A Wireless Acoustic Array System for Binaural Loudness Evaluation in Cities

Noriega-Linares, Juan Emilio; Rodriguez-Mayol, Alberto; Cobos, Máximo; Segura-García, Jaume; Felici-Castell, Santiago; Navarro, Juan M.

doi:10.1109/jsen.2017.2751665

Cited by 13 publications

(13 citation statements)

References 18 publications

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“…Soundscape monitoring is characterized by requiring tough signal processing algorithms. These algorithms are explained and analyzed in [22,23]. Behind this monitoring process, there are several rules and standards such as Environmental Noise Directives (ENDs) 2002/49/EC and ISO 12913 (soundscape) [24,25].…”

Section: Test Bed For Soundscape Monitoring and Its Performance Analysismentioning

confidence: 99%

Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes

et al. 2019

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The Internet of Things (IoT) is a network widely used with the purpose of connecting almost everything, everywhere to the Internet. To cope with this goal, low cost nodes are being used; otherwise, it would be very expensive to expand so fast. These networks are set up with small distributed devices (nodes) that have a power supply, processing unit, memory, sensors, and wireless communications. In the market, we can find different alternatives for these devices, such as small board computers (SBCs), e.g., Raspberry Pi (RPi)), with different features. Usually these devices run a coarse version of a Linux operating system. Nevertheless, there are many scenarios that require enhanced computational power that these nodes alone are unable to provide. In this context, we need to introduce a kind of collaboration among the devices to overcome their constraints. We based our solution in a combination of clustering techniques (building a mesh network using their wireless capabilities); at the same time we try to orchestrate the resources in order to improve their processing capabilities in an elastic computing fashion. This paradigm is called fog computing on IoT. We propose in this paper the use of cloud computing technologies, such as Linux containers, based on Docker, and a container orchestration platform (COP) to run on the top of a cluster of these nodes, but adapted to the fog computing paradigm. Notice that these technologies are open source and developed for Linux operating system. As an example, in our results we show an IoT application for soundscape monitoring as a proof of concept that it will allow us to compare different alternatives in its design and implementation; in particular, with regard to the COP selection, between Docker Swarm and Kubernetes. We conclude that using and combining these techniques, we can improve the overall computation capabilities of these IoT nodes within a fog computing paradigm.

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Section: Test Bed For Soundscape Monitoring and Its Performance Analysismentioning

confidence: 99%

Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes

et al. 2019

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“…The implementation of the Zwicker’s model [ 32 ] allowed a computing perspective for loudness monitoring. In a previous work [ 33 ], the authors developed a binaural loudness monitoring system by using the Zwicker’s model and using binaural synthesis by means of a combination of Head-Related Transfer Functions (HRTFs) and microphone array processing.…”

Section: Related Workmentioning

confidence: 99%

“…In [ 36 ], the authors implemented a system oriented to compute the psychoacoustic parameters in the server side from recorded audio chunks. In [ 33 ], the authors implemented a edge-computing system by using different Raspberry Pi 3 (Rpi3) nodes in order to perform an evaluation of performance when computing the binaural loudness directly on the Rpi3 nodes.…”

Section: Related Workmentioning

confidence: 99%

Spatio-Temporal Analysis of Urban Acoustic Environments with Binaural Psycho-Acoustical Considerations for IoT-Based Applications

Segura-García

Navarro

Pérez-Solano

et al. 2018

Sensors

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Sound pleasantness or annoyance perceived in urban soundscapes is a major concern in environmental acoustics. Binaural psychoacoustic parameters are helpful to describe generic acoustic environments, as it is stated within the ISO 12913 framework. In this paper, the application of a Wireless Acoustic Sensor Network (WASN) to evaluate the spatial distribution and the evolution of urban acoustic environments is described. Two experiments are presented using an indoor and an outdoor deployment of a WASN with several nodes using an Internet of Things (IoT) environment to collect audio data and calculate meaningful parameters such as the sound pressure level, binaural loudness and binaural sharpness. A chunk of audio is recorded in each node periodically with a microphone array and the binaural rendering is conducted by exploiting the estimated directional characteristics of the incoming sound by means of DOA estimation. Each node computes the parameters in a different location and sends the values to a cloud-based broker structure that allows spatial statistical analysis through Kriging techniques. A cross-validation analysis is also performed to confirm the usefulness of the proposed system.

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“…Wireless Sensor Networks have proven to be a very effective technology for numerous environmental monitoring applications. WSNs currently enable the automatic monitoring of air pollution [30], noise pollution [31][32][33], forest fires [34], climatological conditions [35], and much more over wide areas, something previously impossible. The use of WSNs for WQM is particularly appealing due to the low cost of the sensor nodes and hence the cost-effectiveness of this solution.…”

Section: Introductionmentioning

confidence: 99%

On the Use of an IoT Integrated System for Water Quality Monitoring and Management in Wastewater Treatment Plants

Martínez

Vela

Aatik

et al. 2020

Water

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The deteriorating water environment demands new approaches and technologies to achieve sustainable and smart management of urban water systems. Wireless sensor networks represent a promising technology for water quality monitoring and management. The use of wireless sensor networks facilitates the improvement of current centralized systems and traditional manual methods, leading to decentralized smart water quality monitoring systems adaptable to the dynamic and heterogeneous water distribution infrastructure of cities. However, there is a need for a low-cost wireless sensor node solution on the market that enables a cost-effective deployment of this new generation of systems. This paper presents the integration to a wireless sensor network and a preliminary validation in a wastewater treatment plant scenario of a low-cost water quality monitoring device in the close-to-market stage. This device consists of a nitrate and nitrite analyzer based on a novel ion chromatography detection method. The analytical device is integrated using an Internet of Things software platform and tested under real conditions. By doing so, a decentralized smart water quality monitoring system that is conceived and developed for water quality monitoring and management is accomplished. In the presented scenario, such a system allows online near-real-time communication with several devices deployed in multiple water treatment plants and provides preventive and data analytics mechanisms to support decision making. The results obtained comparing laboratory and device measured data demonstrate the reliability of the system and the analytical method implemented in the device.

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A Wireless Acoustic Array System for Binaural Loudness Evaluation in Cities

Cited by 13 publications

References 18 publications

Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes

Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes

Spatio-Temporal Analysis of Urban Acoustic Environments with Binaural Psycho-Acoustical Considerations for IoT-Based Applications

On the Use of an IoT Integrated System for Water Quality Monitoring and Management in Wastewater Treatment Plants

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