JOURNAL ARTICLE

Landmark Graph-Based Indoor Localization

Fuqiang GuShahrokh ValaeeKourosh KhoshelhamJianga ShangRui Zhang

Year: 2020 Journal:   IEEE Internet of Things Journal Vol: 7 (9)Pages: 8343-8355   Publisher: Institute of Electrical and Electronics Engineers

Abstract

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.

Keywords:
Landmark Computer science Graph Artificial intelligence Computer vision Location-based service Spatial analysis Data mining Theoretical computer science Computer network

Metrics

40
Cited By
2.85
FWCI (Field Weighted Citation Impact)
59
Refs
0.92
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Underwater Vehicles and Communication Systems
Physical Sciences →  Engineering →  Ocean Engineering
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
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