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A RESEARCH ON INDOOR POSITIONING SYSTEMS

Year 2020, Volume: 8 Issue: 5, 90 - 105, 29.12.2020
https://doi.org/10.21923/jesd.831775

Abstract

Today, positioning technology takes an important place. Using the data received from satellites, GPS (Global Positioning Systems) is with us in most areas of our lives. GPS Technology works well in outdoor. However, when we consider the fact that satellite signals interact with walls, we observe that the issue of positioning in indoor areas is more complex than in outdoor or open areas. The need for indoor positioning services is increasing day by day. Today, different approaches have been developed in order to realize indoor positioning due to the distortion of satellite signals as a result of manipulation. In order to improve these approaches used in indoor positioning systems, many different methods such as the use of machine learning and hybrid integration of different approaches are used. There are many literature works with different working structures with the combination of different algorithms and methods. In this work, systems used in indoor positioning are reviewed.

Project Number

3180329

References

  • Abbas, M., Elhamshary M., Rizk, H., Torki, M., Youssef, M., 2019. WiDeep: WiFi-based Accurate and Robust Indoor Localization System using Deep Learning. 2019 IEEE International Conference on Pervasive Computing and Communications. 1-10.
  • Alarifi, A., Al-Salman, A., Alsaleh, M., Alnafessah, A., Al-Hadhrami, S., Al-Ammar, M. A., Al-Khalifa, H. S., 2016. Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances. Sensors. 16, 1-36.
  • Belhadi, Z., Fergani, L., Fergani, B., Laheurte, J, 2014, RFID Tag Indoor Localization by Fingerprinting Methods. International Conference on Multimedia Computing and Systems (ICMCS), 10.1109/ICMCS.2014.6911192
  • Cengiz, K., 2020, Analyzing The Performance of Pure Lateration in Indoor Environments with Various Performance Metrics, Commun.Fac.Sci.Univ.Ank.Series A2-A3, 62 (2), 123-133.
  • Cengiz, K., 2020, Comprehensive Analysis on Least Squares Lateration for Indoor Positioning Systems, IEEE Internet of Things Journal, 10.1109/JIOT.2020.3020888
  • Doughangi, H., 2017. Kapalı Alanda Konum Belirleme Sistemi. Yüksek Lisans Tezi. İstanbul Ticaret Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Anabilim Dalı, İstanbul, Türkiye.
  • Ergen, E., Artan İlter, D., Tekçe, I. A., Kula, B., Dönmez, D., 2017. Utilizing Indoor Locali-zation Technologies For Occupant Feedback Collection. 7th International Congress on Construction Management-IMO, 245 – 255.
  • Fischer, G., Dietrich, B., Winkler, F., 2004. Bluetooth Indoor Localization System, WPNC’04, 147-152.
  • İnternet: Floreani, L., 2015. Indoor positioning with beacons and mobile devices. URL: https://bits.theorem.co/indoor-positioning-with-beacons/, Son Erişim Tarihi: 28.08.2019
  • İnternet: Gifford, M., 2018, Indoor Positioning with Ultrasonic/Ultrasound , URL: https://www.leverege.com/blogpost/ultrasonic-indoor-positioning, Son Erişim Tarihi: 30.08.2019
  • Jianyong, Z., Haiyong, L., Zili, C., Zhaohui, L., 2014. RSSI Based Bluetooth Low Energy Indoor Positioning. IPIN, 10.1109/IPIN.2014.7275525.
  • Küçük, K., 2016. Geniş bant konum belirleme sistemi performans analizi ve iyileştirilmesi. SAUFENBILDER, 21, 1-33.
  • Lembo, S., Horsmanheimo, S., Honkamaa, P., 2019. Indoor positioning based on RSS fingerprinting in a LTE network: method based on Genetic Algorithms. 2019 IEEE International Conference on Communications Workshops (ICC Workshops), 1-6.
  • Li, G., Geng, E., Ye, Z., Xu, Y., Zhu. H., 2018. Indoor Positioning Algorithm Based on the Improved RSSI Distance Model. 14th IEEE International Conference on Signal Processing (ICSP), 129-133.
  • Morais, K., Bosco, D., 2017. RFID based Indoor Positioning System. IJSRD, 4(11), 454-457.
  • Oldenburg, L., Meznaric, J., Lukau, E., Hechenberger A., 2016. Indoor Navigation/Indoor Positioning with mobile Devices, 10.13140/RG.2.1.3100.4568.
  • Özdemir, B. N., Ceylan, A., Alçay, S., Yiğit, C.Ö., 2014. Kapalı Mekanlarda Uygulanan Konum Belirleme Yöntemleri Ve Karşılaştırılması. Harita ve Kadastro Mühendisleri Odası, Mühendislik Ölçmeleri STB Komisyonu 7. Mühendislik Ölçmeleri Sempozyumu 15-17 Ekim 2014, Hitit Üniversitesi, Çorum, 1-9.
  • Sakpere, W., Oshin, M. A., Mlitwa, N. B. W., 2017. A state-of-the-art survey of indoor posi-tioning and navigation systems and technologies. South African Computer Journal, 29(3), 145.
  • Sugano, M., Kawazoe, T., Ohta, Y., Murata, M., 2006. Indoor Localization System Using Rssi Measurement Of Wireless Sensor Network Based On Zigbee Standard. The 6th IASTED International Multi-Conference on Wireless and Optical Communications, 538.
  • Tsanga, P.Y.P., Wua, C.H., Ipa, W.H., Hoa, G.T.S., Tseb, Y.K, 2015. A Bluetooth-based In-door Positioning System: a Simple and Rapid Approach. Annual Journal IIE, 35, 11-26.
  • Tunca, C., Toplan, E., Işık, S., Ersoy, C., 2014. Yapay Sinir Ağları ile WiFi Tabanlı İç Mekan Konumlandırma. AB 2014, 10.13140/2.1.4021.2486.
  • Wen, L. P., Nee, C. W., Chun, K. M., Shiang-yen, T., Idrus, R., 2011. Application of WiFi-based Indoor Positioning System in Handheld Directory System. 5th Proceedings of the European Computing Conference, 21-27.
  • Xiao, A., Chen, R., Li, D., Chen, Y., Wu, D., 2018. An Indoor Positioning System Based on Static Objects in Large Indoor Scenes by Using Smartphone Cameras. Sensors, 18(7), 2229.
  • Xu, H., Ding, Y., Li, P., Wang, R., 2017. An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor. Sensors, 17(8), 1806.
  • Zegeye, W. K., Amsalu, B., Astatke, Y., Moazzami, F., 2016. WiFi RSS Fingerprinting Indoor Localization for Mobile Devices. UEMCON, 1-6.
  • Zheng, J., Wu, C., Chu, H., Xu, Y., 2011. An Improved RSSI Measurement In Wireless Sensor Networks. SciVerse Science Direct, 15, 876-880.
  • Zou, H., Xie, L., Jia, Q., Wang, H., 2014. Platform and Algorithm Development for a RFID-Based IndoorPositioning System. Unmanned Systems, 2(3), 279-291.

