Topological Indoor Mapping through WiFi Signals

• URL: http://arxiv.org/abs/2106.09789v1
• Date: Thu, 17 Jun 2021 20:06:09 GMT
• Title: Topological Indoor Mapping through WiFi Signals
• Authors: Bastian Schaefermeier and Gerd Stumme and Tom Hanika
• Abstract summary: WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in localization and mapping. Previous approaches were hindered by problems such as effortful map-building processes, changing environments and hardware differences. We tackle these problems focussing on topological maps. In our unsupervised method, we employ WiFi signal strength distributions, dimension reduction and clustering.
• Score: 0.09668407688201358
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The ubiquitous presence of WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in indoor localization and mapping. In particular, no additional infrastructure is required. Previous approaches in this field were, however, often hindered by problems such as effortful map-building processes, changing environments and hardware differences. We tackle these problems focussing on topological maps. These represent discrete locations, such as rooms, and their relations, e.g., distances and transition frequencies. In our unsupervised method, we employ WiFi signal strength distributions, dimension reduction and clustering. It can be used in settings where users carry mobile devices and follow their normal routine. We aim for applications in short-lived indoor events such as conferences.

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