{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T19:08:57Z","timestamp":1772910537838,"version":"3.50.1"},"reference-count":62,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,3,5]],"date-time":"2023-03-05T00:00:00Z","timestamp":1677974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Regional Development Fund","award":["MIS 5076606"],"award-info":[{"award-number":["MIS 5076606"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The rapid growth in the technological advancements of the smartphone industry has classified contemporary smartphones as a low-cost and high quality indoor positioning tools requiring no additional infrastructure or equipment. In recent years, the fine time measurement (FTM) protocol, achieved through the Wi-Fi round trip time (RTT) observable, available in the most recent models, has gained the interest of many research teams worldwide, especially those concerned with indoor localization problems. However, as the Wi-Fi RTT technology is still new, there is a limited number of studies addressing its potential and limitations relative to the positioning problem. This paper presents an investigation and performance evaluation of Wi-Fi RTT capability with a focus on range quality assessment. A set of experimental tests was carried out, considering 1D and 2D space, operating different smartphone devices at various operational settings and observation conditions. Furthermore, in order to address device-dependent and other type of biases in the raw ranges, alternative correction models were developed and tested. The obtained results indicate that Wi-Fi RTT is a promising technology capable of achieving a meter-level accuracy for ranges both in line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, subject to suitable corrections identification and adaptation. From 1D ranging tests, an average mean absolute error (MAE) of 0.85 m and 1.24 m is achieved, for LOS and NLOS conditions, respectively, for 80% of the validation sample data. In 2D-space ranging tests, an average root mean square error (RMSE) of 1.1m is accomplished across the different devices. Furthermore, the analysis has shown that the selection of the bandwidth and the initiator\u2013responder pair are crucial for the correction model selection, whilst knowledge of the type of operating environment (LOS and\/or NLOS) can further contribute to Wi-Fi RTT range performance enhancement.<\/jats:p>","DOI":"10.3390\/s23052829","type":"journal-article","created":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T02:28:34Z","timestamp":1678069714000},"page":"2829","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Testing and Evaluation of Wi-Fi RTT Ranging Technology for Personal Mobility Applications"],"prefix":"10.3390","volume":"23","author":[{"given":"Manos","family":"Orfanos","sequence":"first","affiliation":[{"name":"School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, 15780 Athens, Greece"}]},{"given":"Harris","family":"Perakis","sequence":"additional","affiliation":[{"name":"School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, 15780 Athens, Greece"}]},{"given":"Vassilis","family":"Gikas","sequence":"additional","affiliation":[{"name":"School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, 15780 Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6019-1548","authenticated-orcid":false,"given":"G\u00fcnther","family":"Retscher","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, TU Wien\u2014Vienna University of Technology, 1040 Vienna, Austria"}]},{"given":"Thanassis","family":"Mpimis","sequence":"additional","affiliation":[{"name":"School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, 15780 Athens, Greece"}]},{"given":"Ioanna","family":"Spyropoulou","sequence":"additional","affiliation":[{"name":"School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, 15780 Athens, Greece"}]},{"given":"Vasileia","family":"Papathanasopoulou","sequence":"additional","affiliation":[{"name":"School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, 15780 Athens, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Gikas, V., and Perakis, H. (2016). Rigorous Performance Evaluation of Smartphone GNSS\/IMU Sensors for ITS Applications. Sensors, 16.","DOI":"10.3390\/s16081240"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"153960","DOI":"10.1109\/ACCESS.2020.2973759","article-title":"GNSS Vulnerabilities and Existing Solutions: A Review of the Literature","volume":"9","author":"Zidan","year":"2021","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Hamza, V., Stopar, B., and Sterle, O. (2021). Testing the Performance of Multi-Frequency Low-Cost GNSS Receivers and Antennas. Sensors, 21.","DOI":"10.3390\/s21062029"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Correa, A., Barcelo, M., Morell, A., and Vicario, J.L. (2017). A Review of Pedestrian Indoor Positioning Systems for Mass Market Applications. Sensors, 17.","DOI":"10.3390\/s17081927"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1109\/OJITS.2022.3169700","article-title":"A Data-Driven Model for Pedestrian Behavior Classification and Trajectory Prediction","volume":"3","author":"Papathanasopoulou","year":"2022","journal-title":"IEEE Open J. Intell. Transp. