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Computer Sciences, Information Science
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.
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.