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智慧灌溉大数据管理平台设计与应用

花匠小妙招
2024-12-16 18:58

摘要：

以粗放型为主的漫灌方式浪费水资源，探索高效节水农业灌溉意义重大。本研究研制了集数据采集、数据管理、数据可视化、分析决策和远程管理为一体的智慧灌溉大数据管理平台，旨在以数字化管理与智能化控制方式提升水资源利用效率。平台利用嵌入式、物联网、互联网、3S（GIS、GPS、RS）等技术，采取“1+1+N”的设计模式，构建作物需水预报模型与灌溉决策模型，基于B/S构架和Java语言，设计了1个灌溉数据中心、1个灌溉数据管理系统、4个应用系统，打造了智慧灌溉大数据管理平台。平台在河北、河南、山东、江苏等地区设有多个示范基地，汇聚了8个科研小组、24个试验基地的有关多种作物的生长、灌溉、气象、土壤等数据，平均采集数据18829条/天，帮助管理人员摸清家底；集成了多个团队的软件系统和62套物联网设备，及时、定量地呈现了农作物生长状况及环境状态，实现了农作区动态监测，助力生产决策；生成农作物需水预报和灌溉决策方案，完成了远程灌溉目标，并且经过实地试验，验证了自动灌溉的有效性，将灌溉水有效利用系数最高提升了31%以上；形成了大田产业、温室中心、数字科研和区域灌溉等不同专题可视化布局，满足多种农业场景应用需求。为农业生产和跨区域管理提供了便捷工具，为农业灌溉数字化系统搭建和应用提供了参考。

关键词: 智慧灌溉, 大数据, 作物需水预报, 平台设计, 物联网

Abstract:

Predominantly extensive flood irrigation method leads to wastage of water resources. Therefore, exploring efficient and water-saving agricultural irrigation methods is crucial. This study has developed an intelligent irrigation big data management platform that integrates data collection, management, visualization, analysis, decision-making, and remote management. Its goal is to improve water resource utilization efficiency through digital management and intelligent control. The platform utilizes embedded systems, the Internet of Things(IoT), and Internet technologies, as well as "3S" (GIS, RS, and GPS) technology. It follows the design model of "1+1+N" and includes the construction of a crop water requirement forecasting model, an irrigation decision-making model, an irrigation data center, an irrigation data management system, and four application systems. The entire platform is based on the B/S architecture and programmed using the Java language. The platform has been successfully implemented in several demonstration bases across regions such as Hebei, Henan, Shandong, Jiangsu, etc. It has gathered data on the growth, irrigation, weather, soil, and other aspects of various crops from 8 research teams and 24 experimental bases. On average, it collects 18 829 pieces of data per day, helping management personnel understand the overall situation. It integrates software systems from multiple teams and 62 sets of IoT devices to present the growth and environmental status of crops in a timely and quantitative manner, achieving dynamic monitoring of agricultural areas and assisting production decisions. It has also generated crop water demand forecasts and irrigation decision-making plans, accomplished remote irrigation targets, and through field experiments, validated the effectiveness of automatic irrigation, increasing the irrigation water utilization efficiency by more than 31% at its highest. The platform meets the application needs of different agricultural scenarios through thematic visualizations such as field industry, greenhouse center, digital scientific research, and regional irrigation. The smart irrigation big data management platform serves as a convenient tool for agricultural production and cross-regional management. Its construction and application provide valuable references for the development of digital agricultural irrigation systems.

Key words: smart irrigation, big data, crop water requirement forecasting, platform design, IoT