# Development of Radio-Frequency Sensor Wake-Up with Unmanned Aerial Vehicles as an Aerial Gateway
## 1 Introduction  
With advances in autonomous navigation, positioning, and in general robotics technologies, small to miniature-sized unmanned aerial vehicles (UAVs, or colloquially called drones) are witnessing their ever-increasing use in engineering practice. Small UAVs are low-cost, agile, and flexible in imaging payloads as remote sensing platforms when compared with traditional space- or airborne platforms (e.g., satellites or aircrafts) [1]. Today's UAVs have incorporated the latest GPS technology. Many small UAVs, especially the multi-motor ones, can fly following predetermined GPS waypoints. Some advanced drones have been equipped with lost-cost radar or vision sensors, acquiring a minimum level of flying beyond (visual) line-of-sight (BVLOS or BLOS) due to their sense-and-avoid capabilities [2; 3; 4]. This potentially would further render small UAVs an attractive remote sensing platform for numerous different applications. On the other hand, wireless sensing network (WSN) technology has matured in recent years, with applications found in many scientific and engineering projects. Many WSN applications focus on ad-hoc tasks, wherein the local sensors are deployed with a goal of completing the task in a short time. Therefore, the energy consumption is not excessive. However, for deploying WSNs over a geospatially large or spatially complex space with an expected long-term monitoring mission,both WSN implementation and energy efficiency become the primary challenges. One possible application of sensing is in farming land, wherein precision agriculture (PA) practice demands data sensing at different granular (spatial and temporal) scales [5]. Another application scenario is performing structural health monitoring (SHM) for civil structures and lifeline infrastructure systems that are often massive and spatially complex (e.g., urban buildings, long-span bridges, and power transmission lines/towers, etc.). For structures that are critical to society, sensors, and especially WSNs, can be installed in these structures in their lifetimes to achieve'smart structures'. Continuous health monitoring through these WSNs provides stakeholders a basis for ensuring public safety and for decision-making when dealing with unexpected natural or technological disruptions [6]. Taking the two areas of PA and SHM as the application settings (Figure 1) it is asserted that, in both situations, the necessity of combining UAV-based remote sensing and WSNs is straightforward. In PA, the traditional practice relies on sensing data such as space- or airborne imagery for decision-making and management in farming [7; 8; 9]. However, the high cost and the long revisit period of satellite or aerial imagery may prevent applying precision agriculture solutions at any location and time around the world. Images taken by low altitude UAVs give an alternative solution in the emerging precision agriculture practice [10; 11; 12]. In addition, since microelectromechanical systems (MEMS) technology and, particularly, the emerging Internet of Things (IoT) sensing technology have been rapidly improved in recent decades, many researchers have proposed and implemented different ground-based wireless sensor solutions for facilitating precision agriculture [13; 14; 15; 16; 17]. To achieve data fusions and more intelligent and tactical operations in these sensing modalities, integration of UAVs and ground-based WSNs becomes a rational choice. In the arena of SHM, the traditional approach is to deploy wired or wireless sensors to obtain the real-time responses of structures to environmental or hazard-induced vibrations [18; 19; 20; 21]. In reality, however, for structures with slight to moderate damage, such as local cracking and corrosion, visual or remote sensing-based inspection is the most efficient approach to date.