Rapid penetration of small customized wireless devices and enormous growth of wireless communication technologies has already set the stage for large-scale deployment of wireless sensor networks. Offering precise qual...Rapid penetration of small customized wireless devices and enormous growth of wireless communication technologies has already set the stage for large-scale deployment of wireless sensor networks. Offering precise quality of service (QoS) for multimedia transmission over sensor networks has not received significant attention. However offering some better QoS for wireless multimedia over sensor networks raises significant challenges. In this paper, we propose an adaptive Cross-Layer multi-channel QoS-MAC protocol to support energy-efficient, high throughput, and reliable data transmission in Wireless Multimedia Sensor Network (WMSNs). Our proposed protocol use benefit of TDMA and CSMA/CA to adaptively assign channels and timeslots to active multimedia sensor nodes in clusters. Simulations show that the proposed system achieves the performance objectives of WMSNs with increased network throughput at the cost of a small control and energy overhead.展开更多
In this paper, we present an approach to improve the accuracy of environmental sound event detection in a wireless acoustic sensor network for home monitoring. Wireless acoustic sensor nodes can capture sounds in the ...In this paper, we present an approach to improve the accuracy of environmental sound event detection in a wireless acoustic sensor network for home monitoring. Wireless acoustic sensor nodes can capture sounds in the home and simultaneously deliver them to a sink node for sound event detection. The proposed approach is mainly composed of three modules, including signal estimation, reliable sensor channel selection, and sound event detection. During signal estimation, lost packets are recovered to improve the signal quality. Next, reliable channels are selected using a multi-channel cross-correlation coefficient to improve the computational efficiency for distant sound event detection without sacrificing performance. Finally, the signals of the selected two channels are used for environmental sound event detection based on bidirectional gated recurrent neural networks using two-channel audio features. Experiments show that the proposed approach achieves superior performances compared to the baseline.展开更多
文摘Rapid penetration of small customized wireless devices and enormous growth of wireless communication technologies has already set the stage for large-scale deployment of wireless sensor networks. Offering precise quality of service (QoS) for multimedia transmission over sensor networks has not received significant attention. However offering some better QoS for wireless multimedia over sensor networks raises significant challenges. In this paper, we propose an adaptive Cross-Layer multi-channel QoS-MAC protocol to support energy-efficient, high throughput, and reliable data transmission in Wireless Multimedia Sensor Network (WMSNs). Our proposed protocol use benefit of TDMA and CSMA/CA to adaptively assign channels and timeslots to active multimedia sensor nodes in clusters. Simulations show that the proposed system achieves the performance objectives of WMSNs with increased network throughput at the cost of a small control and energy overhead.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education (NRF2015R1D1A1A01059804)the MSIP (Ministry of Science,ICT and Future Planning),Korea,under the ITRC(Information Technology Research Center) support program (IITP-2016-R2718-16-0011) supervised by the IITP(Institute for Information & communications Technology Promotion)the present Research has been conducted by the Research Grant of Kwangwoon University in 2017
文摘In this paper, we present an approach to improve the accuracy of environmental sound event detection in a wireless acoustic sensor network for home monitoring. Wireless acoustic sensor nodes can capture sounds in the home and simultaneously deliver them to a sink node for sound event detection. The proposed approach is mainly composed of three modules, including signal estimation, reliable sensor channel selection, and sound event detection. During signal estimation, lost packets are recovered to improve the signal quality. Next, reliable channels are selected using a multi-channel cross-correlation coefficient to improve the computational efficiency for distant sound event detection without sacrificing performance. Finally, the signals of the selected two channels are used for environmental sound event detection based on bidirectional gated recurrent neural networks using two-channel audio features. Experiments show that the proposed approach achieves superior performances compared to the baseline.
