Soft-clustering technique for fingerprint-based localization

dc.contributor.authorCherntanomwong, Panarat
dc.contributor.authorSooraksa, Pitikhate
dc.date.accessioned2026-08-06T10:18:51Z
dc.date.available2026-08-06T10:18:51Z
dc.date.issued2018-01-01
dc.description.abstractIn this paper, the soft-clustering algorithm for the fingerprint-based localization technique is proposed. In an indoor environment, the fingerprint-based localization technique is usually employed since it can deal with signal fluctuation. Its basic principle is to find the target location by comparing its signal parameters with a previously recorded database of knownlocation- signal parameters. Here, the received signal strength indicator (RSSI) provided by the wireless sensor network (WSN) is used as the signal parameter. The high accuracy of location estimation requires a very fine spatial resolution of the database, corresponding to the time consumed for pattern matching. To reduce the calculation time, clustering can be applied because it can reduce the database size by grouping similar data in the same cluster. The accuracy of the algorithm to cluster the target location and fingerprint locations is the main concern. The result shows that the clustering technique used can successfully cluster the target sensing node into an appropriate cluster. This implies that, by using soft clustering with the fingerprint technique, the target location can be estimated faster than by using classical fingerprint techniques since the target location can be estimated within a small set of fingerprints in the cluster, not with all fingerprints in the database.
dc.identifier.citationSensors and Materials, 30(10), 2221-2233, 2018
dc.identifier.doi10.18494/SAM.2018.1844
dc.identifier.issn09144935
dc.identifier.other2-s2.0-85055060046
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/8278
dc.sourceSensors and Materials
dc.subjectFingerprint technique
dc.subjectLocalization
dc.subjectSoft clustering
dc.subjectWireless sensor network
dc.subjectZigBee
dc.titleSoft-clustering technique for fingerprint-based localization
dc.typeArticle

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