Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106875
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Title: Monitoring the red palm weevil infestation using machine learning and optical sensing
Authors: Mao, Y
Ashry, I
Wang, B 
Al-Fehaid, Y
Al-Shawaf, A
Ng, TK
Yu, C 
Ooi, BS
Issue Date: 2021
Source: Optical Fiber Communication Conference (OFC) 2021, OSA Technical Digest (Optica Publishing Group, 2021), paper Tu6C.2
Abstract: Red palm weevil (RPW) is a major pest of palm trees, which has destroyed many farms and caused significant economic losses worldwide. It is difficult to detect the RPW infestation in its early stage, especially in vast farms. Here, we introduce combining machine learning and fiber optic distributed acoustic sensing (DAS) as a solution for detecting the RPW in the larvae stage. A single fiber optic cable would possibly monitor hundreds of trees, simultaneously.
Publisher: Optica Publishing Group
ISBN: 978-1-943580-86-6
DOI: 10.1364/OFC.2021.Tu6C.2
Description: Optical Fiber Communication Conference 2021, Washington, DC United States, 6-11 June 2021
Rights: © 2021 The Author(s)
The following publication Y. Mao et al., "Monitoring the Red Palm Weevil Infestation Using Machine Learning and Optical Sensing," 2021 Optical Fiber Communications Conference and Exhibition (OFC), San Francisco, CA, USA, 2021, pp. 1-3 is available at https://doi.org/10.1364/OFC.2021.Tu6C.2.
Appears in Collections:Conference Paper

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