This page has only limited features, please log in for full access.
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), and different acoustic parameters, such as the Speech Intelligibility Index (SII). In this way, the evaluation of room acoustic parameters with asynchronous IR measurements two different applications has been explored. Finally, the network features have been evaluated to assess the effectiveness of this system.
Jesus Lopez-Ballester; Jose Alcaraz Calero; Jaume Segura-Garcia; Santiago Felici-Castell; Miguel Garcia-Pineda; Maximo Cobos. Speech Intelligibility Analysis and Approximation to Room Parameters through the Internet of Things. Applied Sciences 2021, 11, 1430 .
AMA StyleJesus Lopez-Ballester, Jose Alcaraz Calero, Jaume Segura-Garcia, Santiago Felici-Castell, Miguel Garcia-Pineda, Maximo Cobos. Speech Intelligibility Analysis and Approximation to Room Parameters through the Internet of Things. Applied Sciences. 2021; 11 (4):1430.
Chicago/Turabian StyleJesus Lopez-Ballester; Jose Alcaraz Calero; Jaume Segura-Garcia; Santiago Felici-Castell; Miguel Garcia-Pineda; Maximo Cobos. 2021. "Speech Intelligibility Analysis and Approximation to Room Parameters through the Internet of Things." Applied Sciences 11, no. 4: 1430.
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, improving overall capacity in a cluster of these SBC devices. The use of containers is considered a lightweight virtualization, allowing an application to be broken into small tasks as services, enabling load balancing, flexibility and scalability. Nevertheless when the number of devices and containers increases in the cluster, it is required an orchestration layer. There are not many solutions and available alternatives using these technologies applied on these networks, and less an assessment of their performances. This paper focuses on these technologies when we use fog computing with low cost SBC devices in a context of IoT. We use Linux containers and different available orchestration platforms (in particular Docker Swarm and Kubernetes), to run on the top of the cluster of commercial SBC devices. Thus, we carry out a thorough functional and performance comparison with different real topologies (wired and wireless) and using both homogeneous and heterogeneous clusters of SBC devices, showing their results. We conclude that with the collected experimental results, Docker Swarm orchestration platform outperforms its counterparts in the scenarios shown.
Rafael Fayos-Jordan; Santiago Felici-Castell; Jaume Segura-Garcia; Jesus Lopez-Ballester; Maximo Cobos. Performance comparison of container orchestration platforms with low cost devices in the fog, assisting Internet of Things applications. Journal of Network and Computer Applications 2020, 169, 102788 .
AMA StyleRafael Fayos-Jordan, Santiago Felici-Castell, Jaume Segura-Garcia, Jesus Lopez-Ballester, Maximo Cobos. Performance comparison of container orchestration platforms with low cost devices in the fog, assisting Internet of Things applications. Journal of Network and Computer Applications. 2020; 169 ():102788.
Chicago/Turabian StyleRafael Fayos-Jordan; Santiago Felici-Castell; Jaume Segura-Garcia; Jesus Lopez-Ballester; Maximo Cobos. 2020. "Performance comparison of container orchestration platforms with low cost devices in the fog, assisting Internet of Things applications." Journal of Network and Computer Applications 169, no. : 102788.
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.
Rafael Fayos-Jordan; Santiago Felici-Castell; Jaume Segura-Garcia; Adolfo Pastor-Aparicio; Jesus Lopez-Ballester. Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes. Electronics 2019, 8, 1489 .
AMA StyleRafael Fayos-Jordan, Santiago Felici-Castell, Jaume Segura-Garcia, Adolfo Pastor-Aparicio, Jesus Lopez-Ballester. Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes. Electronics. 2019; 8 (12):1489.
Chicago/Turabian StyleRafael Fayos-Jordan; Santiago Felici-Castell; Jaume Segura-Garcia; Adolfo Pastor-Aparicio; Jesus Lopez-Ballester. 2019. "Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes." Electronics 8, no. 12: 1489.
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. This paper proposes the use of a deep convolutional neural network (CNN) trained on a large urban sound dataset capable of efficiently predicting psycho-acoustic annoyance from raw audio signals continuously. We evaluate the proposed regression model and compare the resulting computation times with the ones obtained by the conventional direct calculation approach. The results confirm that the proposed model based on CNN achieves high precision in predicting psycho-acoustic annoyance, predicting annoyance values with an average quadratic error of around 3%. It also achieves a very significant reduction in processing time, which is up to 300 times faster than direct calculation, making CNN designed a clear exponent to work in IoT devices.
Jesus Lopez-Ballester; Adolfo Pastor-Aparicio; Jaume Segura-Garcia; Santiago Felici-Castell; Maximo Cobos. Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks. Applied Sciences 2019, 9, 3136 .
AMA StyleJesus Lopez-Ballester, Adolfo Pastor-Aparicio, Jaume Segura-Garcia, Santiago Felici-Castell, Maximo Cobos. Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks. Applied Sciences. 2019; 9 (15):3136.
Chicago/Turabian StyleJesus Lopez-Ballester; Adolfo Pastor-Aparicio; Jaume Segura-Garcia; Santiago Felici-Castell; Maximo Cobos. 2019. "Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks." Applied Sciences 9, no. 15: 3136.
Enrique A. Navarro-Camba; Antonio Soriano Asensi; Miguel García-Pineda; Jaume Segura-Garcia; Santiago Felici-Castell; Jesus Lopez-Ballester. Study of transmission parameters under controlled multipath environment using Rasp Pi3. Proceedings of the Euro American Conference on Telematics and Information Systems 2018, 33 .
AMA StyleEnrique A. Navarro-Camba, Antonio Soriano Asensi, Miguel García-Pineda, Jaume Segura-Garcia, Santiago Felici-Castell, Jesus Lopez-Ballester. Study of transmission parameters under controlled multipath environment using Rasp Pi3. Proceedings of the Euro American Conference on Telematics and Information Systems. 2018; ():33.
Chicago/Turabian StyleEnrique A. Navarro-Camba; Antonio Soriano Asensi; Miguel García-Pineda; Jaume Segura-Garcia; Santiago Felici-Castell; Jesus Lopez-Ballester. 2018. "Study of transmission parameters under controlled multipath environment using Rasp Pi3." Proceedings of the Euro American Conference on Telematics and Information Systems , no. : 33.