| dc.creator | Varela, Noel | |
| dc.creator | Díaz-Martinez, Jorge L | |
| dc.creator | Ospino, Adalberto | |
| dc.creator | Lizardo Zelaya, Nelson Alberto | |
| dc.date | 2021-01-04T21:15:02Z | |
| dc.date | 2021-01-04T21:15:02Z | |
| dc.date | 2020 | |
| dc.date.accessioned | 2023-10-03T20:09:53Z | |
| dc.date.available | 2023-10-03T20:09:53Z | |
| dc.identifier | 1877-0509 | |
| dc.identifier | https://hdl.handle.net/11323/7652 | |
| dc.identifier | https://doi.org/10.1016/j.procs.2020.07.061 | |
| dc.identifier | Corporación Universidad de la Costa | |
| dc.identifier | REDICUC - Repositorio CUC | |
| dc.identifier | https://repositorio.cuc.edu.co/ | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/9174663 | |
| dc.description | Some 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. | |
| dc.format | application/pdf | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | Corporación Universidad de la Costa | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [6]Biswas, P., & Samanta, T. (2020). True Event-Driven and Fault-Tolerant Routing in Wireless Sensor Network. Wireless Personal
Communications, 1-23. | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [10] Hariyawan, M. Y., Gunawan, A., & Putra, E. H. (2013). Wireless sensor network for forest fire detection. Telkomnika, 11(3), 563. | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [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. | |
| dc.relation | [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_71 | |
| dc.rights | CC0 1.0 Universal | |
| dc.rights | http://creativecommons.org/publicdomain/zero/1.0/ | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights | http://purl.org/coar/access_right/c_abf2 | |
| dc.source | Procedia Computer Science | |
| dc.source | https://www.sciencedirect.com/science/article/pii/S1877050920317427 | |
| dc.subject | Data analysis | |
| dc.subject | Wireless sensor network | |
| dc.subject | Forest fire detection | |
| dc.title | Wireless sensor network for forest fire detection | |
| dc.type | Artículo de revista | |
| dc.type | http://purl.org/coar/resource_type/c_6501 | |
| dc.type | Text | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
| dc.type | http://purl.org/redcol/resource_type/ART | |
| dc.type | info:eu-repo/semantics/acceptedVersion | |
| dc.type | http://purl.org/coar/version/c_ab4af688f83e57aa | |
