Evaluation of Valued Tolerance Rough Set and Decision Rules Method for WiFi-based Indoor Localization in Different Environments
Among various technologies being applied for indoor localization, WiFi has become a reliable source of information to determine the pedestrian’s position due to the widespread of WiFi access points in indoor environments. In this paper, the valued tolerance rough set and decision rules method (VTRS-...
Gorde:
| Egile Nagusiak: | , , , , |
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| Formatua: | Conference paper |
| Hizkuntza: | English |
| Argitaratua: |
Springer
2023
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| Gaiak: | |
| Sarrera elektronikoa: | https://scholar.dlu.edu.vn/handle/123456789/2720 |
| Etiketak: |
Etiketa erantsi
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| Thư viện lưu trữ: | Thư viện Trường Đại học Đà Lạt |
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| Gaia: | Among various technologies being applied for indoor localization, WiFi has become a reliable source of information to determine the pedestrian’s position due to the widespread of WiFi access points in indoor environments. In this paper, the valued tolerance rough set and decision rules method (VTRS-DR), which is firstly registered to WiFi fingerprinting-based localization, will be implemented and evaluated using two public datasets. The first one was conducted by a subject using a smartphone at a library including two floors in several months. Furthermore, to evaluate the localization accuracy when WiFi data was collected from different pedestrians as well as different smartphones, a crowdsourced WiFi fingerprinting dataset was utilized. From the deep analyses of localization results, the VTRS-DR method shows high accuracy and high robustness when testing in different environments with a mean error of 3.84 m, which is 27.87% lower than other compared methods. |
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