Making the DYNAMAP project a reality in the suburban area of Rome

Bellucci, Patrizia; Peruzzi, Laura; Cruciani, Francesca R.; Ferrari, Cristina

doi:10.1121/1.4988398

Cited by 3 publications

(5 citation statements)

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“…Another project with a similar conceptual background is the DYNAMAP project [36], which deployed two pilot areas in Italy, located in Rome [37] and Milan [38], with the idea of computing and comparing the noise impact of road infrastructures in suburban and urban areas, respectively. The two WASNs monitored road traffic noise by reliably collecting data at a frequency of 44,100 Hz, managing to remove specific non-traffic audio events [39,40] in order to build a more accurate road traffic noise map [41].…”

Section: Ad Hoc Developed Acoustic Sensor Networkmentioning

confidence: 99%

Multilabel Acoustic Event Classification Using Real-World Urban Data and Physical Redundancy of Sensors

Vidaña-Vila

Navarro

Stowell

et al. 2021

Sensors

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Many people living in urban environments nowadays are overexposed to noise, which results in adverse effects on their health. Thus, urban sound monitoring has emerged as a powerful tool that might enable public administrations to automatically identify and quantify noise pollution. Therefore, identifying multiple and simultaneous acoustic sources in these environments in a reliable and cost-effective way has emerged as a hot research topic. The purpose of this paper is to propose a two-stage classifier able to identify, in real time, a set of up to 21 urban acoustic events that may occur simultaneously (i.e., multilabel), taking advantage of physical redundancy in acoustic sensors from a wireless acoustic sensors network. The first stage of the proposed system consists of a multilabel deep neural network that makes a classification for each 4-s window. The second stage intelligently aggregates the classification results from the first stage of four neighboring nodes to determine the final classification result. Conducted experiments with real-world data and up to three different computing devices show that the system is able to provide classification results in less than 1 s and that it has good performance when classifying the most common events from the dataset. The results of this research may help civic organisations to obtain actionable noise monitoring information from automatic systems.

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Section: Ad Hoc Developed Acoustic Sensor Networkmentioning

confidence: 99%

Multilabel Acoustic Event Classification Using Real-World Urban Data and Physical Redundancy of Sensors

Vidaña-Vila

Navarro

Stowell

et al. 2021

Sensors

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“…The project deployed two pilot areas in Italy, located in Rome [45] and Milan [46], so as to evaluate the noise impact of road infrastructures in suburban and urban areas, respectively. The two WASNs monitor road traffic noise reliably collecting data at 44.1kHz to remove specific audio events, which are unrelated to road traffic [47,48] for the noise map computation [49]. Based on their experience in this project and particularly the time and effort spent transforming the original prototyping code into real operable language, the team developed a low-cost flexible acoustic sensor for rapid real-time algorithm development and testing [50].…”

Section: Wasns Based On Ad-hoc Designed Nodesmentioning

confidence: 99%

Low-Cost Distributed Acoustic Sensor Network for Real-Time Urban Sound Monitoring

Vidaña-Vila

Navarro²,

Borda-Fortuny³

et al. 2020

Electronics

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Continuous exposure to urban noise has been found to be one of the major threats to citizens’ health. In this regard, several organizations are devoting huge efforts to designing new in-field systems to identify the acoustic sources of these threats to protect those citizens at risk. Typically, these prototype systems are composed of expensive components that limit their large-scale deployment and thus reduce the scope of their measurements. This paper aims to present a highly scalable low-cost distributed infrastructure that features a ubiquitous acoustic sensor network to monitor urban sounds. It takes advantage of (1) low-cost microphones deployed in a redundant topology to improve their individual performance when identifying the sound source, (2) a deep-learning algorithm for sound recognition, (3) a distributed data-processing middleware to reach consensus on the sound identification, and (4) a custom planar antenna with an almost isotropic radiation pattern for the proper node communication. This enables practitioners to acoustically populate urban spaces and provide a reliable view of noises occurring in real time. The city of Barcelona (Spain) and the UrbanSound8K dataset have been selected to analytically validate the proposed approach. Results obtained in laboratory tests endorse the feasibility of this proposal.

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“…is project is aimed at the deployment of a low-cost WASN in two pilot areas in Italy, located in Rome [60] and Milan [61], so as to evaluate the noise impact of road infrastructures in suburban and urban areas, respectively. e DYNAMAP project is aimed at monitoring road traffic noise reliably collecting data at 44.1 kHz in order to remove specific audio events, thus making the removal of those events unrelated to road traffic (a.k.a.…”

Section: Wasns Based On Customized Nodesmentioning

confidence: 99%

“…e DYNAMAP project is aimed at monitoring road traffic noise reliably collecting data at 44.1 kHz in order to remove specific audio events, thus making the removal of those events unrelated to road traffic (a.k.a. anomalous noise events) mandatory [62,63] for the noise map computation [60], going further and even evaluating the impact of each anomalous noise event on the final L Aeq level [64]. As far as we know, this is the very first project aimed at the monitoring of one specific noise pollutant in real-world environments, road traffic noise, which has proven to be the main source of noise pollution in urban areas, being, at least, as harmful as air pollution to citizens' health [9,65].…”

Section: Wasns Based On Customized Nodesmentioning

confidence: 99%

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Review of Wireless Acoustic Sensor Networks for Environmental Noise Monitoring in Smart Cities

Álías

Alsina-Pagès

2019

Journal of Sensors

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Nowadays, more than half of the world’s population lives in urban areas. Since this proportion is expected to keep rising, the sustainable development of cities is of paramount importance to guarantee the quality of life of their inhabitants. Environmental noise is one of the main concerns that has to be addressed, due to its negative impact on the health of people. Different national and international noise directives and legislations have been defined during the past decades, which local authorities must comply with involving noise mapping, action plans, policing, and public awareness, among others. To this aim, a recent change in the paradigm for environmental noise monitoring has been driven by the rise of Internet of Things technology within smart cities through the design and development of wireless acoustic sensor networks (WASNs). This work reviews the most relevant WASN-based approaches developed to date focused on environmental noise monitoring. The proposals have moved from networks composed of high-accuracy commercial devices to the those integrated by ad hoc low-cost acoustic sensors, sometimes designed as hybrid networks with low and high computational capacity nodes. After describing the main characteristics of recent WASN-based projects, the paper also discusses several open challenges, such as the development of acoustic signal processing techniques to identify noise events, to allow the reliable and pervasive deployment of WASNs in urban areas together with some potential future applications.

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Making the DYNAMAP project a reality in the suburban area of Rome

Cited by 3 publications

References 0 publications

Multilabel Acoustic Event Classification Using Real-World Urban Data and Physical Redundancy of Sensors

Multilabel Acoustic Event Classification Using Real-World Urban Data and Physical Redundancy of Sensors

Low-Cost Distributed Acoustic Sensor Network for Real-Time Urban Sound Monitoring

Review of Wireless Acoustic Sensor Networks for Environmental Noise Monitoring in Smart Cities

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