文章基本信息

标题：Wifi Indoor Positioning with Genetic and Machine Learning Autonomous War-Driving Scheme
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作者：Pham Doan Tinh ; Bui Huy Hoang
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2022
卷号：13
期号：2
DOI：10.14569/IJACSA.2022.0130279
语种：English
出版社：Science and Information Society (SAI)
摘要：Wifi Fingerprinting is a widely used method for indoor positioning due to its proven accuracy. However, the offline phase of the method requires collecting a large quantity of data which costs a lot of time and effort. Furthermore, interior changes in the environment can have impact on system accuracy. This paper addresses the issue by proposing a new data collecting procedure in the offline phase that only needs to collect some data points (Wi-fi reference point). To have a sufficient amount of data for the offline phase, we proposed a genetic algorithm and machine learning model to generate labeled data from unlabeled user data. The experiment was carried out using real Wi-fi data collected from our testing site and the simulated motion data. Results have shown that using the proposed method and only 8 Wi-fi reference points, labeled data can be generated from user’s live data with a positioning error of 1.23 meters in the worst case when motion error is 30%. In the online phase, we achieved a positioning error of 1.89 meters when using the Support Vector Machine model at 30% motion error.
关键词：Wifi fingerprinting; indoor positioning; machine learning; genetic algorithm