AIoT-Cloud-Integrated Smart Livestock Surveillance via Assembling Deep Networks with Considering Robustness and Semantics Availability

Wei Tsung Su, Lin Yi Jiang, O. Tang-Hsuan, Yu Chuan Lin, Min Hsiung Hung, Chao Chun Chen

研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)

摘要

In this letter, we propose a novel smart livestock surveillance system through cooperation of AIoT (artificial intelligence of things) devices and the cloud computing platform, aiming at providing semantic information via assembling deep networks with AIoT devices of limited resource. The key of the proposed system includes two designs: Deep-net assembling as a semantic surveillance service and the expandable-convolutional-block neural network (ECB-Net). The first is a development architecture of the divide-and-conquer philosophy for establishing semantic surveillance systems, and this work provides a concrete instance for promoting deep-net assembling to livestock industries. The second is an AIoT device-friendly neural network for filtering insignificant camera images to achieve high robustness of smart surveillance systems. The technical details from the architecture design to optimal ECB-Net model creation are presented in related sections. Finally, we develop the prototype of the smart livestock surveillance system and deploy it by swine rooms for conducting real-world integrated tests. Testing results reveal the superior performance of our proposed smart livestock surveillance scheme.

原文English
文章編號9460764
頁(從 - 到)6140-6147
頁數8
期刊IEEE Robotics and Automation Letters
6
發行號4
DOIs
出版狀態Published - 2021 10月

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 生物醫學工程
  • 人機介面
  • 機械工業
  • 電腦視覺和模式識別
  • 電腦科學應用
  • 控制和優化
  • 人工智慧

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