems through the use of wireless sensor networks

  • Rodrigo Atilio Elgueta Docente / Estudiante de Posgrado
  • Miguel Mendez Garabetti
Keywords: wireless sensor networks, early detection of forest fires, WRF-SFIRE, forest fire behavior prediction, forest fire suppression

Abstract

Natural catastrophes cause great losses and environmental damage. Forest fires are among them. Currently, there are various technologies in order to obtain environmental variables that serve to take actions and reduce their damage, one of the technologies used are wireless sensor networks (Wireless Sensor Networks, or WSN). In this context, the present work aims to plan the deployment of a WSN for the quantification of environmental variables that allow detecting fires. This would make it possible to obtain information about the fires and useful data for their extinction through knowledge of the behavior of a forest fire in progress, helping to make the right decisions in the mitigation plan. For this, it is necessary that the data be used in models for predicting the behavior of forest fires, such as the method known as WRF-SFIRE (Weather and climate simulation model coupled to a fire propagation model). To this end, the proposed network aims, in addition to monitoring fires and feeding input variables to predictive models of fire behavior, to become a useful tool to minimize the damage caused by this type of phenomenon.
Published
2023-07-27
How to Cite
Elgueta, R., & Mendez Garabetti, M. (2023). Capture of variables for early warning of forest fires and their storage for integration into prediction systems through the use of wireless sensor networks. Proceedings of JAIIO, 9(11), 7-10. Retrieved from https://ojs.sadio.org.ar/index.php/JAIIO/article/view/649
Section
SAIC - Simposio Argentino en Ingeniería en Computación