Sabah, LeventArgun, İrem Düzdar2020-04-302020-04-302019978-1-7281-1013-4https://hdl.handle.net/20.500.12684/2616International Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science (EBBT) -- APR 24-26, 2019 -- Istanbul Arel Univ, Kemal Gozukara Campus, Istanbul, TURKEYWOS: 000491430200027Detecting 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.trinfo:eu-repo/semantics/closedAccessdata miningclassificationnaive bayesk nearest neighborindoor location detectionConference ObjectN/A