Automated acoustic detection of a cicadid pest in coffee plantations
| Autor: | João Paulo Lemos Escola, Ivan Nunes da Silva, Rodrigo Capobianco Guido, Alexandre Moraes Cardoso, Douglas Henrique Bottura Maccagnan, Artur Kenzo Dezotti |
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| Přispěvatelé: | Instituto Federal de São Paulo, Universidade Estadual Paulista (Unesp), Universidade de São Paulo (USP), Universidade Estadual de Goiás |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
Feature engineering Resource (biology) Computer science Bark Scale (BS) Cicada Agricultural engineering Horticulture 01 natural sciences law.invention law Bark scale Paraconsistent Feature Engineering (PFE) Support Vector Machine (SVM) Forestry 04 agricultural and veterinary sciences Computer Science Applications Support vector machine South american 040103 agronomy & agriculture Wavelet-packet Transform (WPT) 0401 agriculture forestry and fisheries PEST analysis Agronomy and Crop Science Mechanical devices 010606 plant biology & botany |
| Zdroj: | Scopus Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP |
| Popis: | Made available in DSpace on 2020-12-12T02:33:37Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-02-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) South american countries are the largest coffee producers in the world. Nevertheless, Cicadidae, the colloquial term for cicadas, is one of the key pests responsible for dropping the production. Currently, there is no electronic device or autonomous technological resource commercially available for detecting certain species of cicadas in the crop, penalizing the farmers on the management of that insect. Thus, this article presents a novel algorithm implemented in a low-cost real-time plataform for the acoustic detection of cicadas in plantations. Based on the Bark Scale (BS), Wavelet-packet Transform (WPT), Paraconsistent Feature Engineering (PFE) and Support Vector Machines (SVMs), the proposed technique was assessed with a database of 1366 recordings, presenting a value of accuracy of 96.41% for the distinction among cicadas and background noise, where the latter includes sounds from mechanical devices, birds, animals in general and speech, among others. Instituto Federal de São Paulo, Av. C-1, 250 Instituto de Biociências Letras e Ciências Exatas Unesp – Univ Estadual Paulista (São Paulo State University), Rua Cristóvão Colombo 2265, Jd Nazareth, 15054-000 Universidade de São Paulo, Av. Trabalhador São-carlense, 400 Universidade Estadual de Goiás, Campus Iporá, Av. R2 Qd.1, s/n, Novo Horizonte II Instituto de Biociências Letras e Ciências Exatas Unesp – Univ Estadual Paulista (São Paulo State University), Rua Cristóvão Colombo 2265, Jd Nazareth, 15054-000 CNPq: 306808/2018-8 CNPq: 800694/2016-3 |
| Databáze: | OpenAIRE |
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