A Comprehensive Analysis of Pig Behavior Recognition in Conventional Pig Farming
Abstract
In recent years, conventional pig farming techniques have seen substantial changes; with a growing emphasis on technological innovations to improve production and animal welfare. This paper provides a comprehensive investigation of pig behavior recognition in the framework of conventional pig farming methods. In this research, we observe and evaluate several patterns of pig behavior using computer vision technologies. To observe and understand different parts of pig behavior, the study employs a multi-pronged strategy that includes cutting-edge video surveillance methods. A collection of videos shows 30 pigs engaging in many common behaviors, including sleeping, scratching, eating and drinking. In video data preparation, useful segments are selected and organized into a structured dataset, as well as distorted or incorrect films are filtered. Important details about the pigs' actions over three days are uncovered by the findings. The research investigates the possible advantages of using pig behavior recognition in traditional agricultural systems, including better parenting, early health problem diagnosis and optimized feeding techniques. Furthermore, the ethical implications of using this technology in pig farming are examined, highlighting the need to strike a balance between technical improvements, standards for animal welfare and ethical behavior. This study seeks to promote a sustainable and compassionate method of pig farming that meets the changing needs of society and the agricultural economy. The findings will provide useful insights into the areas of animal welfare and precision livestock production via the recognition of pig behavior.
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