WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms
With the rapid advances of mobile devices, location-based services have received significant attention. Among the available services, finding the exact position of a person, especially indoors, is a challenging problem. For indoor environments, using WiFi-based technology for positioning purposes is...
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| Định dạng: | Conference paper |
| Ngôn ngữ: | English |
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Khoa học và Kỹ thuật
2022
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| Truy cập trực tuyến: | http://scholar.dlu.edu.vn/handle/123456789/1647 |
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oai:scholar.dlu.edu.vn:123456789-16472022-12-26T09:59:19Z WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms Ninh Duong-Bao, Luong Nguyen Thi, Huy Quang Pham, and Khanh Nguyen-Huu WiFi fingerprinting, indoor positioning, machine learning, support vector machine, decision tree, random forest With the rapid advances of mobile devices, location-based services have received significant attention. Among the available services, finding the exact position of a person, especially indoors, is a challenging problem. For indoor environments, using WiFi-based technology for positioning purposes is reasonable due to its utilization of existing WiFi infrastructure. In this paper, we implement and compare the positioning results of three machine learning algorithms such as support vector machine, decision tree, and random forest. The algorithms are applied to a multi-condition WiFi fingerprinting dataset which was conducted in an office room where different environmental conditions are considered. The results show that the random forest achieves the best classification result with an accuracy of over 85%, while the two others get an approximate accuracy of 80%. 67-71 2022-12-26T09:59:19Z 2022-12-26T09:59:19Z 2022-07 Conference paper Bài báo đăng trên KYHT trong nước (có ISBN) http://scholar.dlu.edu.vn/handle/123456789/1647 en The 2022 Information and Communication Technology (ICT) Conference 978-604-67-2385-1 Khoa học và Kỹ thuật Hà Nội |
| institution |
Thư viện Trường Đại học Đà Lạt |
| collection |
Thư viện số |
| language |
English |
| topic |
WiFi fingerprinting, indoor positioning, machine learning, support vector machine, decision tree, random forest |
| spellingShingle |
WiFi fingerprinting, indoor positioning, machine learning, support vector machine, decision tree, random forest Ninh Duong-Bao, Luong Nguyen Thi, Huy Quang Pham, and Khanh Nguyen-Huu WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms |
| description |
With the rapid advances of mobile devices, location-based services have received significant attention. Among the available services, finding the exact position of a person, especially indoors, is a challenging problem. For indoor environments, using WiFi-based technology for positioning purposes is reasonable due to its utilization of existing WiFi infrastructure. In this paper, we implement and compare the positioning results of three machine learning algorithms such as support vector machine, decision tree, and random forest. The algorithms are applied to a multi-condition WiFi fingerprinting dataset which was conducted in an office room where different environmental conditions are considered. The results show that the random forest achieves the best classification result with an accuracy of over 85%, while the two others get an approximate accuracy of 80%. |
| format |
Conference paper |
| author |
Ninh Duong-Bao, Luong Nguyen Thi, Huy Quang Pham, and Khanh Nguyen-Huu |
| author_facet |
Ninh Duong-Bao, Luong Nguyen Thi, Huy Quang Pham, and Khanh Nguyen-Huu |
| author_sort |
Ninh Duong-Bao, Luong Nguyen Thi, Huy Quang Pham, and Khanh Nguyen-Huu |
| title |
WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms |
| title_short |
WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms |
| title_full |
WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms |
| title_fullStr |
WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms |
| title_full_unstemmed |
WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms |
| title_sort |
wifi fingerprinting-based indoor positioning with machine learning algorithms |
| publisher |
Khoa học và Kỹ thuật |
| publishDate |
2022 |
| url |
http://scholar.dlu.edu.vn/handle/123456789/1647 |
| _version_ |
1768306224428744704 |