An Indoor Localization System with Pedestrian Dead Reckoning and WiFi Fingerprinting Techniques Based on Holding Styles
Luận văn thạc sĩ
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| Định dạng: | Luận văn |
| Ngôn ngữ: | English |
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Hallym University
2023
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| Những chủ đề: | |
| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/116231 |
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oai:scholar.dlu.edu.vn:DLU123456789-1162312023-10-05T16:56:31Z An Indoor Localization System with Pedestrian Dead Reckoning and WiFi Fingerprinting Techniques Based on Holding Styles Nguyễn, Hữu Khánh PDR WiFi fingerprinting Inertial sensor Smartphone Luận văn thạc sĩ Nowadays with the dramatically developing of the technology there are lots of new systems and devices that are very useful to support human being. Location-based services (LBS) are the services that can use real-time geo-data to control features and can play an important role in providing information, entertainment or security services (E.g. some services allow consumers to “check in” at restaurant, coffee shops, etc. such as Google Maps, Facebook; some services can track the location of a person or an object and some can be used to navigate for vehicles or pedestrians, etc.). For an outdoor environment, LBS use global navigation satellite systems (GNSS) such as Global Positioning System (GPS) to determine the current position of an object. But for an indoor environment, the GPS signal cannot work effectively because its limitation, thus, how can we track a pedestrian’s position in this environment accurately with low cost devices and energy saving is still a difficult question. Currently, smartphones have become an indispensable device for our daily life and everybody has started to own one. More than that, a smartphone has a number of integrated sensor types (E.g. accelerometer, gyroscope, magnetometer, etc. [1]) that include many useful features and suitable to combine with many techniques to solve the problems of indoor localization. In this thesis, pedestrian dead reckoning (PDR) and WiFi fingerprinting are potential techniques that are combined with the smartphone to build a full indoor positioning system that can be important in cases of managing the people in hospital or office. Lots of newly suggested methods have been applied to improve the overall performance and accuracy of the PDR system. Through many experiments, we can show the accuracy of within 4 m at 85th percentile. The contributions in this thesis are: (1) Recognition of different smartphone holding styles, (2) Detection of walking step, (3) Estimation of step length, (4) Estimation of Heading, (5) Compensation of WiFi fingerprinting. 2023-08-12T13:34:13Z 2023-08-12T13:34:13Z 2015 Thesis https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/116231 en application/pdf Hallym University |
| institution |
Thư viện Trường Đại học Đà Lạt |
| collection |
Thư viện số |
| language |
English |
| topic |
PDR WiFi fingerprinting Inertial sensor Smartphone |
| spellingShingle |
PDR WiFi fingerprinting Inertial sensor Smartphone Nguyễn, Hữu Khánh An Indoor Localization System with Pedestrian Dead Reckoning and WiFi Fingerprinting Techniques Based on Holding Styles |
| description |
Luận văn thạc sĩ |
| format |
Thesis |
| author |
Nguyễn, Hữu Khánh |
| author_facet |
Nguyễn, Hữu Khánh |
| author_sort |
Nguyễn, Hữu Khánh |
| title |
An Indoor Localization System with Pedestrian Dead Reckoning and WiFi Fingerprinting Techniques Based on Holding Styles |
| title_short |
An Indoor Localization System with Pedestrian Dead Reckoning and WiFi Fingerprinting Techniques Based on Holding Styles |
| title_full |
An Indoor Localization System with Pedestrian Dead Reckoning and WiFi Fingerprinting Techniques Based on Holding Styles |
| title_fullStr |
An Indoor Localization System with Pedestrian Dead Reckoning and WiFi Fingerprinting Techniques Based on Holding Styles |
| title_full_unstemmed |
An Indoor Localization System with Pedestrian Dead Reckoning and WiFi Fingerprinting Techniques Based on Holding Styles |
| title_sort |
indoor localization system with pedestrian dead reckoning and wifi fingerprinting techniques based on holding styles |
| publisher |
Hallym University |
| publishDate |
2023 |
| url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/116231 |
| _version_ |
1819802482805571584 |