Sensors, Vol. 20, Pages 5583: RaveGuard: A Noise Monitoring Platform Using Low-End Microphones and Machine Learning

Sensors, Vol. 20, Pages 5583: RaveGuard: A Noise Monitoring Platform Using Low-End Microphones and Machine Learning Sensors doi: 10.3390/s20195583 Authors: Lorenzo Monti Mattia Vincenzi Silvia Mirri Giovanni Pau Paola Salomoni Urban noise is one of the most serious and underestimated environmental problems. According to the World Health Organization, noise pollution from traffic and other human activities, negatively impact the population health and life quality. Monitoring noise usually requires the use of professional and expensive instruments, called phonometers, able to accurately measure sound pressure levels. In many cases, phonometers are human-operated; therefore, periodic fine-granularity city-wide measurements are expensive. Recent advances in the Internet of Things (IoT) offer a window of opportunities for low-cost autonomous sound pressure meters. Such devices and platforms could enable fine time–space noise measurements throughout a city. Unfortunately, low-cost sound pressure sensors are inaccurate when compared with phonometers, experiencing a high variability in the measurements. In this paper, we present RaveGuard, an unmanned noise monitoring platform that exploits artificial intelligence strategies to improve the accuracy of low-cost devices. RaveGuard was initially deployed together with a professional phonometer for over two months in downtown Bologna, Italy, with the aim of collecting a large amount of precise noise pollutio...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research