近年來物聯網及無線感測技術已廣泛的應用於結構健康監測上。此
類系 統大多為電池供電，必須定時休眠以延長電池使用壽命。此外，多
數的系統都建置在較難以到達的區域，常利用傳輸中繼站(含資料擷取
器 )，以 3G/4G 等無線方式傳回遠端資料平台。 在實務上，固定式中繼
站會因為災害等事件造成毀損，因此要隨時準備好臨時中繼站；再來，
中繼站設在固定位置，理論上越高越好，但實務上很難辦到，所以才有
用 UAV 的想法。 因此，本研究目的為開發並整合 LoRa（ Long Range）
與磁導喚醒技術的 UAV(unmanned aerial vehicle) 行動閘道器 (UAVbased Moving Gateway)，完成了初步 UAV 結構健康監測物聯網架構，
包含了地面監測中心用來發送喚醒訊息並藉由 LoRa 無線傳輸發送至
UAV 行動閘道器，及透過 mission planner 介面監控 UAV 任務與飛行
狀態； UAV 行動閘道器則以四旋翼無人機與 MCU(Micro-Control Unit)
控制板為主要核心，由微控器 (MCU)整合各項感測器與微控制器，如低
頻發射天線與 LoRa，接收從地面監測中心所傳出之指令，再將指令透
過 LoRa 無線傳輸至感測節點，或是由低頻發射天線透過 MI(Magnetic
Induction)技術觸發喚醒感測節點運行，再接收由感測節點所傳回之資
料，由 LoRa 無線傳輸傳至地面監測中心；感測節點則由微控器 (MCU)
為主要核心，由微控器 (MCU)整合各項感測器與微控制器，接收從 UAV
ii
行動閘道器 所傳出之指令，再將感測器所得到之感測資料無線傳輸回
UAV 行動閘道器。本研究結果表明本系統可以成功的遠端利用喚醒睡
眠中之感測節點，並可發送訊號令其從睡眠狀態喚醒。低頻天線在 12V
供電之情況下，觸發距離約為 1～3 公尺。而 LoRa 於近距離下幾乎不
會有信號延遲與掉包率之結果，若再加上 4G 或 5G 通訊，則會提高
UAV 行動閘道器之使用性。

In recent years, the Internet of Things and wireless sensing technologies have been widely
used in structural health monitoring. Most of these systems are battery-powered and must
sleep periodically to extend battery life. In addition, most systems are built in areas that
are difficult to reach, and often use transmission relay stations (including data capture
devices) to transmit back to remote data platforms via wireless methods such as 3G/4G.
In practice, fixed relay stations will be damaged due to disasters and other events, so you
should always be prepared for temporary relay stations; again, relay stations should be
located in fixed locations. In theory, the higher the better, but in practice, it is difficult to
do so, so UAV is useful. Thoughts. Therefore, the purpose of this research is to develop
and integrate LoRa (Long Range) and UAV (unmanned aerial vehicle) mobile gateway
(UAV-based Moving Gateway) that integrates LoRa (Long Range) and permeance wake
technology, and completes the preliminary UAV structural health monitoring IoT
architecture, including The ground monitoring center is used to send wake-up messages
and sent to the UAV mobile gateway via LoRa wireless transmission, and to monitor the
UAV mission and flight status through the mission planner interface; the UAV mobile
gateway uses quadrotor drones and MCU (Micro -Control Unit) The control board is the
main core. The microcontroller (MCU) integrates various sensors and microcontrollers,
such as low-frequency transmitting antennas and LoRa, to receive instructions from the
ground monitoring center, and then transmit the instructions LoRa is wirelessly
transmitted to the sensing node, or the low-frequency transmitting antenna triggers the
wake-up of the sensing node to operate through MI (Magnetic Induction) technology, and
then receives the data returned by the sensing node, and transmits it to the ground
monitoring center by LoRa wireless transmission; The sensor node is composed of a
microcontroller (MCU) as the main core. The microcontroller (MCU) integrates various
iv
sensors and microcontrollers, receives instructions from the UAV mobile gateway, and
then detects The sensing data obtained by the device is wirelessly transmitted back to the
UAV mobile gateway. The results of this research show that the system can successfully
remotely use to wake up the sensing node in sleep and send a signal to wake it from sleep.
When the low-frequency antenna is powered by 12V, the trigger distance is about 1 to 3
meters. In LoRa, there is almost no signal delay and packet drop rate at short distances.
If 4G or 5G communication is added, the usability of UAV mobile gateways will be
improved.

1. Yamada, M., et al. Development and field test of novel two-wheeled UAV for bridge inspections. in 2017 International Conference on Unmanned Aircraft Systems (ICUAS). 2017.
2. Máthé, K. and L. Busoniu, Vision and Control for UAVs: A Survey of General Methods andof Inexpensive Platforms for Infrastructure Inspection. Sensors (Basel, Switzerland), 15: p. 14887-916，2015.
