Wireless Sensor Network Based Localization for Enhanced Device Tracking in Healthcare Environments

Laszlo Gogolak

doi:10.14232/analecta.2025.1.1-8

Authors

Laszlo Gogolak University of Szeged - Faculty of Engineering https://orcid.org/0000-0002-6653-3534

DOI:

https://doi.org/10.14232/analecta.2025.1.1-8

Keywords:

indoor localisation, wireless sensors network, UWB, ESP32

Abstract

The growing demand for accurate, real-time indoor positioning in healthcare environments has led to the exploration of alternative localization technologies beyond traditional GPS. Hospitals face the challenge of tracking mobile diagnostic equipment and coordinating personnel under tight operational constraints. This paper presents a practical implementation of an indoor positioning system (IPS) within an outpatient medical facility in Hungary, designed to track the movement of a shared mobile ultrasound device. Three technologies were investigated: Wi-Fi (using RSSI fingerprinting), Bluetooth Low Energy (BLE) beacons, and Ultra-Wideband (UWB) with ToF-based trilateration. All solutions were implemented using ESP32 microcontrollers, supported by custom Arduino code and MATLAB for data analysis. Results show significant differences in accuracy and reliability, with UWB proving superior for precision-demanding medical use cases.

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References

[1] Koyuncu, H., Yang, S.H.: A Survey of Indoor Positioning and Object Locating Sys-tems. IJCSNS Int. J. Comput. Sci. Netw. Secur. 10(5), 121–128 (2010)

[2] Petropoulos, G.P., Srivastava, P.K.: GPS and GNSS Technology in Geosciences. Else-vier, Amsterdam (2021)

[3] Li, C.-H.: Ultra-Wideband Technology: Characteristics, Applications, and Challenges. In: Proceedings of IEEE 2023, pp. 1–12. IEEE, New York (2023)

[4] Azaddel, M.: Energy-Efficient Design and Cost Advantages of BLE. In: IEEE Transac-tions on Communications, vol. 71, pp. 330-335 (2023)

[5] Gomes, A.: Principles and Applications of RFID Technology. In: International Journal of Wireless Networks, vol. 15, pp. 112–120 (2023).

[6] Turgut, Z.: WiFi-Based Indoor Positioning Using RSSI: Enhancing Localization in WLAN Systems. In: Proceedings of IEEE International Conference on IoT and Smart Systems, pp. 45–52 (2023).

[7] Simon, J., et al.: Navigation of Mobile Robots Using WSN’s RSSI Parameter and Poten-tial Field Method. Acta Polytechnica Hungarica, vol. 10, no. 4, pp. 111-116 (2013)

[8] Gogolák, L., Fürstner, I.: Wireless Sensor Network Aided Assembly Line Monitoring According to Expectations of Industry 4.0. Appl. Sci. 11(1), 25 (2021).

[9] Ismail, S., Dawoud, D.W., Reza, H.: Securing Wireless Sensor Networks Using Machine Learning and Blockchain: A Review. Future Internet 15(6), 200 (2023).

[10] IEEE: Indoor Positioning Techniques using RSSI from Wireless Devices. In: IEEE Con-ference Publication, 9038591 (2022).

[11] Sarcevic, P., Csik, D., Odry, A.: Indoor 2D Positioning Method for Mobile Robots Based on the Fusion of RSSI and Magnetometer Fingerprints. Sensors 23(4), 1855 (2023).

[12] Navarro, E.: WiFi fingerprinting for indoor positioning systems. In: Indoor Positioning Techniques, pp. 22–29 (2010).

[13] Ramesh, A., Patel, M., & Singh, K.: Analysis of outdoor signal propagation using transmission equations. Journal of Wireless Communication Systems, 12(3), 102–110 (2020).