期刊文献+

Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms 被引量:3

原文传递
导出
摘要 Management of poultry farms in China mostly relies on manual labor.Since such a large amount of valuable data for the production process either are saved incomplete or saved only as paper documents,making it very difficult for data retrieve,processing and analysis.An integrated cloud-based data management system(CDMS)was proposed in this study,in which the asynchronous data transmission,distributed file system,and wireless network technology were used for information collection,management and sharing in large-scale egg production.The cloud-based platform can provide information technology infrastructures for different farms.The CDMS can also allocate the computing resources and storage space based on demand.A real-time data acquisition software was developed,which allowed farm management staff to submit reports through website or smartphone,enabled digitization of production data.The use of asynchronous transfer in the system can avoid potential data loss during the transmission between farms and the remote cloud data center.All the valid historical data of poultry farms can be stored to the remote cloud data center,and then eliminates the need for large server clusters on the farms.Users with proper identification can access the online data portal of the system through a browser or an APP from anywhere worldwide.
出处 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2016年第4期106-115,共10页 国际农业与生物工程学报(英文)
基金 the“12th Five-Year-Plan”for National Science and Technology for Rural Development in China(No.2014BAD08B05).
  • 相关文献

参考文献7

二级参考文献82

  • 1金澈清,钱卫宁,周傲英.流数据分析与管理综述[J].软件学报,2004,15(8):1172-1181. 被引量:161
  • 2陆昌华.计算机在20万羽蛋鸡场生产管理中的应用研究(初报)[J].农业工程学报,1997,13(1):157-159. 被引量:13
  • 3徐守渊.乳品超高温杀菌和无菌包装[M].北京:轻工业出版社,1986..
  • 4徐宜为,最新禽病与防制,1993年,42页
  • 5Babcock B, Babu S, Datar M, Motwani R, Widom J. Models and issues in data streams. In: Popa L, ed. Proc. of the 21st ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Systems. Madison: ACM Press, 2002. 1~16.
  • 6Terry D, Goldberg D, Nichols D, Oki B. Continuous queries over append-only databases. SIGMOD Record, 1992,21(2):321-330.
  • 7Avnur R, Hellerstein J. Eddies: Continuously adaptive query processing. In: Chen W, Naughton JF, Bernstein PA, eds. Proc. of the 2000 ACM SIGMOD Int'l Conf. on Management of Data. Dallas: ACM Press, 2000. 261~272.
  • 8Hellerstein J, Franklin M, Chandrasekaran S, Deshpande A, Hildrum K, Madden S, Raman V, Shah MA. Adaptive query processing: Technology in evolution. IEEE Data Engineering Bulletin, 2000,23(2):7-18.
  • 9Carney D, Cetinternel U, Cherniack M, Convey C, Lee S, Seidman G, Stonebraker M, Tatbul N, Zdonik S. Monitoring streams?A new class of DBMS applications. Technical Report, CS-02-01, Providence: Department of Computer Science, Brown University, 2002.
  • 10Guha S, Mishra N, Motwani R, O'Callaghan L. Clustering data streams. In: Blum A, ed. The 41st Annual Symp. on Foundations of Computer Science, FOCS 2000. Redondo Beach: IEEE Computer Society, 2000. 359-366.

共引文献234

同被引文献34

引证文献3

二级引证文献44

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部