A Multi-Floor Indoor Pedestrian Localization Method Using Landmarks Detection for Different Holding Styles
| Autor: | Seon-Woo Lee, Khanh Nguyen-Huu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Article Subject
Computer Networks and Communications Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Word error rate TK5101-6720 02 engineering and technology Pedestrian Tracking (particle physics) 01 natural sciences law.invention Stairs Position (vector) law Dead reckoning 0202 electrical engineering electronic engineering information engineering Computer vision Landmark business.industry 010401 analytical chemistry 020206 networking & telecommunications 0104 chemical sciences Computer Science Applications Barometer Telecommunication Artificial intelligence business |
| Zdroj: | Mobile Information Systems, Vol 2021 (2021) |
| ISSN: | 1574-017X |
| DOI: | 10.1155/2021/6617417 |
| Popis: | The pedestrian dead reckoning (PDR) technique is widely used due to its ease of implementation on portable devices such as smartphones. However, the position error that accumulates over time is the main drawback of this technology. In this paper, we propose a fusion method combining a PDR technique and the landmark recognition methods for multi-floor indoor environments using a smartphone in different holding styles. The proposed method attempts to calibrate the position of a pedestrian by detecting whether the pedestrian passes by specific locations called landmarks. Three kinds of landmarks are defined, which are the WiFi, the turning, and the stairs landmarks, and the detection methods for each landmark are proposed. Besides, an adaptive floor detection method using a barometer and a WiFi fingerprinting technique is suggested for tracking a pedestrian in a multi-floor building. The developed system can track the pedestrian holding a smartphone in four styles. The results of the experiment conducted by three subjects changing the holding style in a three-floor building show the superior performance of the proposed method. It reduces the error rate of positioning results to less than 57.51% compared with the improved PDR alone system. |
| Databáze: | OpenAIRE |
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