Wi-Fi indoor positioning fingerprint health analysis for a large scale deployment

Indoor positioning systems (IPS) have witnessed continuous improvements over the years. However, large-scale commercial deployments remain elusive due to various factors such as high deployment cost and lack market drivers. Among the state of the art indoor positioning approaches, the Wi-Fi fingerprinting technique, in particular, is gaining much attention due to its ease of deployment. This is largely due to widespread deployment of WiFi infrastructure and its availability in all existing mobile devices. Although WiFi fingerprinting approach is relatively low cost and fast to deploy, the accuracy of the system tends to deteriorate over time due to WiFi access points (APs) being removed and shifted. In this paper, we carried out a study on such deterioration, which we refer to as fingerprint health analysis on a 2 million square feet shopping mall in South of Kuala Lumpur, Malaysia. We focus our study on APs removal using the actual data collected from the premise. The study reveals the following findings: 1) based on per location pin analysis, ~50% of APs belong to the mall operator which is a preferred group of APs for fingerprinting. For some location, however, the number of operator-managed APs are too few for fingerprinting positioning approach. 2) To maintain mean error distance of ~5 meters, up to 80% of the APs can be removed using the selected positioning algorithms at some locations. At some other locations, however, the accuracy will exceed 5m upon > 20% of APs being removed. 3) On average, around 40% - 60% of the APs can be removed randomly in order to maintain the accuracy of ~5m.