# Development of Radio-Frequency Sensor Wake-Up with Unmanned Aerial Vehicles as an Aerial Gateway
## 1 Introduction
In recent years, as UAV technology has penetrated into many industrial sectors, small UAVs have enabled remote sensing that is low-cost, highly mobile, and is being treated as an emerging tool that expands the SHM technology inventory [22; 23; 24]. This further corroborates the necessity of combining WSNs and UAV-based remote sensing technologies. Reflecting on the trends in PA, SHM, and other similar geospatial-scale monitoring applications for critical missions, we have proposed and developed a prototype to realize a wireless aerial imaging and ground-sensing network; in short, it is termed the aerial-ground wireless sensing network (AG-WSN) [25]. First, this AG-WSN features the use of one or multiple UAVs as the primary imaging nodes, which will serve as the gateway to the ground sensors; second, the wireless sensing units are deployed (by UAV delivering or manual installation) in the ground (or ground structures) over a geospatially large or a spatially complex space. The combination of low altitude imaging and ground sensing provides the power of fusing remotely captured images with a high resolution and point-based ground-truth data in the field. The high mobility of the UAV allows it to be deployed  
Figure 1: Conceptual illustrations of the proposed aerial–ground wireless sensing network (AG-WSN) for field monitoring: (**a**) complex 3D field in an urban setting and (**b**) largely 2D terrain field in an agriculture setting. opportunistically according to scheduled tasks or in response to unexpected urgencies (e.g., disasters). Combining the collaborative aerial and ground sensing and the opportunistic operation modes (e.g., a ground node may be only active when the UAV hovers above it and collects data from it), we state that the proposed AG-WSN can potentially provide the most high-fidelity and most flexible sensing solutions to many monitoring problems arising from the need to assess geospatially large and complex built/agriculture environments. In this paper we first address the opportunistic nature of the AG-WSN by reviewing the related UAV-WSN integration efforts and proposing a conceptual operation design, which further motivates the proposition of sensor activation for network energy efficiency. Centering around sensor activation, we propose to develop a sensor wake-up solution. Related work is reviewed that shows the benefits and drawbacks of different wake-up designs and the rationale for choosing an active radio frequency (RF) mechanism. Subsequently, a general out-band RF wake-up mechanism is developed and demonstrated. For a comparative purpose, the infrared wake-up prototype is implemented too. We further conduct a comprehensive study on energy conservation, followed by the conclusions and remarks for this paper. The scholarly contribution in the design of this work is two-fold: first, it provides a realistic design of active RF-based wake-up mechanisms for sensor activation in a novel aerial-ground sensing network (AG-WSN), which bears the goals of rapid prototyping and having a realistic application in urban- or farming-scale monitoring tasks; second, the experimental evaluation reveals the superb effectiveness of the proposed wake-up method and its appropriateness for the AG-WSN system. The technical contribution in the experimentation of this work also includes (1) the use of a digital imaging approach to measure the wake-up time delay and (2) the resulting time-dependent rates of the battery-based power consumption using three different wake-up methods. Unmanned Aerial Vehicle Wireless Sensing Network (UAV-WSN) Integration, Opportunistic Sensing, and Research Needs  
To our best knowledge, there were only a few efforts that attempted to integrate UAVs with wireless sensor networks. In [26], UAVs were considered as mobile sinks for ground sensor data dissemination. This approach intended to optimize the route from a given sensor node on the ground to a few mobile sinks that move in the area. Authors in [27] presented a different approach that kept the sensor network continually connected.