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基于Hadoop的蛋雞設(shè)施養(yǎng)殖智能監(jiān)測(cè)管理系統(tǒng)研究
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國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2017YFD0701602、2016YFD0700204)


Design of Intelligent Monitoring and Management System Based on Hadoop for Largescale Layer House
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    摘要:

    為實(shí)現(xiàn)對(duì)蛋雞生產(chǎn)過(guò)程中長(zhǎng)期積累的海量數(shù)據(jù)進(jìn)行高效存儲(chǔ)和實(shí)時(shí)查詢,利用Hadoop生態(tài)系統(tǒng),設(shè)計(jì)了規(guī)模化蛋雞設(shè)施養(yǎng)殖智能監(jiān)測(cè)管理系統(tǒng)。針對(duì)環(huán)境數(shù)據(jù)的實(shí)時(shí)監(jiān)測(cè)及大規(guī)模數(shù)據(jù)查詢,用MySQL數(shù)據(jù)庫(kù)存儲(chǔ)近期數(shù)據(jù)、HBase存儲(chǔ)歷史數(shù)據(jù),有效提升了檢索速度;針對(duì)海量異構(gòu)視頻數(shù)據(jù)的統(tǒng)一管理,設(shè)計(jì)實(shí)現(xiàn)了基于MapReduce并行處理框架的分布式轉(zhuǎn)碼模塊,將1.5GB的視頻分割為多個(gè)128MB分段后進(jìn)行轉(zhuǎn)碼,轉(zhuǎn)碼效率提高了50%。該系統(tǒng)實(shí)現(xiàn)了規(guī)模化蛋雞場(chǎng)生產(chǎn)養(yǎng)殖中對(duì)實(shí)時(shí)信息、歷史信息、基礎(chǔ)設(shè)施信息、生產(chǎn)過(guò)程信息的統(tǒng)一管理,并提供了統(tǒng)計(jì)分析模塊對(duì)采集獲取的數(shù)據(jù)進(jìn)行整合分析,開(kāi)發(fā)了Web端網(wǎng)頁(yè)版本及移動(dòng)端APP版本的智能監(jiān)測(cè)管理系統(tǒng),便于用戶進(jìn)行實(shí)時(shí)訪問(wèn),提高了生產(chǎn)養(yǎng)殖的工作效率。

    Abstract:

    With the appearance and continuous development of the Internet of things, the monitoring data grows explosively. Accordingly, traditional data storage and processing can not meet the requirements.In order to store data effectively and query data in real time, intelligent monitoring and management system based on Hadoop for largescale layer house was developed. The HDFS file system and HBase database in the Hadoop ecosystem can store massive data distributed. The environmental monitoring data had the characteristics of once writing and multiple queries. In order to realize the realtime monitoring and largescale data query for environmental data, MySQL database was used to store recent data and HBase database was used to store historical data. Experiments indicated that the query speed was improved effectively. For the unified management of massive heterogeneous video data, the distributed transcoding of video was designed and implemented. Experimental results showed that the proposed scheme can increase about 50% of the transcoding efficiency when the video size was 1.5GB and the segment size was 128MB. The system realized realtime information display, historical information query, infrastructure management, production process management and statistical data analysis, environmental alerts and system management in production and breeding of largescale layer house, which can be accessed through web pages and mobile APP by users in real time. The actual application showed that the system helped managers to control the production process on all aspects and improve the efficiency of the production personnel.

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孟超英,張雪彬,陳紅茜,李 輝.基于Hadoop的蛋雞設(shè)施養(yǎng)殖智能監(jiān)測(cè)管理系統(tǒng)研究[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2018,49(9):166-175. MENG Chaoying, ZHANG Xuebin, CHEN Hongqian, LI Hui. Design of Intelligent Monitoring and Management System Based on Hadoop for Largescale Layer House[J]. Transactions of the Chinese Society for Agricultural Machinery,2018,49(9):166-175.

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  • 收稿日期:2018-03-25
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  • 在線發(fā)布日期: 2018-09-10
  • 出版日期: 2018-09-10
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