This article introduces a highly intelligent and widely applicable system for intelligent management and control of livestock production. This system mainly provides the functions of feed use monitoring and control, RFID e-label identification, quality traceability, animal farming environment monitoring, growth monitoring and predication, etc. This article gives detailed introduction of the animal farming environment monitoring, growth monitoring and algorithms used by the predication function in the system. This system effectively improves the production efficiency of animal farming as well as the survival rate and off-taking rate of animal products, thus shortening cycles of animal farming. This system provides a convenient platform for standardized livestock production and management. Animal farming in multiple locations and for multiple times finally generate big data of farming of various types of animals. Constant exploration of such data can help optimize animal farming practices and provide technical support for more science-based and precise animal farming.
[1]
P. Cochat,et al.
Et al
,
2008,
Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[2]
Zhe-min Li,et al.
Edible agro-products quality and safety in China
,
2015
.
[3]
Yoshua. Bengio,et al.
Learning Deep Architectures for AI
,
2007,
Found. Trends Mach. Learn..
[4]
Toyota Celica.
COMPUTER CONTROL SYSTEM
,
1988
.
[5]
A. S. Kaunananda.
Design of an intelligence device for household circuit balancing
,
1997,
Proceedings of Second International Conference on Power Electronics and Drive Systems.
[6]
Yunqian Ma,et al.
Practical selection of SVM parameters and noise estimation for SVM regression
,
2004,
Neural Networks.
[7]
Chen Wei,et al.
Application of intelligence information fusion technology in agriculture monitoring and early-warning research
,
2015,
2015 International Conference on Control, Automation and Robotics.