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http://hdl.handle.net/10397/90842
Title: | Towards detecting red palm weevil using machine learning and fiber optic distributed acoustic sensing | Authors: | Wang, B Mao, Y Ashry, I AlFehaid, Y AlShawaf, A Ng, TK Yu, C Ooi, BS |
Issue Date: | Mar-2021 | Source: | Sensors, Mar. 2021, v. 21, no. 5, 1592, p. 1-14 | Abstract: | Red palm weevil (RPW) is a detrimental pest, which has wiped out many palm tree farms worldwide. Early detection of RPW is challenging, especially in large-scale farms. Here, we introduce the combination of machine learning and fiber optic distributed acoustic sensing (DAS) techniques as a solution for the early detection of RPW in vast farms. Within the laboratory environment, we reconstructed the conditions of a farm that includes an infested tree with ∼12 day old weevil larvae and another healthy tree. Meanwhile, some noise sources are introduced, including wind and bird sounds around the trees. After training with the experimental time-and frequency-domain data provided by the fiber optic DAS system, a fully-connected artificial neural network (ANN) and a convolutional neural network (CNN) can efficiently recognize the healthy and infested trees with high classification accuracy values (99.9% by ANN with temporal data and 99.7% by CNN with spectral data, in reasonable noise conditions). This work paves the way for deploying the high efficiency and cost-effective fiber optic DAS to monitor RPW in open-air and large-scale farms containing thousands of trees. | Keywords: | Fiber optic acoustic sensing Machine learning Red palm weevil |
Publisher: | Molecular Diversity Preservation International (MDPI) | Journal: | Sensors | EISSN: | 1424-8220 | DOI: | 10.3390/s21051592 | Rights: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The following publication Wang, B.; Mao, Y.; Ashry, I.; Al-Fehaid, Y.; Al-Shawaf, A.; Ng, T.K.; Yu, C.; Ooi, B.S. Towards Detecting Red Palm Weevil Using Machine Learning and Fiber Optic Distributed Acoustic Sensing. Sensors 2021, 21, 1592 is available at https://doi.org/10.3390/s21051592 |
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