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Design And Implementation Of Remote Anti-frost Control System Based On Internet Of Things

Posted on:2020-11-12Degree:MasterType:Thesis
Country:ChinaCandidate:X Y WangFull Text:PDF
GTID:2370330623957656Subject:Computer technology
Abstract/Summary:PDF Full Text Request
Frost is more common in China's agricultural meteorological disasters,which causes different degrees of obstacles to agricultural development in various regions.Ningxia is an area prone to frost disasters,which often results in lower agricultural product quality and impaired production in the region.As a necessary means of agricultural disaster prevention,frost prevention has attracted the attention of researchers,but the traditional frost prevention measures are single and the equipment is complicated to deploy,which still cannot meet the agricultural frost prevention needs.In order to solve the problems of low efficiency and incomplete automation of a single type of anti-frost measures,this article combines agricultural Internet of Things technology and remote control technology to develop a flexible anti-frost plan that can be used to allocate farming fruit shed resources.The remote anti-frost control system of the Internet of Things can effectively reduce the loss of resources,improve the effect of agricultural anti-frost,and has practical value in the application of agricultural anti-frost.Combining the characteristics of the Internet of Things,the system is divided into a perception layer,a network layer,and an application layer.The sensing layer of the system realizes the sensing and automatic regulation of the temperature and humidity of the orchard.In view of the large area of the site,multiple points of frost protection are needed.Therefore,the sensing layer is divided into the main control terminal,the ignition control terminal and the anti-frost fan control terminal according to actual needs.In part,the main control terminal selects STM32F103VET6 as the main control chip.It obtains the temperature and humidity on site through DS18B20 and SHT10,and uses the preset temperature and humidity threshold to determine the occurrence of frost.When the field environment reaches the threshold,it will send the ignition control terminal through the Lora module Control instructions to achieve automatic anti-frost operation.At the same time,the main control terminal will periodically receive status information from the terminal through Lora and transmit it to the system network layer.The ignition control terminal selects STM8L151K4T6 as the main control chip,receives control commands from the main control terminal through the Lora module,ignites the anti-frost heating device or ignites the smoke bomb to implement anti-frost.The anti-frost fan is a large-scale equipment,and it needs to be controlled separately to perform anti-frost.The system network layer is a bridge that builds the communication between the perception layer and the application layer.On the one hand,it obtains the field environment information from the perception layer and uploads it to the server through the GPRS module,enabling users to view the orchard information on the APP in real time;Users can issue remote control instructions to the perception layer through the APP to achieve remote frost protection on the orchard.The main research results of this paper:(1)Design and implement for the first time an IoT remote frost control system with multi-method integration of anti-frost plans,equipped with local and remote control methods,making the system more flexible.(2)Based on Ningxia meteorological data over the years,logistic and LSTM models were used to perform simulation experiments on four types of frost prediction indicators,and the results showed that the logistic accuracy rates were 97.1%,96.9%,97.1%,and 97.3%,respectively,compared with Hao Ling in 2018 The related research results(training accuracy rate of 93.994%)have been improved to some extent;LSTM accuracy rates are: 98.2%,98.3%,98.0%,and 98.1%.
Keywords/Search Tags:Internet of Things, Remote Anti-Frost, Frost Prediction, Logistic, LSTM
PDF Full Text Request
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