After the occurrence of the cellular networks fifth generation auction (5G), carried out by the
National Telecommunications Agency (ANATEL), carriers started to implement the technology
on Brazilian soil and it is expected that a massive amount of smart devices will become capable to
connect to 5G networks, promoting the advancement and improvement of internet of things (IoT).
However, Narrowband-IoT (NB-IoT) technology, used by 5G for IoT applications, is still not
enough to meet all user requirements, with that in mind, LoRa technology emerges as an auxiliary
to meet the requirements of users. Given this scenario, this work aims to analyze the behavior
of the LoRa signal in a suburban and densely wooded environment. For this, measurement
campaigns are carried out at the Federal University of Pará (UFPA) and from the collected data a
neural network model capable of reproducing this behavior is proposed. The standard model is
compared to baseline models and proves to be superior in the downlink and uplink scenarios
with a minimum RMSE error of 1,6623 dB for the first and 1,3891 dB for the second
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