A Context-Aware Assisted WiFi Positioning Method | Zendy

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A Context-Aware Assisted WiFi Positioning Method

Author(s) -

Feng Qi,

Bing Jia,

Xi Luo,

Sha Li

Publication year - 2021

Publication title -

wireless communications and mobile computing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.42

H-Index - 64

eISSN - 1530-8677

pISSN - 1530-8669

DOI - 10.1155/2021/6683456

Subject(s) - computer science , context (archaeology) , computer network , paleontology , biology

With the convenience brought by Location-based service (LBS), users’ requirements for indoor positioning accuracy are getting higher than ever. However, many traditional indoor WiFi positioning methods may result in limited positioning accuracy because of the limited information of Received Signal Strength (RSS) of WiFi signal. This paper proposed a context-aware assisted WiFi positioning method (CAA-PM), which uses context information (i.e., light and sound) to assist WiFi-RSS for indoor positioning and uses an improved variable weight dynamic KNN fingerprint identification algorithm (VWD-KNN). Finally, experiments are carried out by using the dataset collected in both a closed laboratory and an open long corridor, and it is shown that the proposed algorithm substantially improves the localization accuracy comparing with other three classical algorithms.

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