Hotspots and Smoke Detection from Forest and Land Fires Using the YOLO Algorithm ( You Only Look Once )
DOI:
https://doi.org/10.58794/jim.v1i1.410Keywords:
YOLO, Deep Learning, Hotspots, Image Processing, Forest FireAbstract
The term forest and land fires is used to refer to unplanned, controlled and unwanted fires that destroy vegetated areas and their ecosystems triggered by natural or human causes . Early detection of hotspots can reduce the risk of wider forest and land fires. The use of the Deep Learning YOLO ( You Only Look Once ) algorithm is carried out to detect fire and also the smoke it produces. This study tested in 3 ways, 1) 1341 after data augmentation (496 original data), 2) 608 after data augmentation (253 original data), and 3) 1790 after data augmentation (746 original data). Detection of fire and smoke objects in the form of design, implementation and testing resulted in the YOLOv4 framework successfully producing high confidence of up to 97% in the second test. Based on the test results in this study, it is known that the image datasets used for training data greatly affect object detection and affect the confidence value. The more diverse the shape of the object from the image datasets, the lower the confidence value obtained.
References
N. A. Ulya, E. A. Waluyo, S. Lestari, and B. T. Premonoi, “Peat Swamp Forest Degradation: Impacts, Affected
Communities and Losses,” E3S Web of Conferences, vol. 68, no. 1, pp. 1–7, 2018, doi:
1051/e3sconf/20186803007.
G. Dieterle, “Sustainable Forest Management in a Changing World: a European Perspective,” Agriculture, vol.
, pp. 83–91, 2009, doi: 10.1007/978-90-481-3301-7
M. D. Flannigan, B. D. Amiro, K. A. Logan, B. J. Stocks, and B. M. Wotton, “Forest fires and climate change in
the 21ST century,” Mitig Adapt Strateg Glob Chang, vol. 11, no. 4, pp. 847–859, 2006, doi: 10.1007/s11027-
-9020-7.
B. Langmann, B. Duncan, C. Textor, J. Trentmann, and G. R. van der Werf, “Vegetation fire emissions and their
impact on air pollution and climate,” Atmos Environ, vol. 43, no. 1, pp. 107–116, 2009, doi:
1016/j.atmosenv.2008.09.047.
B. Berwyn, “How Wildfires Can Affect Climate Change (and Vice Versa),” INSIDECLIMATE NEWS, 2018.
fire-management-black-carbon-co2 (accessed Jan. 15, 2020).
Z. A. Holden et al., “Decreasing fire season precipitation increased recent western US forest wildfire activity,”
Proc Natl Acad Sci U S A, vol. 115, no. 36, pp. E8349–E8357, 2018, doi: 10.1073/pnas.1802316115.
G. Eftychidis, “Forest and Range Fires,” in Encyclopedia of Natural Hazards, P. T. Bobrowsky, Ed. Dordrecht:
Springer Netherlands, 2013, pp. 346–359. doi: 10.1007/978-1-4020-4399-4_146.
C. M. Countryman, “The fire environment concept,” p. 15, 1972.
NWCG, “Fire,” NWCG Glossary Of Wildland Fire, PMS 205. https://www.nwcg.gov/term/glossary/fire
(accessed Apr. 01, 2020).
B. L. Estes, E. E. Knapp, C. N. Skinner, J. D. Miller, and H. K. Preisler, “Factors influencing fire severity under
moderate burning conditions in the Klamath Mountains, northern California, USA,” Ecosphere, vol. 8, no. 5,
, doi: 10.1002/ecs2.1794.
L. Syaufina, Kebakaran hutan dan lahan di Indonesia: perilaku api, penyebab, dan dampak kebakaran.
Bayumedia Pub., 2008.
M. Unik and Sri Nadriati, “Overview: Random Forest Algorithm for PM2.5 Estimation Based on Remote
Sensing,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 3, no. 3, pp. 422–430, Dec.
, doi: 10.37859/coscitech.v3i3.4380.
M. L. Nazilly, B. Rahmat, and E. Y. Puspaningrum, “IMPLEMENTASI ALGORITMA YOLO ( YOU ONLY
LOOK,” Jurnal Informatika dan Sistem Informasi, vol. 1, no. 1, pp. 81–91, 2020.
J. S. D. R. G. A. F. Redmon, “(YOLO) You Only Look Once,” Cvpr, 2016, doi: 10.1109/CVPR.2016.91.
K. Gunadi, E. Setyati, and J. S. Surabaya, “Deteksi Helm pada Pengguna Sepeda Motor dengan Metode
Convolutional Neural Network,” Jurnal Infra, vol. 8, no. 1, pp. 295–301, 2020.
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