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[:az]WI-FI BARMAQ İZİ METODU ƏSASINDA DAXİLİ MÖVQENİN (QAPALI MƏKANIN) ÖYRƏNİLMƏSİ[:ru]ВНУТРЕННЕЕ ИССЛЕДОВАНИЕ ПОЗИЦИОНИРОВАНИЯ НА ОСНОВЕ МЕТОДА ПЕЧАТИ WI-FI[:en]AN INDOOR POSITIONING STUDY BASED ON THE WI-FI FINGERPRINTING METHOD[:]
[:az]Özdemir B., Ceylan A.
Xülasə.
Geniş applikasiyaların yayılması və əsas Location-based servislərin təmin edilməsinə görə qapalı məkan məşhur tədqiqat ərazilərindən biridir. GNSS siqnallarının daha çox zəiflədildiyi və ya tamamilə itirildiyi yerlərdə istifadəçinin yerini qiymətləndirmək üçün bir çox texnologiya və üsul təklif olunur. Bu texnologiyalardan bəziləri Bluetooth Low Energy, Wi-Fi, RFID, ZigBee və başqalarıdır. Mövqenin qiymətləndirilməsi üçün istifadə edilən üsullar bunlardır: Angle of Arrival (AoA) -Çatma bucağı, Time of Arrival (ToA) – Çatma zamanı, Fingerprinting-Barmaq izi, Dead Reckoning and Map Matching. Bu metodlardan barmaq izi ümidverici və ən çox üstünlük verilən üsuldur.
Bu tədqiqatda Səlcuq Universiteti Mühəndislik Fakültəsində Wireless LAN siqnalları ilə barmaq izi tətbiq edilmiş və dəqiqliyi araşdırılmışdır. Yerləşmə dəqiqliyinə təsir göstərən qəbul nöqtələrinin yerləşməsi və mərtəbədə qəbul nöqtələrinin sayı kimi bir neçə amil nəzərə alınmışdır.
Açar sözlər: Indoor Positioning –Qapalı mövqe, yerləşmə, WLAN, Fingerprinting- barmaq izi, Nearest Neighbour
ƏDƏBİYAT
Chen, Y., D. Lymberopoulos, J. Liu and B. Priyantha (2012). FM-based indoor localization. Proceedings of the 10th international conference on Mobile systems, applications, and services, ACM.
Chung, J., M. Donahoe, C. Schmandt, I.-J. Kim, P. Razavai and M. Wiseman (2011). Indoor location sensing using geo-magnetism. Proceedings of the 9th international conference on Mobile systems, applications, and services, ACM.
Huang, W., Y. Xiong, X.-Y. Li, H. Lin, X. Mao, P. Yang and Y. Liu (2014). Shake and walk: Acoustic direction finding and fine-grained indoor localization using smartphones. INFOCOM, 2014 Proceedings IEEE, IEEE.
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 international conference on Mobile computing and networking, ACM.
Liu, S., Y. Jiang and A. Striegel (2014). “Face-to-face proximity estimationusing bluetooth on smartphones.” IEEE Transactions on Mobile Computing 13(4): 811-823.
Mathisen, A., S. K. Sorensen, A. Stisen, H. Blunck and K. Gronbaek (2016). “A Comparative Analysis of Indoor WiFi Positioning at a Large Building Complex.” 2016 International Conference on Indoor Positioning and Indoor Navigation (Ipin).
Ni, L. M., Y. Liu, Y. C. Lau and A. P. Patil (2003). LANDMARC: indoor location sensing using active RFID. Pervasive Computing and Communications, 2003.(PerCom 2003). Proceedings of the First IEEE International Conference on, IEEE.
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 international conference on Ubiquitous computing, ACM.
Thuong, N. T., H. T. Phong, D. T. Do, P. V. Hieu and D. T. Loc (2016). “Android Application for WiFi based Indoor Position: System Design and Performance Analysis.” 2016 International Conference on Information Networking (Icoin): 416-419.
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 Communication Review, ACM.
Xie, H., T. Gu, X. Tao, H. Ye and J. Lv (2014). MaLoc: A practical magnetic fingerprinting approach to indoor localization using smartphones. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, ACM.
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. Proceedings of the 20th annual international conference on Mobile computing and networking, ACM.
Yang, Z., Z. Wang, J. Zhang, C. Huang and Q. Zhang (2015). Wearables can afford: Light-weight indoor positioning with visible light. Proceedings of the 13th annual international conference on mobile systems, applications, and services, ACM.
