Towards Optimization of Patients’ Turnaround Time using Bluetooth Low Energy Based Solutions

Main Article Content

Ganes Raj Muthu Arumugam
Saravanan Muthaiyah
Thein Oak Kyaw Zaw


BLE, Healthcare, RSSI, Optimization, Patients' Turnaround Time (PTAT)


Smart Healthcare can use the Internet of Things (IoT) to broaden the reach of digital healthcare by collecting patient data remotely using sensors. This can reduce Patient Turnaround Time (PTAT) and enable high-quality care to be provided. PTAT is the length of time from when a patient arrives at the hospital until they are allowed to return home. Malaysia's Ministry of Health claimed in 2016 that healthcare at government hospitals continues to encounter issues in providing high-quality care to patients, particularly in terms of the PTAT of patients who receive treatment versus those who are sent home without treatment. In this paper, we propose a Bluetooth Low Energy-based solution that optimizes PTAT using low calibrated transmission power, allowing hospitals to enable Real-time Patient Localization and Patient Movement Monitoring. The RSSI value is used to calculate the distance between a wearable device and the Access Points (AP) situated throughout the facility. When a patient passes an AP, data such as the wearable device name and RSSI value are taken and saved in a database, to determine the patient's location. A proof of concept was conducted using three AP points and 8 wearable devices to gauge distance measurement.


Download data is not yet available.
Abstract 166 | 615-PDF-v10n4pp57-71 Downloads 6


Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of Things: A survey on enabling technologies protocols and applications. IEEE Communications Surveys & Tutorials, 17(4), 2347–2376.
Bensky, A. (2019). Short-range Wireless Communication, 3rd Edition. Elsevier.
Farahani, S. (2008). ZigBee Wireless Networks and Transceivers. Elsevier.
Figueiredo e Silva, P., Richter, P., Talvitie, J., Laitinen, E., & Lohan, E. S. (2018). Challenges and Solutions in Received Signal Strength-Based Seamless Positioning. In Conesa, J., Pérez-Navarro, A., Torres-Sospedra, J., & Montoliu, R. (eds), Geographical and Fingerprinting Data to Create Systems for Indoor Positioning and Indoor/Outdoor Navigation. Academic Press.
García, L., Jiménez, J. M., Taha, M., & Lloret, J. (2018). Wireless Technologies for IoT in Smart Cities. Network Protocols and Algorithms, 10(1).
Gardašević, G., Katzis, K., Bajić, D., & Berbakov, L. (2020). Emerging Wireless Sensor Networks and Internet of Things Technologies—Foundations of Smart Healthcare. Sensors 2020, 20(13), 3619.
Glow labs. (2019). Table Comparing Wireless Protocols For IoT Devices. Available at
Herres, D. (2021). Understanding decibels and decibel measurements. Test & Measurement Tips.
Huang, Y.-C., Hwang, J.-C., & Lin, Y.C. (2021). The Optimization between Physician Satisfaction and Hospital Profit in Cross-Hospital Scheduling—A Case Study of Some Hospitals in Taiwan. Healthcare (Basel), 9(8), 1004.
Labrique, D. (2020). Effects of obstructions on the accuracy of Bluetooth contact tracing. OSF Preprints. Available from
Lin, Y.-W., & Lin, C.-Y. (2018). An Interactive Real-Time Locating System Based on Bluetooth Low-Energy Beacon Network. Sensors, 18(5), 1637.
Maccari, L., & Cagno, V. (2021). Do we need a contact tracing app? Computer Communications, 166, 9–18.
Mackey, A., Spachos, P., Song, L., & Plataniotis, K. N. (2020). Improving BLE Beacon Proximity Estimation Accuracy Through Bayesian Filtering. IEEE Internet of Things Journal, 7(4), 3160–3169.
Ministry of Health. (2016). Annual Report Kementerian Kesihatan Malaysia.
National Institute for Health and Clinical Excellence. (2007). Acutely ill patients in hospital- Recognition of and response to acute illness in adults in hospital. NICE clinical guideline 50, London, UK.
Nordic Semiconductor. (2021). nRF52832, Versatile Bluetooth 5.3 SoC supporting Bluetooth Low Energy, Bluetooth mesh and NFC. [Internet]. Available from
Parker, M. (2017). Digital Signal Processing 101, 2nd Edition. Newnes. Available at
Sibiński, D. (2021). WiFi and Bluetooth interference — diagnosing and fixing. [Internet]. Available from:
Vize, R. (2017). How can health services keep pace with the rapid growth of cities? The Guardian, 24 February 2017.
Zhao, Q., Wen, H., Lin, Z., Xuan, D., & Shroff, N. (2020). On the accuracy of measured proximity of Bluetooth-based contact tracing apps. In Park, N., Sun, K., Foresti, S., Butler, K., Saxena, N. (eds), Security and Privacy in Communication Networks. SecureComm 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 335. Springer, Cham.
Zhu, H., Wu, C. K., Koo, C. H., Tsang, Y. T., Liu, Y., Chi, H. R., & Tsang, K.-F. (2019). Smart Healthcare in the Era of Internet-of-Things. IEEE Consumer Electronics Magazine, 8(5), 26—30.