Application of Intelligence Control in Agriculture Greenhouses

2015 ◽  
Vol 719-720 ◽  
pp. 293-297 ◽  
Author(s):  
Hui Guo Lu ◽  
Cong Ying Li ◽  
Juan Ping Jiang

Agriculture is the foundation of the national economy, and the guarantee of national industry. Greenhouse can grow counter-season production of crops and bring higher profits to farmers. But in our country the informatization level of agricultural is low. By using data acquisition technology, wireless communication technique and computer technology, this project can make intelligent monitoring, management and control of the large-scale plastic greenhouse come true and make agricultural information access and remote data transmission and exchange automated. The project is of simple circuit, low cost, good maintainability, and the expected results (the management of the greenhouse control) is operating conveniently and hommization, which can reduce a lot of manual work. It is expected to be widely popularized in agricultural plastic greenhouses in China. Key words:Intelligent Agriculture; Automation; Data acquisition; Sensors;

Author(s):  
Joby Antony ◽  
Basanta Mahato ◽  
Sachin Sharma ◽  
Gaurav Chitranshi

In the present IT age, we are in need of fully automated industrial system. To design of Data Acquisition System (DAS) and its control is a challenging part of any measurement, automation and control system applications. Advancement in technology is very well reflected and supported by changes in measurement and control instrumentation. To move to highspeed serial from Parallel bus architectures has become prevalent and among these Ethernet is the most preferred switched Serial bus, which is forward-looking and backwardcompatible. Great stride have been made in promoting Ethernet use for industrial networks and factory automation. The Web based distributed measurement and control is slowly replacing parallel architectures due to its non-crate architecture which reduces complexities of cooling, maintenance etc. for slow speed field processing. A new kind of expandable, distributed large I/O data acquisition system based on low cost microcontroller based electronic web server[1] boards has been investigated and developed in this paper, whose hardware boards use 8-bit RISC processor with Ethernet controller, and software platform use AVR-GCC for firmware and Python for OS independent man machine interface. This system can measure all kinds of electrical and thermal parameters such as voltage, current, thermocouple, RTD, and so on. The measured data can be displayed on web pages at different geographical locations, and at the same time can be transmitted through RJ-45 Ethernet network to remote DAS or DCS monitoring system by using HTTP protocol. A central embedded single board computer (SBC) can act as a central CPU to communicate between web servers automatically.


2016 ◽  
Vol 21 (5) ◽  
pp. 660-670 ◽  
Author(s):  
Abdul Rashid Husain ◽  
Yaser Hadad ◽  
Muhd Nazrul Hisham Zainal Alam

2021 ◽  
Vol 269 ◽  
pp. 02006
Author(s):  
Yu Tang ◽  
Gang Wu

In recent years, with the improvement of large-scale planting in rural areas, greenhouse cultivation technology has been developed rapidly. Intelligent monitoring and control of modern agricultural greenhouse is a hot topic at present. Based on the design requirements of modern greenhouse and the architecture of software design, this paper designs and develops the main program, data acquisition subroutine, alarm subroutine, control keystroke subroutine and display driver subroutine of the system based on the STM32F103ZET6 main control chip, and realizes the design of intelligent monitoring and control system of greenhouse, This study is of great significance for the establishment of scientific ecological environment of plants and the realization of high quality and high yield of crops.


2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zhijin Wang ◽  
Yaohui Huang ◽  
Bingyan He ◽  
Ting Luo ◽  
Yongming Wang ◽  
...  

Infectious diarrhea has high morbidity and mortality around the world. For this reason, diarrhea prediction has emerged as an important problem to prevent and control outbreaks. Numerous studies have built disease prediction models using large-scale data. However, these methods perform poorly on diarrhea data. To address this issue, this paper proposes a parsimonious model (PM), which takes historical outpatient visit counts, meteorological factors (MFs) and Baidu search indices (BSIs) as inputs to perform prediction. An experimental evaluation was done to compare the short-term prediction performance of ten algorithms for four groups of inputs, using data collected in Xiamen, China. Results show that the proposed method is effective in improving the prediction accuracy.


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