###### Abstract  
Currently, smart farming is considered an effective solution to enhance the productivity of farms; thereby, it has recently received broad interest from service providers to offer a wide range of applications, from pest identification to asset monitoring. Although the emergence of digital technologies, such as the Internet of Things (IoT) and low-power wide-area networks (LPWANs), has led to significant advances in the smart farming industry, farming operations still need more efficient solutions. On the other hand, the utilization of unmanned aerial vehicles (UAVs), also known as drones, is growing rapidly across many civil application domains. This paper aims to develop a farm monitoring system that incorporates UAV, LPWAN, and IoT technologies to transform the current farm management approach and aid farmers in obtaining actionable data from their farm operations. In this regard, an IoT-based water quality monitoring system was developed because water is an essential aspect in livestock development. Then, based on the Long-Range Wide-Area Network (LoRaWAN(r)) technology, a multi-channel LoRaWAN(r) gateway was developed and integrated into a vertical takeoff and landing drone to convey collected data from the sensors to the cloud for further analysis. In addition, to develop LoRaWAN(r)-based aerial communication, a series of measurements and simulations were performed under different configurations and scenarios. Finally, to enhance the efficiency of aerial-based data collection, the UAV path planning was optimized. Measurement results showed that the maximum achievable LoRa coverage when operating on-air via the drone is about 10 km, and the Longley-Rice irregular terrain model provides the most suitable path loss model for the scenario of large-scale farms, and a multi-channel gateway with a spreading factor of 12 provides the most reliable communication link at a high drone speed (up to 95 km/h). Simulation results showed that the developed system can overcome the coverage limitation of LoRaWAN(r) and it can establish a reliable communication link over large-scale wireless sensor networks. In addition, it was shown that by optimizing flight paths, aerial data collection could be performed in a much shorter time than industrial mission planning (up to four times in our case). unmanned aircraft vehicle (UAV); drone; long range (LoRa); wireless sensor network; Internet of Things (IoT); remote sensing; smart farming; path planning +
Footnote †: journal: Sensors  
0000-0001-9000-0001-9000-90001-9000-90001-90001-90001-90001-90001-90001-90001-90001-90001-90001-90001-90001-9001-9000 significant advances have been made in farm management. Utilizing such technologies becomes even more beneficial and exciting when integrating them with unmanned aerial vehicles (UAVs). Such integration can be utilized to develop advanced livestock and farming monitoring systems. Long Range (LoRa) is an LPWAN communication technology that enables a long-range transmission of data with low power consumption among things such as sensors [1]. Therefore, it can provide a reliable wireless communications link for remote areas with no or poor terrestrial wireless coverage [2] with affordable capital expenditure (CapEx) and operational expenditure (OpEx) [3]. In addition, it can connect sensors to the cloud and provide real-time communication for further data analysis and monitoring [4]. Generally, UAVs (also known as drones) can be categorized into two classes: high-altitude platform (HAP) and low-altitude platform (LAP). HAPs operate at an altitude above 17 km and stay for a long time at that altitude, like aircraft and balloons. On the other hand, LAPs operate at altitudes of tens of meters to a few kilometers and their endurance, size, and weight are less than HAPs, which can offer the advantage of high operating performance, reliability, and low CapEx [5], such as fixed-wing and rotary-wing drones.