Eliopoulos, P. A.

Ganchev, T.

Kontodimas, D. C.

Potamitisa, I.

English

JKI Open Journal Systems (Julius Kühn-Institut)

 10th International Working Conference on Stored Product Protection 110  Julius-Kühn-Archiv, 425, 2010 On automatic bioacoustic detection of stored product pests: the case of Sitophilus oryzae Potamitisa, I.1, Ganchev, T.2, Kontodimas, D.C.3, Eliopoulos, P.A.*#, 1 Department of Music Technology and Acoustics, Technological Educational Institute of Crete, Daskalaki-Perivolia, 74100 Rethymno, Greece. Email: potamitis@stef.teicrete.gr 2 Wire Communications Laboratory, Electrical and Computer Engineering Department, University of Patras, Sofocleous-Adiparou 1, 265 00 Rion, Patras, Greece. Email: tganchev@wcl.ee.upatras.gr 3 Laboratory of Agricultural Entomology, Department of Entomology and Agricultural Zoology, Benaki Phytopathological Institute, 45100 Athens, Greece. Email: d.kontodimas@bpi.gr  4 Technological Educational Institute of Larissa, Department of Plant Production, 41 110 Larissa, Greece.  Email: eliopoulos@teilar.gr *Corresponding author  # Presenting author DOI: 10.5073/jka.2010.425.109 Abstract The present work reports research efforts towards the development and evaluation of a unified framework for automatic bioacoustic recognition of specific insect pests. Our approach is based on capturing and automatically recognizing the acoustic emission resulting from typical behaviour, i.e., locomotion, feeding, etc., of the target pests. After acquisition the signals are amplified, filtered, parameterized and classified by advanced machine learning methods on a portable computer. Specifically, we investigate an advanced signal parameterization scheme that relies on variable size signal segmentation. The feature vector computed for each segment of the signal is composed of the dominant harmonic, which carries information about the periodicity of the signal, and the cepstral coefficients, which carry information about the relative distribution of energy among the different spectral sub-bands. This parameterization offers a reliable representation of both the acoustic emissions of the pests of interest and the interferences from the environment. We illustrate the practical significance of our methodology using Sitophilus oryzae (Rice Weevil – RW), (Coleoptera: Curculionidae). This approach led to 100% successful detection. *Corresponding author: Email: eliopoulos@teilar.gr # Presenting author : Panagiotis A. Eliopoulos  

On automatic bioacoustic detection of stored product pests: the case of Sitophilus oryzae

https://ojs.openagrar.de/index.php/JKA/article/download/322/1177

On automatic bioacoustic detection of stored product pests: the case of Sitophilus oryzae

Abstract

Similar works

Full text

Available Versions

JKI Open Journal Systems (Julius Kühn-Institut)