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Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant

Precision farming or precision agriculture requires the use of new technologies, mainly Global Positioning (GPS) and Machine Vision Systems. The current trend is to make precision agriculture solutions as practical as possible which requires a high level of portability at the first step. Both of the...

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Main Author: Kavandi, Nader
Format: Thesis
Language:English
Published: 2011
Online Access:http://psasir.upm.edu.my/id/eprint/41784/1/FK%202011%209R.pdf
http://psasir.upm.edu.my/id/eprint/41784/
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spelling my.upm.eprints.417842016-02-19T08:02:37Z http://psasir.upm.edu.my/id/eprint/41784/ Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant Kavandi, Nader Precision farming or precision agriculture requires the use of new technologies, mainly Global Positioning (GPS) and Machine Vision Systems. The current trend is to make precision agriculture solutions as practical as possible which requires a high level of portability at the first step. Both of the mentioned key technologies are already available in any modern Personal Digital Assistant (PDA), nominating them as capable, programmable and ultra-mobile devices in this field. The main objective of this research was to develop a software program that enables a regular PDA to replace a conventional camera vision system used for maturity inspection of oil palm fresh fruit bunches. The developed location aware software is named “Genius Farmer” and technical aspects of its development process are described. The software allows the user to take a picture from the FFBs using the built-in camera of the PDA and analyze it inside the PDA using a wisely implemented Hue based image processing algorithm. User can review the results on the screen, Geotag it with the current location data received through the built-in GPS receiver of the PDA, and lastly save them in a database for further analysis or future referencing. The results include the status of the fruit, its predicted oil content and suggested optimum harvesting date. A case study was carried out to verify the capabilities of the developed software in maturity assessment of the oil palm FFBs in a plantation. User-friendliness of the interface, compatibility with PDAs running Microsoft Windows Mobile® operating system and utilization of the built-in components of the PDA (Camera, GPS receiver and CPU) are the most important focused topics. The possibility of implementing other similar applications into the described device is discussed as a guideline for interested researchers in this field. 2011-04 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/41784/1/FK%202011%209R.pdf Kavandi, Nader (2011) Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant. Masters thesis, Universiti Putra Malaysia.
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Precision farming or precision agriculture requires the use of new technologies, mainly Global Positioning (GPS) and Machine Vision Systems. The current trend is to make precision agriculture solutions as practical as possible which requires a high level of portability at the first step. Both of the mentioned key technologies are already available in any modern Personal Digital Assistant (PDA), nominating them as capable, programmable and ultra-mobile devices in this field. The main objective of this research was to develop a software program that enables a regular PDA to replace a conventional camera vision system used for maturity inspection of oil palm fresh fruit bunches. The developed location aware software is named “Genius Farmer” and technical aspects of its development process are described. The software allows the user to take a picture from the FFBs using the built-in camera of the PDA and analyze it inside the PDA using a wisely implemented Hue based image processing algorithm. User can review the results on the screen, Geotag it with the current location data received through the built-in GPS receiver of the PDA, and lastly save them in a database for further analysis or future referencing. The results include the status of the fruit, its predicted oil content and suggested optimum harvesting date. A case study was carried out to verify the capabilities of the developed software in maturity assessment of the oil palm FFBs in a plantation. User-friendliness of the interface, compatibility with PDAs running Microsoft Windows Mobile® operating system and utilization of the built-in components of the PDA (Camera, GPS receiver and CPU) are the most important focused topics. The possibility of implementing other similar applications into the described device is discussed as a guideline for interested researchers in this field.
format Thesis
author Kavandi, Nader
spellingShingle Kavandi, Nader
Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant
author_facet Kavandi, Nader
author_sort Kavandi, Nader
title Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant
title_short Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant
title_full Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant
title_fullStr Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant
title_full_unstemmed Development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant
title_sort development of oil palm fresh fruit bunch maturity assessment software for personal digital assistant
publishDate 2011
url http://psasir.upm.edu.my/id/eprint/41784/1/FK%202011%209R.pdf
http://psasir.upm.edu.my/id/eprint/41784/
_version_ 1643833098275651584
score 13.211869

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