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IONavi: An Indoor-Outdoor Navigation Service via Mobile Crowdsensing

Published: 24 April 2017 Publication History

Abstract

The proliferation of mobile computing has prompted navigation to be one of the most attractive and promising applications. Conventional designs of navigation systems mainly focus on either indoor or outdoor navigation. However, people have a strong need for navigation from a large open indoor environment to an outdoor destination in real life. This article presents IONavi, a joint navigation solution, which can enable passengers to easily deploy indoor-outdoor navigation service for subway transportation systems in a crowdsourcing way. Any self-motivated passenger records and shares individual walking traces from a location inside a subway station to an uncertain outdoor destination within a given range, such as one kilometer. IONavi further extracts navigation traces from shared individual traces, each of which is not necessary to be accurate. A subsequent following user achieves indoor-outdoor navigation services by tracking a recommended navigation trace. Extensive experiments are conducted on a subway transportation system. The experimental results indicate that IONavi exhibits outstanding navigation performance from an uncertain location inside a subway station to an outdoor destination. Although IONavi is to enable indoor-outdoor navigation for subway transportation systems, the basic idea can naturally be extended to joint navigation from other open indoor environments to outdoor environments.

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  1. IONavi: An Indoor-Outdoor Navigation Service via Mobile Crowdsensing

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      Published In

      cover image ACM Transactions on Sensor Networks
      ACM Transactions on Sensor Networks  Volume 13, Issue 2
      May 2017
      235 pages
      ISSN:1550-4859
      EISSN:1550-4867
      DOI:10.1145/3081318
      • Editor:
      • Chenyang Lu
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Publication History

      Published: 24 April 2017
      Accepted: 01 January 2017
      Revised: 01 October 2016
      Received: 01 May 2016
      Published in TOSN Volume 13, Issue 2

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      Author Tags

      1. Indoor-outdoor navigation
      2. indoor localization
      3. mobile crowdsensing
      4. subway station navigation
      5. trace clustering

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      • Research-article
      • Research
      • Refereed

      Funding Sources

      • Preliminary Research Funding of National University of Defense Technology
      • National Natural Science Foundation of China
      • Program for New Century Excellent Talents in University and Distinguished Young Scholars of National University of Defense Technology
      • National Postdoctoral Program for Innovative Talents
      • National Natural Science Foundation for Outstanding Excellent young scholars of China
      • National Basic Research Program (973 program)

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      • (2023)Multi-Sensor Data Fusion Solutions for Blind and Visually Impaired: Research and Commercial Navigation Applications for Indoor and Outdoor SpacesSensors10.3390/s2312541123:12(5411)Online publication date: 7-Jun-2023
      • (2023)Collusion-Resistant Worker Recruitment in Crowdsourcing SystemsIEEE Transactions on Mobile Computing10.1109/TMC.2021.307109322:1(129-144)Online publication date: 1-Jan-2023
      • (2022)The Rescuer’s Navigation in Metro Stations Based on Inertial Sensors and WiFiElectronics10.3390/electronics1201010812:1(108)Online publication date: 27-Dec-2022
      • (2022)A Survey of Application and Key Techniques for Mobile CrowdsensingWireless Communications & Mobile Computing10.1155/2022/36935372022Online publication date: 1-Jan-2022
      • (2022)IntroductionPrivacy-Preserving in Mobile Crowdsensing10.1007/978-981-19-8315-3_1(3-22)Online publication date: 21-Dec-2022
      • (2021)Defining a Model for Integrating Indoor and Outdoor Network Data to Support Seamless Navigation ApplicationsISPRS International Journal of Geo-Information10.3390/ijgi1008056510:8(565)Online publication date: 21-Aug-2021
      • (2021)Investigating the Relationship between Capability and Motivation of Crowd Worker to Get Better Performance: A Mathematical ApproachMathematical Problems in Engineering10.1155/2021/15485462021(1-14)Online publication date: 18-Sep-2021
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      • (2021)SiFiACM Transactions on Internet of Things10.1145/34505672:3(1-21)Online publication date: 8-Jul-2021
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