A Mobile Crowd-Sensing Platform for Noise Monitoring in Smart Cities - Zappatore, M.; Longo, A.; Bochicchio, M.A.; Zappatore, D.; Morrone, A.A.; De Mitri, G. (EAI Endorsed Transactions on Smart Cities, 2016)
Modern cities are moving towards novel approaches for urban sustainability for improving citizenship’s life quality, thus aiming at the Smart City model. Environmental and mobility issues represent two key areas where policy makers address their interventions and, amongst them, noise pollution is one of the most significant causes of public concern. However, noise monitoring campaigns are expensive and require skilled personnel. A viable alternative is represented by Mobile Crowd Sensing (MCS) paradigm, which exploits mobile devices as sensing platforms. In this paper, we propose a MCS-based platform that exploits noise measurements collected by citizens and offers a suggestion system to city managers about noise abatement measures (in terms of both estimated noise reduction and average installation costs). Several field tests demonstrated the feasibility of this approach as a suitable way to support city managers and to widen the possibilities of collaborative urban noise monitoring.