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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Forest Fire Detection System using LoRa Technology

Author 1: Nicoleta Cristina GAITAN
Author 2: Paula HOJBOTA

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2020.0110503

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 5, 2020.

  • Abstract and Keywords
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Abstract: Millions of hectares of forest worldwide are affected annually by fires, which can lead to the loss of human lives, materials, destruction of natural flora and fauna but also can lead to the losses of raw materials. The problem is even greater in forests that are not guarded and do not have communication systems available. Thus, in recent years, have been proposed various systems that use devices based on Internet of Things (IoT) for real-time forest fire detection. In this paper, it is proposed a system capable of quickly detecting forest fires on long wide distance. In the development of this system it is used LoRa (Long Range) technology based on LoRaWAN (Long Range Wide Area Network) protocol which is capable to connect low power devices distributed on large geographical areas being an innovative and great solution for transmissions of a low data transfer rate and a low transmission power on high ranges, and because has a great efficiency.

Keywords: LoRa; real-time; long range wide area network; internet of things

Nicoleta Cristina GAITAN and Paula HOJBOTA, “Forest Fire Detection System using LoRa Technology” International Journal of Advanced Computer Science and Applications(IJACSA), 11(5), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110503

@article{GAITAN2020,
title = {Forest Fire Detection System using LoRa Technology},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110503},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110503},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {5},
author = {Nicoleta Cristina GAITAN and Paula HOJBOTA}
}


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