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as to redress the issue. The position of noise as an environmental pollutant and its influence on health are being increasingly acknowledged. Beyond its effects on the auditory system, noise causes annoyance and disturbs sleep, and it impairs cognitive efficiency. Furthermore, evidence from epidemiologic studies demonstrates that environmental noise is related to an elevated incidence of arterial hypertension, myocardial infarction, and stroke. Both observational and experimental research indicate that particularly evening-time noise could cause disruptions of sleep construction, vegetative arousals (e.g. increases of blood stress and coronary heart fee) and will increase in stress hormone levels and oxidative stress, which in turn might result in endothelial dysfunction and arterial hypertension. This evaluate focuses on the cardiovascular consequences of environmental noise exposure and stresses the importance of noise mitigation strategies for public health. The idea of Smart Cities and the monitoring of environmental parameters is an area of analysis that has attracted scientific attention over the past decade. These environmental parameters are properly-known as important factors in their affection in direction of people. Massive monitoring of this sort of parameters in cities is an expensive and complex task. Recent technologies of low-cost computing and low-power devices have opened researchers to a wide and more accessible analysis field, creating monitoring units for deploying Wireless Sensor Networks. Gathering data from them, improved city plans could possibly be carried out and the knowledge could help residents. In this work, the prototyping of a low-price acoustic sensor based mostly on the Raspberry Pi platform for its use within the analysis of the sound area is described. The system can also be linked to the cloud to share leads to real time. The computation assets of the Raspberry Pi permit treating high quality audio for calculating acoustic parameters. A pilot test was carried out with the installation of two acoustic units within the refurbishment works of a neighbourhood. In this deployment, the analysis of these gadgets through long-time period measurements was carried out, obtaining a number of acoustic parameters in real time for its broadcasting and examine. This check has proven the Raspberry Pi as a powerful and affordable computing core of a low-cost
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