An Experimental Study on WeChat-Based Large Scale Indoor Localization System

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Min Gao, Xiao Zhang, Tao Zhang, Ci Chen, Zhouhong Wang, Zhihao Lu, Weijie Ding, Jiang Ouyang

Published: 01 Dec 2018, Last Modified: 07 Nov 2025Proceedings 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS)EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: In the new era of wireless communication, there has been an increased interest in indoor positioning systems that propelled researchers to come up with various solutions. Fusing the fuzzy locations from Bluetooth (BT) beacons with the ones from pedestrian dead reckoning (PDR) comes out a promising solution to provide meter-level positioning without additional infrastructure. Despite the remarkable efforts the community put to build the system, it lacks the performance examination of large-scale deployments. In this report, we implement and deploy a real system in Guangzhou South Railway Station to enable a large scale indoor positioning service. The framework used Bluetooth beacons and pedestrian dead reckoning to calculate the estimated position of the user then refine the accuracy through a fuzzy fusion algorithm. We distribute up to 2849 beacons in the indoor space of 81654 square meters. When applied to the real ceiling with a height of 8m and above, our approach is still able to reliably achieve a high accuracy of 5 meters. Also in buildings whose outer walls are nonstructural but large glass curtain wall that wraps around the roof of the facility, the GPS signal could serve as useful complement under careful utilization; last but not least significant, in practice we incorporate our indoor positioning services into WeChat HyperText Markup Language (HTML) platform, we discover that the headings provided by HTML5 are not always correct, the orientation error scale has a strong correlation with the temperature of phone, the residual error is accumulated along with the time to make matters worse.