摘 要:针对传统设施农业物联网系统设计难以处理多源数据采集、复杂数据处理和多信息融合的问题,设计了一种融合深度学习的多信息融合设施农业物联网系统。该系统由环境监测子系统、视频监控子系统、水肥一体化系统、AI 分析子系统、信息融合子系统组成。其中 AI 分析子系统获取作物生长信息,信息融合子系统对环境、生长信息等多维度信息进行融合分析并输出生长管理调控策略。系统的设计可根据作物生长信息、设施大棚环境综合评价指标对设施设备提供智能化决策和调控策略,实现设施农业的精准调控。
关键词:设施农业;物联网;多信息融合;深度学习
DOI:10.19850/j.cnki.2096-4706.2022.19.033
中图分类号:TP212 文献标识码:A 文章编号:2096-4706(2022)19-0136-06
Design of Facility Agriculture IoT System Based on Multi-information Fusion
LIN Shanchi, LIU Lin, LI Xiangguo
(Gloryview Technology Co.,Ltd., Guangzhou 510663, China)
Abstract: Aiming at the problems that the traditional facility agricultural IoT system design is difficult to deal with multi-source data collection, complex data processing and multi-information fusion, a multi-information fusion facility agricultural IoT system integrating deep learning is designed. The system consists of environmental monitoring subsystem, video monitoring subsystem, water and fertilizer integration system, AI analysis subsystem, and information fusion subsystem. The AI analysis subsystem obtains crop growth information and the information fusion subsystem fuses and analyzes multi-dimensional information such as environment and growth information, and outputs growth management and regulation strategies. The design of the system can provide intelligent decision-making and regulation strategies for facilities and equipment according to the crop growth information and comprehensive evaluation indicators of facility greenhouse environment, so as to realize precise control of facility agriculture.
Keywords: facility agriculture; IoT; multi-information fusion; deep learning
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作者简介:林山驰(1971—),男,汉族,广东汕头人,高级工程师,硕士研究生,研究方向:电子信息技术方向。