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1080\/10095020.2019.1613778","article-title":"Indoor localization for pedestrians with real-time capability using multi-sensor smartphones","volume":"22","author":"Ehrlich","year":"2019","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_7","unstructured":"Gj\u00f8v\u00e5g, C.W. (2020). WiFi RTT for Indoor Localization using Google WiFi and Google Pixel 3a. [Master\u2019s Thesis, NTNU]."},{"key":"ref_8","unstructured":"Bai, Y.B., Kealy, A., Retscher, G., and Hoden, L. (2020, January 5\u20137). A Comparative Evaluation of Wi-Fi RTT and GPS Based Positioning. Proceedings of the International Global Navigation Satellite Systems IGNSS 2020 Conference, Sydney, Australia."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Subedi, S., and Pyun, J.Y. (2020). A Survey of Smartphone-Based Indoor Positioning System Using RF-Based Wireless Technologies. Sensors, 20.","DOI":"10.3390\/s20247230"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1049\/csy2.12004","article-title":"A review of smartphones-based indoor positioning: Challenges and applications","volume":"3","author":"Nguyen","year":"2021","journal-title":"IET Cyber-Syst. Robot."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1372","DOI":"10.1049\/iet-com.2019.1059","article-title":"Survey on WiFi-based indoor positioning techniques","volume":"14","author":"Liu","year":"2020","journal-title":"IET Commun."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Perakis, H., and Gikas, V. (2022, January 5\u20138). Towards collaborative multi-agent positioning based on combined Wi-Fi RTT\/UWB\/IMU measurements. Proceedings of the IAG 2nd International Symposium of Commission 4: Positioning and Applications, Potsdam, Germany.","DOI":"10.5194\/iag-comm4-2022-41"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/MC.2018.3191259","article-title":"Accurate Indoor Location for the IoT","volume":"51","author":"Want","year":"2018","journal-title":"Computer"},{"key":"ref_14","unstructured":"Van Diggelen, F., Want, R., and Wang, W. (GPS World, 2018). How to Achieve 1-Meter Accuracy in Android, GPS World."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Garcia-Fernandez, M., Hoyas-Ester, I., Lopez-Cruces, A., Siutkowska, M., and Banqu\u00e9-Casanovas, X. (2021). Accuracy in WiFi Access Point Position Estimation Using Round Trip Time. Sensors, 21.","DOI":"10.3390\/s21113828"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Xu, S., Wang, Y., and Si, M. (2022). A Two-Step Fusion Method of Wi-Fi FTM for Indoor Positioning. Sensors, 22.","DOI":"10.3390\/s22093593"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"325","DOI":"10.2478\/popets-2022-0048","article-title":"Privacy-Preserving Positioning in Wi-Fi Fine Timing Measurement","volume":"2022","author":"Schepers","year":"2022","journal-title":"Proc. Priv. Enhancing Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4428","DOI":"10.1109\/TVT.2022.3151018","article-title":"Enhanced Wi-Fi RTT Ranging: A Sensor-Aided Learning Approach","volume":"71","author":"Choi","year":"2022","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Gentner, C., Ulmschneider, M., Kuehner, I., and Dammann, A. (2020, January 20\u201323). WiFi-RTT Indoor Positioning. Proceedings of the 2020 IEEE\/ION Position, Location and Navigation Symposium (PLANS), Portland, OR, USA.","DOI":"10.1109\/PLANS46316.2020.9110232"},{"key":"ref_20","unstructured":"Perakis, H., Orfanos, M., Stratakos, I., Gikas, V., and Albanopoulos, C. (2022, January 11\u201315). Towards a prototype low-cost\/multi-RF based positioning system for underground marble quarry management: Design considerations and preliminary results. Proceedings of the FIG Congress 2022, Warsaw, Poland."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Perakis, H., and Gikas, V. (2018, January 24\u201327). Evaluation of Range Error Calibration Models for Indoor UWB Positioning Applications. Proceedings of the 2018 International Conference on Indoor Positioning and Indoor Navigation IPIN 2018, Nantes, France.","DOI":"10.1109\/IPIN.2018.8533755"},{"key":"ref_22","unstructured":"Retscher, G., Gikas, V., Perakis, H., Hofer, H., and Kealy, A. (2019, January 8\u201318). Evaluation of UWB and Wi-Fi Cooperative Localization Performance in Indoor Environments. Proceedings of the 27th IUGG General Assembly, Montreal, QC, Canada."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Gabela, J., Retscher, G., Goel, S., Perakis, H., Masiero, A., Toth, C., Gikas, V., Kealy, A., Koppanyi, Z., and B\u0142aszczak-B\u0105k, W. (2019). Experimental Evaluation of a UWB based Cooperative Positioning System for Pedestrians in GNSS Denied Environment. Sensors, 19.","DOI":"10.3390\/s19235274"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Horn, B. (2020). Doubling the Accuracy of Indoor Positioning: Frequency Diversity. Sensors, 20.","DOI":"10.3390\/s20051489"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1109\/TSMCC.2007.905750","article-title":"Survey of Wireless Indoor Positioning Techniques and Systems","volume":"37","author":"Liu","year":"2007","journal-title":"IEEE Trans. Syst. Man, Cybern. Part Appl. Rev."