Modeling of green agricultural environment and rape hyperspectral analysis based on machine learning algorithm

被引:2
作者
Liao, Xiaoyi [1 ]
Liao, Guiping [1 ]
Cao, Jiajun [1 ]
机构
[1] Hunan Agr Univ, Coll Agr, Changsha 410128, Hunan, Peoples R China
来源
OPTIK | 2023年 / 273卷
关键词
Machine learning; Internet of Things; Green agricultural environment; Rape hyperspectral analysis modeling; CHLOROPHYLL FLUORESCENCE; MANAGEMENT-SYSTEM;
D O I
10.1016/j.ijleo.2022.170395
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In recent years, China's agricultural Internet of Things technology has attracted great attention. Document No. 1 emphasizes that we will make every effort to use Internet of Things technology, big data, mobile Internet, cloud computing technology, etc. to promote the progress of "Internet + " modern agriculture. Government departments have taken the lead in accelerating the development of agricultural and animal husbandry technology, improving the infrastructure construction of the agricultural industry chain and upgrading the management decision-making management system, building a comprehensive logistics information management service platform, ensuring effective production scheduling in the agricultural and animal husbandry sales market, and improving the construction Agriculture and animal husbandry industry chain. WSNbased has many advantages over traditional solutions, such as long-term monitoring, accuracy, scalability, easy deployment, and low cost, making wireless sensors widely used in the environment and agriculture. Therefore, in the agricultural Internet of Things, a variety of sensor connection points can be arranged around the crops to form system software and a comprehensive monitoring website, which can help farmers deal with problems in a timely manner and propose corresponding solutions to this. Form an integrated production model based on the agricultural Internet of Things system that generates intelligent decisions.
引用
收藏
页数:13
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