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Application of 3D-HEVC fast coding by Internet of Things data in intelligent decision

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Abstract

This research aims to further promote the popularization and application of agricultural Internet of Things (IoT) and solve the practical problems of low transmission efficiency in agricultural data transmission. The targeted study is conducted on the video coding in agricultural IoT system to further promote the development of agricultural IoT system and improve the application effect of video surveillance technology. Firstly, an intelligent decision management platform is designed based on agricultural IoT system, consisting of the remote control module and video surveillance module. Meanwhile, a three-dimensional High Efficiency Video Coding (3D-HEVC) fast algorithm based on Bayesian Decision Theory is designed aiming to optimize the 3D-HEVC technology. Experiments are also performed to investigate the performance of intelligent management platform and 3D-HEVC fast algorithm based on Bayesian Decision Theory. The experimental results show that the intelligent management platform has good application effects in the database performance test, website access concurrency test, and data reception performance test. Compared to the traditional 3D-HEVC algorithm, the proposed 3D-HEVC fast algorithm reduces the coding time of depth map and total coding time by 46.5% and 22.52%, respectively, in addition to a better application effect. Meanwhile, with the support of the 3d-HEVC fast algorithm, the agricultural intelligent management platform shows better video transmission performance and application effect meeting the actual needs at this stage. The experiment results have certain practical value, providing scientific and effective reference data for subsequent research.

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Acknowledgements

This study was supported by EU Commission (Contract 2018-1-ES01-KA201-05093); Ministry of Science, Unversities and Innovation of the Spanish Kingdom (Grant RTI2018-100683-B-I00); Ministerio de Economía y Competitividad (ES) (Research Project ECO2015-63880-R); Fundación Centro de Supercomputación de Castilla y León.

Funding

It was also supported by Fujian Province Young and Middle-aged Teacher Education Research Project (No. JAT200838).

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  1. School of Electronic and Electrical Engineering, Xiamen Institute of Technology, Xiamen, 361021, China

    Xiaolan Wang

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  1. Xiaolan Wang
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Correspondence to Xiaolan Wang.

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Wang, X. Application of 3D-HEVC fast coding by Internet of Things data in intelligent decision. J Supercomput 78, 7489–7508 (2022). https://doi.org/10.1007/s11227-021-04137-0

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