Research Article
An Edge-Assisted Video Computing Framework for Industrial IoT
@INPROCEEDINGS{10.1007/978-3-030-64214-3_4, author={Zeng Zeng and Yuze Jin and Weiwei Miao and Chuanjun Wang and Shihao Li and Peng Zhou and Hongli Zhou and Meiya Dong}, title={An Edge-Assisted Video Computing Framework for Industrial IoT}, proceedings={Mobile Computing, Applications, and Services. 11th EAI International Conference, MobiCASE 2020, Shanghai, China, September 12, 2020, Proceedings}, proceedings_a={MOBICASE}, year={2020}, month={12}, keywords={Industrial IoT Edge computing Rendering}, doi={10.1007/978-3-030-64214-3_4} }- Zeng Zeng
Yuze Jin
Weiwei Miao
Chuanjun Wang
Shihao Li
Peng Zhou
Hongli Zhou
Meiya Dong
Year: 2020
An Edge-Assisted Video Computing Framework for Industrial IoT
MOBICASE
Springer
DOI: 10.1007/978-3-030-64214-3_4
Abstract
With the rapid development of industrial demands, the Internet of Things triggers enormous interests by industry and academia. By employing IoT technologies, a large number of problems in the industry can be solved by intelligent sensing, wireless communication, and smart software analysis. However, in applying Industrial IoT to improve real-time and immerse user experiences, we found that compared to traditional application scenarios such as tourism, or daily experiences, industrial IoT applications face challenges in scalability, real-time reaction, and immerse user experiences. In this paper, we propose an edge-assisted framework that fits in industrial IoT to solve this fatal problem. We design a multi-pass algorithm that can successfully provide a real sense of immersion without changing the single frame image visual effect in terms of increasing rendering frame rate. From experimental evaluation, it shows that this edge-assisted rendering framework can apply to multiple scenarios in Industrial IoT systems.
