OpenThread as a tool for localization of devices and patients in healthcare systems

Efficient patient flow management is a key factor for optimizing workflows in cost-intensive hospital units such as operating rooms. While existing prediction models can accurately estimate surgical durations, uncertainties in patient transport and availability of resources continue to affect daily schedules. Real-time location systems offer the potential to address this gap by providing information on patient and device locations. However, commercially available solutions are often costly and closed by providers. In this work, we present a scalable, research-oriented real-time location system, designed for low-power and low-cost deployment in hospital environments.

Our system uses Bluetooth Low Energy beacons for device tracking and OpenThread as a transport layer to a database. A custom localization algorithm enables room-level assignment and triangulation-based localization in terms of coordinates. This setup is designed for low-power and low-cost deployment for research purposes.

Preliminary results demonstrate the feasibility of the proposed network for room-level assignment and position estimation of beacons while revealing notable variability in accuracy. Triangulation-based localization achieved a mean positioning error of 3.53 m, while room-level assignment showed error rates ranging from 0 to 40%, reflecting typical RSSI (Received Signal Strength Indicator) effects such as shadowing and signal reflections.

The presented system provides an open, standards-based foundation for future improvements, including latency analysis, reliability assessments, advanced filtering methods and latest ranging techniques and represents a promising approach for adaptive patient flow management and clinical workflow optimization.