Advances in Indoor Localization: Comparative Study of RFID, Wi-Fi, and Visible Light Methods
DOI:
https://doi.org/10.54097/hset.v62i.10423Keywords:
Indoor Localization, RFID Localization, Wi-Fi Localization, Visible Light Localization.Abstract
Due to the limitation that the global positioning system cannot be used in indoor settings and the increasing demand for location-based services in indoor environments, indoor localization has become one of the hottest research topics in recent years. A variety of techniques have been proposed for indoor localization. This review paper aims to provide an overview of working principles of radio frequency identification based, Wi-Fi based and visible light localization techniques and their applications. The paper also presents a comprehensive analysis of the advantages and disadvantages of each technique, including their accuracy, cost-effectiveness, and ease of deployment. In the end, the paper predicts a few future research directions and potential opportunities for indoor localization. This paper will be of interest to researchers, practitioners, and industry professionals working on indoor localization and related fields.
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References
Wye K, Kanagaraj E, Zakaria S, et al. 2.4GHz RF based Active RFID Localization in Industrial Environment, 2019 IEEE International Conference on Sensors and Nanotechnology (SENSORS & NANO). IEEE, 2019.
Ni L M, Liu Y. Manufactured in The Netherlands. LANDMARC: Indoor Location Sensing Using Active RFID. 2008.
Motroni A, Nepa P, Buffi A, et al. A Phase-Based Method for Mobile Node Localization through UHF-RFID Passive Tags, 2019 IEEE International Conference on RFID Technology and Applications (RFID-TA). IEEE, 2019.
Feng Y, Jiang M , Jing L , et al. Expansion RSS-based Indoor Localization Using 5G WiFi Signal, 2014 International Conference on Computational Intelligence and Communication Networks. IEEE, 2015.
Yoon, Giwan, Lee, et al. Building a Practical Wi-Fi-Based Indoor Navigation System, IEEE pervasive computing, 2014, 13(2):72-79.
Li L, Hu P, Peng C, et al. Epsilon: A Visible Light Based Positioning System, usenix org, 2014.
Weinstein, R. RFID: a technical overview and its application to the enterprise, It Professional, 2005, 7(3):27-33.
Uddin S, Shareef H, Mohamed A, et al. LEDs as energy efficient lighting systems: A detail review, 2011 IEEE Student Conference on Research and Development. IEEE, 2012.
Yasir M, Ho S W, Vellambi B N. Indoor Position Tracking Using Multiple Optical Receivers, Journal of Lightwave Technology, 2016, 34(4):1166-1176.
Y. Gao, S. Wang, H. Chen, and Y. Chen, An Ultra-High Accuracy Localization Algorithm for Passive RFID Tags in Indoor Environment, IEEE Access, 2019, 7:119430-119440.
Li S, Hedley M, Bengston K, et al. TDOA-based passive localization of standard WiFi devices, Ubiquitous Positioning, Indoor Navigation and Location-Based Services. 0.
Dinh-Van N, Nashashibi F, Thanh-Huong N, et al. Indoor Intelligent Vehicle localization using WiFi Received Signal Strength Indicator, IEEE Mtt-s International Conference on Microwaves for Intelligent Mobility. IEEE, 2017.
Aswin P K, Shyama P, Das L B. Indoor localization using visible light communication and image processing, 2018 IEEE International Conference on Consumer Electronics (ICCE). IEEE, 2018.
Bastiaens S, Deprez K, Martens L, et al. Experimental Assessment of the Accuracy of Modulated and Unmodulated Visible Light Positioning, 2020 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). IEEE, 2020.
Rahman A, Li T, Wang Y. Recent Advances in Indoor Localization via Visible Lights: A Survey, Sensors, 2020, 20(5):1382.
Pathak P H, Feng X, Hu P, et al. Visible Light Communication, Networking, and Sensing: A Survey, Potential and Challenges, IEEE Communications Surveys & Tutorials, 2015, 17(4):2047-2077.
Z. Xu, B. Huang, B. Jia, W. Li and H. Lu, A Boundary Aware WiFi Localization Scheme Based on UMAP and KNN, IEEE Communications Letters, 2022, 26(8): 1789-1793.
Markom M A, Adom A H, Shukor S, et al. Scan matching and KNN classification for mobile robot localisation algorithm, 2017 IEEE 3rd International Symposium in Robotics and Manufacturing Automation (ROMA). IEEE, 2017.
Du C, Peng B, Zhang Z, et al. KF-KNN: Low-Cost and High-Accurate FM-Based Indoor Localization Model via Fingerprint Technology, IEEE Access, 2020, 8:197523-197531.
Mahdavi F, Zayyani H, Rajabi R. RSS Localization Using an Optimized Fusion of Two Deep Neural Networks, IEEE Sensors Letters, 2021(5-12).
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