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Autonomic computing in a beef-production process for Precision Livestock Farming by Rodrigo García; Jose Aguilar; Mauricio Toro; Nelson Pérez; Angel Pinto; Paul Rodríguez is a Engineering article available to read on EtoBox.
What is Autonomic computing in a beef-production process for Precision Livestock Farming about?
Precision livestock farming (PLF) offers farmers real-time monitoring and management system. PLF provides a real-time warning when something goes wrong so that the farmer can take immediate action to solve the problem. PLF introduces many new challenges and questions that must be resolved. Some of these challenges are related to the integration of grazing and animal health into the beef-production process. This article introduces an architecture for the self-managing of a beef-production farm. In particular, the architecture includes three autonomous cycles of data analysis tasks (ACODAT) that allow beef producers to have adequate coordination, optimization and planning of the productive process, which are: (i) circuit preparation, (ii) animal purchase, and (iii) animal fattening. This article also instantiates, in a farm, the autonomous animal-fattening cycle, as the first step towards efficient and effective beef-production processes. The main contributions of this architecture are (i) the ability to use everything mining to improve the knowledge of the system and decision-making processes, and (ii) three ACODAT for real-time analysis for sustainable and environmentally-friendly
Who reads Autonomic computing in a beef-production process for Precision Livestock Farming?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Rodrigo García; Jose Aguilar; Mauricio Toro; Nelson Pérez; Angel Pinto; Paul Rodríguez
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Engineering (Physical Sciences)