Modelagem, Simulação e Avaliação de Redes LoRaWAN com Dados Empíricos de Floresta Tropical
Resumo
Este trabalho apresenta uma metodologia abrangente para modelagem, validação e simulação de redes LoRaWAN em ambientes de floresta tropical densa. Baseado em medições de campo no Parque Nacional da Serra dos Órgãos, um modelo empírico de propagação foi derivado para cenários estáticos e móveis utilizando uma Regressão de Distância Ortogonal híbrida com restrição de referência (ODR+CI). Os parâmetros extraídos foram integrados ao framework de simulação FLoRaExt. O modelo proposto foi validado estatisticamente via análise de RMSE, mostrando que os erros de simulação permanecem dentro da variabilidade intrínseca do ambiente. Além da validação, o estudo explora uma implementação em larga escala para monitoramento geotécnico de encostas, destacando o papel crítico da densificação da rede e estratégias robustas de Taxa de Dados Adaptativa (ADR) sob condições extremas de propagação.Referências
Aalto University (2025). FLoRa: Framework for LoRa simulations with OMNeT++. Disponível em: [link]. Acesso em: 13 jan. 2026.
Chen, M., Zhao, H., Shi, C., Chen, X., and Niu, D. (2023). Multi-scene lora positioning algorithm based on kalman filter and its implementation on ns-3. Ad Hoc Networks, 141:103097.
Dieng, O. et al. (2020). Comparing path loss models for lorawan in tropical environments. In 2020 IEEE International Conference on Communications.
Ferreira, A., Ortiz, F., Costa, L., Foubert, B., Amadou, I., and Mitton, N. (2020). A study of the lora signal propagation in forest, urban, and suburban environments. Annals of Telecommunications, 75:333–351.
Fraire, J., Madoery, P., Mesbah, M., et al. (2022). Simulating lora-based direct-to-satellite iot networks with florasat. In 2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pages 464–470.
Haxhibeqiri, J., De Poorter, E., Moerman, I., and Hoebeke, J. (2018). A survey of lorawan for iot: From technology to application. Sensors, 18:3995.
Hope Microelectronics (2014). RFM95/96/97/98(W) - Low Power Long Range Transceiver Module V1.0. Available online: [link], Acesso em 13/01/2026.
INET Community (2025). The INET Framework. Disponível em: [link]. Acesso em: 13 jan. 2026.
Lima, W., Lopes, A., Cardoso, C., et al. (2024). Lora technology propagation models for iot network planning in the amazon regions. Sensors, 24:1621.
Linka, H., Rademacher, M., Aliu, O., and Jonas, K. (2018). Path loss models for low-power wide-area networks: Experimental results using LoRa. VDE Verlag.
Marini, R., Mikhaylov, K., Pasolini, G., and Buratti, C. (2021). Lorawansim: A flexible simulator for lorawan networks. Sensors, 21:695.
Masadan, A. et al. (2018). Lora propagation analysis in tropical vegetation. IEEE Access.
Maurya, P., Hazra, A., Kumari, P., Sørensen, T., and Das, S. (2024). A comprehensive survey of data-driven solutions for lorawan: Challenges & future directions. Authorea Preprints.
Mekki, K., Bajic, E., Chaxel, F., and Meyer, F. (2019). A comparative study of lpwan technologies for large-scale iot deployment. ICT Express, 5:1–7.
Oliveira, F. (2025). FLoRaExt: LoRa Simulator. Disponível em: [link]. Acesso em: 13 jan. 2026.
OMNeT++ Community (2025). OMNeT++ Discrete Event Simulator. Disponível em: [link]. Acesso em: 13 jan. 2026.
Petajajarvi, J., Mikhaylov, K., Roivainen, A., Haapola, J., and Pouttu, A. (2015). On the coverage of lorawan deployments: City-wide measurements and analysis. In 2015 International Conference on Wireless Communications and Signal Processing (WCSP), pages 1–5. IEEE.
Ruz-Nieto, A., Egea-Lopez, E., Molina-Garcıa-Pardo, J.-M., and Santa, J. (2023). A 3d simulation framework with ray-tracing propagation for lorawan communication. Internet of Things, 24:100964.
Seye, A., Ngom, B., Gueye, B., and Mansouri, A. (2018). A lorawan propagation model for rural areas. In 2018 IEEE Wireless Communications and Networking Conference (WCNC), pages 1–6. IEEE.
Słabicki, M., Premsankar, G., and Di Francesco, M. (2018). Adaptive configuration of LoRa networks for dense IoT deployments. In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), pages 1–9.
u blox (2011). NEO-6 GPS Modules. u-blox AG.
