RADIOELECTRONIC AND COMPUTER SYSTEMS

Motivation. After the Fukushima, nuclear power plant (NPP) accident, an unmanned aerial vehicle (UAV)-enabled wireless network (UEWN) is considered to be used for transmitting the data from monitoring stations (MSs) to the crisis center (CrS) during NPP post-accident monitoring missions. Nevertheless, the popular lightweight UAVs have an endurance of about 20–40 minutes only. The last fact presents a significant barrier to use a UEWN in complex, long-term NPP post-accident monitoring missions. The subject matter of the paper is the process of ensuring the persistent operation of UEWN. This paper aims to propose an approach to ensuring the persistent operation of UEWN during NPP post-accident monitoring missions via automatic battery replacement stations (ABRSs). The objectives of the paper are: to propose a scheme of deployment of a UEWN with ABRSs for the given scenario; to give an example of the proposed scheme application for persistent transmitting the data from a MS to the CrS during Zaporizhzhia NPP (ZNPP) post-accident monitoring missions; to discuss an example of the proposed scheme application. The following results were obtained. A simplified scheme of deployment of a UEWN with ABRSs for transmitting the data from the MS to the CrS during NPP post-accident monitoring missions was developed and described. Two segments within the UEWN were considered: 1) Wi-Fi segment, comprising the WiFi equipment of the MS, the onboard WiFi equipment of the UAVs of a multi-rotor type (MUAVs), and onboard WiFi equipment of the UAV of an airplane-type (AUAV); 2) LoRaWAN segment, comprising the LoRaWAN equipment of the AUAV and the LoRaWAN equipment of the CrS. An example of deployment of a UEWN with ABRSs for transmitting the data from an MS of ZNPP to the CrS was given and described. A shift schedule for 2 MUAV fleets ensuring the persistent operation of the UEWN during post-accident ZNPP monitoring missions was built and analyzed. It was evaluated how the flight distance for the MUAV between its location point in the WiFi segment and the ABRS effects: the duty time for the MUAV fleet; the waiting time for the MUAV to flight to the point of its location in the WiFi segment; the number of the MUAV fleets for ensuring the persistent operation of the UEWN. The new research will aim at developing a scheme of deployment of the UEWN with ABRSs for several WiFi segments

unmanned aerial vehicle; nuclear power plant; a wireless network; WiFi; LoRaWAN; post-accident monitoring; monitoring station; a crisis center

Sachenko, A. A., Kochan, V. V., Kharchenko, V. S., Yastrebenetskii, M. A., Fesenko, H. V., Yanovskii, M. E. Sistema posleavariinogo monitoringa AES s ispol'zovaniem bespilotnykh letatel'nykh apparatov: kontseptsiya, printsipy postroeniya [NPP post-accident monitoring system based on unmanned aircraft vehicle: сoncept, design principles]. Yaderna ta radiatsiina bezpeka – Nuclear and Radiation Safety, 2017, vol. 73, no. 1, pp. 24-29.

Kharchenko, V., Fesenko, H., Sachenko, A., Hiromoto, R., Kochan, V. Reliability issues for a multi-version post-severe NPP accident monitoring system. IEEE 9th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technologies and Application (IDAACS), Bucharest, Romania, 21-23 Sept., 2017, pp. 942-946. DOI: 10.1109/IDAACS.2017.8095225.

Fesenko, H., Kharchenko, V., Sachenko, A., Hiromoto, R., Kochan, V. An Internet of Drone-based multi-version post-severe accident monitoring system: structures and reliability. Dependable IoT for human and industry modeling, architecting, implementation, Denmark, The Netherlands, River Publishers, 2018, pp. 197-217.

Michini, B., Toksoz, T., Redding, J., Michini, M., How, J., Vavrina, M., Vian, J. Automated battery swap and recharge to enable persistent UAV missions [Electronic resource]. Infotech@Aerospace 2011. American Institute of Aeronautics and Astronautics. Available at: http://hdl.handle.net/1721.1/8. (Accessed 10.11.2019).

Fujii, K., Higuchi, K., Rekimoto, J. Endless flyer: a continuous flying drone with automatic battery replacement. IEEE 10th International Conference on Ubiquitous Intelligence and Computing, New York City, NY, USA, 8-10 Nov., 2013, pp. 216-223.

Ure, N. K., Chowdhary, G., Toksoz, T., How, J. P., Vavrina, M. A., Vian, J. An automated battery management system to enable persistent missions with multiple aerial vehicles. IEEE/ASME Transactions on Mechatronics, 2015, vol. 20, no. 1, pp. 275-286. DOI:10.1109/tmech.2013.2294805.

