CrowdX

Author:

Chen Huijie1,Li Fan1,Hei Xiaojun2,Wang Yu3

Affiliation:

1. School of Computer Science, Beijing Institute of Technology, Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China

2. School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

3. Department of Computer Science, University of North Carolina at Charlotte, Charlotte, USA

Abstract

The lack of floorplan limits the spread of pervasive indoor location-based services. Existing crowdsourcing based approaches mostly rely on identifying, locating landmarks in the environment and utilizing the spatial relationship between the landmarks and traces for efficiently constructing fine-grained floorplan. However, these methods are always restricted by the sparse landmark distribution or may cause privacy leakage. In this paper, we propose CrowdX, a crowdsourcing system for accurate, low-cost indoor floorplan construction enhanced with opportunistic encounters among mobile users. The key insight is that the spatial relation (i.e., the displacement of each user and the distance between each other during the encounter) will be extracted from the audio and inertia data, which are aligned by the proposed vibration event-based method. Such information can be used to calibrate the drift of encounter position. The calibrated encounter position is beneficial to most of the floorplan generation steps, such as trace drift elimination, landmark positioning, hallway assembling, and room area estimation. Our experiments in three shopping malls show that CrowdX achieves an average F-measure around 89.4%. In addition, the average estimated room area error within about 20%. The evaluation results demonstrate a significant improvement of accuracy enhanced with opportunistic encounters.

Funder

U.S. Department of Transportation Center for Advanced Multimodal Mobility Solutions and Education

China Scholarship Council

National Natural Science Foundation of China

US National Science Foundation under Grant

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Reference35 articles.

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Robust indoor localization based on multi-modal information fusion and multi-scale sequential feature extraction;Future Generation Computer Systems;2024-02

2. Fair Incentive Mechanism for Mobile Crowdsensing;Incentive Mechanism for Mobile Crowdsensing;2024

3. A Brief Introduction;Incentive Mechanism for Mobile Crowdsensing;2024

4. A survey of crowdsourcing-based indoor map learning methods using smartphones;Results in Control and Optimization;2023-03

5. TransFloor;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2022-12-21

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