Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
Computer Sciences, Information Science
Abstract
Citieshaveanincreasinglydensenetworkofconnectedaccess points that enable individuals and groups to access the web on a range of different devices. Although, in most cases, the data collected from these networks is anonymised, when aggregated, it provides a rich illustration of how cities, public places and urban spaces are used. However, making use of this data can prove challenging as rarely, due to anonymization and data protection measures, is the data labelled and often the accuracy of the location information is questionable. Given these constraints, we have investigated a set of methods that can be applied to anonymous WiFi- location-based data. Through two specific use-cases, we show successful examples of each method, describing insights and intuitions along with providing an explanation of their application.
DOI
https://doi.org/10.13140/RG.2.2.23587.76323
Recommended Citation
McAuley, J., Roux, C., & Little, J. (2017). Approaches and Techniques for analysing WiFi location data. The 25th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, 2017. doi:10.13140/RG.2.2.23587.76323
Funder
SFI Connect Center, Trinity College Dublin
Publication Details
Paper presented at the 25th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, 2017.