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Y. Bai, R. Norman, Y. Zhao, S. Tang, S. Wu, H. Wu, G. Retscher, K. Zhang:
"A New Algorithm for Improving the Tracking and Positioning of Cell of Origin";
Talk: 2015 International Association of Institutes of Navigation World Congress IAIN, Prag, Tschechien (invited); 2015-10-20 - 2015-10-23; in: "2015 International Association of Institutes of Navigation World Congress", IEEE Xplore, (2015), ISBN: 978-1-4673-7634-1; 6 pages.

Wi-Fi and smartphone based positioning technologies are playing a more and more important role for tracking and positioning due to the rapid development of the smartphone market. However, the low positioning accuracy of these technologies is still an issue for indoor positioning. This research is part of an Australian Research Council (ARC) project required by a large global shopping mall company located in Australia. It aims to develop an effective customer tracking approach for acquiring shopping behavior of customers and providing better services. Currently, the log data provided by the company only records one Wi-Fi connection at a time for each smartphone user, which makes most of the conventional tracking and positioning methods inapplicable. Only the cell of origin (CoO) method can be selected for the customer tracking and positioning. The designated shopping mall floor was initially partitioned based on the distribution of the access point (AP), received signal strength indicator (RSSI) values and the Voronoi diagram. However, the cells created by the Voronoi diagram did not reflect the real indoor complexity of the surrounding environment. In order to solve this problem, a new approach called the common hand over point determination (CHOPD) algorithm was developed, in which the statistical RSSI values from the real Wi-Fi network log data are used for the spatial and temporal position calculation of the hand-over point (HOP). The boundary of the cell can be determined once the HOP position is calculated. The RSSI values are detected by the Wi-Fi network from the smartphone carried by each customer walking on the shopping mall floor as they passed through two adjacent APs. The new algorithm was tested in a large shopping-mall-like space and 100 test sampling records were used for the test. The results from the new algorithm were assessed and were found to be within 9cm of the true HOP recorded.