A dynamic model switching algorithm for WiFi fingerprinting indoor positioning

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Abstract

In 2023, there are various WiFi technologies and algorithms for an indoor positioning system. However, each technology and algorithm comes with their own strengths and weaknesses that may not universally benefit all building locations. Therefore, we propose a novel algorithm to dynamically switch to the most optimal positioning model at any given location, by utilising a Machine Learning based weighted model selection algorithm, with WiFi RSS and RTT signal measures as the input features. We evaluated our algorithm in three real-world indoor scenarios to demonstrate an improvement of up to 1.8 metres, compared to standard WiFi fingerprinting algorithm.
Original languageEnglish
Title of host publication13th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2023)
PublisherIEEE
ISBN (Electronic)979-8-3503-2011-4
ISBN (Print)979-8-3503-2012-1
DOIs
Publication statusPublished - 25 Sept 2023

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