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Smart city article details
| Title | An Optimal Coverage Model For The Deployment Of Iot Devices In Feature-Based Video Transmission Systems |
|---|---|
| ID_Doc | 8843 |
| Authors | Wang Y.; Xu J.; Ji W. |
| Year | 2019 |
| Published | 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019 |
| DOI | http://dx.doi.org/10.1109/VCIP47243.2019.8965802 |
| Abstract | With the development of visual devices and artificial intelligence technologies, many researchers focus on how to deploy a massive of IoT devices efficiently. The visual devices in smart cities produce large amount of real-Time visual data, which challenges the ability of current transmission architecture in Cloud computing. We address how to improve the utilization of both computation and transmission resources for visual data processing through introducing the Fog computing technologies. We propose to use deep learning models and salient zones extraction method to decrease the data amount as well as maintaining important features of visual data. Furthermore, we develop how to arrange Fog nodes reasonably according to the location of the end devices and the data produced from the devices. Simulation results on public video dataset demonstrate that the proposed method achieves 48.85% in term of SSIM higher than that of HEVC. The proposed approach decreases the delay by around 75.93% than the traditional transmission without Fog nodes. The proposed method achieves a high compression ratio and guarantees the quality of the video. © 2019 IEEE. |
| Author Keywords | Fog node deployment; video feature; video transmission; visual IoT |
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