Noise Mapping Through Mobile Crowdsourcing for Enhanced Living Environments

Abstract

Environmental noise pollution has a significant impact on health. The noise effects on health are related to annoyance, sleep and cognitive performance for both adults and children are reported in the literature. The smart city concept can be assumed as a strategy to mitigate the problems generated by the urban population growth and rapid urbanisation. Noise mapping is an important step for noise pollution reduction. Although, noise maps are particularly time-consuming and costly to create as they are produced with standard methodologies and are based on specific sources such as road traffic, railway traffic, aircraft and industrial. Therefore, the actual noise maps are significantly imperfect because the noise emission models and sources are extremely limited. Smartphones have incredible processing capabilities as well as several powerful sensors such as microphone and GPS. Using the resources present in a smartphone as long with participatory sensing, a crowdsourcing noise mobile application can be used to provide environmental noise supervision for enhanced living environments. Crowdsourcing techniques applied to environmental noise monitoring allow creating reliable noise maps at low-cost. This paper presents a mobile crowdsourcing solution for environmental noise monitoring named iNoiseMapping. The environmental noise data is collected through participatory sensing and stored for further analysis. The results obtained can ensure that mobile crowdsourcing offers several enhanced features for environmental noise supervision and analytics. Consequently, this mobile application is a significant decision-making tool to plan interventions for noise pollution reduction.