{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T21:05:27Z","timestamp":1773695127947,"version":"3.50.1"},"reference-count":22,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,4,8]],"date-time":"2019-04-08T00:00:00Z","timestamp":1554681600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The smartphone market is rapidly spreading, coupled with several services and applications. Some of these services require the knowledge of the exact location of their handsets. The Global Positioning System (GPS) suffers from accuracy deterioration and outages in indoor environments. The Wi-Fi Fingerprinting approach has been widely used in indoor positioning systems. In this paper, Principal Component Analysis (PCA) is utilized to improve the performance and to reduce the computation complexity of the Wi-Fi indoor localization systems based on a machine learning approach. The experimental setup and performance of the proposed method were tested in real indoor environments at a large-scale environment of 960 m2 to analyze the performance of different machine learning approaches. The results show that the performance of the proposed method outperforms conventional indoor localization techniques based on machine learning techniques.<\/jats:p>","DOI":"10.3390\/s19071678","type":"journal-article","created":{"date-parts":[[2019,4,8]],"date-time":"2019-04-08T11:54:52Z","timestamp":1554724492000},"page":"1678","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Comprehensive Investigation on Principle Component Large-Scale Wi-Fi Indoor Localization"],"prefix":"10.3390","volume":"19","author":[{"given":"Ahmed H.","family":"Salamah","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering Department, University of Waterloo, Waterloo, ON N2L 3G1, Canada"},{"name":"Electronics and Communications Engineering Department, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8821-7164","authenticated-orcid":false,"given":"Mohamed","family":"Tamazin","sequence":"additional","affiliation":[{"name":"Electronics and Communications Engineering Department, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4132-3984","authenticated-orcid":false,"given":"Maha A.","family":"Sharkas","sequence":"additional","affiliation":[{"name":"Electronics and Communications Engineering Department, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Khedr","sequence":"additional","affiliation":[{"name":"Electronics and Communications Engineering Department, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Mahmoud","sequence":"additional","affiliation":[{"name":"Electronics and Communications Engineering Department, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Torres-Sospedra, J., Montoliu, R., Mart\u00ednez-Us\u00f3, A., Avariento, J.P., Arnau, T.J., Benedito-Bordonau, M., and Huerta, J. (2014, January 27\u201330). UJIIndoorLoc: A new multi-building and multi-floor database for WLAN fingerprint-based indoor localization problems. Proceedings of the 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, Korea.","DOI":"10.1109\/IPIN.2014.7275492"},{"key":"ref_2","unstructured":"Misra, P., and Enge, P. (2006). Global Positioning System: Signals, Measurements and Performance, Ganga-Jamuna Press. [2nd ed.]."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Salamah, A.H., Tamazin, M., Sharkas, M.A., and Khedr, M. (2016, January 4\u20137). An enhanced WiFi indoor localization system based on machine learning. Proceedings of the 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Madrid, Spain.","DOI":"10.1109\/IPIN.2016.7743586"},{"key":"ref_4","unstructured":"Z\u00e1ruba, G.V., Huber, M., Kamangar, F.A., and Chlarmtac, I. (December, January 29). Monte Carlo sampling based in-home Location tracking with minimal RF infrastructure requirements. Proceedings of the IEEE Global Telecommunications Conference GLOBECOM \u201904, Dallas, TX, USA."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"109","DOI":"10.3182\/20100906-3-IT-2019.00021","article-title":"Comparison of opportunistic signals for localisation","volume":"43","author":"Merry","year":"2010","journal-title":"IFAC Proc. Vol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/98.626982","article-title":"A new location technique for the active office","volume":"4","author":"Ward","year":"1997","journal-title":"IEEE Pers. Commun."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Kj\u00e6rgaard, M.B. (2007). A Taxonomy for radio location fingerprinting. International Symposium on Location-and Context-Awareness, Springer.","DOI":"10.1007\/978-3-540-75160-1_9"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1186\/1687-1499-2013-272","article-title":"Fingerprint indoor positioning algorithm based on affinity propagation clustering","volume":"2013","author":"Tian","year":"2013","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"key":"ref_9","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 IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, Israel."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zang, H., Baccelli, F., and Bolot, J. (2010, January 14\u201319). Bayesian inference for localization in cellular networks. Proceedings of the IEEE INFOCOM, San Diego, CA, USA.","DOI":"10.1109\/INFCOM.2010.5462018"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1007\/s11276-006-0725-7","article-title":"The horus location determination system","volume":"14","author":"Youssef","year":"2007","journal-title":"Wirel. Netw."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"King, T., Kopf, S., Haenselmann, T., Lubberger, C., and Effelsberg, W. (2006, January 29). COMPASS: A probabilistic indoor positioning system based on 802.11 and digital compasses. Proceedings of the 1st ACM International Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization (WiNTECH), Los Angeles, CA, USA.","DOI":"10.1145\/1160987.1160995"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Ding, X., Li, H., Li, F., and Wu, J. (2008, January 18\u201320). A novel infrastructure WLAN locating method based on neural network. Proceedings of the 4th Asian Conference on Internet Engineering, Bangkok, Thailand.","DOI":"10.1145\/1503370.1503385"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lkopf, B., and Smola, A.J. (2002). Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, MIT Press.","DOI":"10.7551\/mitpress\/4175.001.0001"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"914","DOI":"10.3969\/j.issn.1004-4132.2010.05.028","article-title":"Multilayer ANN indoor location system with area division in WLAN environment","volume":"21","author":"Zhou","year":"2010","journal-title":"J. Syst. Eng. Electron."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/TMC.2011.30","article-title":"Principal component localization in indoor WLAN environments","volume":"11","author":"Fang","year":"2012","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_17","unstructured":"Lima, M.W.S., de Oliveira, H.A.F., dos Santos, E.M., de Moura, E.S., Costa, R.K., and Levorato, M. (2018, January 1\u20133). Efficient and robust WiFi indoor positioning using hierarchical navigable small world graphs. Proceedings of the 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Cambridge, MA, USA."},{"key":"ref_18","first-page":"64","article-title":"Radio-map establishment based on fuzzy clustering for WLAN hybrid KNN\/ANN indoor positioning","volume":"7","author":"Mu","year":"2010","journal-title":"Chin. Commun."},{"key":"ref_19","unstructured":"Joachims, T. (1999, January 27\u201330). Transductive inference for text classification using support vector machines. Proceedings of the 16th International Conference on Machine Learning (ICML-99), Bled, Slovenia."},{"key":"ref_20","unstructured":"Krishnakumar, A.S., and Krishnan, P. (2005, January 19\u201322). The theory and practice of signal strength-based location estimation. Proceedings of the 2005 International Conference on Collaborative Computing: Networking, Applications and Worksharing, San Jose, CA, USA."},{"key":"ref_21","unstructured":"Battiti, R., Le, N.T., and Villani, A. (2002). Location-Aware Computing: A Neural Network Model for Determining Location in Wireless LANs, Information Engineering and Computer Science."},{"key":"ref_22","unstructured":"(2018, December 10). Cisco Aironet 1600 Series Access Points. Available online: https:\/\/www.cisco.com\/c\/en\/us\/td\/docs\/wireless\/access_point\/1600\/quick\/guide\/ap1600getstart.pdf."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/7\/1678\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:43:45Z","timestamp":1760186625000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/7\/1678"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,8]]},"references-count":22,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2019,4]]}},"alternative-id":["s19071678"],"URL":"https:\/\/doi.org\/10.3390\/s19071678","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,8]]}}}