# Data Collection in Areas without Infrastructure Using LoRa Technology and a Quadrotor
## 6 Conclusions  
The proposal shown in this work has, as its primary foundation, the use of a UAV-LoRa network, which has, as its main advantage, a direct LoS between the monitoring station and the UAV (which flies at 30 m high) used to collect information. This guarantees direct visibility between the UAV and the LoRa stations (monitoring stations), allowing data transmission/collection at a distance of up to 690 m in a direct LoS. The instrumentation selected for water quality monitoring meets the sampling time and quality expectations for our implementation; however, in future implementation, the replacement of the sensors should be considered based on the requirements of the final application. During the test, it was identified that the transmission distance is significantly reduced due to environmental conditions and differs from the transceiver's communication range specification. Despite the above, the developed system allows the transfer of information at different speeds, protecting the integrity of the data through regular expressions, and allows the UAV to start the collection of packages again in case corruption is detected in the information. In addition, the algorithms responsible for sensor reading, management, packaging, and data transmission worked correctly. The developed proposal has the advantage of  
Figure 11: Comparison between different topologies. (**a**) 1 gateway (30 m high) and 2 monitoring stations. (**b**) 1 gateway (80 m high) and 2 monitoring stations. (**c**) 2 gateways (40 m high) and 2 monitoring stations. (**d**) 1 gateway (UAV) and 2 monitoring stations. energy savings since it is not required to send information constantly, and the sending of information occurs only when it is detected that the UAV is within a range of at least 400 m. Thus, the data transmission diameter analysis shown in this work is relevant for the development of future applications in which it is required to consider the influence of speed and height on the interruption of communication or alteration during data transmission. The flight autonomy obtained in this work is 8 km, considering its return. However, it can achieve greater autonomy by replacing the rotary-wing UAV with a fixed-wing one, since the latter performs more efficiently for long-distance flights [29]. Thus, this article provides relevant results regarding the parameters present in collection and transmission through UAV-LoRa systems and their effects. As a result, we contribute to the state-of-the-art and describe in detail a proposed methodology to develop the collection system and the steps to follow to replicate our results. In future work, it is proposed that the work developed for use in buoys for monitoring oceanographic variables be implemented and scaled to collect data with a tilt-wing hybrid UAV to achieve more outstanding performance in terms of distance and energy autonomy. Additionally, problems related to the evaluation of the Doppler effect and its effects on the speed of UAVs could be addressed. Also, it is interesting to analyze the behavior of different mobile gateways (marine vehicles or other types of UAVs). Thus, the results shown serve as a basis for the development of future work focused on the generation and implementation of solution proposals focused on UAV-LoRa systems, for example, optimal trajectory planning for UAVs in data collection tasks with sensor nodes [30; 31; 32], energy minimization of UAV-LoRa systems [33; 34], and protocols for efficient data transmission in networks [35]. Addressing the problems above requires the construction and instrumentation of a UAV-LoRa system and knowledge of the parameters that influence data collection (effects of LoS on the signal-to-noise ratio (SNR) and signal intensity), which is addressed in this work.