Leahy, K., Zhou, D., Vasile, C.-I., Konstantinos, O., Schwager, M., Belta, C. Persistent surveillance for unmanned aerial vehicles subject to charging and temporal logic constraints. Autonomous Robots, 2016, vol. 40, no. 8, pp. 1363-1378. DOI: 0.1007/s10514-015-9519-z.

Khonji, M., Alshehhi, M., Tseng, Ch., Chau, Ch. Autonomous inductive charging system for battery-operated electric drones. 8th International Conference on Future Energy Systems (e-Energy), Shatin, Hong Kong, 16-19 May, 2017, pp. 322-327. DOI: 10.1145/3077839.3078462.

Tseng, Ch., Chau, Ch., Elbassioni, K., Khonji, M. Autonomous recharging and flight mission planning for battery-operated autonomous drones. Available at: https://arxiv.org/abs/1703.10049. (Accessed 10.11.2019).

Ke, D., Liu, C., Jiang, C., Zhao, F. Design of an effective wireless air charging system for electric unmanned aerial vehicles. 43rd Annual Conference of the IEEE Industrial Electronics Society (IECON), Beijing, China, 29 Oct.-1 Nov., 2017, pp. 6949-6954. DOI: 10.1109/iecon.2017.821721.

Barrett, E., Reiling, M., Mirhassani, S., Meijering, R., Jager, J., Mimmo, N., Callegati, F., Marconi, L., Carloni, R., Stramigioli, S. Autonomous battery exchange of UAVs with a mobile ground base. IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 21-26 May, 2018, pp. 699-705. DOI: 10.1109/icra.2018.8460201.

Dong, X., Ren, Y., Meng, J., Lu, S., Wu, T., Sun, Q. Design and implementation of multi-rotor UAV power relay platform. IEEE 2nd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), Xi'an, China, 25-27 May, 2018, pp. 1142-1146. DOI: 10.1109/IMCEC.2018.8469759.

Shinkuma, R., Mandayam, N. B. Design of ad hoc wireless mesh networks formed by unmanned aerial vehicles with advanced mechanical automation. Available at: https://arxiv.org/abs/1804.07428. (Accessed 10.11.2019).

Rohan, A., Rabah, M., Talha, M., Kim, S.-H. Development of intelligent drone battery charging system based on wireless power transmission using hill climbing algorithm. Applied System Innovation, 2018, vol. 44, no. 4. Available at: https://www.mdpi.com/2571-5577/1/4/44. (Accessed 10.11.2019). DOI: 10.3390/asi1040044.

Boggio-Dandry, A., Soyata, T. Perpetual flight for UAV drone swarms using continuous energy replenishment. IEEE 9th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)), New York City, NY, USA, 8-10 Nov., 2018, pp. 478-484. DOI: 10.1109/UEMCON.2018.8796684.

Campi, T., Cruciani, S., Maradei, F., Feliziani, M. Innovative design of drone landing gear used as a receiving coil in wireless charging application. Energies, 2019. Available at: https://www.mdpi.com/1996-1073/12/18/3483. (Accessed 10.11.2019).

Shin, M., Kim, J., Levorato, M. Auction-based charging scheduling with deep learning framework for multi-drone networks. IEEE Transactions on Vehicular Technology, 2019, vol. 68, no. 5, pp. 4235-4248. DOI: 10.1109/tvt.2019.2903144.

Erdelj, M., Saif, O., Natalizio, E., Fantoni, I. UAVs that fly forever: uninterrupted structural inspection through automatic UAV replacement. Ad Hoc Networks, 2019, vol. 94. Available at: https://hal.archives-ouvertes.fr/hal-02184513. (Accessed 10.11.2019). DOI: 10.1016/j.adhoc.2017.11.012.

Fesenko, H. V. Marshrutyzatsiya pol'otu mul'tyrotornoho BPLA z vykorystannyam povitryanoyi avtomatychnoyi servisnoyi stantsiyi pid chas monitorynhu terytoriyi potentsiyno nebezpechnoho ob"yekta [Routing of a multi-rotor UAV using an airborne automatic service station while monitoring the territory of a potentially dangerous object]. Systemy ta tekhnolohiyi – Systems and Technologies, 2019, vol. 58, no. 2, pp. 50-66. DOI: 10.32836/2521-6643-2019-2-58-3.