0000000000255767
AUTHOR
Jesus Lopez-ballester
Psychoacoustic Annoyance Implementation With Wireless Acoustic Sensor Networks for Monitoring in Smart Cities
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 …
Adaptive live video streaming on low-cost wireless multihop networks for road traffic surveillance in smart cities
Abstract Traffic surveillance is an important issue for Intelligent Transportation Systems (ITS) that helps detect incidents automatically, such as wrong-way drivers, still-standing vehicles and jams. Sometimes these systems require a fast and short-term deployment of video cameras. In these cases, ad-hoc networks could be a low-cost and feasible option, but they have poor performance for video delivery. Thus, we propose a smart live video adaptive streaming technique in order to transport video streams from the cameras to the external road traffic monitoring servers. To achieve this goal, these networks need a thorough study in order to analyze video quality under their inherent constraint…
Thorough analysis of Raspberry Pi devices in outdoor/indoor communications in terms of QoS
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…
Speech Intelligibility Analysis and Approximation to Room Parameters through the Internet of Things
In recent years, Wireless Acoustic Sensor Networks (WASN) have been widely applied to different acoustic fields in outdoor and indoor environments. Most of these applications are oriented to locate or identify sources and measure specific features of the environment involved. In this paper, we study the application of a WASN for room acoustic measurements. To evaluate the acoustic characteristics, a set of Raspberry Pi 3 (RPi) has been used. One is used to play different acoustic signals and four are used to record at different points in the room simultaneously. The signals are sent wirelessly to a computer connected to a server, where using MATLAB we calculate both the impulse response (IR…
Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks
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…
Performance comparison of container orchestration platforms with low cost devices in the fog, assisting Internet of Things applications
Abstract In the last decade there has been an increasing interest and demand on the Internet of Things (IoT) and its applications. But, when a high level of computing and/or real time processing is required for these applications, different problems arise due to their requirements. In this context, low cost autonomous and distributed Small Board Computers (SBC) devices, with processing, storage capabilities and wireless communications can assist these IoT networks. Usually, these SBC devices run an operating system based on Linux. In this scenario, container-based technologies and fog computing are an interesting approach and both have led to a new paradigm in how devices cooperate, improvi…
Enabling Real-Time Computation of Psycho-Acoustic Parameters in Acoustic Sensors Using Convolutional Neural Networks
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 …
AI-IoT Platform for Blind Estimation of Room Acoustic Parameters Based on Deep Neural Networks
Room acoustical parameters have been widely used to describe sound perception in indoor environments, such as concert halls, conference rooms, etc. Many of them have been standardized and often have a high computational demand. With the increasing presence of deep learning approaches in automatic monitoring systems, wireless acoustic sensor networks (WASNs) offer great potential to facilitate the estimation of such parameters. In this scenario, Convolutional Neural Networks (CNNs) offer significant reductions in the computational requirements for in-node parameter predictions, enabling the so-called Artificial Intelligence-Internet of Things (AI-IoT). In this paper, we describe the design a…
Development of a low-cost IoT system to detect and locate lightning strikes
Lightnings are violent natural phenomena and can generate many expenditures, specially when they strike in urban areas. The identification of the concrete geographic area where they strike is of critical importance for emergency services in order to enhance their effectiveness by doing an intensive coverage of the affected area. To achieve this aim, this paper proposes a design, prototype and validation of a distributed network of Internet of Things (IoT) devices to enable detection and location of lightning strikes. The IoT devices are empowered with lightning detection capabilities and are synchronized with the other devices in the sensor network. All of them cooperate within a network th…