## 5 Conclusions  
The objective of this study was to develop a multi-disciplinary methodology capable of maximizing the coverage area and minimizing the number of gateways needed to implement a LoRa network at the Belem Campus, at the Federal University of Para, in a typical highly wooded Amazonian environment, considering the particularities of the scenario studied, such as the fact that it is separated by forests and streams, which causes the signal to suffer strong attenuation.  
Therefore, it is necessary to associate several areas of knowledge as instrumentation for measurements of electromagnetic wave signals to obtain RSSI values in the studied environment. Propagation was essential for developing the fit of the UFPA propagation loss model, performed through GA and multi-objective bio-inspired optimization to establish the maximum coverage with the least number of gateways. Additionally, the simulations were validated through statistical means using the Monte Carlo method.  
Statistical analysis determined that a sensitivity threshold of \(-108\) dBm was adequate to cover the proposed environment, obtaining an estimated radius with the adjusted UFPA model of 668.62 m. The optimal solution found using the EPSO technique for positioning LoRa gateways was to establish three gateways positioned at candidate points 9-13-22, providing 100% coverage for the studied environment. This demonstrates that the proposed methodology can assist in the future planning of IoT networks by reducing costs  
Figure 13: Optimal gatewayplacement for sensitivity of \(-108\) dBm.  
and possible deployment errors using a suitable propagation loss model for each region to be implemented.  
Finally, in future work, the application will be expanded to analyze the positioning of gateways for the city of Belem and the implementation of other metaheuristic techniques to statistically analyze the best approach for the optimal positioning of gateways for IoT LoRaWAN network planning.  
Conceptualization, H.A.O.C., S.C.B.F., J.P.L.A., F.J.B.B. and G.P.S.C.; Data curation, H.A.O.C., S.C.B.F., J.P.L.A., F.J.B.B., F.S.F. and G.P.S.C.; Formal analysis, H.A.O.C., S.C.B.F., J.P.L.A, M.E.L.T. and A.A.N.; Funding acquisition F.J.B.B., M.E.L.T., A.A.N. and G.P.S.C.; Investigation H.A.O.C., S.C.B.F., J.P.L.A. and F.J.B.B.; Methodology, H.A.O.C., S.C.B.F., J.P.L.A., M.C.A.N., F.J.B.B. and F.S.F.; Project administration, M.C.A.N., M.E.L.T., A.A.N. and G.P.S.C.; Resources, M.C.A.N., M.E.L.T., A.A.N. and G.P.S.C.; Software, H.A.O.C., S.C.B.F., J.P.L.A. and F.S.F.; Supervision, M.C.A.N., M.E.L.T., A.A.N. and G.P.S.C.; Validation, H.A.O.C., S.C.B.F., J.P.L.A., F.J.B.B., and F.S.F.; Visualization, H.A.O.C., S.C.B.F., J.P.L.A., F.J.B.B. and F.S.F; Writing--original draft, H.A.O.C., S.C.B.F., J.P.L.A., F.J.B.B. and F.S.F; Writing--review and editing, H.A.O.C., S.C.B.F., J.P.L.A., F.J.B.B. and F.S.F. All authors have read and agreed to the published version of the manuscript.  
The authors would like to thank LCT members, PROPESP/UFPA, CAPES, CNPq, National Institute of Science and Technology--Wireless (INCT-CSF), and Norte Energia S.A. through the project R&D ANEEL 07427-0319/2019 (Intelligent Systems for Efficient Management of Multimodal Electric Mobility) for the support given to the research.  
Not applicable.  
The authors reserve the right to not disclose the private data set used in this study.  
The authors declare no conflict of interest.