Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.

<h4>Objective</h4>To realize the regulation of the position of corn seed planting in precision farming, an intelligent monitoring system is designed for corn seeding based on machine vision and the Genetic Algorithm-optimized Back Propagation (GABP) algorithm.<h4>Methods</h4>...

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Autores principales:	Jiangtao Ji, Yayuan Sang, Zhitao He, Xin Jin, Shengsheng Wang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/cd09cc2f8c8f4d6d8b043b598dc5171b
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spelling	oai:doaj.org-article:cd09cc2f8c8f4d6d8b043b598dc5171b2021-12-02T20:09:11ZDesigning an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.1932-620310.1371/journal.pone.0254544https://doaj.org/article/cd09cc2f8c8f4d6d8b043b598dc5171b2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254544https://doaj.org/toc/1932-6203<h4>Objective</h4>To realize the regulation of the position of corn seed planting in precision farming, an intelligent monitoring system is designed for corn seeding based on machine vision and the Genetic Algorithm-optimized Back Propagation (GABP) algorithm.<h4>Methods</h4>Based on the research on precision positioning seeding technology, comprehensive application of sensors, Proportional Integral Derivative (PID) controllers, and other technologies, combined with modern optimization algorithms, the online dynamic calibration controls of line spacing and plant spacing are implemented. Based on the machine vision and GABP algorithm, a test platform for the seeding effect detection system is designed to provide a reference for further precision seeding operations. GA can obtain better initial network weights and thresholds and find the optimal individual through selection, crossover, and mutation operations; that is, the optimal initial weight of the Back Propagation (BP) neural network. Field experiments verify the seeding performance of the precision corn planter and the accuracy of the seeding monitoring system.<h4>Results</h4>1. The deviation between the average value of the six precision positioning seeding experiments of corn under the random disturbance signal and the ideal value of the distance is less than or equal to 0.5 cm; the deviation between the average value of the six precision positioning seeding experiments of corn under the sine wave disturbance signal (1 Hz) is less than or equal to 0.4 cm; the qualified rate of grain distance reaches 100%. 2. The precision control index, replay index, and missed index of the designed corn precision seeding intelligent control system have all reached the national standard. During the operation of the seeder, an alarm of the seeder leaking occurred, and the buzzer sounded and the screen displayed 100 times each; therefore, the reliability of the alarm system is 100%.<h4>Conclusion</h4>The intelligent corn seeder designed based on precision positioning seeding technology can reduce the seeding rate of the seeder and ensure the stability of the seed spacing effectively. Based on the machine vision and GABP algorithm, the seeding effect detection system can provide a reference for the further realization of precision seeding operations.Jiangtao JiYayuan SangZhitao HeXin JinShengsheng WangPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0254544 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jiangtao Ji Yayuan Sang Zhitao He Xin Jin Shengsheng Wang Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.
description	<h4>Objective</h4>To realize the regulation of the position of corn seed planting in precision farming, an intelligent monitoring system is designed for corn seeding based on machine vision and the Genetic Algorithm-optimized Back Propagation (GABP) algorithm.<h4>Methods</h4>Based on the research on precision positioning seeding technology, comprehensive application of sensors, Proportional Integral Derivative (PID) controllers, and other technologies, combined with modern optimization algorithms, the online dynamic calibration controls of line spacing and plant spacing are implemented. Based on the machine vision and GABP algorithm, a test platform for the seeding effect detection system is designed to provide a reference for further precision seeding operations. GA can obtain better initial network weights and thresholds and find the optimal individual through selection, crossover, and mutation operations; that is, the optimal initial weight of the Back Propagation (BP) neural network. Field experiments verify the seeding performance of the precision corn planter and the accuracy of the seeding monitoring system.<h4>Results</h4>1. The deviation between the average value of the six precision positioning seeding experiments of corn under the random disturbance signal and the ideal value of the distance is less than or equal to 0.5 cm; the deviation between the average value of the six precision positioning seeding experiments of corn under the sine wave disturbance signal (1 Hz) is less than or equal to 0.4 cm; the qualified rate of grain distance reaches 100%. 2. The precision control index, replay index, and missed index of the designed corn precision seeding intelligent control system have all reached the national standard. During the operation of the seeder, an alarm of the seeder leaking occurred, and the buzzer sounded and the screen displayed 100 times each; therefore, the reliability of the alarm system is 100%.<h4>Conclusion</h4>The intelligent corn seeder designed based on precision positioning seeding technology can reduce the seeding rate of the seeder and ensure the stability of the seed spacing effectively. Based on the machine vision and GABP algorithm, the seeding effect detection system can provide a reference for the further realization of precision seeding operations.
format	article
author	Jiangtao Ji Yayuan Sang Zhitao He Xin Jin Shengsheng Wang
author_facet	Jiangtao Ji Yayuan Sang Zhitao He Xin Jin Shengsheng Wang
author_sort	Jiangtao Ji
title	Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.
title_short	Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.
title_full	Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.
title_fullStr	Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.
title_full_unstemmed	Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.
title_sort	designing an intelligent monitoring system for corn seeding by machine vision and genetic algorithm-optimized back propagation algorithm under precision positioning.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/cd09cc2f8c8f4d6d8b043b598dc5171b
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Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.

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