Performance analysis of multiple Indoor Positioning Systems in a healthcare environment

Abstract

BackgroundThe combination of an aging population and nursing staff shortages implies the need for more advanced systems in the healthcare industry. Many key enablers for the optimization of healthcare systems require provisioning of location awareness for patients (e.g. with dementia), nurses, doctors, assets, etc. Therefore, many Indoor Positioning Systems (IPSs) will be indispensable in healthcare systems. However, although many IPSs have been proposed in literature, most of these have been evaluated in non-representative environments such as office buildings rather than in a hospital.MethodsTo remedy this, the paper evaluates the performance of existing IPSs in an operational modern healthcare environment: the “Sint-Jozefs kliniek Izegem” hospital in Belgium. The evaluation (data-collecting and data-processing) is executed using a standardized methodology and evaluates the point accuracy, room accuracy and latency of multiple IPSs. To evaluate the solutions, the position of a stationary device was requested at 73 evaluation locations. By using the same evaluation locations for all IPSs the performance of all systems could objectively be compared.ResultsSeveral trends can be identified such as the fact that Wi-Fi based fingerprinting solutions have the best accuracy result (point accuracy of 1.21 m and room accuracy of 98 %) however it requires calibration before use and needs 5.43 s to estimate the location. On the other hand, proximity based solutions (based on sensor nodes) are significantly cheaper to install, do not require calibration and still obtain acceptable room accuracy results.ConclusionAs a conclusion of this paper, Wi-Fi based solutions have the most potential for an indoor positioning service in case when accuracy is the most important metric. Applying the fingerprinting approach with an anchor installed in every two rooms is the preferred solution for a hospital environment.

Evaluation of accurate indoor localization systems in industrial environments

“…However, most of these efforts only focus on theory, system design, survey of localization techniques or evaluation in non-industrial environments, usually offices or healthcare spaces [7][8][9][10]. The main contributions of this paper are (i) a detailed performance evaluation and comparison of two different promising accurate localization technologies, Bluetooth LE and UWB, in an industrial environment, (ii) an experimental understanding of their behavior in similar conditions and (iii) investigation of their potential to be used in industrial applications with given localization requirements.…”

Location-based Mechanism for Positioning of a Mobile Relay

“…A per-coordinate error of location information of a device is modeled as a zero-mean normally distributed random variable. Modeling per-coordinate localization errors with a Gaussian distribution is a well established procedure, with some examples being [12,30,33]. All per-coordinate localization errors have the same standard deviation σ .…”

Benchmarking of Localization Solutions: Guidelines for the Selection of Evaluation Points

“…For example, Xiaowei Luo et al present in [4] 2 ). Similarly, in [5] 8 different localization solutions are evaluated in the same hospital environment, using the same 73 evaluation points. Although in this case more evaluation points are used, it is not clear whether using such a dense evaluation point grid was either overkill (i.e.…”

“…The authors organized two measurement campaigns to capture a raw dataset of WiFi, Zigbee and BLE RSSI traces at the mentioned evaluation points mentioned in Section 3, once in the w.iLab.t II testbed [1] and once in the hospital [5]. To eliminate the influence of environmental randomness (e.g.…”