Abstract

One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps’ generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work.

Highlights

  • Nowadays, more people live in urban than in rural areas, representing in 2010 50.5% of the world’s population for the first time in history [1]

  • Tools and protocols have to be predefined to allow information integration of all of the individual measurements. When it comes to measuring city noise levels, two main participative sensing approaches can be found in the literature, depending on the tools used by citizens: (i) those considering citizens’

  • As in [78], the development of this application will be based on a Service-Oriented Architecture (SOA), in which most of the control is distributed in the server, which will access the remote sensing platform through SOAP messages to a web service developed for the control software solution

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Summary

Introduction

More people live in urban than in rural areas, representing in 2010 50.5% of the world’s population for the first time in history [1]. ENV/IT/001254) [20] aims to develop a dynamic noise mapping system able to detect and represent in real time the acoustic impact of road infrastructure based on a static network of acoustic sensors, reducing the cost of the periodical actualization of the noise maps [21,22] The latter builds on the conclusions obtained from the SENSEable PISA project [23,24], which proposed collecting the information describing the urban environment, and some aspects of the social behavior of the citizens, to study possible relationships with public health, mobility or pollution.

State of the Art of Dynamic Acoustic Urban Sensing
Static Acoustic Urban Sensing
Mobile Acoustic Urban Sensing
Participative Urban Sensing
Hybrid Urban Sensing
Mobile Measure Platforms and Their Connectivity
Hardware Platforms
Connectivity of the Platforms
Mobile Bus Acoustic Measurement
Signal Processing Challenges
Reliability of the Leq Measure
Mobile Vehicle Noise Contribution
Classification of Road Traffic Vehicles
Challenges in Terms of Noise Mapping
Mobile Trajectories Design and Data Collection
Noise Mapping Real-Time Update
Challenges in Terms of Hardware Platform Selection
Conclusions
A Street Categorization Method to Study Urban Noise
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