Veluru Sai, A., Nithya, G., and Rao, S. (2017). A comprehensive survey of electromagnetic propagation models. In Proceedings of the 2017 International Conference on Communication and Signal Processing (ICCSP), pages 1457–1462.
Chen, M., Zhao, H., Shi, C., Chen, X., and Niu, D. (2023). Multi-scene lora positioning algorithm based on kalman filter and its implementation on ns-3. Ad Hoc Networks, 141:103097.
Dieng, O. et al. (2020). Comparing path loss models for lorawan in tropical environments. In 2020 IEEE International Conference on Communications.
Ferreira, A., Ortiz, F., Costa, L., Foubert, B., Amadou, I., and Mitton, N. (2020). A study of the lora signal propagation in forest, urban, and suburban environments. Annals of Telecommunications, 75:333–351.
Fraire, J., Madoery, P., Mesbah, M., et al. (2022). Simulating lora-based direct-to-satellite iot networks with florasat. In 2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pages 464–470.
Haxhibeqiri, J., De Poorter, E., Moerman, I., and Hoebeke, J. (2018). A survey of lorawan for iot: From technology to application. Sensors, 18:3995.
Hope Microelectronics (2014). RFM95/96/97/98(W) - Low Power Long Range Transceiver Module V1.0. Available online: [link], Acesso em 13/01/2026.
INET Community (2025). The INET Framework. Disponível em: [link]. Acesso em: 13 jan. 2026.
Lima, W., Lopes, A., Cardoso, C., et al. (2024). Lora technology propagation models for iot network planning in the amazon regions. Sensors, 24:1621.
Linka, H., Rademacher, M., Aliu, O., and Jonas, K. (2018). Path loss models for low-power wide-area networks: Experimental results using LoRa. VDE Verlag.
Marini, R., Mikhaylov, K., Pasolini, G., and Buratti, C. (2021). Lorawansim: A flexible simulator for lorawan networks. Sensors, 21:695.
Masadan, A. et al. (2018). Lora propagation analysis in tropical vegetation. IEEE Access.
Maurya, P., Hazra, A., Kumari, P., Sørensen, T., and Das, S. (2024). A comprehensive survey of data-driven solutions for lorawan: Challenges & future directions. Authorea Preprints.
Mekki, K., Bajic, E., Chaxel, F., and Meyer, F. (2019). A comparative study of lpwan technologies for large-scale iot deployment. ICT Express, 5:1–7.
Oliveira, F. (2025). FLoRaExt: LoRa Simulator. Disponível em: [link]. Acesso em: 13 jan. 2026.
OMNeT++ Community (2025). OMNeT++ Discrete Event Simulator. Disponível em: [link]. Acesso em: 13 jan. 2026.
Petajajarvi, J., Mikhaylov, K., Roivainen, A., Haapola, J., and Pouttu, A. (2015). On the coverage of lorawan deployments: City-wide measurements and analysis. In 2015 International Conference on Wireless Communications and Signal Processing (WCSP), pages 1–5. IEEE.
Ruz-Nieto, A., Egea-Lopez, E., Molina-Garcıa-Pardo, J.-M., and Santa, J. (2023). A 3d simulation framework with ray-tracing propagation for lorawan communication. Internet of Things, 24:100964.
Seye, A., Ngom, B., Gueye, B., and Mansouri, A. (2018). A lorawan propagation model for rural areas. In 2018 IEEE Wireless Communications and Networking Conference (WCNC), pages 1–6. IEEE.
Słabicki, M., Premsankar, G., and Di Francesco, M. (2018). Adaptive configuration of LoRa networks for dense IoT deployments. In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS), pages 1–9.
u blox (2011). NEO-6 GPS Modules. u-blox AG.
Veluru Sai, A., Nithya, G., and Rao, S. (2017). A comprehensive survey of electromagnetic propagation models. In Proceedings of the 2017 International Conference on Communication and Signal Processing (ICCSP), pages 1457–1462.
Publicado
25/05/2026
Como Citar
SILVA, Fábio O.; ASSIS, Laura S. de; BARROS, Ana Lúcia F. de; HADDAD, Diego B.; HENRIQUES, Felipe da R..
Modelagem, Simulação e Avaliação de Redes LoRaWAN com Dados Empíricos de Floresta Tropical. In: WORKSHOP DE COMPUTAÇÃO URBANA (COURB), 10. , 2026, Praia do Forte/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 169-182.
ISSN 2595-2706.
DOI: https://doi.org/10.5753/courb.2026.24054.
