Collaborative learning from Mobile Crowd Sensing: A case study in electromagnetic monitoring

Personal mobile devices are nowadays so pervasive that a broad range of novel learning practices and paradigms can profitably exploits them. Mobile Crowd Sensing (MCS) is one of them. In MCS, mobiles act as data sources for monitoring tasks (e.g., traffic planning, air pollution monitoring, emergency management), thanks to their computational capability and their embedded sensors. From a pedagogical perspective, MCS offers continuous learning experiences that increases students' skills and expertise by engaging them directly into practical activities and on-the-field analyses. However, the wide diffusion of mobiles requires a reliable wireless coverage, to guarantee proper Quality of Service levels, thus potentially increasing the electromagnetic field levels in a given geographical area. Therefore, we propose a complete data warehouse solution that exploits MCS paradigm to pursue three main research purposes. Firstly, motivating students from engineering courses to acquire a better knowledge in wireless communication topics by offering them experiential and collaborative learning approaches. Secondly, performing a preliminary screening of the signals received by mobiles for 3G/4G standards (e.g., UMTS, LTE), since this domain did not benefit from MCS solutions so far. Thirdly, identifying prospective areas where more detailed measuring campaigns must be addressed. A deep analysis of the achievable pedagogical benefits as well as the thorough description of both design and implementation phases is provided. Evaluation results and preliminary users' feedback complete this research work.