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Growing an organic indoor location system

Published: 15 June 2010 Publication History

Abstract

Most current methods for 802.11-based indoor localization depend on surveys conducted by experts or skilled technicians. Some recent systems have incorporated surveying by users. Structuring localization systems "organically," however, introduces its own set of challenges: conveying uncertainty, determining when user input is actually required, and discounting erroneous and stale data. Through deployment of an organic location system in our nine-story building, which contains nearly 1,400 distinct spaces, we evaluate new algorithms for addressing these challenges. We describe the use of Voronoi regions for conveying uncertainty and reasoning about gaps in coverage, and a clustering method for identifying potentially erroneous user data. Our algorithms facilitate rapid coverage while maintaining positioning accuracy comparable to that achievable with survey-driven indoor deployments.

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cover image ACM Conferences
MobiSys '10: Proceedings of the 8th international conference on Mobile systems, applications, and services
June 2010
382 pages
ISBN:9781605589855
DOI:10.1145/1814433
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 ACM 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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Published: 15 June 2010

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  1. crowd-sourcing
  2. localization
  3. location-based services

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Overall Acceptance Rate 274 of 1,679 submissions, 16%

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  • (2024)A Comprehensive Survey on Delaunay Triangulation: Applications, Algorithms, and Implementations Over CPUs, GPUs, and FPGAsIEEE Access10.1109/ACCESS.2024.335470912(12562-12585)Online publication date: 2024
  • (2024)Robust Indoor LocalizationLocation, Localization, and Localizability10.1007/978-981-97-3176-3_8(131-162)Online publication date: 12-Jul-2024
  • (2023)Laser Range Scanners for Enabling Zero-overhead WiFi-based Indoor Localization SystemACM Transactions on Spatial Algorithms and Systems10.1145/35396599:1(1-25)Online publication date: 12-Jan-2023
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  • (2023)Implicit Multimodal Crowdsourcing for Joint RF and Geomagnetic FingerprintingIEEE Transactions on Mobile Computing10.1109/TMC.2021.308826822:2(935-950)Online publication date: 1-Feb-2023
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