Tampere University of Technology

TUTCRIS Research Portal

Indoor Localisation using Aroma Fingerprints: Comparing Nearest Neighbour Classification Accuracy using Different Distance Measures

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2018 7th International Conference on Systems and Control (ICSC)
Subtitle of host publication24-26 Oct. 2018, Valencia, Spain
Place of PublicationValencia, Spain
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-5386-8537-2
ISBN (Print)978-1-5386-8538-9
DOIs
Publication statusPublished - Oct 2018
Publication typeA4 Article in a conference publication
EventInternational Conference on Systems and Control -
Duration: 1 Jan 2000 → …

Publication series

Name
ISSN (Electronic)2379-0067

Conference

ConferenceInternational Conference on Systems and Control
Period1/01/00 → …

Abstract

Measurements from an ion mobility spectrometry electronic nose (eNose) can be used for distinguishing different rooms in indoor localisation. An earlier study showed that the Nearest Neighbour classifier with Euclidean distance for features provides reasonable accuracy under certain conditions. In this paper 66 alternative distance measures are compared to the Euclidean distance and principal component analysis (PCA) is applied to the data. PCA shows that the measurements on the various channels of the eNose are correlated and that using principal components 1, 2 and 4 increases the accuracy considerably. Furthermore, the experiments revealed three Pareto optimal distance measures that reduce the misclassification rate between 9-10% while using only 82-88% of the search time compared with Euclidean distance.

Publication forum classification

Field of science, Statistics Finland

Downloads statistics

No data available