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Landmark-Based Indoor Positioning: a Non-Intrusive and Cost-Effective Approach

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This paper proposes a method for identifying indoor landmarks that can serve as fingerprints in indoor environments. The reason for this proposal is that every building has several distinctive locations. These signatures will be used as positional markers if they can be found. Landmarks such as Wi-Fi, entrance, windows, and elevators are recognizable. The proposed method detects these landmarks as follows: Wi-Fi Received Signal Strength (RSS) is used to detect the Wi-Fi landmark. The difference between GPS signals and Wi-Fi RSS values is used to locate the entrance landmark. GPS signals, though not available indoors, can be detected near windows and used to locate windows. Elevators are identified using two criteria: user movement behavior and loss of Wi-Fi RSS. The accuracy of detecting Wi-Fi, entrance, and window landmarks is 2 m, while the accuracy of detecting the elevator landmark is 1 m.
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Wi-Fi Received Signal Strength (RSS); Landmarks; GPS; Acceleration; Fingerprints

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J. Zhang, Z. Yu, X. Wang, Y. Lyu, S. Mao, S. Periaswamy, J. Patton, and X. Wang, RFHUI: An RFID based human-unmanned aerial vehicle interaction system in an indoor environment, Elsevier/KeAi Digital Communications and Networks J., vol. 6, no. 1, pp. 14-22, Feb. 2020.

N. Singh, S. Choe and R. Punmiya, Machine Learning Based Indoor Localization Using Wi-Fi RSSI Fingerprints: An Overview, in IEEE Access, vol. 9, pp. 127150-127174, 2021.

Obeidat, Huthaifa, et al. A review of indoor localization techniques and wireless technologies. Wireless Personal Communications 119.1 (2021): 289-327.

Andò, Bruno, et al. An Introduction to Indoor Localization Techniques. Case of Study: A Multi-Trilateration-Based Localization System with User-Environment Interaction Feature. Applied Sciences 11.16 (2021): 7392.

Obeidat, Huthaifa. Performance Comparisons of Angle of Arrival Detection Techniques Using ULA. Wireless Personal Communications (2022): 1-13.

Abadleh, Ahmad, et al. Step detection algorithm for accurate distance estimation using dynamic step length. 2017 18th IEEE international conference on mobile data management (MDM). IEEE, 2017.

Abadleh, Ahmad, et al. Construction of indoor floor plan and localization. Wireless Networks 22.1 (2016): 175-191.

Alabadleh, Ahmad, et al. A RSS-based localization method using HMM-based error correction. Journal of Location Based Services 12.3-4 (2018): 273-285.

Abadleh, Ahmad. Wi-Fi RSS-based approach for locating the position of indoor Wi-Fi access point. Communications-Scientific letters of the University of Zilina 21.4 (2019): 69-74.

Abadleh, Ahmad, et al. Smartphones-Based Crowdsourcing Approach for Installing Indoor Wi-Fi Access Points. International Journal of Advanced Computer Science and Applications 10.4 (2019).

Al-Tarawneh, Nagham A., Ahmad H. Abadleh, and Zaid T. Alhalhouli. Direction Estimation using Patterns of User Movement. Journal of Engineering Science & Technology Review 12.4 (2019).

Obeidat, H., Shuaieb, W., Obeidat, O. et al. A Review of Indoor Localization Techniques and Wireless Technologies. Wireless Pers Commun 119, 289-327 (2021).

Vy, T. D., Nguyen, T. L. N., & Shin, Y. (2019). A smartphone indoor localization using inertial sensors and single Wi-Fi access point, in International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2019, 1-7.

Dian, Z., Kezhong, L., & Rui, M. (2015). A precise RFID indoor localization system with sensor network assistance. China Communication, 12(4), 13-22.

Alfurati, I. S., & Rashid, A. T. (2018). Performance comparison of three types of sensor matrices for indoor multi-robot localization. International Journal of Computers and Applications, 181(26), 22-29.

Zou, H., Chen, Z., Jiang, H., Xie, L., & Spanos, C. (2017). Accurate indoor localization and tracking using mobile phone inertial sensors, WiFi and iBeacon. In IEEE International Symposium on Inertial Sensors and Systems (INERTIAL), 2017, 1-4.

