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Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees

Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In thi...

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Detalles Bibliográficos
Autores principales: Ramos Giraldo, Paula Jimena, Guerrero Aguirre, Álvaro, Muñoz, Carlos Mario, Prieto, Flavio Augusto, Oliveros, Carlos Eugenio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422059/
https://www.ncbi.nlm.nih.gov/pubmed/28383494
http://dx.doi.org/10.3390/s17040786
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author Ramos Giraldo, Paula Jimena
Guerrero Aguirre, Álvaro
Muñoz, Carlos Mario
Prieto, Flavio Augusto
Oliveros, Carlos Eugenio
author_facet Ramos Giraldo, Paula Jimena
Guerrero Aguirre, Álvaro
Muñoz, Carlos Mario
Prieto, Flavio Augusto
Oliveros, Carlos Eugenio
author_sort Ramos Giraldo, Paula Jimena
collection PubMed
description Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: (i) Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and (ii) Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases.
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spelling pubmed-54220592017-05-12 Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees Ramos Giraldo, Paula Jimena Guerrero Aguirre, Álvaro Muñoz, Carlos Mario Prieto, Flavio Augusto Oliveros, Carlos Eugenio Sensors (Basel) Article Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: (i) Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and (ii) Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases. MDPI 2017-04-06 /pmc/articles/PMC5422059/ /pubmed/28383494 http://dx.doi.org/10.3390/s17040786 Text en © 2017 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
Ramos Giraldo, Paula Jimena
Guerrero Aguirre, Álvaro
Muñoz, Carlos Mario
Prieto, Flavio Augusto
Oliveros, Carlos Eugenio
Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees
title Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees
title_full Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees
title_fullStr Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees
title_full_unstemmed Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees
title_short Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees
title_sort sensor fusion of a mobile device to control and acquire videos or images of coffee branches and for georeferencing trees
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422059/
https://www.ncbi.nlm.nih.gov/pubmed/28383494
http://dx.doi.org/10.3390/s17040786
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