Decision support system for optimizing field operation of selected tillage implements

Mechanization in agriculture involves all levels of cultivating and preparing innovations, from basic and essential hand devices to more complex and mechanized implements. Fundamentally, it carried out agricultural activities for developing different crop yields to different neighborhoods in the...

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Main Author:	Al-Shakarchi, Haider Fawzi Mahmood
Format:	Thesis
Language:	English
Published:	2019
Subjects:	Tillage - Case studies Decision support systems Agricultural implements
Online Access:	http://psasir.upm.edu.my/id/eprint/85614/1/FK%202020%2012%20ir.pdf
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id	my-upm-ir.85614
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spelling	my-upm-ir.856142021-12-09T03:05:52Z Decision support system for optimizing field operation of selected tillage implements 2019-10 Al-Shakarchi, Haider Fawzi Mahmood Mechanization in agriculture involves all levels of cultivating and preparing innovations, from basic and essential hand devices to more complex and mechanized implements. Fundamentally, it carried out agricultural activities for developing different crop yields to different neighborhoods in the world’s ecological system. Advanced automation models have been proposed to facilitate and lessen different agriculture operations and one of which is tillage. They are found to reduce work deficiencies, enhance cultivation work profitability, enhances efficiency and convenience of farming activities, enhances the productive utilization of assets, improves economy access and adds to relieving atmosphere related risks. However, distinctive innovations of Decision Support System (DSS) need to be given that match the condition of the tractor and the plough to help the operators during the tillage operations to improve the tillage efficiency including reduces human workload, tillage cost, fuel consumption and wheel slippage. This thesis represents another attempt that focuses on improving tillage mechanization performance in agriculture. Subsequently, it contributes the modelling, implementation, testing and evaluation of a proposed Tillage Operations Quality Optimization (TOQO) model that serves as a tillage DSS. The TOQO model has an Internet of Things (IoT) architecture and includes cloud computing technology. The model observes, processes and estimates a set of tillage operation evaluation parameters and tools in real-time for a number of tractors and ploughs. Then accordingly the DSS provides recommendations and guidance to the tractors and ploughs’ operators that lead to improving the efficiency of the tillage operations. The involved parameters are vibration, bulk density, slippage ratio, fuel consumption real tillage depth and field efficiency. The TOQO was implemented in a Smart Tillage Operations Assistance (STOA) web-based system. The STOA system was tested in Malaysia and Iraq to check its suitability in real-world tillage operations. The STOA system relatively increased the bulk density by 0.24g/cm3, the tillage depth by 0. 43 cm and field efficiency by 12.28% and reduced the soil cohesiveness, slippage ratio below 15% and fuel consumption by 1.22 litre per hour on average. Tillage - Case studies Decision support systems Agricultural implements 2019-10 Thesis http://psasir.upm.edu.my/id/eprint/85614/ http://psasir.upm.edu.my/id/eprint/85614/1/FK%202020%2012%20ir.pdf text en public doctoral Universiti Putra Malaysia Tillage - Case studies Decision support systems Agricultural implements Ahmad, Desa
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Ahmad, Desa
topic	Tillage - Case studies Decision support systems Agricultural implements
spellingShingle	Tillage - Case studies Decision support systems Agricultural implements Al-Shakarchi, Haider Fawzi Mahmood Decision support system for optimizing field operation of selected tillage implements
description	Mechanization in agriculture involves all levels of cultivating and preparing innovations, from basic and essential hand devices to more complex and mechanized implements. Fundamentally, it carried out agricultural activities for developing different crop yields to different neighborhoods in the world’s ecological system. Advanced automation models have been proposed to facilitate and lessen different agriculture operations and one of which is tillage. They are found to reduce work deficiencies, enhance cultivation work profitability, enhances efficiency and convenience of farming activities, enhances the productive utilization of assets, improves economy access and adds to relieving atmosphere related risks. However, distinctive innovations of Decision Support System (DSS) need to be given that match the condition of the tractor and the plough to help the operators during the tillage operations to improve the tillage efficiency including reduces human workload, tillage cost, fuel consumption and wheel slippage. This thesis represents another attempt that focuses on improving tillage mechanization performance in agriculture. Subsequently, it contributes the modelling, implementation, testing and evaluation of a proposed Tillage Operations Quality Optimization (TOQO) model that serves as a tillage DSS. The TOQO model has an Internet of Things (IoT) architecture and includes cloud computing technology. The model observes, processes and estimates a set of tillage operation evaluation parameters and tools in real-time for a number of tractors and ploughs. Then accordingly the DSS provides recommendations and guidance to the tractors and ploughs’ operators that lead to improving the efficiency of the tillage operations. The involved parameters are vibration, bulk density, slippage ratio, fuel consumption real tillage depth and field efficiency. The TOQO was implemented in a Smart Tillage Operations Assistance (STOA) web-based system. The STOA system was tested in Malaysia and Iraq to check its suitability in real-world tillage operations. The STOA system relatively increased the bulk density by 0.24g/cm3, the tillage depth by 0. 43 cm and field efficiency by 12.28% and reduced the soil cohesiveness, slippage ratio below 15% and fuel consumption by 1.22 litre per hour on average.
format	Thesis
qualification_level	Doctorate
author	Al-Shakarchi, Haider Fawzi Mahmood
author_facet	Al-Shakarchi, Haider Fawzi Mahmood
author_sort	Al-Shakarchi, Haider Fawzi Mahmood
title	Decision support system for optimizing field operation of selected tillage implements
title_short	Decision support system for optimizing field operation of selected tillage implements
title_full	Decision support system for optimizing field operation of selected tillage implements
title_fullStr	Decision support system for optimizing field operation of selected tillage implements
title_full_unstemmed	Decision support system for optimizing field operation of selected tillage implements
title_sort	decision support system for optimizing field operation of selected tillage implements
granting_institution	Universiti Putra Malaysia
publishDate	2019
url	http://psasir.upm.edu.my/id/eprint/85614/1/FK%202020%2012%20ir.pdf
_version_	1747813568883982336

Decision support system for optimizing field operation of selected tillage implements

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