Employing spatial analysis in indoor positioning and tracking using wi-fi access points

A practical WiFi-based positioning system has to be adaptable to the variations of indoor environmental dynamic factors. In this work, we propose a novel Wi-Fi indoor positioning and tracking framework which employs the spatial analysis and image processing techniques. The Wi-Fi surfaces can be dynamically constructed and updated and thus help to address the challenges of signal spatial heterogeneity and environmental variations. A mobile app for indoor positioning application has been developed as a proof of concept. Based on the experiments we conducted at the Esri campus, this method can achieve about 2-meter positioning accuracy. The proposed methodology and theoretical frame-work can guide engineers to implement cost-effective indoor positioning infrastructure, and thus offer insights on future smart campus applications. The introduced spatial analysis and geoprocessing workflow may also bring the attention of GIScientists to make more efforts to conquer the indoor positioning and tracking challenges.