KAPALI MEKAN KONUMLANDIRMA ÜZERİNE BİR ÇALIŞMA

Year 2020, Volume: 8 Issue: 5, 90 - 105, 29.12.2020
https://doi.org/10.21923/jesd.831775

Abstract

Günümüzde konumlandırma teknolojisi birçok alanda önemli yere sahiptir. Uydulardan elde edilen verileri kullanan GPS (Global Positioning Systems) hayatımızın çoğu alanında bizimle birliktedir. GPS Teknolojisi açık alanda gayet düzgün çalışabilmektedir. Ancak uydu sinyallerinin duvarlar ile etkileşime girdiği gerçeğini göz önüne aldığımızda kapalı alanlarda konum bulma konusunun açık alandakine göre daha karmaşık bir durum olduğunu gözlemlemiş oluruz. Gün geçtikçe farklı birçok alanda, kapalı mekan konumlandırma servislerine olan ihtiyaç artmaktadır. Uydu sinyallerinin uğradığı manipülasyon sonucu bozulması sebebiyle kapalı mekan konumlandırma servislerinin gerçekleştirilmesi adına günümüzde farklı yaklaşımlar geliştirilmiştir. Literatürde bu konu üzerine yapılan çalışmalar devam etmekle birlikte geliştirilen bu yaklaşımların iyileştirilmesi ve yeni algoritmaların geliştirilmesi de söz konusudur. Kapalı mekan konumlandırma sistemlerinde kullanılan yaklaşımların iyileştirilmesi hususunda, makine öğreniminden faydalanılması, farklı yaklaşımların hibrit entegrasyonu gibi farklı birçok yönteme başvurulmaktadır. Farklı algoritma ve yöntemlerin bir araya gelmesiyle pek çok farklı çalışma yapısına sahip literatür çalışmaları bulunmaktadır. Bu çalışmada, kapalı mekan konumlandırmada kullanılan sistemler derlenmiş ve bunlar ile ilgili yapılabilecek konular detaylandırılmıştır.

