# Development of Radio-Frequency Sensor Wake-Up with Unmanned Aerial Vehicles as an Aerial Gateway
## 1 Introduction
It used multiple UAVs to establish a reliable relay network to guarantee the delivery of data produced by the wireless network nodes on the ground to the users. Given these few simulation-based and conceptual efforts, even fewer efforts are found that physically realized a UAV-based sensing network system. In a recent effort, the authors developed a WSN using a fixed-wing UAV as the aerial gateway for marine data collection [28]. In our recent effort, we further investigated the interference between the WiFi-based video transmission link and the ZigBee-based ground-data transmission links [25]. The use of flying single or multiple UAVs, either as a mobile sensor node or a data sink, triggers the need to optimize network efficiency between sensors and sinks. Energy cost is an inevitable constraint, considering that both the UAVs and ground sensors are, to date, usually battery-powered. An opportunistic network is the emerging technology that solves such an optimization problem. In [29], protocols were proposed to better exploit the durations of high-quality channel conditions. Based on that, authors [30] proposed routing protocols that increase the throughput of large unicast transfers in a multi-hop wireless network. There are also a number of research efforts on optimizing resource and performance in wireless sensor networks. In [31], the authors considered a different scenario where the paths from message sources to their destinations do not always exist. Then the authors analyzed protocols that alleviated the problem of chronically disconnected paths by having a node store the packet, carrying it until meeting another relay node and forwarding the packet to the other relay node. In a more recent effort, researchers also developed middleware that implemented the opportunistic network into mobile social networks [32]. It is noted that for general opportunistic networking systems (without using a UAV as a gateway node), different protocols are proposed, including the flooding protocol and the history-based protocol (e.g., [33; 34]). Another possible approach at a higher level is to apply the software defined network (SDN) concept into an opportunistic system. In a recent work [35], the author proposed an energy efficient SDN framework for wireline-wireless cross networks, which can potentially be helpful for large-scale deployment. Last, it is stated that these optimization or software-based schemes mostly focus on designing improved communication protocols by assuming that either the UAVs or the sensors are not constrained by the battery-based power. To illustrate such energy constraint, Figure 2 illustrates a conceptual AG-WSN, where (besides being the imaging and computing hub) the UAV is designed as a robotic vehicle that flies to ground sensors at tactical locations. This operational mode, and furthermore, the possible loss of sensors, sensor malfunctions, and out-of-range communication, renders the underlying network as opportunistic, which affects energy consumption in the UAV and sensors. In Figure 2a four subnets are shown, which indicate four physically isolated sensor networks in the fields, except that the UAV can fly to each subnet to execute opportunistic sensing. Figure 2b indicates the idealized situation where sensor failure (or other malfunctions) and energy consumption does not need to be considered. Hence, assuming each node \(\mathrm{N_{mn}}\) can communicate with its neighboring nodes \(\mathrm{N_{m\pm 1,m\pm 1}}\) through a wireless connection, when the UAV flies into this sub-network some of the nodes are in the communication range of the UAV (within the red dashed-line circle), while some are not. The UAV will pick one of the nodes in the range as a relay node, herein which is \(\mathrm{N_{21}}\), and collect data from any other node in this subnet. Figure 2c illustrates when sensor failure happens; the UAV can move from one disconnected zone to another one.