Sequence detection of movement for accurate area based indoor positioning and tracking

This paper introduces a novel sequential approach to user movement analysis and tracking for indoor positioning systems. The algorithm utilizes stored reference and measured received signal strength indication (RSSI) data to determine the most likely movement paths represented as sequences of rectangular zones. It is demonstrated that the application of the proposed approach results in an improvement of user position estimation accuracy compared to the random forest classifier trained on the same reference data set.