458 Advanced computing and information technology to address challenges in livestock production
Dan Tulpan
- Year
- 2024
- Citations
- 2
- Access
- Open access
Abstract
Abstract Advanced computing and information technology have a crucial role in addressing challenges in livestock production by offering innovative solutions to improve efficiency, productivity, and animal welfare. These technologies rely on intelligent combinations of data analytics, Machine and Deep Learning (ML, DL), Internet of Things (IoT), and robotics solutions. In livestock production, advanced computing facilitates the collection, management, and analysis of vast amounts of data generated from various sources such as sensors, wearable devices, and monitoring systems. This data can provide insights into animal behavior, health status, production, and environmental conditions, enabling farmers to make informed decisions in real-time. Machine learning algorithms can build data-driven models able to predict disease outbreaks, optimize feed formulations, and identify patterns for better breeding selection. IoT devices can monitor environmental parameters like temperature, humidity, and air quality, ensuring optimal conditions for animal comfort and health. Robotics technologies can automate tasks such as feeding, milking, and cleaning, reducing labor costs and improving efficiency. Additionally, advanced computing enables the development of virtual modelling and simulation tools to test different scenarios and optimize production processes without the need for extensive physical experimentation. This presentation will focus on various technical aspects and examples related to leveraging advanced computing and information technology such that livestock producers can enhance productivity, minimize resource wastage, and promote sustainable practices, ultimately leading to improved profitability and animal welfare in the industry.
Keywords
Related papers
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martı́n Abadi, Ashish Agarwal, Paul Barham +17 more
2016
Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray
Mark Schena, Dari Shalon, Ronald W. Davis +1 more
1995
The Organization of Behavior
D. O. Hebb
2005
Fractional Brownian Motions, Fractional Noises and Applications
Benoît B. Mandelbrot, John W. Van Ness
1968