An approach to the use of Wi-Fi signals for hospital indoor location detection: Performance comparison of classification algorithms

dc.authorscopusid57198798113
dc.authorscopusid57203011622
dc.contributor.authorSabah, L.
dc.contributor.authorArgun, U. I. D.
dc.date.accessioned2021-12-01T18:38:50Z
dc.date.available2021-12-01T18:38:50Z
dc.date.issued2019
dc.department[Belirlenecek]en_US
dc.description2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 -- 24 April 2019 through 26 April 2019 -- -- 148870en_US
dc.description.abstractDetecting the location in the indoor is relatively difficult compared to the outdoor places. Location detection in outdoor places GPS-enabled devices and signals from at least 3 different satellites are easy to implement due to various difficulties (such as forested areas, high-rise buildings). On the other hand, In indoor places like hospital, airports, car parks, mines; Wi-Fi, Beacon and Radio Frequency (RF) signals are used for position detection. In this study, on a sample data set consisting of signals from 7 different access points in a closed area, analyzes were made by using machine learning algorithms on the correct position determination. With the obtained values and the comparisons made, it was seen that the location could be determined by using the access point signals in the indoor. In this pre - study, it is aimed to reduce adverse conditions with rapid and high accuracy location detection in emergency situations which may occur in hospital buildings where time is crucial. © 2019 IEEE.en_US
dc.identifier.doi10.1109/EBBT.2019.8741769
dc.identifier.isbn9781728110134
dc.identifier.scopus2-s2.0-85068574387en_US
dc.identifier.urihttps://doi.org/10.1109/EBBT.2019.8741769
dc.identifier.urihttps://hdl.handle.net/20.500.12684/9863
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassificationen_US
dc.subjectData miningen_US
dc.subjectIndoor location detection.en_US
dc.subjectK nearest neighboren_US
dc.subjectNaive bayesen_US
dc.titleAn approach to the use of Wi-Fi signals for hospital indoor location detection: Performance comparison of classification algorithmsen_US
dc.typeConference Objecten_US

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