A crowdsensing approach for mobile learning in acoustics and noise monitoring

Novel technologies represent a promising way for boosting learning quality in scientific sectors, by engaging students more effectively into experimental activities. Mobile devices allow increasing learning effectiveness significantly, thanks to their diffusion, especially amongst youngsters. Built-in sensors can enable easily-deployable, low-cost and large-scale sensing networks, which exploit the Mobile Crowd-Sensing (MCS) paradigm and involve their owners directly into scientific monitoring activities. For such reasons, in this paper we present a MCS-based noise-sensing platform for engaging students in learning acoustics and sound metering. The proposed platform can be included into traditional didactic activities about those topics. This capability is fostered also by the Bring Your Own Device (BYOD) approach, which further eases the platform diffusion across students. Moreover, BYOD paves the way for the platform application as a MOOC (Massive Online Open Course) enabler. The paper presents the adopted design and implementation methodologies, as well as the platform prototype and its technical validation. We believe that our approach offers students new possibilities for learning how to use professional sound level meters profitably and how to perform measurements correctly.