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Authors
# Name
1 Tiago Araújo(tiago.brasileiro@ifpb.edu.br)
2 Damião de Almeida(damiao.almeida@ifpb.edu.br)
3 José Gomes Lopes(jose.lopes@itaipuparquetec.org.br)
4 Hicaro Ferreira(hicaro.brasil@academico.ifpb.edu.br)
5 Ester Trevisan(ester.trevisan@academico.ifpb.edu.br)
6 Igor Sobral(igor.sobral@academico.ifpb.edu.br)
7 Igor de Souza(igor.gusmao@academico.ifpb.edu.br)
8 Carlos Henrique Queiroz(henrique.queiroz@academico.ifpb.edu.br)
9 Ana Lícia Soares(ana.licia@academico.ifpb.edu.br)
10 Anna Beatriz Sales(gomes.anna@academico.ifpb.edu.br)
11 Wanderley Junior(melo.wanderley@ifpb.edu.br)

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Reference
# Reference
1 Arab, S. T., Islam, M. M., Shamsuzzoha, M., Alam, K. F., Muhsin, N., Noguchi, R., & Ahamed, T. (2022). A review of remote sensing applications in agriculture and forestry to establish big data analytics. Remote sensing application: regional perspectives in agriculture and forestry, 1-24.
2 Castro-Basurto, K., Jijon-Veliz, F., Medina, W., & Velasquez, W. (2021). Outside dynamic evacuation routes to escape a wildfire: A prototype app for forest firefighters. Sustainability, 13(13), 7295.
3 Cazzolato, M. T., Avalhais, L. P., Chino, D. Y., Ramos, J. S., de Souza, J. A., Rodrigues-Jr, J. F., & Traina, A. (2017, October). Fismo: A compilation of datasets from emergency situations for fire and smoke analysis. In Brazilian symposium on databases-SBBD (pp. 213-223). Uberlândia, Brazil: SBC.
4 Çolak, E., & Sunar, F. (2020). The importance of ground-truth and crowdsourcing data for the statistical and spatial analyses of the NASA FIRMS active fires in the Mediterranean Turkish forests. Remote Sensing Applications: Society and Environment, 19, 100327.
5 da Silva, S. S., Fearnside, P. M., de Alencastro Graça, P. M. L., Brown, I. F., Alencar, A., & de Melo, A. W. F. (2018). Dynamics of forest fires in the southwestern Amazon. Forest ecology and management, 424, 312-322.
6 Komalapati, N., Yarra, V. C., Kancharla, L. A. V., & Shankar, T. N. (2021, March). Smart fire detection and surveillance system using iot. In 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS) (pp. 1386-1390). IEEE.
7 Maia, J. M., Sousa, V. F. D. O., Lira, E. D., & Lucena, A. M. A. D. (2017). Motivações socioeconômicas para a conservação e exploração sustentável do bioma Caatinga. Desenvolvimento e meio ambiente, 41(1), 295-310.
8 Seifert, M., Kuehnel, S., & Sackmann, S. (2023). Hybrid clouds arising from software as a service adoption: challenges, solutions, and future research directions. ACM Computing Surveys, 55(11), 1-35.
9 Shah, S. A., Seker, D. Z., Hameed, S., & Draheim, D. (2019). The rising role of big data analytics and IoT in disaster management: recent advances, taxonomy and prospects. IEEE Access, 7, 54595-54614.
10 Silva Junior, J. A. D., & Pacheco, A. D. P. (2021). Avaliação de incêndio em ambiente de Caatinga a partir de imagens Landsat-8, índice de vegetação realçado e análise por componentes principais. Ciência Florestal, 31, 417-439.
11 Subburaj, J., Murugan, K., Keerthana, P., & Aalam, S. S. (2024). Catastropheguard: A Guard Against Natural Catastrophes Through Advances in AI and Deep Learning Technologies. In Internet of Things and AI for Natural Disaster Management and Prediction (pp. 28-55). IGI Global.