Yeni Bir İç Mekân Konum Bulma Sistemi
Year 2021,
, 636 - 645, 25.04.2021
Şeyda Yaman
,
Köksal Gündoğdu
,
Ali Çalhan
Abstract
Teknolojinin gelişimine paralel olarak konum bulma sistemleri çok önem kazanmıştır. Konum bulma sistemleri dış mekân konum bulma sistemleri ve iç mekân konum bulma sistemleri diye temel olarak iki sınıf altında toplanmıştır. Dış mekân konum bulma sistemleri genellikle GPS sinyallerini temel aldığı için iç ortamda verimli bir şekilde çalışmamaktadır. İç mekân konum bulma sistemleri gelişimini sürdürmektedir ve üzerine birçok çalışma yapılmaktadır. Bu çalışmada, verimli bir iç mekan konum bulma sistemi oluşturabilmek için elektronik kart tasarımları gerçekleştirilmiştir. İç mekân konum bulma yöntemi için bu kartlara uygun yazılımlar hazırlanmıştır. Ayrıca sistemi verimli bir şekilde analiz edebilmek için arayüz programı tasarlanmıştır. Yapılan test sonuçları ve veriler incelendiğinde iç mekân konum bulma sistemi için uygun maliyet ile yakın doğruluk değerlerine ulaşıldığı gözlemlenmiştir.
References
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Year 2021,
, 636 - 645, 25.04.2021
Şeyda Yaman
,
Köksal Gündoğdu
,
Ali Çalhan
References
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- [2] Wu, T.; Xia, H.; Liu, S.; Qiao, “Y. Probability-Based Indoor Positioning Algorithm Using iBeacons,” Sensors, vol. 19, no. 23, pp. 5226-5244, 2019
- [3] C. Kowalski, K. Blohm, S. Weiss, M Pfingsthorn, P. Gliesche, and A. Hein, “MultiLow-resolution Infrared Sensor Setup for Privacy-preserving Unobtrusive Indoor Localization,” 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, 2019, pp. 183-188.
- [4] N. Duong and T. Dinh, "Indoor Localization with lightweight RSS Fingerprint using BLE iBeacon on iOS platform," 2019 19th International Symposium on Communications and Information Technologies (ISCIT), 2019, pp. 91-95.
- [5] A. Sato, M. Nakajima and N. Kohtake, "Rapid BLE Beacon Localization with Range-Only EKF-SLAM Using Beacon Interval Constraint," 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2019, pp. 1-8.
[6] A. Poulose and D. S. Han, H, “Indoor Localization Using IMU Sensors and Smartphone Camera,” Sensors, vol. 19, no. 23, pp. 5084-5101, 2019
- [7] R. Montoliu, E. Sansano, A. Gasco, O. Belmonte and A. Caballer “Senior Monitoring: A Real Case of Applying a WiFi Fingerprinting-based Indoor Positioning Method for People Monitoring,” IPIN, 2019
- [8] Y.F. Tang, Y.X. Zhang, S.W. Hing and S.L. Kan, “Pixel-based Map Matching Algorithm for Pedestrian Dead Reckoning System,” IPIN, 2019
- [9] D. Namiot, “On Indoor Positioning,” International Journal of Open Information Technologies, vol. 3, no. 3, pp. 23-26, 2015
- [10] R. Brena, J. García-Vázquez, C. Galván-Tejada, D. Muñoz-Rodriguez, C. Vargas-Rosales, and J. FangmeyerJr, “Evolution of Indoor Positioning Technologies: A Survey,” Journal of Sensors, 2017,
[11] M. A. Al-Ammar et al., "Comparative Survey of Indoor Positioning Technologies, Techniques, and Algorithms," 2014 International Conference on Cyberworlds, 2014, pp. 245-252.
- [12] M. Kwak, C. Hamm, S. Park and T. T. Kwon, "Magnetic Field based Indoor Localization System: A Crowdsourcing Approach," 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2019, pp. 1-8.
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- [14] B. Sekmen, K. R. Özyılmaz and G. İnce, "An efficient beacon hardware for indoor location services," 2016 24th Signal Processing and Communication Application Conference (SIU), 2016, pp. 217-220.
- [15] A. Alarifi, A. Al-Salman, M. Alsaleh, A. Alnafessah, S. Al-Hadhrami, M. Al-Ammar ve H. Al-Khalifa, “Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances,” Sensors, vol.16, no. 5, pp. 707-743, 2016
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- [17] S. C. Aydalka, “Bluetooth Beacon Teknolojisi Kullanarak Lokasyon Ve Müze Eser Tanıtım Uygulaması Gerçekleştirilmesi,” Yüksek Lisans Tezi, Fen Bilimleri Enstitüsü, Balıkesir Üniversitesi, Balıkesir, Türkiye, 2018.
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- [19] Y. Yelkovan et al., "Infrared beacon based sub-meter indoor localization," 2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014, pp. 1427-1430.
- [20] X. Li, D. Xu, X. Wang and R. Muhammad, "Design and implementation of indoor positioning system based on iBeacon," 2016 International Conference on Audio, Language and Image Processing (ICALIP), 2016, pp. 126-130.
- [21] T. Kitasuka, K. Hisazumi, T. Nakanishi and A. Fukuda, "WiPS: Location and Motion Sensing Technique of IEEE 802.11 Devices," Third International Conference on Information Technology and Applications (ICITA'05), 2005, pp. 346-349.
- [22] A. S. Taşbaş, E. Erdal and S. Özdemir, "Real-Time Object and Personnel Tracking in Indoor Location," 2019 4th International Conference on Computer Science and Engineering (UBMK), 2019, pp. 585-590.
- [23] S. Bozkurt, S. Günal, U. Yayan and V. Bayar, "Classifier selection for RF based indoor positioning," 2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015, pp. 791-794.
- [24] M. Qathrady and A. Helmy, ”Improving BLE Distance Estimation and Classification Using TX Power and Machine Learning: A Comparative Analysis,” 20th ACM Int'l Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems, 2017, pp. 79-83.
- [25] E. G. Larsson, "Cramer-Rao bound analysis of distributed positioning in sensor networks," in IEEE Signal Processing Letters, vol. 11, no. 3, pp. 334-337, March 2004.
- [26] H. ARSLANTAŞ ve S. ÖKDEM, “İç Mekân Konumlandırma Yöntemleri,” 4th International Symposium on Innovative Approaches in Engineering and Natural Sciences, vol.4, no.6, pp. 441-443, 2019.