Supporting Institution

TÜBİTAK TEYDEB

Project Number

3180329

References

  • Abbas, M., Elhamshary M., Rizk, H., Torki, M., Youssef, M., 2019. WiDeep: WiFi-based Accurate and Robust Indoor Localization System using Deep Learning. 2019 IEEE International Conference on Pervasive Computing and Communications. 1-10.
  • Alarifi, A., Al-Salman, A., Alsaleh, M., Alnafessah, A., Al-Hadhrami, S., Al-Ammar, M. A., Al-Khalifa, H. S., 2016. Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances. Sensors. 16, 1-36.
  • Belhadi, Z., Fergani, L., Fergani, B., Laheurte, J, 2014, RFID Tag Indoor Localization by Fingerprinting Methods. International Conference on Multimedia Computing and Systems (ICMCS), 10.1109/ICMCS.2014.6911192
  • Cengiz, K., 2020, Analyzing The Performance of Pure Lateration in Indoor Environments with Various Performance Metrics, Commun.Fac.Sci.Univ.Ank.Series A2-A3, 62 (2), 123-133.
  • Cengiz, K., 2020, Comprehensive Analysis on Least Squares Lateration for Indoor Positioning Systems, IEEE Internet of Things Journal, 10.1109/JIOT.2020.3020888
  • Doughangi, H., 2017. Kapalı Alanda Konum Belirleme Sistemi. Yüksek Lisans Tezi. İstanbul Ticaret Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Anabilim Dalı, İstanbul, Türkiye.
  • Ergen, E., Artan İlter, D., Tekçe, I. A., Kula, B., Dönmez, D., 2017. Utilizing Indoor Locali-zation Technologies For Occupant Feedback Collection. 7th International Congress on Construction Management-IMO, 245 – 255.
  • Fischer, G., Dietrich, B., Winkler, F., 2004. Bluetooth Indoor Localization System, WPNC’04, 147-152.
  • İnternet: Floreani, L., 2015. Indoor positioning with beacons and mobile devices. URL: https://bits.theorem.co/indoor-positioning-with-beacons/, Son Erişim Tarihi: 28.08.2019
  • İnternet: Gifford, M., 2018, Indoor Positioning with Ultrasonic/Ultrasound , URL: https://www.leverege.com/blogpost/ultrasonic-indoor-positioning, Son Erişim Tarihi: 30.08.2019
  • Jianyong, Z., Haiyong, L., Zili, C., Zhaohui, L., 2014. RSSI Based Bluetooth Low Energy Indoor Positioning. IPIN, 10.1109/IPIN.2014.7275525.
  • Küçük, K., 2016. Geniş bant konum belirleme sistemi performans analizi ve iyileştirilmesi. SAUFENBILDER, 21, 1-33.
  • Lembo, S., Horsmanheimo, S., Honkamaa, P., 2019. Indoor positioning based on RSS fingerprinting in a LTE network: method based on Genetic Algorithms. 2019 IEEE International Conference on Communications Workshops (ICC Workshops), 1-6.
  • Li, G., Geng, E., Ye, Z., Xu, Y., Zhu. H., 2018. Indoor Positioning Algorithm Based on the Improved RSSI Distance Model. 14th IEEE International Conference on Signal Processing (ICSP), 129-133.
  • Morais, K., Bosco, D., 2017. RFID based Indoor Positioning System. IJSRD, 4(11), 454-457.
  • Oldenburg, L., Meznaric, J., Lukau, E., Hechenberger A., 2016. Indoor Navigation/Indoor Positioning with mobile Devices, 10.13140/RG.2.1.3100.4568.