3. Eschmann, C. and T. Wundsam, Web-Based Georeferenced 3D Inspection and Monitoring of Bridges with Unmanned Aircraft Systems. Journal of Surveying Engineering, 143(3): p. 04017003，2017.
4. Abdullah, A., I. Machfudin, and M. Zamuswara, Flying weather network system based on wireless sensor, a flights investigation. Journal of Physics: Conference Series, 1193: p. 012016，2019.
5. Jordan, S., et al., State-of-the-art technologies for UAV inspections. IET Radar, Sonar & Navigation, 12(2): p. 151-164，2018.
6. Hallermann, N. and G. Morgenthal, Visual inspection strategies for large bridges using Unmanned Aerial Vehicles (UAV)，2014.
7. Boccardo, P., et al., UAV Deployment Exercise for Mapping Purposes: Evaluation of Emergency Response Applications. Sensors (Basel, Switzerland), 15: p. 15717-15737，2015.
8. Erdelj, M., M. Król, and E. Natalizio, Wireless Sensor Networks and Multi-UAV systems for natural disaster management. Computer Networks, 124: p. 72-86，2017.
9. Mark C. Tatum*, J.L., Unmanned Aircraft System Applications In Construction. CC BY-NC-ND license, 2017.
10. Park, C., et al., Formation Flight of Multiple UAVs Using Onboard Information Sharing. Sensors, 15: p. 17397-17419，2015.
11. Murcia, H., et al., Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture. Sensors, 2015.
12. Mukherjee, A., et al., Distributed aerial processing for IoT-based edge UAV swarms in smart farming. Computer Networks, 167: p. 107038，2020.
13. Jawhar, I., N. Mohamed, and J. Al-Jaroodi, UAV-based data communication in wireless sensor networks: Models and strategies. 2015 International Conference on Unmanned Aircraft Systems, ICUAS 2015, p. 687-694，2015
14. Dong, M., et al., UAV-assisted data gathering in wireless sensor networks. The Journal of Supercomputing, 70: p. 1142-1155，2014.
15. Zhan, P., K. Yu, and A.L. Swindlehurst, Wireless Relay Communications with Unmanned Aerial Vehicles: Performance and Optimization. IEEE Transactions on Aerospace and Electronic Systems, 47(3)，05 July 2011.
16. Mozaffari, M., et al., Mobile Unmanned Aerial Vehicles (UAVs) for Energy-Efficient Internet of Things Communications. IEEE Transactions on Wireless Communications, p. 16，2017.
17. Yue, W. and Z. Jiang, Path Planning for UAV to Collect Sensors Data Based on Spiral Decomposition. Procedia Computer Science, 131: p. 873-879，2018.
18. Liu, B. and H. Zhu, Energy-Effective Data Gathering for UAV-Aided Wireless Sensor Networks. Sensors (Basel, Switzerland), 19(11): p. 2506，2019.
19. Feltrin, Luca, et al. "LoRaWAN: Evaluation of link-and system-level performance." IEEE Internet of Things Journal 5.3: 2249-2258. (2018)
20. Sanchez-Iborra, Ramon, et al. "Performance evaluation of LoRa considering scenario conditions." Sensors 18.3: 772. (2018)
21. Pasolini, Gianni, et al. "Smart city pilot projects using LoRa and IEEE802. 15.4 technologies." Sensors 18.4: 1118. (2018)
22. Adelantado, Ferran, et al. "Understanding the limits of LoRaWAN." IEEE Communications magazine 55.9: 34-40. (2017)
23. Chen, Ye. Design of magneto-inductive waveguide for sensing applications. Diss. 2014.
24. Ahmed, Niaz, et al. "A multi-coil magneto-inductive transceiver for low-cost wireless sensor networks." 2014 Underwater Communications and Networking (UComms). IEEE, 2014.
25. Wang, Yibin, Andrew Dobbin, and Jean-François Bousquet. "A compact low-power underwater magneto-inductive modem." Proceedings of the 11th ACM International Conference on Underwater Networks & Systems. 2016.
26. Tan, Xin, Zhi Sun, and Ian F. Akyildiz. "A testbed of magnetic induction-based communication system for underground applications." arXiv preprint arXiv:1503.02519 (2015).
27. Sun, Y. & Xu, S. & Shi, W. & Wu, T. & Wang, X. & Niu, H.. Analysis and Implementation of Magnetic Induction Wireless Underground Communication System. Chinese Journal of Sensors and Actuators. 30. 904-908.
28. Zhang, Zhengqing, et al. "Cooperative magnetic induction based through-the-earth communication." 2014 IEEE/CIC International Conference on Communications in China (ICCC). IEEE, 2014.
29. Yan, Bin, et al. "Design of induction magnetometer receiving sensor for through-the-earth communications." IEEE Sensors Journal 15.2: 1139-1144. (2014)
30. Tajudeen, Mohammed Ashiq Rahman. "GENERAL WAKE-UP RADIO MODULE FOR ISM BAND." (2018).