Yoon, S., K. Lee and I. Rhee (2013). FM-based indoor localization via automatic fingerprint DB construction and matching. Proceeding of the 11th annual international conference on Mobile systems, applications, and services, ACM.
Zandbergen, P. A. (2009). “Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning.” Transactions in Gis 13: 5-25.
Zhao, X., Z. Xiao, A. Markham, N. Trigoni and Y. Ren (2014). Does BTLE measure up against WiFi? A comparison of indoor location performance. European Wireless 2014; 20th European Wireless Conference; Proceedings of, VDE.
Zheng, Z. W., Y. Y. Chen, T. He, F. Li and D. Chen (2015). “Weight-RSS: A Calibration-Free and Robust Method for WLAN-Based Indoor Positioning.” International Journal of Distributed Sensor Networks.
Məqaləni yüklə[:ru]Оздемир Б., Джейлан А.
Аннотация. Indoor Positioning является очень популярной областью исследований из-за ее широкого спектра приложений, в основном предоставляющих услуги на основе определения местоположения. Многие технологии и методы предлагаются для оценки местоположения пользователя в помещениях, где сигналы GNSS в основном ослаблены или полностью потеряны. Некоторыми из этих технологий являются Bluetooth Low Energy, Wi-Fi, RFID, ZigBee и так далее. Методы, используемые для оценки местоположения, представляют собой различные методы, такие как угол прихода (AoA), время прибытия (ToA), дактилоскопия, мертвый расчет и сопоставление карты. Среди этих методов дактилоскопия является перспективным и наиболее предпочтительным методом.
В этом исследовании дактилоскопия с сигналами беспроводной локальной сети была применена на инженерном факультете Сельджукского университета и была изучена полученная точность. Несколько факторов были приняты во внимание, такие как расположение точек доступа, которые влияют на точность определения местоположения, и количество точек доступа на этаже.
Ключевые слова: внутреннее позиционирование, WLAN, дактилоскопия, ближайший сосед
ЛИТЕРАТУРА
Chen, Y., D. Lymberopoulos, J. Liu and B. Priyantha (2012). FM-based indoor localization. Proceedings of the 10th international conference on Mobile systems, applications, and services, ACM.
Chung, J., M. Donahoe, C. Schmandt, I.-J. Kim, P. Razavai and M. Wiseman (2011). Indoor location sensing using geo-magnetism. Proceedings of the 9th international conference on Mobile systems, applications, and services, ACM.
Huang, W., Y. Xiong, X.-Y. Li, H. Lin, X. Mao, P. Yang and Y. Liu (2014). Shake and walk: Acoustic direction finding and fine-grained indoor localization using smartphones. INFOCOM, 2014 Proceedings IEEE, IEEE.
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 international conference on Mobile computing and networking, ACM.
Liu, S., Y. Jiang and A. Striegel (2014). “Face-to-face proximity estimationusing bluetooth on smartphones.” IEEE Transactions on Mobile Computing 13(4): 811-823.
Mathisen, A., S. K. Sorensen, A. Stisen, H. Blunck and K. Gronbaek (2016). “A Comparative Analysis of Indoor WiFi Positioning at a Large Building Complex.” 2016 International Conference on Indoor Positioning and Indoor Navigation (Ipin).
Ni, L. M., Y. Liu, Y. C. Lau and A. P. Patil (2003). LANDMARC: indoor location sensing using active RFID. Pervasive Computing and Communications, 2003.(PerCom 2003). Proceedings of the First IEEE International Conference on, IEEE.
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 international conference on Ubiquitous computing, ACM.
Thuong, N. T., H. T. Phong, D. T. Do, P. V. Hieu and D. T. Loc (2016). “Android Application for WiFi based Indoor Position: System Design and Performance Analysis.” 2016 International Conference on Information Networking (Icoin): 416-419.
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 Communication Review, ACM.
Xie, H., T. Gu, X. Tao, H. Ye and J. Lv (2014). MaLoc: A practical magnetic fingerprinting approach to indoor localization using smartphones. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, ACM.
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. Proceedings of the 20th annual international conference on Mobile computing and networking, ACM.
Yang, Z., Z. Wang, J. Zhang, C. Huang and Q. Zhang (2015). Wearables can afford: Light-weight indoor positioning with visible light. Proceedings of the 13th annual international conference on mobile systems, applications, and services, ACM.
