An Open Platform for Studying and Testing Context-Aware Indoor Positioning Algorithms
Nearchos Paspallis () and
Marios Raspopoulos ()
Additional contact information
Nearchos Paspallis: University of Central Lancashire
Marios Raspopoulos: University of Central Lancashire
A chapter in Complexity in Information Systems Development, 2017, pp 39-50 from Springer
Abstract:
Abstract This paper presents an open platform for studying and analyzing indoor positioning algorithms. While other such platforms exist, our proposal features novelties related to the collection and use of additional context data. The platform is realized in the form of a mobile client, currently implemented on Android. It enables manual collection of radio-maps—i.e. fingerprints of Wi-Fi signals—while also allowing for amending the fingerprints with various context data which could help improve the accuracy of positioning algorithms. While this is a research-in-progress platform, an initial experiment was carried out and its results were used to justify its applicability and relevance.
Keywords: Indoor positioning; Fingerprint; Context-aware; Android (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-319-52593-8_3
Ordering information: This item can be ordered from
http://www.springer.com/9783319525938
DOI: 10.1007/978-3-319-52593-8_3
Access Statistics for this chapter
More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().