Fusing passive RFID and BIM for increased accuracy in indoor localization

Author:

Costin Aaron M.,Teizer Jochen

Abstract

Abstract Background Finding the current location of a specific utility or oneself in an unfamiliar facility can be difficult and time consuming. The hypothesis tested in this paper is that using the information contained within Building Information Models (BIM) can increase the accuracy of indoor positioning algorithms using context-aware sensing technology. The presented work demonstrates how the integration of passive Radio Frequency Identification (RFID) tracking technology and Building Information Modeling (BIM) can assist indoor localization for potential applications in facilities management for proactive preventative maintenance. Methods This paper includes (1) developing a framework that utilizes the integration of commercially-available RFID and a building information model; (2) evaluating the framework for real-time resource location tracking within an indoor environment; and (3) developing an algorithm for real-time localization and visualization in a BIM. A prototype application has been developed that simultaneously connects the RFID readers on a maintenance cart, an asset maintenance database and a BIM model. Three multilateralization approaches were compared in the system to use in the algorithm. Testing was conducted in a facility with a corridor that loops around in a rectangle. Results The goal is to have a system accuracy within 3 m. Results show that fusing BIM with multilateralization techniques for RFID technology can decrease the number of false reads by 64 % versus standalone multilateralization equations. The greatest system accuracy achieved was 1.66 m. Conclusions Significantly, the results validate the hypothesis that BIM can increase indoor localization accuracy, and show the usefulness of using BIM for indoor localization in addition to real-time visualization.

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Engineering (miscellaneous),Modelling and Simulation

Cited by 40 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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3