Title :
Mining WiFi Data for Business Intelligence
Author :
Arora, D. ; Neville, Stephen ; Kin Fun Li
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Victoria, Victoria, BC, Canada
Abstract :
The WiFi networks provide an ease of accessing email, Web, and other Internet applications while on the move. However, deploying additional WiFi hotspots that can provide both increased coverage and enhance user quality of service largely depends upon the number of access points already existing and user densities. Extracting usage patterns and information from the available data has the potential to answer several business-focussed questions. In this paper, we show that by plotting WiFi locations in a two-dimensional space of incoming (downloading) and outgoing (uploading) data amount, in conjunction with the simple k-means clustering, it is possible to gain insight into the basic data usage patterns. When combined with information about geographic location of the WiFi hotspots such analysis can answer questions related to spatial patterns of data usage and make informed business decisions including charging customers at selected locations for WiFi service.
Keywords :
competitive intelligence; data mining; pattern clustering; quality of service; wireless LAN; Internet applications; Web access; Wi-Fi data mining; Wi-Fi hotspots; Wi-Fi location plotting; Wi-Fi networks; Wi-Fi service; access points; business decision making; business intelligence; business-focussed questions; coverage improvement; data usage patterns; downloaded data amount; e-mail access; geographic location; incoming data amount; information extraction; k-means clustering; outgoing data amount; spatial data patterns; two-dimensional space; uploaded data amount; usage pattern extraction; user densities; user quality-of-service enhancement; Business; Clustering algorithms; Data mining; IEEE 802.11 Standards; Machine learning algorithms; Quality of service; WiFi; clustering; machine learning; telecommunications;
Conference_Titel :
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2013 Eighth International Conference on
Conference_Location :
Compiegne
DOI :
10.1109/3PGCIC.2013.67
