INTEGRAÇÃO DO MONITORAMENTO METEOROLÓGICO–PREDIÇÃO–CONDIÇÕES DA ÁGUA EM ÁREAS DE TURISMO DE CONSERVAÇÃO DE CORAIS
DOI:
https://doi.org/10.18623/rvd.v23.n2.3899Palabras clave:
Coastal Weather Prediction, Coral Reef Conservation, Decision Tree, IoT Monitoring, Sustainable Blue EconomyResumen
O sistema de monitoramento de corais foi desenvolvido para acompanhar o crescimento e a taxa de sobrevivência dos corais, integrando previsões meteorológicas e informações em tempo real sobre as condições ambientais marinhas no local de conservação de corais Bahoi Likupang, no Município de Minahasa do Norte. O objetivo é fornecer aos turistas e aos gestores da atração informações sobre condições climáticas e marítimas favoráveis ao plantio de corais. A análise preditiva foi realizada utilizando o algoritmo Decision Tree, que apresentou 85% de acurácia, 0,83 de precisão e 0,87 de recall. Esses resultados demonstram a capacidade do modelo de prever precipitação e identificar padrões de relacionamento entre parâmetros ambientais. Testes de campo mostraram que o sistema IoT é capaz de transmitir dados em tempo real para um painel baseado na web, exibindo temperatura do mar, umidade e previsões meteorológicas. A integração do modelo preditivo com o sistema de monitoramento em tempo real oferece uma função de alerta precoce para possíveis mudanças ambientais que possam ameaçar a saúde dos recifes de corais.
Citas
AHMAD, R.; PUTRA, I. D. N. N.; DARMENDRA, I. P. Y. Pemetaan terumbu karang berbasis citra Unmanned Aerial Vehicle (UAV) dan Satelit Sentinel 2A dengan metode Object Based Image Analysis (OBIA) di perairan Pulau Menjangan Bali. Journal of Marine Research and Technology, v. 7, n. 1, p. 25–33, 2024. Disponível em: https://doi.org/10.24843/JMRT.2024.v07.i01.p05
AMIN, G.; RAHMIATI, F.; ISMAIL, Y.; PRAYOGA, T. Z. Community-based tourism impression self-esteem in rural tourism development. Asia Pacific Journal of Management and Education, v. 6, n. 2, p. 37–45, 2023. Disponível em: https://doi.org/10.32535/apjme.v4i3.1639
APPRILL, A.; GIRDHAR, Y.; MOONEY, T. A.; HANSEL, C. M.; LONG, M. H.; LIU, Y.; GREENE, A. Toward a new era of coral reef monitoring. Environmental Science & Technology, v. 57, n. 13, p. 5117–5124, 2023. Disponível em: https://doi.org/10.1021/acs.est.2c05369
BAI, Y.; XU, Z.; LAN, W.; PENG, X.; DENG, Y.; CHEN, Z.; CHENG, J. Predicting Coastal Water Quality with Machine Learning, a Case Study of Beibu Gulf, China. Water, v. 16, n. 16, 2024. Disponível em: https://doi.org/10.3390/w16162253
BATES, H.; PIERCE, M.; BENTER, A. Real-time environmental monitoring for aquaculture using a LoRaWAN-based IoT sensor network. Sensors, v. 21, n. 23, p. 7963, 2021. Disponível em: https://doi.org/10.3390/s21237963.
BURNS, J. H.; PASCOE, K. H.; KANE, H. H.; NAKAO III, J. W.; PASCOE, M.; PIERUCCI, S. R.; KAPONO, C. Community-based monitoring for rapid assessment of nearshore coral reefs amid disturbances in Teahupo’o, Tahiti. Remote Sensing, v. 16, n. 5, p. 853, 2024. Disponível em: https://doi.org/10.3390/rs16050853
GAMAZO-REAL, J. C.; FERNÁNDEZ, R. T.; ARMAS, A. M. Comparison of edge computing methods in Internet of Things architectures for efficient estimation of indoor environmental parameters with Machine Learning. Engineering Applications of Artificial Intelligence, v. 126, p. 107149, 2023. Disponível em: https://doi.org/10.1016/j.engappai.2023.107149
GUBBI, J.; BUYYA, R.; MARUSIC, S.; PALANISWAMI, M. Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, v. 29, n. 7, p. 1645–1660, 2013. Disponível em: https://doi.org/10.1016/j.future.2013.01.010
HU, S.; XIE, S. P.; SEAGER, R.; CANE, M. A. Spatial and seasonal variations of sea surface temperature threshold for tropical convection. Journal of Climate, v. 36, n. 15, p. 4899–4912, 2023. Disponível em: https://doi.org/10.1175/JCLI-D-22-0545.1
ITZKIN, M.; PALMSTEN, M. L.; BUCKLEY, M. L.; BIRCHLER, J. J.; TORRES-GARCIA, L. M. Developing a decision tree model to forecast runup and assess uncertainty in empirical formulations. Coastal Engineering, v. 195, p. 104641, 2025. Disponível em: https://doi.org/10.1016/j.coastaleng.2024.104641
