Name
Abstract | ||
|---|---|---|
This 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. |
Year | Venue | Field |
|---|---|---|
2017 | ICAT-EGVE | Computer science,Augmented reality,Digital camera,Agriculture,Mobile device,Livestock,Global Positioning System,Human-centered computing,Database,Dairy farming |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zongyuan Zhao | 1 | 20 | 2.74 |
| Wenli Yang | 2 | 4 | 3.13 |
| Winyu Chinthammit | 3 | 34 | 10.94 |
| Richard Rawnsley | 4 | 0 | 0.34 |
| Paul Neumeyer | 5 | 0 | 0.34 |
| Hadi Ghaderi | 6 | 6 | 0.81 |