A comparative analysis of Indoor WiFi Positioning at a large building complex

Abstract

Indoor Positioning based on WiFi has received extensive focus from research communities, owing its promises of ubiquitous positioning indoors for a variety of applications. The majority of the existing research on WiFi positioning centers around the improvement of positioning accuracy. However, to this end there is missing a unanimous evaluation methodology appropriately reflecting criteria relevant in real-world use. Assessing and advancing the state-of-the-art is often hindered by incomparable evaluation settings, and in many cases a missing rigor in describing evaluation methodology, metrics, and data collection, which is often decoupled from realistic use scenarios and their diversity. This leads to major challenges—and often disappointments—when implementing positioning methods in the hope of the promised accuracies. We believe that this holds especially in large real world environments, as only few extensive experimental evaluations have been reported in such environments. This paper presents a comparative evaluation of several indoor positioning techniques set at a large university hospital spanning 160, 000m2—an environment where several location- and context-aware logistic applications are in daily use. The positioning methods utilize measurements of signal strengths using existing WiFi infrastructure, which eases deployment and maintenance. We identify meaningful key metrics which describe different aspects of the methods' performance. Using these metrics, we furthermore report on experiences with implementing and utilizing indoor positioning solutions in a highly diverse environment, in which building types and materials, as well as building use differ across the complex. Correspondingly, the evaluation data we use is gathered at different building complex parts, days, and daytimes, and both at static locations as well as traveling within the building complex. Our results illustrate and quantify the challenges and breakdowns in transferring performance results from a small controlled setting, such as a small office environment, to a large dynamic building complex.