AI in agriculture

Artificial intelligence solutions in the field of agriculture and animal health

Bence Tarr (MATE) will give the first lecture entitled "Problems of data-based Artificial Intelligence solutions in the field of agriculture". In agriculture, data has long been collected from the point of view of health, quality assurance, and production management. Due to the availability of large amounts of historical data, agriculture provides excellent opportunities for data-based artificial intelligence procedures. Required by food safety procedures and industry in order to meet strict quality requirements, prediction procedures are often used. Thus, in precision agriculture, modern GPS and image processing-based geospatial procedures are present at the same time, and sensor-based artificial intelligence tools control the production and breeding methods. Through some practical examples, the presentation will present their application possibilities.

The title of Zsófia Czudor's (E-Group) presentation is "Integration of animal health data as a preparation for reducing the development of antibiotic resistance".
The reduction and rationalization of antibiotic use is one of the serious challenges of our future in animal health. The problem of antibiotic resistance arising from current use in Hungary mainly affects the poultry and pig sectors. The University of Veterinary Medicine, E-Group ICT Software Zrt. and the The employees of Prim-A-Vet Gyógyszer-nagykereskedelmi Kft. wish to develop a preparation that, through its synergistic effect, can reduce the amount of antibiotics used, and also reduce the chance of developing resistance when antibiotics are used. data is extremely heterogeneous both from a domain and IT point of view. Data harmonization requires a broad analysis of data, where machine learning methods must also be used. The platform can also serve as the basis for the creation of a food chain safety data lake, which can be collected from different sources in animal health, veterinary public health, food safety and human health data, and may trigger a part of data collection for research purposes with ad hoc, heterogeneous structures and data protection challenges.

The lectures are followed by an informal discussion and a club-like discussion.

We look forward to welcoming those interested!

Peter Antal,
Co-chairman of HTE Artificial Intelligence department