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chen, R. (2012). Ubiquitous Positioning and Mobile Location-Based Services in Smart Phones, IGI Global.","DOI":"10.4018\/978-1-4666-1827-5"},{"key":"ref_27","first-page":"57","article-title":"Indoor Localization and Tracking: Methods, Technologies and Research Challenges","volume":"13","year":"2014","journal-title":"Acta Univ. Ser. Autom. Control. Robot."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Grafarend, E.W. (2016). Encyclopedia of Geodesy, Earth Sciences Series, Springer International Publishing. Chapter 9-1.","DOI":"10.1007\/978-3-319-02370-0"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/17489725.2013.870419","article-title":"Editorial: Special Issue International Conference on Indoor Positioning and Navigation 2012, Part 2","volume":"8","author":"Li","year":"2014","journal-title":"J. Locat. Based Serv."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"9047","DOI":"10.3390\/s130709047","article-title":"Seamless Positioning and Navigation by Using Geo-referenced Images and Multi-sensor Data","volume":"13","author":"Li","year":"2013","journal-title":"Sensors"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1515\/jag-2019-0031","article-title":"A Benchmarking Measurement Campaign in GNSS-denied\/challenged Indoor\/outdoor and Transitional Environments","volume":"14","author":"Retscher","year":"2020","journal-title":"J. Appl. Geod."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Chen, R. (2012). Ubiquitous Positioning and Mobile Location-Based Services in Smart Phones, IGI Global. Chapter 4.","DOI":"10.4018\/978-1-4666-1827-5"},{"key":"ref_33","unstructured":"Ruotsalainen, L. (2013). Vision-Aided Pedestrian Navigation for Challenging GNSS Environments. [Ph.D. Thesis, University of Helsinki]."},{"key":"ref_34","unstructured":"EUSPA (2022, June 30). GNSS User Technology Report 2018. Available online: https:\/\/www.gsa.europa.eu\/newsroom\/news\/gnss-user-technology-report-2018-available-download-now."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Zhou, B., Wu, Z., Chen, Z., Liu, X., and Li, Q. (2023). Wi-Fi RTT\/Encoder\/INS-based Robot Indoor Localization using Smartphones. IEEE Trans. Veh. Technol., 1\u201313.","DOI":"10.1109\/TVT.2023.3234283"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"16322","DOI":"10.1109\/JIOT.2022.3150958","article-title":"A Robust Integration Platform of Wi-Fi RTT, RSS Signal, and MEMS-IMU for Locating Commercial Smartphone Indoors","volume":"9","author":"Guo","year":"2022","journal-title":"IEEE Internet Things J."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"11165","DOI":"10.1109\/ACCESS.2019.2891942","article-title":"An Indoor Position-Estimation Algorithm Using Smartphone IMU Sensor Data","volume":"7","author":"Poulose","year":"2019","journal-title":"IEEE Access"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compag.2005.09.003","article-title":"Wireless Sensors in Agriculture and Food Industry\u2014Recent Development and Future Perspective","volume":"50","author":"Wang","year":"2006","journal-title":"Comput. Electron. Agric."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Retscher, G. (2020). Fundamental Concepts and Evolution of Wi-Fi User Localization: An Overview Based on Different Case Studies. Sensors, 20.","DOI":"10.3390\/s20185121"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1860","DOI":"10.1109\/TCE.2010.5606338","article-title":"Robust Indoor Positioning Using Differential Wi-Fi Acess Points","volume":"56","author":"Chang","year":"2010","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Chen, X., Kong, J., Guo, Y., and Chen, X. (2014, January 8\u201312). An Empirical Study of Indoor Localization Algorithms With Densely Deployed APs. Proceedings of the BGlobal Communications Conference GLOBECOM, Austin, TX, USA.","DOI":"10.1109\/GLOCOM.2014.7036860"},{"key":"ref_42","unstructured":"Banin, L., Bar-Shalom, O., Dvorecki, N., and Amizur, Y. (2023, February 23). High-Accuracy Indoor Geolocation using Collaborative Time of Arrival (CToA). Intel White Paper. Available online: https:\/\/www.researchgate.net\/publication\/320146822_High-Accuracy_Indoor_Geolocation_using_Collaborative_Time_of_Arrival_CToA."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Yu, Y., Chen, R., Chen, L., Guo, G., Ye, F., and Liu, Z. (2019). A Robust Dead Reckoning Algorithm Based on Wi-Fi FTM and Multiple Sensors. Remote Sens., 11.","DOI":"10.3390\/rs11050504"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Ibrahim, M., Liu, H., Jawahar, M., Nguyen, V., Gruteser, M., Howard, R., Yu, B., and Bai, F. (2018, January 29). Verification: Accuracy Evaluation of WiFi Fine Time Measurements on an Open Platform. Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, MobiCom \u201918, New Delhi, India.","DOI":"10.1145\/3241539.3241555"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Feng, X., Nguyen, K.A., and Luo, Z. (2022). WiFi Access Points Line-of-Sight Detection for Indoor Positioning Using the Signal Round Trip Time. Remote Sens., 14.","DOI":"10.3390\/rs14236052"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Si, M., Wang, Y., Xu, S., Sun, M., and Cao, H. (2020). A Wi-Fi FTM-Based Indoor Positioning Method with LOS\/NLOS Identification. Appl. Sci., 10.","DOI":"10.3390\/app10030956"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Cao, H., Wang, Y., Bi, J., Xu, S., Si, M., and Qi, H. (2020). Indoor Positioning Method Using WiFi RTT Based on LOS Identification and Range Calibration. ISPRS Int. J.-Geo-Inf., 9.","DOI":"10.3390\/ijgi9110627"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"14589","DOI":"10.1109\/JIOT.2021.3070367","article-title":"Exploiting User Mobility for WiFi RTT Positioning: A Geometric Approach","volume":"8","author":"Han","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_49","unstructured":"Houle, D.E. (2021). Analysis of the Position-Dependent Error in FTM RTT Indoor Navigation. [Ph.D. Thesis, Massachusetts Institute of Technology]."},{"key":"ref_50","unstructured":"Kia, G., Talvitie, J., and Ruotsalainen, L. (December, January 29). RSS-Based Fusion of UWB and WiFi-Based Ranging for Indoor Positioning. Proceedings of the IPIN 2021 WiP Proceedings, Lloret de Mar, Spain."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.1017\/S0373463320000193","article-title":"Wi-Fi Fine Time Measurement: Data Analysis and Processing for Indoor Localisation","volume":"73","author":"Yu","year":"2020","journal-title":"J. Navig."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1109\/TMC.2020.3012563","article-title":"Wi-Fi RTT Ranging Performance Characterization and Positioning System Design","volume":"21","author":"Ma","year":"2022","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"176767","DOI":"10.1109\/ACCESS.2019.2957753","article-title":"Indoor Smartphone Localization: A Hybrid WiFi RTT-RSS Ranging Approach","volume":"7","author":"Guo","year":"2019","journal-title":"IEEE Access"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1504\/IJWGS.2006.011714","article-title":"Semantically enriched navigation for indoor environments","volume":"2","author":"Tsetsos","year":"2006","journal-title":"IJWGS Int. J. Web Grid Serv."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1080\/17489725.2016.1231351","article-title":"A low-cost wireless sensors positioning solution for indoor parking facilities management","volume":"10","author":"Gikas","year":"2016","journal-title":"J. Locat. Based Serv."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1166","DOI":"10.1016\/j.ijdrr.2017.09.032","article-title":"A framework for risk reduction for indoor parking facilities under constraints using positioning technologies","volume":"31","author":"Antoniou","year":"2018","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"ref_57","unstructured":"Perakis, H., Mpimis, A., Gikas, V., Papathanasopoulou, V., and Antoniou, K. (2015, January 13\u201316). Driving Behavior Classification within Indoor Parking Facilities Based on Inertial Smartphone Data. Proceedings of the 6th International Conference on Indoor Positioning and Indoor Navigation (IPIN), Banff, AB, Canada."},{"key":"ref_58","unstructured":"Czogalla, O., Naumann, S., Schade, J., and Sch\u00f6nrock, R. (2015, January 5\u20139). Indoor Positioning and Navigation for Pedestrian Guidance in Public Transport Facilities. Proceedings of the 22nd ITS World Congress, Bordeaux, France. Available online: https:\/\/www.researchgate.net\/publication\/283045487_Indoor_Positioning_and_Navigation_for_Pedestrian_Guidance_in_Public_Transport_Facilities."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/s43020-021-00041-3","article-title":"Indoor navigation: State of the art and future trends","volume":"2","author":"Li","year":"2021","journal-title":"Satell. Navig."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1080\/13467581.2019.1696805","article-title":"Designing indoor navigation interfaces on smartphones compatible with human information processing in an emergency evacuation scenario","volume":"18","author":"Zheng","year":"2019","journal-title":"J. Asian Archit. Build. Eng."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Shekhar, S., Xiong, H., and Zhou, X. (2015). Encyclopedia of GIS, Springer International Publishing.","DOI":"10.1007\/978-3-319-23519-6"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Zahabi, M., Zheng, X., Maredia, A., and Shahini, F. (2022). Design of Navigation Applications for People with Disabilities: A Review of Literature and Guideline Formulation. Int. J. Hum.-Comput. Interact., 1\u201323.","DOI":"10.1080\/10447318.2022.2088883"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/5\/2829\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:48:12Z","timestamp":1760122092000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/5\/2829"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,5]]},"references-count":62,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["s23052829"],"URL":"https:\/\/doi.org\/10.3390\/s23052829","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,5]]}}}