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Study On The Key Technologies Of Big Data For Agriculture

Posted on:2017-02-17Degree:DoctorType:Dissertation
Country:ChinaCandidate:L F GuoFull Text:PDF
GTID:1108330485487314Subject:Information Technology and Digital Agriculture
Abstract/Summary:PDF Full Text Request
Data drives the innovation of technologies and innovation drives the progress of the society. Today, many countries take data as a strategic resource, just like material, energy and human resources. However, how to enhance the vitality of data from all walks of life and extract potential and valuable knowledge from huge data sets is the primary problem in front of us. This paper had important practical significance and value to the promotion of the transformation and upgrading of traditional agriculture and the development of big data industry. On the one hand, China’s agriculture is facing severe challenges, such as resource shortages, excessive exploitation, increasing pollution and market fluctuations. It is urgent to innovate agriculture development pattern with the help of ICTs. On the other hand, the development of big data requires its deep integration with the industry, otherwise big data like water and trees can not survive without source. Agriculture, which is a highly complicated ecosystem, can produce huge raw data sets. And also agriculture is the very important area for the application of big data. This paper conducted researches on the application of big data technologies in agriculture to realize three goals as following. Firstly, we introduced the definition, process flow and the architecture of agriculture big data combined with the agricultural sector characteristics. Secondly, the key big data technologies such as data collecting, management and process technologies were studied based on the data process theory. Thirdly, the relevant countermeasures for the development of agriculture big data were put forward to provide reference and basis for the promotion of agriculture big data application. The main contents of the paper are as follows. 1) This paper combed the elementary theory of big data. Big data originated from modern scientific research and data-intensive science in turn push the scientific research innovation. The whole world committed to e-science construction to promote the development of data science. We reviewed the definition, characteristic of big data and introduced the research highlights of big data. 2) This paper deeply studied related issues on agriculture big data. The application of ICTs in agriculture was divided into four models in this paper. We proposed the definition, characteristic and architecture of agriculture big data from the perspective of convergence of agriculture and ICTs. We also studied the process flow of agriculture big data based on the data process theory and the component of agriculture big data based on agricultural industrial chain theory. 3) This paper made a systematic study on agriculture big data collecting. The big data was classified into three types based on its source. The data collecting in agriculture was divided into four stages in this paper. Agriculture big data was divided into agricultural remote sensing data, agricultural production data, animal and plant life data, agricultural market data, and agricultural network data depending on the data collecting technology. We designed and realized an agriculture website data capturing system using Scrapy to automatically collect project, conference and other information. 4) This paper made a systematic study on big data management and processing technology. We introduced NewSQL and NoSQL which is new database technology for big data management and combed the mainly data storage model, such as key-value store, document store, column-based store, and graph store. We realized visualized management of part agriculture data using Neo4 j database. We introduce batch processing and stream processing technology on big data processing. We realized the word segmentation for agriculture technology data based on Spark platform. This study incorporates several innovations as follows. Firstly, we made a systematic study on agriculture big data and proposed its process and architecture, which will provide references and suggestions for the further development of agriculture big data. Secondly, we made a systematic study on big data technology and studied its application in agriculture field combined with specific examples.
Keywords/Search Tags:agriculture big data, architecture, data collecting, data management, data processing
PDF Full Text Request
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