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Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps
Fruit flies (Diptera: Tephritidae) cause losses to world fruit growing. For a fast and effective control of the pest, it is necessary to identify the species and their populations. Thus, we developed an infrared optoelectronic sensor using phototransistors to capture the signal of the partial occlus...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427400/ https://www.ncbi.nlm.nih.gov/pubmed/30871087 http://dx.doi.org/10.3390/s19051254 |
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author | Sandrini Moraes, Fabiano Edson Nava, Dori Scheunemann, Tiago Santos da Rosa, Vagner |
author_facet | Sandrini Moraes, Fabiano Edson Nava, Dori Scheunemann, Tiago Santos da Rosa, Vagner |
author_sort | Sandrini Moraes, Fabiano |
collection | PubMed |
description | Fruit flies (Diptera: Tephritidae) cause losses to world fruit growing. For a fast and effective control of the pest, it is necessary to identify the species and their populations. Thus, we developed an infrared optoelectronic sensor using phototransistors to capture the signal of the partial occlusion of the infrared light caused by the beating of the fly wings. Laboratory experiments were conducted using the sensor to capture the wing beat signal of A. fraterculus and C. capitata. The captured signals were used to obtain the characteristics of the flies’ wing beats frequency and for a production of a dataset made available as one of the results of this work. For the passage detection, we developed the algorithm of detection of events of passage (PEDA) that uses the root mean square (RMS) value of a sliding window applied to the signal compared to a threshold value. We developed the algorithm of detection of events of passage (CAEC) that uses the techniques of autocorrelation and Fourier transform for the extraction of the characteristics of the wings’ beat signal. The results demonstrate that it is possible to use the sensor for the development of an intelligent trap with detection and classification in real time for A. fraterculus and C. capitata using the wing beat frequency obtained by the developed sensor. |
format | Online Article Text |
id | pubmed-6427400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64274002019-04-15 Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps Sandrini Moraes, Fabiano Edson Nava, Dori Scheunemann, Tiago Santos da Rosa, Vagner Sensors (Basel) Article Fruit flies (Diptera: Tephritidae) cause losses to world fruit growing. For a fast and effective control of the pest, it is necessary to identify the species and their populations. Thus, we developed an infrared optoelectronic sensor using phototransistors to capture the signal of the partial occlusion of the infrared light caused by the beating of the fly wings. Laboratory experiments were conducted using the sensor to capture the wing beat signal of A. fraterculus and C. capitata. The captured signals were used to obtain the characteristics of the flies’ wing beats frequency and for a production of a dataset made available as one of the results of this work. For the passage detection, we developed the algorithm of detection of events of passage (PEDA) that uses the root mean square (RMS) value of a sliding window applied to the signal compared to a threshold value. We developed the algorithm of detection of events of passage (CAEC) that uses the techniques of autocorrelation and Fourier transform for the extraction of the characteristics of the wings’ beat signal. The results demonstrate that it is possible to use the sensor for the development of an intelligent trap with detection and classification in real time for A. fraterculus and C. capitata using the wing beat frequency obtained by the developed sensor. MDPI 2019-03-12 /pmc/articles/PMC6427400/ /pubmed/30871087 http://dx.doi.org/10.3390/s19051254 Text en © 2019 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sandrini Moraes, Fabiano Edson Nava, Dori Scheunemann, Tiago Santos da Rosa, Vagner Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps |
title | Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps |
title_full | Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps |
title_fullStr | Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps |
title_full_unstemmed | Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps |
title_short | Development of an Optoelectronic Sensor for Detecting and Classifying Fruit Fly (Diptera: Tephritidae) for Use in Real-Time Intelligent Traps |
title_sort | development of an optoelectronic sensor for detecting and classifying fruit fly (diptera: tephritidae) for use in real-time intelligent traps |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427400/ https://www.ncbi.nlm.nih.gov/pubmed/30871087 http://dx.doi.org/10.3390/s19051254 |
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