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Forest Fire Prevention, Detection, and Fighting Based on Fuzzy Logic and Wireless Sensor Networks

Author

Listed:
  • Josué Toledo-Castro
  • Pino Caballero-Gil
  • Nayra Rodríguez-Pérez
  • Iván Santos-González
  • Candelaria Hernández-Goya
  • Ricardo Aguasca-Colomo

Abstract

Huge losses and serious threats to ecosystems are common consequences of forest fires. This work describes a forest fire controller based on fuzzy logic and decision-making methods aiming at enhancing forest fire prevention, detection, and fighting systems. In the proposal, the environmental monitoring of several dynamic risk factors is performed with wireless sensor networks and analysed with the proposed fuzzy-based controller. With respect to this, meteorological variables, polluting gases and the oxygen level are measured in real time to estimate the existence of forest fire risks in the short-term and to detect the recent occurrence of fire outbreaks over different forest areas. Besides, the Analytic Hierarchy Process method is used to determine the level of fire spread, and, when necessary, environmental alerts are sent by a Web service and received by a mobile application. For this purpose, integrity, confidentiality, and authenticity of environmental information and alerts are protected with implementations of Lamport’s authentication scheme, Diffie-Lamport signature, and AES-CBC block cipher.

Suggested Citation

  • Josué Toledo-Castro & Pino Caballero-Gil & Nayra Rodríguez-Pérez & Iván Santos-González & Candelaria Hernández-Goya & Ricardo Aguasca-Colomo, 2018. "Forest Fire Prevention, Detection, and Fighting Based on Fuzzy Logic and Wireless Sensor Networks," Complexity, Hindawi, vol. 2018, pages 1-17, December.
    • Handle: RePEc:hin:complx:1639715
    DOI: 10.1155/2018/1639715
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    References listed on IDEAS

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    1. Zanakis, Stelios H. & Solomon, Anthony & Wishart, Nicole & Dublish, Sandipa, 1998. "Multi-attribute decision making: A simulation comparison of select methods," European Journal of Operational Research, Elsevier, vol. 107(3), pages 507-529, June.
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    1. Krassimir T. Atanassov & Peter Vassilev & Vassia Atanassova & Olympia Roeva & Rosen Iliev & Dafina Zoteva & Veselina Bureva & Deyan Mavrov & Alexander Alexandrov, 2021. "Generalized Net Model of Forest Zone Monitoring by UAVs," Mathematics, MDPI, vol. 9(22), pages 1-10, November.

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