在农业生产过程中,温度、湿度、光照强度、二氧化碳浓度、水分以及其他养分

在农业生产过程中,温度、湿度、光照强度、二氧化碳浓度、水分以及其他养分等多种自然因素共同促进或影响着农作物的生长,传统的农业生产方式通过人的自我感知去调节上述环境参数,这种粗放式的管理方法不仅浪费劳动力,而且无法达到准确性要求,实际效果不佳。因此,文中基于物联网技术设计一种农作物管理系统,实现对农作物的生长状况进行实时检测,对获取到的数据进行可视化分析,并进行远程智能调控,推动现代农业的自动化、智能化水平,降低人力和资源消耗,提高农作物生产效率及产品质量。该系统基于物联网技术与Web技术设计开发,由数据采集模块、网络传输模块、应用管理模块、远程调控模块组成。实践表明:所提系统能够在农业生产过程中对农作物进行远程调控管理,实时了解相应农作物信息,推进智慧农业进程,为"三农"问题提供可行的解决方案,同时在应用的过程中,采集的数据还可以进行二次开发,从多方面多源反应研究环境因素对农作物生长的影响。

在农业生产过程中,温度、湿度、光照强度、二氧化碳浓度、水分以及其他养分等多种自然因素共同促进或影响着农作物的生长,传统的农业生产方式通过人的自我感知去调节上述环境参数,这种粗放式的管理方法不仅浪费劳动力,而且无法达到准确性要求,实际效果不佳。 因此,文中基于物联网技术设计一种农作物管理系统,实现对农作物的生长状况进行实时检测,对获取到的数据进行可视化分析,并进行远程智能调控,推动现代农业的自动化、智能化水平,降低人力和资源消耗,提高农作物生产效率及产品质量。 该系统基于物联网技术与Web技术设计开发,由数据采集模块、网络传输模块、应用管理模块、远程调控模块组成。 实践表明:所提系统能够在农业生产过程中对农作物进行远程调控管理,实时了解相应农作物信息,推进智慧农业进程,为"三农"问题提供可行的解决方案,同时在应用的过程中,采集的数据还可以进行二次开发,从多方面多源反应研究环境因素对农作物生长的影响。

In the process of agricultural production, many natural factors such as temperature, humidity, light intensity, carbon dioxide concentration, moisture and other nutrients jointly promote or affect the growth of crops. The traditional agricultural production mode adjusts the above environmental parameters through human self perception. This extensive management method not only wastes labor but also fails to meet the accuracy requirements, The actual effect is not good. Therefore, based on the Internet of things technology, this paper designs a crop management system to realize real-time detection of crop growth, visual analysis of the data obtained, and remote intelligent control, so as to promote the automation and intelligent level of modern agriculture, reduce the consumption of manpower and resources, and improve the production efficiency and product quality of crops. The system is designed and developed based on Internet of things technology and web technology, which is composed of data acquisition module, network transmission module, application management module and remote control module. The practice shows that the system can carry out remote control and management of crops in the process of agricultural production, understand the corresponding crop information in real time, promote the process of intelligent agriculture, and provide feasible solutions for the "three rural" problems. At the same time, in the process of application, the collected data can also be redeveloped to study the impact of environmental factors on crop growth from various aspects and multi-source reactions.<BR>