JUNIANI, A. I.; NUGRAHA, A. T.; SETIAWAN, E.; AMELIA, P.; HANDANDI, Z. Z.; HIDAYANA, E. Enhancing water quality prediction using the decision tree approach with the C4.5 Algorithm. JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science), v. 8, n. 1, p. 17–30, 2025. Disponível em: https://doi.org/10.26905/jeemecs.v8i1.14369
KIM, D.; KIM, E.; KIM, E. Performance of decision-tree-based ensemble classifiers in predicting fog frequency in ungauged areas. Weather and Forecasting, v. 38, n. 11, p. 2379–2393, 2023. Disponível em: https://doi.org/10.1175/WAF-D-23-0024.1
KUSUMA, H. A.; ALFAHMI, M. H.; SUHENDRA, T.; SETYONO, D. E. D. Buoy observasi data parameter oseanografi dan meteorologi di perairan terumbu karang: Desain dan implementasi. Techné: Jurnal Ilmiah Elektroteknika, v. 22, n. 2, p. 259–272, 2023. Disponível em: https://doi.org/10.31358/techne.v22i2.363
LITTLE, C. M.; LIU, G.; DE LA COUR, J. L.; EAKIN, C. M.; MANZELLO, D.; HERON, S. F. Global coral bleaching event detection from satellite monitoring of extreme heat stress. Frontiers in Marine Science, v. 9, p. 883271, 2022. Disponível em: https://doi.org/10.3389/fmars.2022.883271
PIÑEROS, V. J.; REVELES-ESPINOZA, A. M.; MONROY, J. A. From remote sensing to artificial intelligence in coral reef monitoring. Machines, v. 12, n. 10, p. 693, 2024. Disponível em: https://doi.org/10.3390/machines12100693
POQUITA-DU, R. C.; DU, I. P. M.; TODD, P. A. EmerSense: A low-cost multiparameter logger to monitor occurrence and duration of emersion events within intertidal zones. HardwareX, v. 14, e00410, 2023. Disponível em: https://doi.org/10.1016/j.ohx.2023.e00410
PRIHATMANTO, A.; KETAREN, A.; SUKOCO, D. Sustainable marine resource management through adaptive and technology-driven approaches. Journal of Marine Policy and Sustainability, v. 12, n. 1, p. 45–56, 2024. Disponível em: https://doi.org/10.1234/jmps.2024.0012b
RAHMAN, M. M.; SHAFIULLAH, M.; ALAM, M. S.; RAHMAN, M. S.; ALSANAD, M. A.; ISLAM, M. M.; RAHMAN, S. M. Decision tree-based ensemble model for predicting national greenhouse gas emissions in Saudi Arabia. Applied Sciences, v. 13, n. 6, p. 3832, 2023. Disponível em: https://doi.org/10.3390/app13063832
RAZAK, T. B.; BOSTRÖM-EINARSSON, L.; ALISA, C. A. G.; VIDA, R. T.; LAMONT, T. A. Coral reef restoration in Indonesia: A review of policies and projects. Marine Policy, v. 137, p. 104940, 2022. Disponível em: https://doi.org/10.1016/j.marpol.2021.104940
REZK, N. G.; ALSHATHRI, S.; SAYED, A.; EL-DIN HEMDAN, E. EWAIS: An ensemble learning and explainable AI approach for water quality classification toward IoT-enabled systems. Processes, v. 12, n. 12, p. 2771, 2024. Disponível em: https://doi.org/10.3390/pr12122771
TANGIAN, D.; KAMAGI, J.; PONGTULURAN, A. K.; POLII, B. D.; SARAPIL, C. I.; KUMASEH, E. I.; CELA, F. P. House reef farming development model to strengthen marine tourism in North Minahasa Regency. Library Progress International, v. 44, n. 3, p. 26154, 2024. Disponível em: https://doi.org/10.48165/bapas.2024.44.2.1
WALTERS, C. J.; HOLLING, C. S. Large-scale management experiments and learning by doing. Ecology, v. 71, n. 6, p. 2060–2068, 1990. Disponível em: https://doi.org/10.2307/1938620
WILKINSON, C. Status of Coral Reefs of the World: 2008. Global Coral Reef Monitoring Network; Reef and Rainforest Research Centre, 2008.
XU, G.; SHI, Y.; SUN, X.; SHEN, W. Internet of things in marine environment monitoring: A review. Sensors, v. 19, n. 7, p. 1711, 2019. Disponível em: https://doi.org/10.3390/s19071711
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
I (we) submit this article which is original and unpublished, of my (our) own authorship, to the evaluation of the Veredas do Direito Journal, and agree that the related copyrights will become exclusive property of the Journal, being prohibited any partial or total copy in any other part or other printed or online communication vehicle dissociated from the Veredas do Direito Journal, without the necessary and prior authorization that should be requested in writing to Editor in Chief. I (we) also declare that there is no conflict of interest between the articles theme, the author (s) and enterprises, institutions or individuals.
I (we) recognize that the Veredas do Direito Journal is licensed under a CREATIVE COMMONS LICENSE.
Licença Creative Commons Attribution 3.0
