Remote monitoring and automatic detection of grain crop attributes

McCarthy, Alison ORCID: https://orcid.org/0000-0003-4595-6447 and Tscharke, Matthew and Schmidt, Erik (2014) Remote monitoring and automatic detection of grain crop attributes. Project Report. University of Southern Queensland , Toowoomba, Australia. [Report]

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Abstract

This project has developed a proof-of-concept low cost internet-enabled camera-based monitoring and image processing system for National Variety Trials (NVT). The system will reduce labour requirements and travel costs associated with manual inspection of grain variety trials, and improve timeliness and accuracy of growth stage identification. A camera-based system remotely captures images of a plot, automatically detects plant growth and flowers for two grain crop types and displays results on a website. Manual measurements have been compared with image analysis results in collaboration with NVT Trial Service Providers.

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Item Type:	Report (Project Report)
Item Status:	Live Archive
Faculty/School / Institute/Centre:	Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019)
Faculty/School / Institute/Centre:	Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 Jul 2013 - 5 Sep 2019)
Date Deposited:	30 Aug 2016 01:29
Last Modified:	11 Dec 2017 06:50
Fields of Research (2008):	09 Engineering > 0906 Electrical and Electronic Engineering > 090602 Control Systems, Robotics and Automation 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Fields of Research (2020):	40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400799 Control engineering, mechatronics and robotics not elsewhere classified 46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460306 Image processing
Socio-Economic Objectives (2008):	D Environment > 96 Environment > 9609 Land and Water Management > 960904 Farmland, Arable Cropland and Permanent Cropland Land Management
URI:	http://eprints.usq.edu.au/id/eprint/27602

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