Prototype Design and Experimental Evaluation of Autonomous Collaborative Communication System for Emerging Maritime Use Cases
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
FV40309
Ministerstvo Průmyslu a Obchodu
813278
Horizon 2020
PubMed
34205190
PubMed Central
PMC8200044
DOI
10.3390/s21113871
PII: s21113871
Knihovny.cz E-zdroje
- Klíčová slova
- UAV, USV, autonomous vehicles, collaborative communication system, directional wireless links, maritime use cases, prototype design,
- Publikační typ
- časopisecké články MeSH
Automated systems have been seamlessly integrated into several industries as part of their industrial automation processes. Employing automated systems, such as autonomous vehicles, allows industries to increase productivity, benefit from a wide range of technologies and capabilities, and improve workplace safety. So far, most of the existing systems consider utilizing one type of autonomous vehicle. In this work, we propose a collaboration of different types of unmanned vehicles in maritime offshore scenarios. Providing high capacity, extended coverage, and better quality of services, autonomous collaborative systems can enable emerging maritime use cases, such as remote monitoring and navigation assistance. Motivated by these potential benefits, we propose the deployment of an Unmanned Surface Vehicle (USV) and an Unmanned Aerial Vehicle (UAV) in an autonomous collaborative communication system. Specifically, we design high-speed, directional communication links between a terrestrial control station and the two unmanned vehicles. Using measurement and simulation results, we evaluate the performance of the designed links in different communication scenarios and we show the benefits of employing multiple autonomous vehicles in the proposed communication system.
Mechatronics Research Group Tampere University Korkeakoulunkatu 6 337 20 Tampere Finland
Unit of Electrical Engineering Tampere University Korkeakoulunkatu 7 337 20 Tampere Finland
Zobrazit více v PubMed
Sullivan B.P., Arias Nava E., Desai S., Sole J., Rossi M., Ramundo L., Terzi S. Defining Maritime 4.0: Reconciling principles, elements and characteristics to support maritime vessel digitalisation. IET Collab. Intell. Manuf. 2021 doi: 10.1049/cim2.12012. DOI
Sanchez-Gonzalez P.L., Díaz-Gutiérrez D., Leo T.J., Núñez-Rivas L.R. Toward digitalization of maritime transport? Sensors. 2019;19:926. doi: 10.3390/s19040926. PubMed DOI PMC
Zolich A., Palma D., Kansanen K., Fjørtoft K., Sousa J., Johansson K.H., Jiang Y., Dong H., Johansen T.A. Survey on communication and networks for autonomous marine systems. J. Intell. Robot. Syst. 2019;95:789–813. doi: 10.1007/s10846-018-0833-5. DOI
Khosravi Z., Gerasimenko M., Urama J., Pyattaev A., Escusol J.V., Hosek J., Andreev S., Koucheryavy Y. Designing high-speed directional communication capabilities for unmanned surface vehicles; Proceedings of the 2019 16th International Symposium on Wireless Communication Systems (ISWCS); Oulu, Finland. 27–30 August 2019; pp. 651–655.
Ma K. Master’s Thesis. Tampere University; Tampere, Finland: 2020. Implementation and Evaluation of Communication System for Autonomous Offshore Vehicles.
Valavanis K.P., Vachtsevanos G.J. Handbook of Unmanned Aerial Vehicles. Volume 1 Springer; Berlin, Germany: 2015.
