# Development of Radio-Frequency Sensor Wake-Up with Unmanned Aerial Vehicles as an Aerial Gateway
## 7 Conclusions and Remarks  
In this paper we reviewed the concept of using an aerial-ground wireless sensing network (AG-WSN) in a remote and geospatially large, complex space. We particularly recognized the need of implementing such sensing solutions in precision agriculture and structural health monitoring practices. We then recognized the technical challenges in achieving energy efficiency in the ground sensors. Different wake-up mechanisms are then reviewed and compared. Among those mechanisms, we chose an active radio frequency (RF)-based wake-up method and implemented it physically. The focus was on evaluating their performances to achieve energy efficiency in the battery-powered ground sensors. The following findings were achieved through the experimental evaluation in this work:  
1. The experimental results in this paper indicated that the RF-based out-band wake-up mechanism can save a great amount of energy compared with the other two solutions (the infrared wake-up and the default duty-cycle methods). A direct comparison between the RF-based solution and the infrared-based solution indicated that the RF-based wake-up mechanism had a noticeably better performance in the wake-up range, and had a tremendous improvement in power consumption. Specifically, the results showed that the RF-based wake-up mechanism could potentially save more than 98.4% of the energy that the traditional duty-cycle method would otherwise consume, and 96.8% if an infrared-receiver method was used. Figure 11: Experimental battery test and capacity dropping for the three different solutions. The energy consumption for different RF wake-up distances was evaluated in this paper. The results indicated that as the distance between the transmitter and receiver increased, the receiver consumed more power (around 8.4 \(\upmu\)J). However, it was argued that this value could be ignored compared to the energy consumed in the listening mode, which was at least \(10^{3}\) times higher. 3. The evaluation of wake-up time delay by using a variety of different wake-up signal codes indicated that the time delay was below 80 ms; hence, the delay will not affect most opportunistic sensing applications (wherein the sensors sense the data at one time and transmit at a later time, then the sensors go back to sleep mode until another abrupt event). However, it was pointed out that a stricter time delay evaluation needs to be conducted if synchronization is critical between the sensors. Given the three findings, it was concluded that the RF wake-up mechanism was the first candidate for implementing the proposed wireless aerial-ground sensing network for monitoring applications in large-scale geospatial or challenging spaces. The technical contribution also included the use of a digital imaging approach to measure the wake-up time delay, and the resulting time-dependent rates of the battery-based power consumption using three different wake-up methods. This experimental and empirical knowledge may be extrapolated in similar sensing network research where sensor activation needs to be integrated. Last, we point out a few limitations in this effort that warrant future exploration. The first limitation is the RF wake-up range with the device used in this effort, which was relatively short (0-7 m) compared with the Xbee communication range (about several hundred meters). One practical solution for this is to increase the power of the wake-up transmitter and to consider advanced antenna design (such as using the multiple input, multiple output, or MIMO technology) to increase the sensitivity of the wake-up signal. This may introduce more power consumption on the UAV side. With this potential long-range RF-based wake-up mechanism, the UAV no longer needs to reach the proximity of the sensor nodes. The UAV path planning then becomes a traveling salesman problem with neighborhoods, which was covered in our recent research [36]. The second limitation is the star topology assumed for the ground-level WSN.