A multiobjective optimization methodology of tuning indoor positioning systems

How can the collected data from testing an indoor positioning deployment be transformed into information concerning the optimal tuning of a positioning system in this deployment? How can such kind of accumulated information from several deployments be transformed into more generic knowledge regarding the system's performance, with respect to several performance goals? In this work, we present a multiobjective optimization methodology of tuning indoor positioning systems, based on real data recorded onsite. Selecting the appropriate tuning for a positioning system is a challenging task, which depends on many factors: the specific deployment, the devices used, the evaluation metrics and their order of significance, the user-case scenarios tested, etc. In order to handle these multiplicities, we introduce the use of multiobjective optimization which allows several objectives to be simultaneously satisfied. We exemplify the methodology performing tests with the GpmStudio platform, a desktop tuning and evaluation platform that supports our Global Positioning Module (GPM). The methodology proves to be a very useful tool in the hands of testers who are designated to optimally tune the positioning system in a variety of scenarios.

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