  • Özdemir, B. N., Ceylan, A., Alçay, S., Yiğit, C.Ö., 2014. Kapalı Mekanlarda Uygulanan Konum Belirleme Yöntemleri Ve Karşılaştırılması. Harita ve Kadastro Mühendisleri Odası, Mühendislik Ölçmeleri STB Komisyonu 7. Mühendislik Ölçmeleri Sempozyumu 15-17 Ekim 2014, Hitit Üniversitesi, Çorum, 1-9.
  • Sakpere, W., Oshin, M. A., Mlitwa, N. B. W., 2017. A state-of-the-art survey of indoor posi-tioning and navigation systems and technologies. South African Computer Journal, 29(3), 145.
  • Sugano, M., Kawazoe, T., Ohta, Y., Murata, M., 2006. Indoor Localization System Using Rssi Measurement Of Wireless Sensor Network Based On Zigbee Standard. The 6th IASTED International Multi-Conference on Wireless and Optical Communications, 538.
  • Tsanga, P.Y.P., Wua, C.H., Ipa, W.H., Hoa, G.T.S., Tseb, Y.K, 2015. A Bluetooth-based In-door Positioning System: a Simple and Rapid Approach. Annual Journal IIE, 35, 11-26.
  • Tunca, C., Toplan, E., Işık, S., Ersoy, C., 2014. Yapay Sinir Ağları ile WiFi Tabanlı İç Mekan Konumlandırma. AB 2014, 10.13140/2.1.4021.2486.
  • Wen, L. P., Nee, C. W., Chun, K. M., Shiang-yen, T., Idrus, R., 2011. Application of WiFi-based Indoor Positioning System in Handheld Directory System. 5th Proceedings of the European Computing Conference, 21-27.
  • Xiao, A., Chen, R., Li, D., Chen, Y., Wu, D., 2018. An Indoor Positioning System Based on Static Objects in Large Indoor Scenes by Using Smartphone Cameras. Sensors, 18(7), 2229.
  • Xu, H., Ding, Y., Li, P., Wang, R., 2017. An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor. Sensors, 17(8), 1806.
  • Zegeye, W. K., Amsalu, B., Astatke, Y., Moazzami, F., 2016. WiFi RSS Fingerprinting Indoor Localization for Mobile Devices. UEMCON, 1-6.
  • Zheng, J., Wu, C., Chu, H., Xu, Y., 2011. An Improved RSSI Measurement In Wireless Sensor Networks. SciVerse Science Direct, 15, 876-880.
  • Zou, H., Xie, L., Jia, Q., Wang, H., 2014. Platform and Algorithm Development for a RFID-Based IndoorPositioning System. Unmanned Systems, 2(3), 279-291.
There are 27 citations in total.

Details

Primary Language Turkish
Subjects Computer Software
Journal Section Research Articles
Authors

Sedat Akleylek 0000-0001-7005-6489

Erdal Kılıç 0000-0003-1585-0991

Burcu Söylemez This is me 0000-0001-7499-6689

Tahir Ergun Aruk This is me 0000-0002-5412-7731

Aslıhan Çavuş This is me 0000-0001-5012-1423

Project Number 3180329
Publication Date December 29, 2020
Submission Date November 26, 2020
Acceptance Date December 26, 2020
Published in Issue Year 2020 Volume: 8 Issue: 5

Cite

APA Akleylek, S., Kılıç, E., Söylemez, B., Aruk, T. E., et al. (2020). KAPALI MEKAN KONUMLANDIRMA ÜZERİNE BİR ÇALIŞMA. Mühendislik Bilimleri Ve Tasarım Dergisi, 8(5), 90-105. https://doi.org/10.21923/jesd.831775