Ibnatta, Youssef, Mohammed Khaldoun, and Mohammed Sadik. Indoor Localization System Based on Mobile Access Point Model MAPM Using RSS With UWB-OFDM. IEEE Access 10 (2022): 46043-46056.

de Souza Mourão, Helmer Augusto, and Horácio Antonio Braga Fernandes de Oliveira. Indoor Localization System Using Fingerprinting and Novelty Detection for Evaluation of Confidence. Future Internet 14.2 (2022): 51.

Chen, X., Chen, Y., Cao, S., Zhang, L., Zhang, X., & Chen, X. (2019). Acoustic indoor localization system integrating TDMA+ FDMA transmission scheme and positioning correction technique. Sensors, 19(10), 2353.

E. Hamadaqa , A. Abadleh , A. Mars, and W. Adi , Highly Secured Implantable Medical Devices, 2018 International Conference on Innovations in Information Technology (IIT), 2018, pp. 7-12.

S. Mulhem , A. Abadleh and W. Adi, Accelerometer-Based Joint User-Device Clone-Resistant Identity, 2018 Second World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), 2018, pp. 230-237.

A. Mars, A. Abadleh, W. Adi, Operator and Manufacturer Independent D2D Private Link for Future 5G Networks, IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops (INFOCOM), 2019, pp. 1-6.

Aljaafreh, A., Alawasa, K., Aljaafreh, S., & Abadleh, A. (2017). Fuzzy inference system for speed bumps detection using smart phone accelerometer sensor. J. Telecommun. Electron. Comput. Eng., 9(2-7), 133-136.

Abadleh, Ahmad, et al. Noise segmentation for step detection and distance estimation using smartphone sensor data. Wireless Networks 27.4 (2021): 2337-2346.

Alnabhan, Mohammad, et al. Enhanced D2D Communication Model in 5G Networks. International Journal of Computing and Digital Systems 10.1 (2021): 217-223.

Alnabhan, Mohammad, et al. Efficient Handover Approach in 5G Mobile Networks. Int. J. Adv. Sci. Eng. Inform. Technol 10 (2020): 1417-1422.

Altarawneh, G. A., Hassanat, A. B., Tarawneh, A. S., Abadleh, A., Alrashidi, M., & Alghamdi, M. (2022). Stock Price Forecasting for Jordan Insurance Companies Amid the COVID-19 Pandemic Utilizing Off-the-Shelf Technical Analysis Methods. Economies, 10(2), 43.

Abadleh, Ahmad, Et Al. Covid-19 Disease Recognition Using Distributed Data Mining And Deep Learning. Journal Of Theoretical And Applied Information Technology 100.2 (2022).

Abbadi, M., et al. Machine Learning-Based Approach For Detecting Driver Behavior Using Smartphone Sensors. International Journal of Scientific and Technology reserach 8.12 (2019): 1057-1060.

Chen, Y., et al. (2021). Survey of indoor localization using visible light communication technology. IEEE Access, 9, 5853-5863.

Huang, Y., et al. (2021). A hybrid indoor localization algorithm based on Wi-Fi fingerprinting and motion sensors. IEEE Sensors Journal, 21(6), 7996-8004.

Liu, Y., et al. (2021). A novel approach for indoor localization based on pedestrian dead reckoning and Wi-Fi fingerprinting. IEEE Access, 9, 14246-14256.

Shum LC, Faieghi R, Borsook T, Faruk T, Kassam S, Nabavi H, Spasojevic S, Tung J, Khan SS, Iaboni A. Indoor Location Data for Tracking Human Behaviours: A Scoping Review. Sensors. 2022; 22(3):1220.

Rizk, H., Yamaguchi, H., Youssef, M., & Higashino, T. (2023). Laser range scanners for enabling zero-overhead wifi-based indoor localization system. ACM Transactions on Spatial Algorithms and Systems, 9(1), 1-25.

Gbamélé, F., Ouattara, Y., Tapigue, S., High Coupled UHF RFID Tags Localization Using the Multilateration RSSI and Genetic Algorithm (GA) Optimization, (2021) International Journal on Communications Antenna and Propagation (IRECAP), 11 (6), pp. 372-382.

Alja'Afreh, S., Huang, Y., Jiang, K., A Coplanar Waveguide-Fed Ultra-Wideband Antenna with Single-Band Notched Characteristic Using Epsilon-Negative Loading, (2022) International Review of Electrical Engineering (IREE), 17 (6), pp. 618-625.


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