# Data Collection in Areas without Infrastructure Using LoRa Technology and a Quadrotor
###### Abstract
LoRa communication makes it possible to transmit/collect data over a few kilometers, creating low-power wide-area networks (LPWANs) [7; 8]. LPWANs are built to enable low-power wide-area connectivity at a low bit rate. Popular LPWAN communication systems include LoRa/LoRaWAN, Sigfox, NB-IoT, and Ingenu [9]. Thus, LoRa technology is attractive since it does not require previously established infrastructure, such as a ground base station or satellite connectivity. An example of an application is the monitoring of the seas using buoys, which must be anchored in a specific position, and using wireless communication systems that usually have a limited range of less than 100 m, hence the common use of satellite communications. In cases of short-range communications and data collection on land, a ship must reach the buoys and extract the data. Compared to ground-based LoRa communication systems, UAV-LoRa-based networks have the advantage of direct LoS between UAVs [9]. For the former, the LOS depends on the area where the system is implemented as well as the equipment and instrumentation used for the UAV. For this work, we use a quadrotor capable of flying at a height of 30 m with a speed of 10 m/s, which moves in an area without obstacles. Furthermore, the use of UAVs makes it possible to monitor areas several kilometers wide, allowing their use in hard-to-reach areas with relative ease; this guarantees direct visibility between them and even with some ground-based LoRa stations, allowing users to exchange data over longer ranges than are possible with terrestrial communication [10]. The UAV acts as a LoRa gateway, and within it, the conversion of the LoRa protocol to Message Queue Telemetry Transport (MQTT) is carried out so that a web server can read the collected information [9; 10]. Therefore, an essential factor to consider in the use of UAV-LoRa networks is the operation time of the UAVs, which, in the case of quadrotors, is tens of minutes, which complicates the data collection for long periods since they would require several landings and battery replacements. In this sense, this work aims to study the behavior of a UAV-LoRa network. To do so, we propose, as an application case, the monitoring of variables related to water quality (temperature, turbidity, conductivity, and dissolved oxygen) through monitoring stations (emulating a buoy). Traditionally, buoys collect data from satellite transmitters using radio waves in the ultra-high-frequency (UHF) spectrum. This technology usually uses big and expensive antennas, increasing the prototype's size and, therefore, manufacturing cost [11; 12]. Instead of satellite transmitters, a quadrotor is used to carry out periodic flights and collect the information stored in the stations. Subsequently, the UAV goes to the ground station and uploads the information to the Internet. This is attractive for collecting information from various sensors placed in remote locations, enabled by the fact that the UAV-LoRa network operates at low power [13]. This work will show the methodology used to develop the collection system and the steps to replicate our results quickly, easily, and economically. Thus, the results shown serve as a basis for future developments and enrichment of the state-of-the-art. Additionally, this work shows experimental results focused on the following points:  
* Parameters that influence data collection when using a UAV as a LoRa gateway;
* Effects of LoS on signal-to-noise ratio (SNR) and signal strength. These results are relevant because they show the parameters present in the collection and transmission through UAV-LoRa systems and their effects, about which only a little information is usually found.