WSN Spatio-temporal Correlation Data Fusion Method for Dairy Cow

International Association of Online Engineering

Yisheng Miao¹  Huarui Wu²  Huaji Zhu² 

[1] Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences;National Engineering Research Center for Information Technology in Agriculture

关键词: internet of things in dairy farming;    wireless sensor network;    data fusion;    time series prediction;    weighted Markov chain;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: International Association of Online Engineering

【 摘 要 】

The cowshed environment has significant impacts on the yield, diseases and behaviors of dairy cows. Heat stress, in particular, has a great impact on yield. The cowshed environment monitoring system based on wireless sensor network can accurately sense the temperature and other environmental parameters in real time and provide basis for manual environmental intervention and control. Energy constraint is one of the important problems that affect the long-term stable monitoring by the dairy cow wireless sensor network. So, the weighted Markov chain method is used to predict the time series of cowshed temperature. Replacing the actual values with the predicted values at the cluster head can effectively reduce data traffic in the cluster, thereby reducing network power consumption. Test data show that, the average variance of the cowshed environment temperature predicted by the method proposed in this paper is 0.185, and the average power consumption is reduced by about 40% when the compression ratio is 0.3, which effectively prolongs the network lifetime. In addition to that, the cowshed environment prediction can also help make pre-judgments for environmental control, reduce or avoid the heat stress of dairy cows after the environmental parameters exceed the thresholds and provide the basis for the multi-source data fusion for dairy cow.

【 授权许可】

Unknown