[01] Shijie Xing, School of Information Engineering, China University of Geosciences, Beijing, China. [02] Xin Zhang, Beijing Agricultural Intelligent Equipment Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China. [03] Mengzhou Zhang, School of Information Engineering, China University of Geosciences, Beijing, China. [04] Mei Li, School of Information Engineering, China University of Geosciences, Beijing, China.

Vegetables play an important role in people's health. According to relevant data, per capita vegetable intake is about 924 grams per day in China, and the country consumes at least 506 million tons of vegetables every year. Under the background of Implementing Rural Revitalization Strategy, attaching great importance to improving agricultural quality and efficiency, green production and driven by scientific and technological innovation, China's vegetable industry is in a critical period of transformation to scale, intelligence and modernization. However, there are some practical problems in the field of vegetable production, such as one-sided, inefficient, spatiotemporal, dynamic, data island and data ocean, which greatly hindered the development of vegetable industry. A new vegetable production model based on big data and artificial intelligence is proposed in this paper according to the characteristics of physiological environment such as vegetable growth period difference and soil climate adaptability. By analyzing the real-time data and intelligent decision-making of knowledge base in vegetable production, this mode studies the data fusion algorithm of heterogeneous data, the intelligent decision analysis method of knowledge base and the personalized intelligent recommendation model, and realizes the nanny AI production and big data intelligence by using the prediction function of the model, the reasoning decision-making function of the expert system, and the data mining and knowledge expression function of the intelligent algorithm cloud service system.

Vegetable Production, Big Data, Artificial Intelligence, Data Fusion, Cloud Service System

[01] Yaguang Huang. Research and development of multi domain simulation data and process management platform [D]. Zhejiang University, 2015. [02] Weersink, Alfons, Fraser, et al. Opportunities and Challenges for Big Data in Agricultural and Environmental Analysis [J]. Annual Review Of Resource Economics [J], 2018 (10): 19-37. [03] Liang Zhao; Zhikui Chen; Yueming Hu; Geyong Min; Zhaohua Jiang. Distributed Feature Selection for Efficient Economic Big Data Analysis [J]. IEEE Transactions on Big Data 2018 (2): 164-176. [04] AI in the Global Agriculture Market to 2025 - ResearchAndMarkets.com. Business Wire (English). 2018. [05] Eissa Alreshidi. Artificial Intelligence in the United States Agriculture Industry (2016-2025): AI Spending with 20+ KPIs, Market Size & Forecast Across 11+ Application Segments, AI Domains, and Technology – Research And Markets.com [J]. Electrical Engineering and Systems Science, 2019. [06] Vijayalakshmi, J, Pandimeena, K. Agriculture talkbot using AI [J]. International Journal of Recent Technology and Engineering, 2019, (2): 186-190. [07] Xu Zhou, Xudong Fang, Bingsong Wen. A gbdt based machine learning algorithm and its application research [J]. Telecommunication engineering technology and standardization, 2019, 32 (11): 27-30 +46. [08] Jun Tan. Research on Smart Medical Cloud Application Service System Against the Backdrop of Smart City [J]. Atlantis Press, 2019. [09] Song Le. Research on fusion and evaluation method of heterogeneous images [D]. Tianjin University, 2008. [10] Yaonan Wang, Shutao Li. Overview of multisensor information fusion and its application [J]. Control and decision making, 2001, (5): 518-522. [11] Guo Jiao, Zhu Lin, Jin Biao. Crop classification based on sentinel-1 and sentinel-2 data fusion [J]. Journal of agricultural machinery, 2018, (4): 192-198. [12] Li Meng, Zhai Yunxia, Yang Aimin. Application of "satellite + big data" technology in agricultural production [n]. Agricultural engineering, 2017-12 (7). [13] Jianguo Xu, Haifeng Xiao. Implementation of Intelligent Agricultural Internet of things system based on big data [J]. Software guide, 2018, (8). [14] Lijie Li. Review on the application of artificial intelligence in China's modern agriculture [J]. Modern information technology, 2019, (5): 177-178. [15] Leifeng Guo. Research on Key Technologies of big data for agriculture [D]. Beijing: Chinese Academy of Agricultural Sciences, 2016. [16] Xiaohong Huang. Research on sensor network data fusion technology and its application in greenhouse control [D]. University of Electronic Science and technology, 2009. [17] Lin Cui. research on multi data fusion technology of wireless sensor in northern solar greenhouse [D]. Shenyang Agricultural University, 2016. [18] Wenting Wang, Yifei Guo. Application of multi-source remote sensing data and its fusion technology in soil moisture monitoring [J]. Water saving irrigation, 2018, (6): 63-66 +70.