Abstract
Intensification of livestock production systems is mainly driven by increasing population and subsequent increase in food demand. Major challenges of an intensified system are monitoring of a large number of animals, fast disease spread, frequent monitoring of health status, scarcity of labor, and optimizing the resources to maximize the profit. Different modern technologies are used to overcome these challenges; computer vision and image analysis techniques are the primary ones. The computer vision approach has gained prominence in contemporary livestock farming and has become an essential component of the farming system in many developed nations. This chapter provides insights into various applications of computer vision and image processing technologies (tracking of individual animals, health and disease monitoring, body size and weight measurement, and analysis of milk and meat quality), limitations, research gaps, and future prospects. This technology reduces labor requirements, eases management, is more precise in monitoring, and acts as a supporting tool for decision-making. However, the need for substantial initial capital, technical knowledge, regular monitoring, breed or strain-specific calibrations, and selection of correct features are identified as challenges of this technology. Lacks automation in computer vision technology, inadequate application of artificial intelligence in thermal imaging, identifying the optimum features for detection of lameness and lack of user-friendly applications are a few identified research gaps. Although computer vision has been implemented in livestock farming, it is still at the intermediate level and the identified challenges and research gaps need to be addressed through research and development for full-fledged automated livestock management.
Original language | English |
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Title of host publication | Engineering Applications in Livestock Production |
Publisher | Elsevier |
Pages | 93-128 |
Number of pages | 36 |
ISBN (Electronic) | 9780323983853 |
ISBN (Print) | 9780323985819 |
DOIs | |
State | Published - 1 Jan 2024 |
Externally published | Yes |
Keywords
- Animal welfare
- Computer vision
- Image processing
- Livestock monitoring
- Phenotyping
ASJC Scopus subject areas
- General Engineering
- General Agricultural and Biological Sciences