{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:20:12Z","timestamp":1760242812132,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2016,12,2]],"date-time":"2016-12-02T00:00:00Z","timestamp":1480636800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research &amp; Development Program","award":["2016YFB0502003","2016YFB0502001"],"award-info":[{"award-number":["2016YFB0502003","2016YFB0502001"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61372110"],"award-info":[{"award-number":["61372110"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.<\/jats:p>","DOI":"10.3390\/s16122055","type":"journal-article","created":{"date-parts":[[2016,12,2]],"date-time":"2016-12-02T10:36:37Z","timestamp":1480674997000},"page":"2055","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments"],"prefix":"10.3390","volume":"16","author":[{"given":"Wen","family":"Liu","sequence":"first","affiliation":[{"name":"School of Electronic Engineering, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Road, Haidian District, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0221-0063","authenticated-orcid":false,"given":"Xiao","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Road, Haidian District, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongliang","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Road, Haidian District, Beijing 100876, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,12,2]]},"reference":[{"key":"ref_1","unstructured":"\u201cIndoor Location in Retail: Where Is the Money?\u201d ABI Research: Location Technologies Market Research. Available online: https:\/\/www.abiresearch.com\/market-research\/service\/location-technologies\/."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1939","DOI":"10.1016\/j.comcom.2012.06.004","article-title":"A survey of active and passive indoor localisation systems","volume":"35","author":"Deak","year":"2012","journal-title":"Comput. Commun."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.comcom.2015.03.001","article-title":"A survey of calibration-free indoor positioning systems","volume":"66","author":"Hossain","year":"2015","journal-title":"Comput. Commun."},{"key":"ref_4","first-page":"121","article-title":"A survey of indoor positioning and object locating systems","volume":"10","author":"Koyuncu","year":"2010","journal-title":"IJCSNS Int. J. Comput. Sci. Netw. Secur."},{"key":"ref_5","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. C Appl. Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1017\/S0373463314000551","article-title":"Precise indoor positioning and attitude determination using terrestrial ranging signals","volume":"68","author":"Jiang","year":"2015","journal-title":"J. Navig."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"707","DOI":"10.3390\/s16050707","article-title":"Ultra wideband indoor positioning technologies: Analysis and recent advances","volume":"16","author":"Alarifi","year":"2016","journal-title":"Sensors"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Yu, F., Jiang, M., Liang, J., Qin, X., Hu, M., Peng, T., and Hu, X. (2014). 5G WiFi signal-based indoor localization system using cluster k-nearest neighbor algorithm. Int. J. Distrib. Sens. Netw., 2014.","DOI":"10.1155\/2014\/247525"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kriz, P., Maly, F., and Kozel, T. (2016). Improving indoor localization using bluetooth low energy beacons. Mob. Inf. Syst., 2016.","DOI":"10.1155\/2016\/2083094"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Cheon, J., Hwang, H., Kim, D., and Jung, Y. (2016). IEEE 802.15. 4 Zigbee-based time-of-arrival estimation for wireless sensor networks. Sensors, 16.","DOI":"10.3390\/s16020203"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.autcon.2013.06.012","article-title":"RFID indoor location identification for construction projects","volume":"39","author":"Montaser","year":"2014","journal-title":"Autom. Constr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1109\/SURV.2009.090103","article-title":"A survey of indoor positioning systems for wireless personal networks","volume":"11","author":"Gu","year":"2009","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_13","unstructured":"Bisio, I., Lavagetto, F., Marchese, M., and Sciarrone, A. (2013, January 7\u201310). Performance comparison of a probabilistic fingerprint-based indoor positioning system over different smartphones. Proceedings of the 2013 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS)\u2014Part of SummerSim 2013 Multiconference, Toronto, ON, Canada."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.pmcj.2016.02.001","article-title":"Smart probabilistic fingerprinting for WiFi-based indoor positioning with mobile devices","volume":"31","author":"Bisio","year":"2016","journal-title":"Pervasive Mob. Comput."