A New Approach to Utilize Augmented Reality on Precision Livestock Farming

Simple item page
dc.contributor.authorZhao, Zongyuanen_US
dc.contributor.authorYang, Wenlien_US
dc.contributor.authorChinthammit, Winyuen_US
dc.contributor.authorRawnsley, Richarden_US
dc.contributor.authorNeumeyer, Paulen_US
dc.contributor.authorCahoon, Stephenen_US
dc.contributor.editorRobert W. Lindeman and Gerd Bruder and Daisuke Iwaien_US
dc.date.accessioned2017-11-21T15:43:00Z
dc.date.available2017-11-21T15:43:00Z
dc.date.issued2017
dc.description.abstractThis paper proposes a new method that utilizes AR to assist pasture-based dairy farmers identify and locate animal within large herds. Our proposed method uses GPS collars on cows and digital camera and on-board GPS on a mobile device to locate a selected cow and show the behavioral and other associated key metrics on our mobile application. The augmented cow's information shown on real scene video steam will help users (farmers) manage their animals with respect to welfare, health, and management interventions. By integrating GPS data with computer vision (CV) and machine learning, our mobile AR application has two major functions: 1. Searching a cow by its unique ID, and 2. Displaying information associated with a selected cow visible on screen. Our proof-of-concept application shows the potential of utilizing AR in precision livestock farming.en_US
dc.description.sectionheadersApplications & Collaborations
dc.description.seriesinformationICAT-EGVE 2017 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments
dc.identifier.doi10.2312/egve.20171357
dc.identifier.isbn978-3-03868-038-3
dc.identifier.issn1727-530X
dc.identifier.pages185-188
dc.identifier.urihttps://doi.org/10.2312/egve.20171357
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egve20171357
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing à Mixed/augmented reality
dc.titleA New Approach to Utilize Augmented Reality on Precision Livestock Farmingen_US
Files
Original bundle
Now showing 1 - 3 of 3
Thumbnail Image
Name:
185-188.pdf
Size:
1.38 MB
Format:
Adobe Portable Document Format
Download
No Thumbnail Available
Name:
demo2.mp4
Size:
27.32 MB
Format:
Unknown data format
Download
No Thumbnail Available
Name:
readme_file_for_the_demo_video.docx
Size:
109.47 KB
Format:
Microsoft Word XML
Download
Collections
ICAT-EGVE2017