Abstract
Forest fires may cause considerable damages both in ecosystems and lives. This proposal describes the application of Internet of Things and wireless sensor networks jointly with multi-hop routing through a real time and dynamic monitoring system for forest fire prevention. It is based on gathering and analyzing information related to meteorological conditions, concentrations of polluting gases and oxygen level around particular interesting forest areas. Unusual measurements of these environmental variables may help to prevent wildfire incidents and make their detection more efficient. A forest fire risk controller based on fuzzy logic has been implemented in order to activate environmental risk alerts through a Web service and a mobile application. For this purpose, security mechanisms have been proposed for ensuring integrity and confidentiality in the transmission of measured environmental information. Lamport’s signature and a block cipher algorithm are used to achieve this objective.
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References
Kumar, V., Jain, A., Barwal, P.: Wireless sensor networks: security issues, challenges and solutions. Int. J. Inf. Comput. Technol. (IJICT) 4(8), 859–868 (2014)
Zadeh, L.A.: Fuzzy logic-a personal perspective. Fuzzy Sets Syst. 281, 4–20 (2015)
Rani, S., Ahmed, S.H.: Multi-hop routing in wireless sensor networks: an overview, taxonomy, and research challenges. Springer, Singapore (2015)
Merkle, R.C.: A certified digital signature. In: Conference on the Theory and Application of Cryptology, pp. 218–238. Springer, New York (1989)
Rajkumar, D.M.N., Sruthi, M., Kumar, D.V.V.: IoT based smart system for controlling Co2 emission. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol. 2(2), 284 (2017)
Zhou, Q., Huang, W., Zhang, Y.: Identifying critical success factors in emergency management using a fuzzy dematel method. Saf. Sci. 49(2), 243–252 (2011)
Iliadis, L.S.: A decision support system applying an integrated fuzzy model for long-term forest fire risk estimation. Environ. Model. Softw. 20(5), 613–621 (2005)
Chan, H., Perrig, A., Song, D.: Random key predistribution schemes for sensor networks. In: 2003 Symposium on Security and Privacy, IEEE, pp. 197–213 (2003)
Pathan, A.S.K., Lee, H.W., Hong, C.S.: Security in wireless sensor networks: issues and challenges. In: The 8th International Conference on Advanced Communication Technology, ICACT 2006, vol. 2, p. 6. IEEE (2006)
Mamdani, E.H.: Application of fuzzy logic to approximate reasoning using linguistic synthesis. In: Proceedings of the sixth international symposium on Multiple-valued logic. IEEE Computer Society Press, pp. 196–202 (1976)
Lecina-Diaz, J., Alvarez, A., Retana, J.: Extreme fire severity patterns in topographic, convective and wind-driven historical wildfires of mediterranean pine forests. PloS one 9(1), e85127 (2014)
New record for CO2 concentration in the atmosphere (2017). Accessed 15 Jul 2017. https://elpais.com/elpais/2017/10/30/ciencia/1509359304_347557.html
Kosko, B.: Fuzzy associative memories (1991)
Runkler, T.A.: Selection of appropriate defuzzification methods using application specific properties. IEEE Trans. Fuzzy Syst. 5(1), 72–79 (1997)
Funai, C., Tapparello, C., Heinzelman, W.: Supporting multi-hop device-to-device networks through wifi direct multi-group networking (2015). arXiv preprint. arXiv:1601.00028
Khan, M.A., Salah, K.: IoT security: Review, blockchain solutions, and open challenges. In: Future Generation Computer Systems (2017)
Naor, M., Yung, M.: Universal one-way hash functions and their cryptographic applications. In: Proceedings of the twenty-first annual ACM symposium on Theory of computing. ACM, pp. 33–43 (1989)
Acknowledgements
Research supported by Binter-Sistemas grant and the Spanish Ministry of Economy and Competitiveness, the European FEDER Fund, and the CajaCanarias Foundation, under Projects TEC2014-54110-R, RTC-2014-1648-8, MTM2015- 69138-REDT,TESIS- 2015010106 and DIG02-INSITU.
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Toledo-Castro, J., Santos-González, I., Caballero-Gil, P., Hernández-Goya, C., Rodríguez-Pérez, N., Aguasca-Colomo, R. (2019). Fuzzy-Based Forest Fire Prevention and Detection by Wireless Sensor Networks. In: Graña, M., et al. International Joint Conference SOCO’18-CISIS’18-ICEUTE’18. SOCO’18-CISIS’18-ICEUTE’18 2018. Advances in Intelligent Systems and Computing, vol 771. Springer, Cham. https://doi.org/10.1007/978-3-319-94120-2_46
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DOI: https://doi.org/10.1007/978-3-319-94120-2_46
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