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An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars

Wu, Hao; Liu, Qi; Liu, Xiaodong; Zhang, Yonghong; Yang, Zhiyun


Hao Wu

Qi Liu

Yonghong Zhang

Zhiyun Yang


Internet of Things (IoT) has been rapidly developed in recent years, being well applied in the fields of Environmental Surveillance, Smart Grid, Intelligent Transportation, and so on. As one of the typical earth-based meteorological observation methods, networked Doppler weather radars, i.e. the Internet of weather Radars (IoR) can detect the signals of large-area water particles in the atmosphere with high resolution, but suffer from beam blockage due to surrounded mountains, buildings, as well as other obstacles. In addition, how to establish a distributed platform for large-scale radar data analytics becomes critical and challenging, especially considering optimised strategies on the storage, processing and exchange of radar raw data, beam/echo signal, and final products etc. In this paper, an edge-assisted cloud framework is proposed to facilitate effective and proficient communication and progression, where echo signal from a single site radar can be analysed and pre-processed at the edge, and then trained in the cloud with elastic resources and distributed learning ability. A Residual Concatenate Fully Convolutional Network (RC-FCN) is presented for beam blockage correction, which is integrated into the framework to be compared with other deep learning models, including FCN, ResNet, VGG, etc. According to experiment results, better performance and efficiency have been achieved using the proposed framework and its fitted RC-FCN model.


Wu, H., Liu, Q., Liu, X., Zhang, Y., & Yang, Z. (2022). An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars. World Wide Web, 25, 1923-1949.

Journal Article Type Article
Acceptance Date Oct 4, 2021
Online Publication Date Dec 15, 2021
Publication Date 2022-09
Deposit Date Nov 26, 2021
Publicly Available Date Dec 16, 2022
Journal World Wide Web
Print ISSN 1386-145X
Electronic ISSN 1573-1413
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 25
Pages 1923-1949
Keywords Edge Computing, Internet of Radars, Residual Concatenate, Beam Blockage Correction, Weather Radar
Public URL


An Edge-Assisted Cloud Framework Using A Residual Concatenate FCN Approach To Beam Correction In The Internet Of Weather Radars (accepted version) (3.3 Mb)

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