Yoon, S., K. Lee and I. Rhee (2013). FM-based indoor localization via automatic fingerprint DB construction and matching. Proceeding of the 11th annual international conference on Mobile systems, applications, and services, ACM.
Zandbergen, P. A. (2009). “Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning.” Transactions in Gis 13: 5-25.
Zhao, X., Z. Xiao, A. Markham, N. Trigoni and Y. Ren (2014). Does BTLE measure up against WiFi? A comparison of indoor location performance. European Wireless 2014; 20th European Wireless Conference; Proceedings of, VDE.
Zheng, Z. W., Y. Y. Chen, T. He, F. Li and D. Chen (2015). “Weight-RSS: A Calibration-Free and Robust Method for WLAN-Based Indoor Positioning.” International Journal of Distributed Sensor Networks.
Скачать статью[:en]Özdemir B., Ceylan A.
Selcuk University, Engineering Faculty, Department of Geomatic Engineering, 42075 Konya, Turkey – (behlulozdemir, aceylan@selcuk.edu.tr)
A b s t r a c t
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.
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.
Keywords: Indoor Positioning, WLAN, Fingerprinting, Nearest Neighbour
REFERENCES
Chen, Y., D. Lymberopoulos, J. Liu and B. Priyantha (2012). FM-based indoor localization. Proceedings of the 10th international conference on Mobile systems, applications, and services, ACM.
Chung, J., M. Donahoe, C. Schmandt, I.-J. Kim, P. Razavai and M. Wiseman (2011). Indoor location sensing using geo-magnetism. Proceedings of the 9th international conference on Mobile systems, applications, and services, ACM.
Huang, W., Y. Xiong, X.-Y. Li, H. Lin, X. Mao, P. Yang and Y. Liu (2014). Shake and walk: Acoustic direction finding and fine-grained indoor localization using smartphones. INFOCOM, 2014 Proceedings IEEE, IEEE.
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 international conference on Mobile computing and networking, ACM.
Liu, S., Y. Jiang and A. Striegel (2014). “Face-to-face proximity estimationusing bluetooth on smartphones.” IEEE Transactions on Mobile Computing 13(4): 811-823.
Mathisen, A., S. K. Sorensen, A. Stisen, H. Blunck and K. Gronbaek (2016). “A Comparative Analysis of Indoor WiFi Positioning at a Large Building Complex.” 2016 International Conference on Indoor Positioning and Indoor Navigation (Ipin).
Ni, L. M., Y. Liu, Y. C. Lau and A. P. Patil (2003). LANDMARC: indoor location sensing using active RFID. Pervasive Computing and Communications, 2003.(PerCom 2003). Proceedings of the First IEEE International Conference on, IEEE.
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 international conference on Ubiquitous computing, ACM.
Thuong, N. T., H. T. Phong, D. T. Do, P. V. Hieu and D. T. Loc (2016). “Android Application for WiFi based Indoor Position: System Design and Performance Analysis.” 2016 International Conference on Information Networking (Icoin): 416-419.
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 Communication Review, ACM.
Xie, H., T. Gu, X. Tao, H. Ye and J. Lv (2014). MaLoc: A practical magnetic fingerprinting approach to indoor localization using smartphones. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, ACM.
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. Proceedings of the 20th annual international conference on Mobile computing and networking, ACM.
Yang, Z., Z. Wang, J. Zhang, C. Huang and Q. Zhang (2015). Wearables can afford: Light-weight indoor positioning with visible light. Proceedings of the 13th annual international conference on mobile systems, applications, and services, ACM.
Yoon, S., K. Lee and I. Rhee (2013). FM-based indoor localization via automatic fingerprint DB construction and matching. Proceeding of the 11th annual international conference on Mobile systems, applications, and services, ACM.
Zandbergen, P. A. (2009). “Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning.” Transactions in Gis 13: 5-25.
Zhao, X., Z. Xiao, A. Markham, N. Trigoni and Y. Ren (2014). Does BTLE measure up against WiFi? A comparison of indoor location performance. European Wireless 2014; 20th European Wireless Conference; Proceedings of, VDE.
Zheng, Z. W., Y. Y. Chen, T. He, F. Li and D. Chen (2015). “Weight-RSS: A Calibration-Free and Robust Method for WLAN-Based Indoor Positioning.” International Journal of Distributed Sensor Networks.
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