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Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology
This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3376617/ https://www.ncbi.nlm.nih.gov/pubmed/22736996 http://dx.doi.org/10.3390/s120303118 |
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author | Han, Ruizhen He, Yong Liu, Fei |
author_facet | Han, Ruizhen He, Yong Liu, Fei |
author_sort | Han, Ruizhen |
collection | PubMed |
description | This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests’ pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture. |
format | Online Article Text |
id | pubmed-3376617 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-33766172012-06-25 Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology Han, Ruizhen He, Yong Liu, Fei Sensors (Basel) Article This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests’ pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture. Molecular Diversity Preservation International (MDPI) 2012-03-06 /pmc/articles/PMC3376617/ /pubmed/22736996 http://dx.doi.org/10.3390/s120303118 Text en © 2012 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 license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Han, Ruizhen He, Yong Liu, Fei Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology |
title | Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology |
title_full | Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology |
title_fullStr | Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology |
title_full_unstemmed | Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology |
title_short | Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology |
title_sort | feasibility study on a portable field pest classification system design based on dsp and 3g wireless communication technology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3376617/ https://www.ncbi.nlm.nih.gov/pubmed/22736996 http://dx.doi.org/10.3390/s120303118 |
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