Optimizing Wi-Fi-based Positioning Systems using Intelligent Weight Distribution and Fuzzy Logic Techniques

Yahya Abdulkadir Giwa, Abdulkadir Mohammed Giwa, Ilori Loretta Onyinye, Sadiq Dogo Ali, Habib Tunji Adeyemo, Mohammed Nasir

Abstract


The application of indoor localization systems has exponentially risen in recent years as its use cuts across several localization-based services. There exist several variants of indoor position systems in literature with the recent variants of the indoor positioning systems being improved with by using one or Multi-Criteria Decision Making (MCDM) techniques to improve the criteria of the localization system. However, these metrics suffer from computational costs and decision bias, which can affect its application in other indoor localization environments. This research adopts an approach that splices two MCDM techniques to develop the infrastructure for a centimetre-level-based localization model. The first of the MCDM, which is Simple Additive Weighting (SAW) considers a selected number of criteria to develop the initial infrastructure for localization. This is further improved by the second MCDM, which is, Fuzzy Analytic Hierarchy Process (FAHP) to modify the weights assigned to the aforementioned criteria to mitigate deviations and achieve better indoor positioning results. Simulation results showed that the model achieved an average localization error of 25cm with a precision of 30cm, which shows the models applicability in indoor settings. Alongside the mean signal strength and RSSI variance, the proposed model showed a considerable level of adaptability for indoor positioning applications.


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