## 2 Related Work  
In this section, we introduce the related work of UAV data collection for environmental monitoring in recent years. The properties of our schemes differing from previous work are given at the end of the section. In some previous studies on data collection using UAV and WSN, the ground nodes were clustered. The researcher introduced a waiting-time-based cluster head with residual energy to ensure the even energy consumption of the head [16]. After the current round of data collection is completed, the next round of cluster head selection is performed. An improved particle swarm optimization algorithm is proposed. Simulation results show that the proposed algorithm is superior to the LEACH algorithm in energy consumption and bit error rate when the UAV travel time is basically the same [17]. The performance gap between them rises with the increase in cluster head nodes. Because of reduced power consumption, the network life can be significantly extended while increasing the amount of data received from the entire network. In [18], the authors proposed a cluster head selection  
Figure 1: Architecture of UAV data collection in the LoRa 2.4 GHz network. framework assisted by UAV, which collects the residual energy of nodes and uses them to select new cluster heads. The framework can reduce the frequency of cluster head selection of damaged nodes and the number of messages damaged by them. The above clustering methods do not consider the influence of the UAV take-off position on flight distance. When the cluster heads are selected, UAV path planning needs to be considered to reduce the flight distance. A geometric algorithm based on Hamiltonian is used to determine the optimal flight path of the UAV for agricultural irrigation [16]. In [19], the authors proposed three improved nearest neighbor (NN) algorithms to enhance the performance of data collection by reducing the tour length. The algorithms do not consider the influence of data transmission time. Once the UAV reaches the edge of the sensor node signal coverage, it will fly to the next node. [PERSON] et al. present the efficient FT-DDNN scheme for the shorter flight paths and faster data delivery with fault tolerant capability, in which once the data is collected from the current node, the UAV changes its direction and moves towards the next nearest node instead of going to the center of the current node [20]. [PERSON] et al. proposed an improved dual-population genetic algorithm for UAV flight path planning, which used an additional population to maintain population diversity of the genetic algorithm [21]. [PERSON] et al. designed a penalizing strategy to adjust the fitness of the GA, without the analytical understanding of their geometry structure in the scenarios with no-fly zones [22]. Regarding the communication between UAV and cluster heads, Zigbee is often considered [23; 24; 25; 26]. [PERSON] et al. designed a telemetry communication system in UAVs using ZigBee protocol [23]. The authors in [27] proposed a UAV-assisted low-consumption time synchronization algorithm for a large-scale WSN. They implemented the algorithm with 30 low-power ZigBee nodes and a UAV on an outdoor highway and an indoor site. Although these studies can be well applied to the UAV application scenarios they describe, as mentioned above, that Zigbee is a short distance communication technology. Therefore, some recent studies have applied LPWAN technologies to UAV communication. LoRa technology is perfect for remote areas without cellular network coverage [28; 29; 30]. [PERSON] et al. designed a LoRa UAV gateway to data collection [30]. The results show performance improvements using LoRa-UAV gateways, compared to traditional fixed LoRa deployments, in terms of link availability and covered areas. [PERSON] et al. developed and tested a technology which shared the location of a UAV using LoRa communication and smartphones. The time, location, speed, and direction data from a UAV can be shared to several people through a smartphone application in real time [31].