In a proof of concept, we devised a system of cameras, microphones and other sensors that were installed in a stable, where machine learning techniques were used to collect data, recognize patterns and create reports. For example, the AI can check whether the farmer is meeting all the legal requirements. Data is the only way to show that statutory daytime light levels are being complied with, and is just one example of how data-driven insights can ensure that identified animal welfare violations are tracked and farmers are advised accordingly.
AI Will Take Over Routine Stable Tasks in the Shift To Farming Digitalization
When farmers go into the stable, they have to check the animals, assess their weight, measure ambient temperature, sense their stress levels and provide them with feed and water. These control rounds could be replaced by cameras, image recognition, microphones and sensors for CO2, humidity and temperature, which can carefully record and control measurements. Conditions in which the livestock is kept could then be improved in a more efficient manner, and lead to increased sustainability.
Finding the Right Slaughter Date
In addition to their holding conditions, the technology can also be applied to the digitalization of livestock. For example, the AI records the size and weight of each pig and can tell the farmer in advance when the ideal slaughter date will be. The aim is to obtain the best meat and the best price while ensuring the efficient use of animal feed. The information can also be used to optimize transportation from the stables to the slaughterhouse. Knowing the weight of the pigs means that truck loads can be optimized without breaching the statutory regulations.
Planning in the SAP System
The digital twins of stables and livestock also mean that simulations can be run and forecasts prepared, as we help businesses map out future scenarios. By transferring the data to the customer’s SAP system in the future, we would enable the company to improve its planning. Because the data could be recorded at a very early stage – and not only when the animals are slaughtered – supply and demand on the market could be adjusted ahead of time using a big data solution and data analytics, for example. By developing an SAP backbone for the client – the Digital Core – the business now has a framework for innovation.