| Full text | |
| Author(s): |
Lemos Escola, Joao Paulo
[1, 2]
;
Guido, Rodrigo Capobianco
[3]
;
da Silva, Ivan Nunes
[1]
;
Cardoso, Alexandre Moraes
[2]
;
Bottura Maccagnan, Douglas Henrique
[4]
;
Dezotti, Artur Kenzo
[2]
Total Authors: 6
|
| Affiliation: | [1] Univ Sao Paulo, Av Trabalhador Sao Carlense 400, BR-13566590 Sao Carlos, SP - Brazil
[2] Inst Fed Sao Paulo, Av C-1, 250, BR-14781502 Barretos, SP - Brazil
[3] Univ Estadual Paulista, Inst Biociencias Letras & Ciencias Exatas, UNESP, Sao Paulo State Univ, Rua Cristovao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, SP - Brazil
[4] Univ Estadual Goias, Campus Ipora, Av R2 Qd 1 S-N, Novo Horizonte 2, BR-76200000 Ipora, Go - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | COMPUTERS AND ELECTRONICS IN AGRICULTURE; v. 169, FEB 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
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. (AU) | |
| FAPESP's process: | 19/04475-0 - Paraconsistent Feature Analysis of Speech Signals: fighting the voice spoofing attacks |
| Grantee: | Rodrigo Capobianco Guido |
| Support Opportunities: | Regular Research Grants |