Wi-Fi signal classification and visitor counting by region

Nejc Župec (2015) Wi-Fi signal classification and visitor counting by region. MSc thesis.

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Abstract

More and more mobile devices transmit Wi-Fi signals which can be detected by access points. Consequently the number of visitors near access points can be measured. Often we are interested in the number of visitors only for a certain region. Therefore, in the context of master's thesis, methods and products for indoor localization were studied. We transformed the localization problem into classification of Wi-Fi signals problem. Based on existing methods (nearest base station, trilateration and RADAR) we developed three new methods. In order to evaluate these methods the sytem for capturing Wi-Fi signals was set up at the Faculty of Computer and Information Science in Ljubljana. The data was being collected for two months. Based on machine learning algorithms we developed a new method, which correctly predicts the region in 85,1 % cases. If regions are separated by walls, the classification accuracy is more than 93 %.

Item Type:

Thesis (MSc thesis)

Keywords:

Wi-Fi, classification, SVM, machine learning, RADAR, trilateration, localization

Number of Pages:

122

Language of Content:

Slovenian

Mentor / Comentors:

Name and Surname	ID	Function
doc. dr. Mojca Ciglarič	256	Mentor

Link to COBISS:

http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1536399555)

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Item ID:

3006

Date Deposited:

02 Jul 2015 12:13

Last Modified:

13 Aug 2015 08:32

URI:

http://eprints.fri.uni-lj.si/id/eprint/3006

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