How AI Is Revolutionizing Livestock Farming
How can AI help address these challenges and transform the livestock industry? Read below to check out some of the latest applications of AI in livestock farming!
AI
11/6/20233 min read
Livestock farming is one of the oldest and most important human activities, providing food and livelihoods for billions of people. However, it also faces many challenges, such as animal health and welfare, environmental sustainability, resource efficiency, and market competitiveness. How can AI help address these challenges and transform the livestock industry? In my last article How AI Is Revolutionizing Farming, I focused on AI applications in crop farming. In this article, we will explore some of the latest applications of AI in livestock farming.
Livestock Counting and Monitoring
AI can be used to detect, track, and count livestock with high accuracy and speed, as well as to monitor their health status and identify signs of illness, injury, or stress. The livestock monitoring market is estimated to be worth USD 1.6 billion in 2022 and is projected to reach USD 3.7 billion by 2030, at a CAGR of 11% during the forecast period (Source: Research and Markets). Growing use of hardware devices such as smart tags, sensors, camera-based systems, and GPS devices in livestock farms is a major factor driving the market growth.
Below is an example of using computer vision for detecting, counting, and monitoring ranch activities in real time, providing a useful repository of data to ranchers. This data enables ranchers to set up automated alerts, forecast and follow trends, and thus improve their profitability.
Livestock Autonomous Feeding
AI can help livestock farmers automate and optimize feeding animals, by using computer vision, sensors, and data analytics to monitor the feed intake, health, and behavior of livestock, and adjusting the feed quantity, quality, and timing accordingly. This can help livestock farmers reduce labor costs, improve animal welfare, and increase productivity and profitability. The market size of autonomous livestock feeding is USD 4.65 billion in 2022 and USD 8.64 billion by 2030, growing at a CAGR of 7.13% per year (Source: VMR).
Examples of companies that are using AI for livestock autonomous feeding are Smart Ag, Lely and more. They have developed solutions such as the Ranch Rover and the Vector, which can feed and manage livestock remotely and intelligently. The video below is the Ranch Rover developed by Smart Ag, an autonomous ranch feeding vehicle
Livestock Waste Management
AI can be used to manage the waste generated by livestock farming, such as manure and methane. By doing so, AI can help reduce the environmental impact of livestock farming, such as greenhouse gas emissions, water pollution, and soil degradation. An example is ZELP (Zero Emission Livestock Project), a startup that uses AI to reduce methane emissions from cattle. ZELP developed a wearable device that attaches to the nose of cows and monitors their breath. ZELP's sensors can collect millions of data points on the animals and AI is trained to detect heat, flag potential welfare conditions, and identify the most efficient animals with a high-level of accuracy.
Looking ahead...
In conclusion, AI is a powerful tool that can revolutionize livestock farming and beyond. By using AI to automate livestock counting and health monitoring, improve livestock feed intake and nutrition, and manage livestock waste, farmers can enhance their operational efficiency and profitability, as well as improve animal welfare and sustainability.
AI-powered farming is beginning to boom, with record amount of investment plowed into Agricultural Tech (AgTech) in recent years, which can be seen from the graph below.
With so much funding in AgTech, I'm sure we will see more and more use cases of AI in farming. What does this mean for you? If you're AgTech industry, now is the time for you to make a difference using AI!