Salhaoui M., Guerrero-González A., Arioua M., Ortiz F.J., El Oualkadi A., Torregrosa C.L. Smart industrial IoT monitoring and control system based on UAV and cloud computing applied to a concrete plant. Sensors. 2019;19:3316. doi: 10.3390/s19153316. PubMed DOI PMC
Delavarpour N., Koparan C., Nowatzki J., Bajwa S., Sun X. A Technical Study on UAV Characteristics for Precision Agriculture Applications and Associated Practical Challenges. Remote Sens. 2021;13:1204. doi: 10.3390/rs13061204. DOI
Mehallegue N., Djellab M., Loukhaoukha K. Efficient Use of UAVs for Public Safety in Disaster and Crisis Management. Wirel. Pers. Commun. 2021;116:369–380. doi: 10.1007/s11277-020-07719-y. DOI
Global Commercial Drone Market Size in 2018 and 2024. [(accessed on 28 May 2021)]; Available online: https://www.statista.com/statistics/878018/global-commercial-drone-market-size/
Mozaffari M., Saad W., Bennis M., Nam Y.H., Debbah M. A tutorial on UAVs for wireless networks: Applications, challenges, and open problems. IEEE Commun. Surv. Tutor. 2019;21:2334–2360. doi: 10.1109/COMST.2019.2902862. DOI
Carrillo D., Mikhaylov K., Nardelli P.J., Andreev S., da Costa D.B. Understanding UAV-Based WPCN-Aided Capabilities for Offshore Monitoring Applications. IEEE Wirel. Commun. 2021 doi: 10.1109/MWC.001.2000218. DOI
Alzenad M., El-Keyi A., Lagum F., Yanikomeroglu H. 3-D placement of an unmanned aerial vehicle base station (UAV-BS) for energy-efficient maximal coverage. IEEE Wirel. Commun. Lett. 2017;6:434–437. doi: 10.1109/LWC.2017.2700840. DOI
Lai C.C., Chen C.T., Wang L.C. On-demand density-aware uav base station 3d placement for arbitrarily distributed users with guaranteed data rates. IEEE Wirel. Commun. Lett. 2019;8:913–916. doi: 10.1109/LWC.2019.2899599. DOI
Li M., Yu F.R., Si P., Yang R., Wang Z., Zhang Y. UAV-Assisted Data Transmission in Blockchain-Enabled M2M Communications with Mobile Edge Computing. IEEE Netw. 2020;34:242–249. doi: 10.1109/MNET.011.2000147. DOI
Zeng Y., Zhang R., Lim T.J. Wireless communications with unmanned aerial vehicles: Opportunities and challenges. IEEE Commun. Mag. 2016;54:36–42. doi: 10.1109/MCOM.2016.7470933. DOI
Khawaja W., Guvenc I., Matolak D.W., Fiebig U.C., Schneckenburger N. A survey of air-to-ground propagation channel modeling for unmanned aerial vehicles. IEEE Commun. Surv. Tutor. 2019;21:2361–2391. doi: 10.1109/COMST.2019.2915069. DOI
Sánchez-García J., Reina D., Toral S. A distributed PSO-based exploration algorithm for a UAV network assisting a disaster scenario. Future Gener. Comput. Syst. 2019;90:129–148. doi: 10.1016/j.future.2018.07.048. DOI
Magán-Carrión R., Camacho J., García-Teodoro P., Flushing E.F., Di Caro G.A. A Dynamical Relay node placement solution for MANETs. Comput. Commun. 2017;114:36–50. doi: 10.1016/j.comcom.2017.10.012. DOI
Zhan C., Zeng Y., Zhang R. Energy-efficient data collection in UAV enabled wireless sensor network. IEEE Wirel. Commun. Lett. 2017;7:328–331. doi: 10.1109/LWC.2017.2776922. DOI
Xu J., Zeng Y., Zhang R. UAV-enabled wireless power transfer: Trajectory design and energy optimization. IEEE Trans. Wirel. Commun. 2018;17:5092–5106. doi: 10.1109/TWC.2018.2838134. DOI
E Silva T.D., de Melo C.F.E., Cumino P., Rosário D., Cerqueira E., De Freitas E.P. STFANET: SDN-based topology management for flying ad hoc network. IEEE Access. 2019;7:173499–173514. doi: 10.1109/ACCESS.2019.2956724. DOI
Zhao Z., Cumino P., Souza A., Rosario D., Braun T., Cerqueira E., Gerla M. Software-defined unmanned aerial vehicles networking for video dissemination services. Ad Hoc Netw. 2019;83:68–77. doi: 10.1016/j.adhoc.2018.08.023. DOI
How To Calculate Distances, Azimuths and Elevation Angles Of Peaks. [(accessed on 28 May 2021)]; Available online: http://tchester.org/sgm/analysis/peaks/how_to_get_view_params.html.
Parsons J.D. The Mobile Radio Propagation Channel. Wiley; Hoboken, NJ, USA: 2000.
Cui Z., Briso C., Guan K., Matolak D.W., Calvo-Ramírez C., Ai B., Zhong Z. Low-altitude UAV air-ground propagation channel measurement and analysis in a suburban environment at 3.9 GHz. IET Microw. Antennas Propag. 2019;13:1503–1508. doi: 10.1049/iet-map.2019.0067. DOI
Yee Hui L., Dong F., Meng Y.S. Near sea-surface mobile radiowave propagation at 5 GHz: Measurements and modeling. Radioengineering. 2014;23:824–830.
Morón Alguacil C. Master’s Thesis. Tampere University; Tampere, Finland: 2019. Design and Analysis of Directional Antenna Structure for Unmanned Surface Vessel.