Understanding students' mobility habits towards the implementation of an adaptive ubiquitous platform

Abstract

Adapting technological environments to users is a concern since Mark Weiser launched the concept of ubiquitous computing and, in order to do that, is necessary to understand users' characteristics. In this context, the purpose of this paper is to present a study about students' mobility habits within a university campus, having the intention of getting insights towards the best place to set an interactive public display and of predicting the main characteristics of the audience that will be present on that spot in forthcoming periods. Thus, the envisioned results of this work will allow the adaptation of the contents exhibited on the device to the audience. To perform the study, a set of logs of accesses to the university's Wi-Fi was used, data mining techniques were implemented and forecasting models were built, using the line of work suggested by the CRISP-DM methodology. As result, students profile were built based on past wireless accesses and on their scholar schedules, and three time series models were used (Holt-Winters, Seasonal Naive and Simple Exponential Smoothing) to predict the presence of students on the envisioned spot in future periods.