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...
Đã lưu trong:
| Những tác giả chính: | , , , |
|---|---|
| Định dạng: | Conference paper |
| Ngôn ngữ: | English |
| Được phát hành: |
Khoa học và Kỹ thuật
2023
|
| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/handle/123456789/2007 |
| Các nhãn: |
Thêm thẻ
Không có thẻ, Là người đầu tiên thẻ bản ghi này!
|
| Thư viện lưu trữ: | Thư viện Trường Đại học Đà Lạt |
|---|
| id |
oai:scholar.dlu.edu.vn:123456789-2007 |
|---|---|
| record_format |
dspace |
| spelling |
oai:scholar.dlu.edu.vn:123456789-20072023-06-14T06:52:57Z WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms Nguyễn, Thị Lương Dương, Bảo Ninh Phạm, Quang Huy Nguyễn, Hữu Khánh 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 2023-04-20T05:04:39Z 2023-04-20T05:04:39Z 2022-07 Conference paper Bài báo đăng trên KYHT trong nước (có ISBN) https://scholar.dlu.edu.vn/handle/123456789/2007 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 |
| 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 |
Nguyễn, Thị Lương Dương, Bảo Ninh Phạm, Quang Huy Nguyễn, Hữu Khánh |
| spellingShingle |
Nguyễn, Thị Lương Dương, Bảo Ninh Phạm, Quang Huy Nguyễn, Hữu Khánh WiFi Fingerprinting-based Indoor Positioning with Machine Learning Algorithms |
| author_facet |
Nguyễn, Thị Lương Dương, Bảo Ninh Phạm, Quang Huy Nguyễn, Hữu Khánh |
| author_sort |
Nguyễn, Thị Lương |
| 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 |
2023 |
| url |
https://scholar.dlu.edu.vn/handle/123456789/2007 |
| _version_ |
1778233835745443840 |