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dc.contributor.authorVarela, Noelspa
dc.contributor.authorDíaz-Martinez, Jorge Lspa
dc.contributor.authorOspino, Adalbertospa
dc.contributor.authorLizardo Zelaya, Nelson Albertospa
dc.date.accessioned2021-01-04T21:15:02Z
dc.date.available2021-01-04T21:15:02Z
dc.date.issued2020
dc.identifier.issn1877-0509spa
dc.identifier.urihttps://hdl.handle.net/11323/7652spa
dc.description.abstractSome methods for fire detection include monitoring from watch towers and the use of satellite images [1] [2]. Unfortunately, these are not efficient due to several reasons, such as high infrastructure costs (sophisticated equipment), the fact that they require a large number of trained personnel and that they make real-time monitoring difficult, since when the phenomenon is detected, its speed of propagation has produced uncontrollable levels of damage. This paper proposes a method for detecting forest fires, using a network of wireless sensors and information fusion methods.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.publisherCorporación Universidad de la Costaspa
dc.rightsCC0 1.0 Universalspa
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/spa
dc.sourceProcedia Computer Sciencespa
dc.subjectData analysisspa
dc.subjectWireless sensor networkspa
dc.subjectForest fire detectionspa
dc.titleWireless sensor network for forest fire detectionspa
dc.typeArtículo de revistaspa
dc.source.urlhttps://www.sciencedirect.com/science/article/pii/S1877050920317427spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1016/j.procs.2020.07.061spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.relation.references[1] Noureddine, H., & Bouabdellah, K. (2020). Field Experiment Testbed for Forest Fire Detection using Wireless Multimedia Sensor Network. International Journal of Sensors Wireless Communications and Control, 10(1), 3-14.spa
dc.relation.references[2] Grover, K., Kahali, D., Verma, S., & Subramanian, B. (2020). WSN-Based System for Forest Fire Detection and Mitigation. In Emerging Technologies for Agriculture and Environment (pp. 249-260). Springer, Singapore.spa
dc.relation.references[3] Chauhan, A., Semwal, S., & Chawhan, R. (2013, December). Artificial neural network-based forest fire detection system using wireless sensor network. In 2013 Annual IEEE India Conference (INDICON) (pp. 1-6). IEEE.spa
dc.relation.references[4] Ghugar, U., & Pradhan, J. (2020). ML-IDS: MAC Layer Trust-Based Intrusion Detection System for Wireless Sensor Networks. In Computational Intelligence in Data Mining (pp. 427-434). Springer, Singapore.spa
dc.relation.references[5]Nugroho, A. A., Iwan, I., Azizah, K. I. N., & Raswa, F. H. (2019). Peatland Forest Fire Prevention Using Wireless Sensor Network Based on Naïve Bayes Classifier. KnE Social Sciences, 20-34.spa
dc.relation.references[6]Biswas, P., & Samanta, T. (2020). True Event-Driven and Fault-Tolerant Routing in Wireless Sensor Network. Wireless Personal Communications, 1-23.spa
dc.relation.references[7] Dubey, V., Kumar, P., & Chauhan, N. (2019). Forest fire detection system using IoT and artificial neural network. In International Conference on Innovative Computing and Communications (pp. 323-337). Springer, Singapore.spa
dc.relation.references[8] Zhang, J., Li, W., Yin, Z., Liu, S., & Guo, X. (2009, May). Forest fire detection system based on wireless sensor network. In 2009 4th IEEE conference on industrial electronics and applications (pp. 520-523). IEEE.spa
dc.relation.references[9] Aliady, W. A., & Al-Ahmadi, S. A. (2019). Energy Preserving Secure Measure Against Wormhole Attack in Wireless Sensor Networks. IEEE Access, 7, 84132-84141.spa
dc.relation.references[10] Hariyawan, M. Y., Gunawan, A., & Putra, E. H. (2013). Wireless sensor network for forest fire detection. Telkomnika, 11(3), 563.spa
dc.relation.references[11] Mohapatra, S., & Khilar, P. M. (2020). Fault Diagnosis in Wireless Sensor Network Using Self/Non-self-Discrimination Principle. In Progress in Computing, Analytics and Networking (pp. 161-168). Springer, Singapore.spa
dc.relation.references[12] Saidi, H., Gretete, D., & Addaim, A. (2020). Game Theory for Wireless Sensor Network Security. In Fourth International Congress on Information and Communication Technology (pp. 259-269). Springer, Singapore.spa
dc.relation.references[13] Aliady, W. A., & Al-Ahmadi, S. A. (2019). Energy Preserving Secure Measure Against Wormhole Attack in Wireless Sensor Networks. IEEE Access, 7, 84132-84141.spa
dc.relation.references[14] Viloria, A., Hernandez-P, H., Lezama, O. B. P., & Orozco, V. D. (2020). Electric Consumption Pattern from Big Data (pp. 479–485). https://doi.org/10.1007/978-981-15-3125-5_47.spa
dc.relation.references[15] Sanchez, L., Vásquez, C., Viloria, A., & Cmeza-Estrada. (2018). Conglomerates of Latin American countries and public policies for the sustainable development of the electric power generation sector. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10943 LNCS, pp. 759–766). Springer Verlag. https://doi.org/10.1007/978-3- 319-93803-5_71spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


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