The Experts below are selected from a list of 906 Experts worldwide ranked by ideXlab platform
Setiawan Ikhsan - One of the best experts on this subject based on the ideXlab platform.
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The effect of Housing volume of a converting loudspeaker on the output electric power of a loudspeaker-based acoustic energy harvester
'Universitas Sebelas Maret', 2020Co-Authors: Setiawan IkhsanAbstract:Acoustic energy harvester is a device that converts sound or acoustic energy into electrical energy. Generally, the main components of this instrument are an acoustic transducer and an acoustic resonator. In this study, the transducer used was a 4-inch woofer loudspeaker, without acoustic resonator but equipped with a cylindrical Housing with a fixed cross-sectional area and a length that can be varied from 6 cm until 25 cm by using a piston. Experimental results for various Housing volumes showed a similar pattern of the dependence of the generated electric power on the incoming sound frequencies. In addition, it was found that (within the range of the volume variations) the output electric power increased significantly when the volume of the Housing was increased. The highest root-mean-square (rms) electric power obtained was 1.72 mW resulting from sound with a sound pressure level (SPL) of 105 dB and a frequency of 84 Hz and by using a length of the Housing Cylinder of 25 cm (Housing volume of 3243.7 cm3
Alberto J. Alvares - One of the best experts on this subject based on the ideXlab platform.
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Underwater radio frequency image sensor using progressive image compression and region of interest
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2017Co-Authors: Eduardo M. Rubino, Diego Centelles, JAY SALES, Jose V. Martí, Raul Marín, Pedro J. Sanz, Alberto J. AlvaresAbstract:The increasing demand for underwater robotic intervention systems around the world in several application domains requires more versatile and inexpensive systems. By using a wireless communication system, supervised semi-autonomous robots have freedom of movement; however, the limited and varying bandwidth of underwater radio frequency (RF) channels is a major obstacle for the operator to get camera feedback and supervise the intervention. This paper proposes the use of progressive (embedded) image compression and region of interest (ROI) for the design of an underwater image sensor to be installed in an autonomous underwater vehicle, specially when there are constraints on the available bandwidth, allowing a more agile data exchange between the vehicle and a human operator supervising the underwater intervention. The operator can dynamically decide the size, quality, frame rate, or resolution of the received images so that the available bandwidth is utilized to its fullest potential and with the required minimum latency. The paper focuses first on the description of the system, which uses a camera, an embedded Linux system, and an RF emitter installed in an OpenROV Housing Cylinder. The RF receiver is connected to a computer on the user side, which controls the camera monitoring parameters, including the compression inputs, such as region of interest (ROI), size of the image, and frame rate. The paper focuses on the compression subsystem and does not attempt to improve the communications physical media for better underwater RF links. Instead, it proposes a unified system that uses well-integrated modules (compression and transmission) to provide the scientific community with a higher-level protocol for image compression and transmission in sub-sea robotic interventions.
Eduardo M. Rubino - One of the best experts on this subject based on the ideXlab platform.
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Underwater radio frequency image sensor using progressive image compression and region of interest
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2017Co-Authors: Eduardo M. Rubino, Diego Centelles, JAY SALES, Jose V. Martí, Raul Marín, Pedro J. Sanz, Alberto J. AlvaresAbstract:The increasing demand for underwater robotic intervention systems around the world in several application domains requires more versatile and inexpensive systems. By using a wireless communication system, supervised semi-autonomous robots have freedom of movement; however, the limited and varying bandwidth of underwater radio frequency (RF) channels is a major obstacle for the operator to get camera feedback and supervise the intervention. This paper proposes the use of progressive (embedded) image compression and region of interest (ROI) for the design of an underwater image sensor to be installed in an autonomous underwater vehicle, specially when there are constraints on the available bandwidth, allowing a more agile data exchange between the vehicle and a human operator supervising the underwater intervention. The operator can dynamically decide the size, quality, frame rate, or resolution of the received images so that the available bandwidth is utilized to its fullest potential and with the required minimum latency. The paper focuses first on the description of the system, which uses a camera, an embedded Linux system, and an RF emitter installed in an OpenROV Housing Cylinder. The RF receiver is connected to a computer on the user side, which controls the camera monitoring parameters, including the compression inputs, such as region of interest (ROI), size of the image, and frame rate. The paper focuses on the compression subsystem and does not attempt to improve the communications physical media for better underwater RF links. Instead, it proposes a unified system that uses well-integrated modules (compression and transmission) to provide the scientific community with a higher-level protocol for image compression and transmission in sub-sea robotic interventions.
