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Infrastructure-Independent Indoor Localization and Navigation
The University of Melbourne.
The University of Melbourne.
RMIT.
Umeå University.ORCID iD: 0000-0001-5629-0981
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2019 (English)In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 52, no 3, article id 61Article in journal (Refereed) Published
Abstract [en]

In the absence of any global positioning infrastructure for indoor environments, research on supporting human indoor localization and navigation trails decades behind research on outdoor localization and navigation. The major barrier to broader progress has been the dependency of indoor positioning on environment-specific infrastructure and resulting tailored technical solutions. Combined with the fragmentation and compartmentalization of indoor environments, this poses significant challenges to widespread adoption of indoor location-based services. This article puts aside all approaches of infrastructure-based support for human indoor localization and navigation and instead reviews technical concepts that are independent of sensors embedded in the environment. The reviewed concepts rely on a mobile computing platform with sensing capability and a human interaction interface (“smartphone”). This platform may or may not carry a stored map of the environment, but does not require in situ internet access. In this regard, the presented approaches are more challenging than any localization and navigation solutions specific to a particular, infrastructure-equipped indoor space, since they are not adapted to local context, and they may lack some of the accuracy achievable with those tailored solutions. However, only these approaches have the potential to be universally applicable.

Place, publisher, year, edition, pages
ACM Digital Library, 2019. Vol. 52, no 3, article id 61
Keywords [en]
spatial information, indoor localization, human navigation, infrastructure-independent positioning
National Category
Infrastructure Engineering Computer Sciences Human Computer Interaction Information Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-161084DOI: 10.1145/3321516OAI: oai:DiVA.org:umu-161084DiVA, id: diva2:1331730
Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2019-06-28Bibliographically approved

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Publisher's full texthttps://dl.acm.org/citation.cfm?id=3321516

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CiteExportLink to record
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Citation style
  • apa
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Output format
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