Monitoring the Red Palm Weevil Infestation Using Machine Learning and Optical Sensing

Yuan Mao; Islam Ashry; Biwei Wang; Biwei Wang; Yousef Al-Fehaid; Abdulmoneim Al-Shawaf; Tien Khee Ng; Changyuan Yu; Boon S. Ooi

doi:10.1364/OFC.2021.Tu6C.2

Optical Fiber Communication Conference (OFC) 2021
OSA Technical Digest (Optica Publishing Group, 2021),
paper Tu6C.2
•https://doi.org/10.1364/OFC.2021.Tu6C.2

Monitoring the Red Palm Weevil Infestation Using Machine Learning and Optical Sensing

Yuan Mao, Islam Ashry, Biwei Wang, Yousef Al-Fehaid, Abdulmoneim Al-Shawaf, Tien Khee Ng, Changyuan Yu, and Boon S. Ooi

Optical Fiber Communication Conference 2021

Washington, DC United States
6–11 June 2021
ISBN: 978-1-943580-86-6

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Novel Sensors and Applications (Tu6C)

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Y. Mao, I. Ashry, B. Wang, Y. Al-Fehaid, A. Al-Shawaf, T. K. Ng, C. Yu, and B. S. Ooi, "Monitoring the Red Palm Weevil Infestation Using Machine Learning and Optical Sensing," in Optical Fiber Communication Conference (OFC) 2021, P. Dong, J. Kani, C. Xie, R. Casellas, C. Cole, and M. Li, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper Tu6C.2.

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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.

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