Abstract
City noise and sound are measured and processed with the purpose of drawing appropriate government legislation and regulations, ultimately aimed at contributing to a healthier environment for humans. The primary use of urban noise analysis is carried out with the main purpose of reporting or denouncing, to the appropriate authorities, a misconduct or correct a misuse of council resources. We believe that urban sounds carry more information than what it is extracted to date. In this paper we present a cloud-based urban sound analysis system for the capturing, processing and trading of urban sound-based information. By leveraging modern artificial intelligence algorithms running on a FOG computing city infrastructure, we will show how the presented solution can offer a valuable solution for exploiting urban sound information. A specific focus is given to the hardware implementation of the sound sensor and its multimicrophone architecture. We discuss how the presented architecture is designed to allow the trading of sound information between independent parties, transparently, using cloud-based sound processing APIs running on an inexpensive consumer-grade microphone.
Highlights
Urban noise is measured and analyzed with the purpose of drawing appropriate regulations [1,2] for a healthier urban environment [3]
There is a significant body of work focusing on Acoustic Event Detection (AED) in urban environments
As Amazon did with Echo, we propose a similar system structure where we host most of the sophisticated sound processing algorithm in a FOG computing platform
Summary
Urban noise is measured and analyzed with the purpose of drawing appropriate regulations [1,2] for a healthier urban environment [3]. From urban sounds, it is possible to extract several other types of valuable information related to human activities (e.g., vehicle traffic, garbage collection, delivery of goods, gunshots, leisure activities, etc) If this information could be made available, in a easy-to-use manner and at a low cost, it could enable the development of several intelligent services and products in the urban environment. Instead of using proprietary and costly acoustic sensors, we propose to explore the use of a consumer-grade commodity hardware for noise capturing and measurement, as a means to drastically reduce the costs of sound exploitation systems With this respect, our idea is to follow a similar strategy to the successful driver-less car manufacturers [9]. The overarching goal of the envisioned idea, hopefully reflected in this paper, is to show that this approach can enable new socially responsible business opportunities in the area of urban sound analysis by enabling the creation of intelligent products and services for the city
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
