Wavelet Frequency Tensor applied to temporary environments in discrete spaces to obtain mobility patterns. Use case in the detection of routes in a territory

Abstract

[EN] The use of frequency tensors for the representation of discrete time series information through wavelet transformations offers a methodology that allows the application of classification methods that result in the detection of mobility patterns in a geographical area. The use case focuses on a territory from which the geolocation of anonymized mobile device identifiers is extracted to aggregate its frequencies in order to ensure personal privacy. Furthermore, the kind of datasets we used in our study were treated with other methods to ensure that the identifiers for a same user change over time. Nowadays, this form of data treatment is implemented using a continuous process in smartcity platforms, first by anonymizing and second by changing the seed of the encryption method. Where the suggested technique is applied, a cluster analysis is performed, by which subsets or routes of the movements between the different points studied are obtained.