.png){kind=icon}
返回
Landmark Graph-Based Indoor Localization
.png){kind=icon}
PRE
AI
DOI：10.1109/JIOT.2020.2989501.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Indoor localization is important for a variety of applications, such as location-based services, mobile social networks, and emergency response. Fusing spatial information is an effective way to achieve accurate indoor localization with little or with no need for extra hardware. However, the existing indoor localization methods that make use of spatial information are either computationally expensive or sensitive to the completeness of landmarks. In this article, we propose a novel, low-cost, high-accuracy indoor localization method based on a landmark graph. The experimental results show that the proposed method outperforms the state-of-the-art methods.
Keyword:
Wireless fidelity
Hidden Markov models
Sensors
Smart phones
Internet of Things
Fingerprint recognition
Calibration
Indoor positioning
landmarks
location-based services
pedestrian dead reckoning (PDR)
smartphones
spatial information
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
8.9
论文数:
1.4W
被引数:
7.8W
机构
引用论文
A TUTORIAL ON HIDDEN MARKOV-MODELS AND SELECTED APPLICATIONS IN SPEECH RECOGNITION关于语音识别中的隐马尔可夫模型和选定应用的教程.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
分享收藏SenseIO: Realistic Ubiquitous Indoor Outdoor Detection System Using SmartphonesIEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
分享收藏Some metric aspects of the permanent and deciduous dentition of the pygmy chimpanzee (Pan paniscus)
PREAI
分享收藏
查看更多内容