How Can Artificial Intelligence Revolutionize the Poultry Sector?

Evelynn Becker, IT Manager , Dean Foods

Artificial intelligence (AI), with all its promises when applied in the poultry industry, might improve the efficiency and help the producers address the growing challenges.

 The global scenario for poultry products is good. The demand is driven by population growth, rising income levels, favorable trends in dietary patterns, and consumer preference, fostering better animal protein demand. But, these opportunities are not without challenges. 

Livestock producers witness more significant pressure to produce more with less and are usually questioned about their environmental impact. The poultry sector might have the lowest emissions levels of all livestock sectors; it should still find ways to lower its carbon dioxide production.

Bird well being and welfare is ever more challenged. While responsible antibiotic use has always been a mandate of the poultry sector, more consumers demand no antibiotics ever, necessitating better management practices and potentially compromising welfare.

The adoption of AI may be able to address many of these issues.

The role of artificial intelligence

By 2050, the average farm will generate 4.1 million data points through the internet of things sensors and related devices, but is the industry ready to make the most of this information? 

Most farms still rely on pen and paper to record information, and collected data must then be fed into a computer to discover what it may reveal.

The real power of AI is that its automatically-collected data and in-depth analysis can immediately optimize production. Data mining is the “gold” for farmers, and AI will help them to extract maximum benefit.

Machines can learn from data – the machine learning process. During supervised learning, numerous examples of what is or is not acceptable production data are provided to train them. This may be, for instance, expected weight at 21 days for a specific line of broilers under local conditions. 

Machines also can learn in an unsupervised manner where data will be categorized, and trends detected without specific programming or labeling. Using resources from the cloud, vast amounts of data can be analyzed quickly, giving advance notice of a particular outcome.

Some companies are now specializing in using farm production data to predict performance. Utilizing data from a wide range of sensors measuring bird weight, temperature, feed and water consumption, humidity, ammonia levels, and many more parameters, they can predict real-time data of broilers’ future performance. Their services offer producers a 14-day view into weight prediction.