ICFICE 2019
Current Result Document :
| 한글제목(Korean Title) |
Design of Wi-Fi based Indoor Positioning System using Machine Learning |
| 영문제목(English Title) |
Design of Wi-Fi based Indoor Positioning System using Machine Learning |
| 저자(Author) |
Chang-Pyo Yoon
Chi-Gon Hwang
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| 원문수록처(Citation) |
VOL 11 NO. 01 PP. 0070 ~ 0072 (2019. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Recently, a study of indoor location recognition technology is being carried out variously based on machine learning. In this case, the process of collecting that is learning and training data for machine learning and the data pre-processing process used as input data of learning algorithm are very important for more accurate location recognition. To do this, the data preprocessing is performed by the association analysis using the ontology. And the selection problem of algorithm is also very important for more accurate position recognition among machine learning algorithms. Especially, when Wi-Fi fingerprint is used, due to characteristics of collected RSSI signal, environment change occurs for location recognition such as noise. When such a low-quality signal is used for position recognition, the low-quality input data is used for machine learning, thereby causing a problem in the position recognition rate. Therefore, in this paper, we propose a method of designing indoor location recognition system based on machine learning using learning model acquisition and grouping technology to collect and manage learning data and obtain more accurate location recognition results.
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| 키워드(Keyword) |
Indoor Positioning
Wi-Fi Fingerprint
Machine Learning
Ontology
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| 파일첨부 |
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