Diego Centelles - One of the best experts on this subject based on the ideXlab platform.
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Underwater radio frequency image sensor using progressive image compression and region of interest
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2017Co-Authors: Eduardo M. Rubino, Diego Centelles, JAY SALES, Jose V. Martí, Raul Marín, Pedro J. Sanz, Alberto J. AlvaresAbstract:The increasing demand for underwater robotic intervention systems around the world in several application domains requires more versatile and inexpensive systems. By using a wireless communication system, supervised semi-autonomous robots have freedom of movement; however, the limited and varying bandwidth of underwater radio frequency (RF) channels is a major obstacle for the operator to get camera feedback and supervise the intervention. This paper proposes the use of progressive (embedded) image compression and region of interest (ROI) for the design of an underwater image sensor to be installed in an autonomous underwater vehicle, specially when there are constraints on the available bandwidth, allowing a more agile data exchange between the vehicle and a human operator supervising the underwater intervention. The operator can dynamically decide the size, quality, frame rate, or resolution of the received images so that the available bandwidth is utilized to its fullest potential and with the required minimum latency. The paper focuses first on the description of the system, which uses a camera, an embedded Linux system, and an RF emitter installed in an OpenROV Housing Cylinder. The RF receiver is connected to a computer on the user side, which controls the camera monitoring parameters, including the compression inputs, such as region of interest (ROI), size of the image, and frame rate. The paper focuses on the compression subsystem and does not attempt to improve the communications physical media for better underwater RF links. Instead, it proposes a unified system that uses well-integrated modules (compression and transmission) to provide the scientific community with a higher-level protocol for image compression and transmission in sub-sea robotic interventions.
JAY SALES - One of the best experts on this subject based on the ideXlab platform.
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Underwater radio frequency image sensor using progressive image compression and region of interest
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2017Co-Authors: Eduardo M. Rubino, Diego Centelles, JAY SALES, Jose V. Martí, Raul Marín, Pedro J. Sanz, Alberto J. AlvaresAbstract:The increasing demand for underwater robotic intervention systems around the world in several application domains requires more versatile and inexpensive systems. By using a wireless communication system, supervised semi-autonomous robots have freedom of movement; however, the limited and varying bandwidth of underwater radio frequency (RF) channels is a major obstacle for the operator to get camera feedback and supervise the intervention. This paper proposes the use of progressive (embedded) image compression and region of interest (ROI) for the design of an underwater image sensor to be installed in an autonomous underwater vehicle, specially when there are constraints on the available bandwidth, allowing a more agile data exchange between the vehicle and a human operator supervising the underwater intervention. The operator can dynamically decide the size, quality, frame rate, or resolution of the received images so that the available bandwidth is utilized to its fullest potential and with the required minimum latency. The paper focuses first on the description of the system, which uses a camera, an embedded Linux system, and an RF emitter installed in an OpenROV Housing Cylinder. The RF receiver is connected to a computer on the user side, which controls the camera monitoring parameters, including the compression inputs, such as region of interest (ROI), size of the image, and frame rate. The paper focuses on the compression subsystem and does not attempt to improve the communications physical media for better underwater RF links. Instead, it proposes a unified system that uses well-integrated modules (compression and transmission) to provide the scientific community with a higher-level protocol for image compression and transmission in sub-sea robotic interventions.