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1109\/TMM.2013.2239631","article-title":"GPS\/HPS-and Wi-fi fingerprint-based location recognition for check-in applications over smartphones in cloud-based LBSs","volume":"15","author":"Bisio","year":"2013","journal-title":"IEEE Trans. Multimedia"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bisio, I., Lavagetto, F., Marchese, M., and Sciarrone, A. (2013, January 9\u201313). Energy efficient WiFi-based fingerprinting for indoor positioning with smartphones. Proceedings of the 2013 IEEE Globecom Workshops (GC Wkshps), Atlanta, GA, USA.","DOI":"10.1109\/GLOCOMW.2013.6855683"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"737","DOI":"10.3390\/s16050737","article-title":"On the choice of access point selection criterion and other position estimation characteristics for WLAN-based indoor positioning","volume":"16","author":"Laitinen","year":"2016","journal-title":"Sensors"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Razavi, A., Valkama, M., and Lohan, E.S. (2015, January 6\u201310). K-means fingerprint clustering for low-complexity floor estimation in indoor mobile localization. Proceedings of the Globecom Workshop on Localization and Tracking: Indoors, Outdoors and Emerging Networks, San Diego, CA, USA.","DOI":"10.1109\/GLOCOMW.2015.7414026"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Huang, Z., Xia, J., Yu, H., Guan, Y., and Chen, J. (2014, January 23\u201325). Clustering combined indoor localization algorithms for crowdsourcing devices: Mining RSSI relative relationship. Proceedings of the Wireless Communications and Signal Processing (WCSP), Hefei, China.","DOI":"10.1109\/WCSP.2014.6992130"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Di, X., Tian, J., and Chen, P. (2016, January 13\u201315). A WLAN planning method for indoor positioning system. Proceedings of the 2016 International Conference on Information Networking (ICOIN), Kota Kinabalu, Malaysia.","DOI":"10.1109\/ICOIN.2016.7427081"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Du, X., and Yang, K. (2016). A Map-assisted WiFi AP placement algorithm enabling mobile device\u2019s indoor positioning. IEEE Syst. J., PP.","DOI":"10.1109\/JSYST.2016.2525814"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Laitinen, E., and Lohan, E.S. (2016, January 28\u201330). Access point topology evaluation and optimization based on Cram\u00e9r-Rao Lower Bound for WLAN indoor positioning. Proceedings of the 2016 International Conference on Localization and GNSS (ICL-GNSS), Barcelona, Spain.","DOI":"10.1109\/ICL-GNSS.2016.7533850"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Liu, W., Fu, X., Deng, Z., Xu, L., and Jiao, J. (2016, January 4\u20137). Smallest enclosing circle-based fingerprint clustering and modified-WKNN matching algorithm for indoor positioning. Proceedings of the 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Madrid, Spain.","DOI":"10.1109\/IPIN.2016.7743694"},{"key":"ref_24","first-page":"3441","article-title":"A survey of grid based clustering algorithms","volume":"2","author":"Ilango","year":"2010","journal-title":"Int. J. Eng. Sci. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2139","DOI":"10.3724\/SP.J.1016.2012.02139","article-title":"Index filtering algorithm based on minimum enclosing circle partition","volume":"35","author":"Chen","year":"2012","journal-title":"Chin. J. Comput."},{"key":"ref_26","first-page":"97","article-title":"Optimization study on k value of k-means algorithm","volume":"2","author":"Yang","year":"2006","journal-title":"Syst. Eng. Theory Pract."},{"key":"ref_27","unstructured":"Bahl, P., and Padmanabhan, V.N. (2000, January 26\u201330). RADAR: An in-building RF-based user location and tracking system. Proceedings of the Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, Israel."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Youssef, M., and Agrawala, A. (2005, January 6\u20138). The Horus WLAN location determination system. Proceedings of the 3rd International Conference on Mobile Systems, Applications, and Services, Seattle, WA, USA.","DOI":"10.1145\/1067170.1067193"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/12\/2055\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:27:56Z","timestamp":1760210876000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/12\/2055"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,2]]},"references-count":28,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2016,12]]}},"alternative-id":["s16122055"],"URL":"https:\/\/doi.org\/10.3390\/s16122055","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2016,12,2]]}}}