An Approach to the use of Wi-Fi Signals for Hospital Indoor Location Detection: Performance Comparison of Classification Algorithms

• Published in: 2019 Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT) pp. 1 - 4
• Main Authors: Sabah, Levent, Argun, Üyesi Írem Duzdar
• Format: Conference Proceeding
• Language: English; Turkish
• Published: IEEE 01-04-2019
• Subjects: classification; Data mining; Global Positioning System; Hospitals; indoor location detection; k nearest neighbor; naive bayes; Support vector machines; Wireless communication; Wireless fidelity
• DOI: 10.1109/EBBT.2019.8741769

Detecting 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.