0000000000255766

AUTHOR

Adolfo Pastor-aparicio

showing 7 related works from this author

Psychoacoustic Annoyance Implementation With Wireless Acoustic Sensor Networks for Monitoring in Smart Cities

2020

Soundscape standard (ISO 12913) is mainly oriented to describe the psychoacoustic annoyance (PA) due to the perceived sound in different environments. The evaluation of this annoyance is commonly based on the Zwicker and Fastl model that defines several components related to this subjective annoyance, such as loudness, sharpness, roughness, and fluctuation strength. But due to their complexity, these components are difficult to be calculated on small board computers (SBCs) in real time in order to enable a wireless acoustic sensor network for PA monitoring. In this article, we describe the necessary procedures to implement the complete psychoacoustic model by Zwicker and Fastl in a precise …

SoundscapeComputer Networks and CommunicationsComputer sciencebusiness.industry010401 analytical chemistryReal-time computingAcoustic sensorAnnoyance02 engineering and technology01 natural sciences0104 chemical sciencesComputer Science ApplicationsLoudnessHardware and ArchitectureSignal Processing0202 electrical engineering electronic engineering information engineeringWireless020201 artificial intelligence & image processingPsychoacousticsbusinessInformation SystemsIEEE Internet of Things Journal
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Thorough analysis of Raspberry Pi devices in outdoor/indoor communications in terms of QoS

2020

The proliferation of commercial low-cost Small Board Computers (SBC) devices have allowed the deployment of many Wireless Sensor Networks (WSN) focused on different applications, mainly based on monitoring issues. These networks are characterized by a set of these SBCs devices working in a collaborative way where each device is sensing, processing and later sending out the data to the sink. These devices are equipped with power supply, a processing unit and communications capabilities (in particular WiFi), making themselves very interesting to fit in many topologies. However, their performance in terms of communications basically depends on the environment and usually heuristic techniques a…

020203 distributed computingHeuristic (computer science)Computer scienceQuality of serviceReal-time computing02 engineering and technologyNetwork topology0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingRay tracing (graphics)Wireless sensor networkThroughput (business)Multipath propagationJitterProceedings of the 10th Euro-American Conference on Telematics and Information Systems
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5G IoT system for real-time psycho-acoustic soundscape monitoring in smart cities

2020

In Next-Generation Technologies, the monitoring of environmental noise nuisance in the Smart City should be as efficient as possible. 5G IoT systems offer a great opportunity to offload the node calculation, as they provide a number of new concepts for dynamic computing that previous technologies did not offer. In this case, a complete 5G IoT system for psycho-acoustic monitoring has been implemented using different options to offload the calculation of the parameters to different parts of the system. This offloading has been implemented by directly computing the metrics in the node (as a Raspberry Pi), and in a ESP32 device (FiPy) and by sampling the audio and sending it to the EDGE in the…

020203 distributed computingSoundscapeComputer sciencebusiness.industryNode (networking)Real-time computingSampling (statistics)02 engineering and technologySmart city0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingEnhanced Data Rates for GSM EvolutionEnvironmental noiseInternet of Thingsbusiness5GProceedings of the 10th Euro-American Conference on Telematics and Information Systems
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Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks

2019

Psycho-acoustic parameters have been extensively used to evaluate the discomfort or pleasure produced by the sounds in our environment. In this context, wireless acoustic sensor networks (WASNs) can be an interesting solution for monitoring subjective annoyance in certain soundscapes, since they can be used to register the evolution of such parameters in time and space. Unfortunately, the calculation of the psycho-acoustic parameters involved in common annoyance models implies a significant computational cost, and makes difficult the acquisition and transmission of these parameters at the nodes. As a result, monitoring psycho-acoustic annoyance becomes an expensive and inefficient task. Thi…

Computer scienceComputationsubjective annoyanceContext (language use)Annoyance02 engineering and technologycomputer.software_genre01 natural sciencesConvolutional neural networklcsh:TechnologyReduction (complexity)lcsh:Chemistryconvolutional neural networks0202 electrical engineering electronic engineering information engineeringWirelessGeneral Materials Sciencewireless acoustic sensor networksInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer Processesbusiness.industrylcsh:TProcess Chemistry and Technology010401 analytical chemistryGeneral EngineeringRegression analysislcsh:QC1-9990104 chemical sciencesComputer Science Applicationspsycho-acoustic parametersTransmission (telecommunications)lcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingData miningbusinesslcsh:Engineering (General). Civil engineering (General)Zwicker modelcomputerlcsh:PhysicsApplied Sciences
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Enabling Real-Time Computation of Psycho-Acoustic Parameters in Acoustic Sensors Using Convolutional Neural Networks

2020

Sensor networks have become an extremely useful tool for monitoring and analysing many aspects of our daily lives. Noise pollution levels are very important today, especially in cities where the number of inhabitants and disturbing sounds are constantly increasing. Psycho-acoustic parameters are a fundamental tool for assessing the degree of discomfort produced by different sounds and, combined with wireless acoustic sensor networks (WASNs), could enable, for example, the efficient implementation of acoustic discomfort maps within smart cities. However, the continuous monitoring of psycho-acoustic parameters to create time-dependent discomfort maps requires a high computational demand that …

Audio signalComputer scienceNoise pollutionbusiness.industryComputation010401 analytical chemistryReal-time computing01 natural sciencesConvolutional neural network0104 chemical sciencesWirelessElectrical and Electronic EngineeringbusinessInstrumentationWireless sensor networkIEEE Sensors Journal
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Stochastic Collaborative Beamforming in Wireless Sensor Networks

2018

Wireless Sensor Networks (WSNs) are composed of spatially distributed autonomous sensor devices, named motes. These devices are constituted by a microcontroller, sensors, and they have the ability to communicate in the ISM frequency band using the IEEE 802.15.4 standard. They have their own power supply, AA or AAA batteries, processing unit, sensors and wireless communications. Usually, the motes exchange packets using a multihop routing, and the maximum communication distance emitter-receiver is around 100m. At least one mote acts as a gateway, and the data gathered by the sensors of each mote have to be sent to this mote that is named sink or Base Station (BS). In a WSN the BS is within t…

Beamformingbusiness.industryComputer scienceNetwork packetComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS020206 networking & telecommunications020302 automobile design & engineering02 engineering and technologySynchronizationBase station0203 mechanical engineeringTransmission (telecommunications)Default gateway0202 electrical engineering electronic engineering information engineeringWirelessComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSbusinessWireless sensor networkComputer networkProceedings of the Euro American Conference on Telematics and Information Systems
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5G IoT System for Real-Time Psycho-Acoustic Soundscape Monitoring in Smart Cities With Dynamic Computational Offloading to the Edge

2021

Environmental noise monitoring for smart cities need to be as much efficient as possible in order to mitigate its significant impact in the health of their inhabitants. 5G Internet of Things (IoT) systems offer a big opportunity to offload the computation from the sensor nodes, since it provides a series of new concepts for dynamic computing that the previous technologies did not offer. In this article, a complete 5G IoT system for psycho-acoustic monitoring has been designed and implemented using different options for offloading computation to different parts of the system. This offloading has been done by developing different functional splittings of the psycho-acoustic metrics algorithms…

SoundscapeComputer Networks and Communicationsbusiness.industryComputer scienceDistributed computingComputation020206 networking & telecommunications02 engineering and technologyComputer Science ApplicationsHardware and ArchitecturePerformance comparisonSmart citySignal Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingEnhanced Data Rates for GSM EvolutionInternet of ThingsbusinessEnvironmental noise5GInformation SystemsIEEE Internet of Things Journal
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