{"id":2287,"date":"2019-09-21T12:48:22","date_gmt":"2019-09-21T08:48:22","guid":{"rendered":"http:\/\/journal.geonatres.az\/?p=2287"},"modified":"2019-09-23T23:49:29","modified_gmt":"2019-09-23T19:49:29","slug":"wi-fi-barmaq-izi-metodu-%c9%99sasinda-daxili-movqenin-qapali-m%c9%99kanin-oyr%c9%99nilm%c9%99si","status":"publish","type":"post","link":"https:\/\/journal.geonatres.az\/en\/wi-fi-barmaq-izi-metodu-%c9%99sasinda-daxili-movqenin-qapali-m%c9%99kanin-oyr%c9%99nilm%c9%99si\/","title":{"rendered":"AN INDOOR POSITIONING STUDY BASED ON THE WI-FI FINGERPRINTING METHOD"},"content":{"rendered":"

\u00d6zdemir B., Ceylan A.<\/strong><\/p>\n

Selcuk University, Engineering Faculty, Department of Geomatic Engineering, 42075 Konya, Turkey<\/em> – (behlulozdemir, aceylan@selcuk.edu.tr)<\/p>\n

 <\/p>\n

A b s t r a c t<\/strong><\/p>\n

Indoor Positioning is a very popular research area because of its wide range of applications, mainly providing location-based services. Many technologies and methods are suggested for estimating the location of the user in indoor environments where GNSS signals are mostly attenuated or completely lost. Some of these technologies are Bluetooth Low Energy, Wi-Fi, RFID, ZigBee and so on. The methods used for position estimation are various methods such as Angle of Arrival (AoA), Time of Arrival (ToA), Fingerprinting, Dead Reckoning and Map Matching. Among these methods, fingerprinting is promising and mostly preferred method.<\/p>\n

In this study, fingerprinting with Wireless LAN signals was applied in Selcuk University Faculty of Engineering and obtained accuracy was examined. Several factors have been taking into account, such as the location of access points that affect location accuracy, and the number of access points on a floor.<\/p>\n

Keywords:\u00a0<\/strong>Indoor Positioning,\u00a0WLAN,\u00a0Fingerprinting,\u00a0Nearest Neighbour<\/p>\n

 <\/p>\n

REFERENCES<\/strong><\/p>\n

Chen, Y., D. Lymberopoulos, J. Liu and B. Priyantha (2012). FM-based indoor localization. Proceedings of the 10th international conference on Mobile sys\u00adtems, applications, and services, ACM.<\/p>\n

Chung, J., M. Donahoe, C. Schmandt, I.-J. Kim, P. Razavai and M. Wiseman (2011). Indoor location sen\u00adsing using geo-magnetism. Proceedings of the 9th international conference on Mobile systems, ap\u00adplications, and services, ACM.<\/p>\n

Huang, W., Y. Xiong, X.-Y. Li, H. Lin, X. Mao, P. Yang and Y. Liu (2014). Shake and walk: Acoustic di\u00adrec\u00adtion finding and fine-grained indoor localization using smartphones. INFOCOM, 2014 Proceedings IEEE, IEEE.<\/p>\n

Kuo, Y.-S., P. Pannuto, K.-J. Hsiao and P. Dutta (2014). Luxapose: Indoor positioning with mobile phones and visible light. Proceedings of the 20th annual in\u00adter\u00adnational conference on Mobile computing and net\u00adworking, ACM.<\/p>\n

Liu, S., Y. Jiang and A. Striegel (2014). “Face-to-face pro\u00adximity estimationusing bluetooth on smart\u00adpho\u00adnes.” IEEE Transactions on Mobile Computing 13(4): 811-823.<\/p>\n

Mathisen, A., S. K. Sorensen, A. Stisen, H. Blunck and K. Gronbaek (2016). “A Comparative Analysis of In\u00addoor WiFi Positioning at a Large Building Com\u00adplex.” 2016 International Conference on Indoor Po\u00adsi\u00adti\u00adoning and Indoor Navigation (Ipin).<\/p>\n

Ni, L. M., Y. Liu, Y. C. Lau and A. P. Patil (2003). LAND\u00adMARC: indoor location sensing using active RFID. Pervasive Computing and Communications, 2003.(PerCom 2003). Proceedings of the First IEEE International Conference on, IEEE.<\/p>\n

Sun, Z., A. Purohit, K. Chen, S. Pan, T. Pering and P. Zhang (2011). PANDAA: physical arrangement detection of networked devices through ambient-sound awareness. Proceedings of the 13th inter\u00adna\u00adti\u00adonal conference on Ubiquitous computing, ACM.<\/p>\n

Thuong, N. T., H. T. Phong, D. T. Do, P. V. Hieu and D. T. Loc (2016). “Android Application for WiFi ba\u00adsed Indoor Position: System Design and Per\u00adfor\u00adman\u00adce Analysis.” 2016 International Conference on In\u00adfor\u00admation Networking (Icoin): 416-419.<\/p>\n

Wang, J. and D. Katabi (2013). Dude, where’s my card?: RFID positioning that works with multipath and non-line of sight. ACM SIGCOMM Computer Com\u00admunication Review, ACM.<\/p>\n

Xie, H., T. Gu, X. Tao, H. Ye and J. Lv (2014). MaLoc: A practical magnetic fingerprinting approach to in\u00addoor localization using smartphones. Proceedings of the 2014 ACM International Joint Conference on Per\u00advasive and Ubiquitous Computing, ACM.<\/p>\n

Yang, L., Y. Chen, X.-Y. Li, C. Xiao, M. Li and Y. Liu (2014). Tagoram: Real-time tracking of mobile RFID tags to high precision using COTS devices. Pro\u00adceedings of the 20th annual international con\u00adfer\u00adence on Mobile computing and networking, ACM.<\/p>\n

Yang, Z., Z. Wang, J. Zhang, C. Huang and Q. Zhang (2015). Wearables can afford: Light-weight indoor po\u00adsitioning with visible light. Proceedings of the 13th annual international conference on mobile sys\u00adtems, applications, and services, ACM.<\/p>\n

Yoon, S., K. Lee and I. Rhee (2013). FM-based indoor localization via automatic fingerprint DB con\u00adstruc\u00adtion and matching. Proceeding of the 11th annual in\u00adter\u00adnational conference on Mobile systems, ap\u00adpli\u00adca\u00adti\u00adons, and services, ACM.<\/p>\n

Zandbergen, P. A. (2009). “Accuracy of iPhone Lo\u00adca\u00adtions: A Comparison of Assisted GPS, WiFi and Cellular Positioning.” Transactions in Gis 13: 5-25.<\/p>\n

Zhao, X., Z. Xiao, A. Markham, N. Trigoni and Y. Ren (2014). Does BTLE measure up against WiFi? A comparison of indoor location performance. Euro\u00adpe\u00adan Wireless 2014; 20th European Wireless Con\u00adfe\u00adrence; Proceedings of, VDE.<\/p>\n

Zheng, Z. W., Y. Y. Chen, T. He, F. Li and D. Chen (2015). “Weight-RSS: A Calibration-Free and Ro\u00adbust Method for WLAN-Based Indoor Positioning.” In\u00adternational Journal of Distributed Sensor Net\u00adworks.<\/p>\n

 <\/p>\n

\n
Download the article<\/strong><\/a><\/article>\n<\/section>\n