Development Of Plant Growth Information Acquisition And Analysis System Based On Android Plantform

As a large country with a large population and agriculture,how to increase production while improving agricultural production efficiency is a problem that Chinese agricultural workers have been expecting to solve.The traditional methods of agricultural management have the disadvantages of unreasonable resource utilization,poor convenience of monitoring equipment and low precision.Based on this,a plant growth analysis and diagnosis system which integrates information acquisition,storage,display and intelligent computing is built in this thesis by combining photodetection technology,fuzzy algorithm,and Internet of Things technology.The reliability of the system is verified through experiments.The research has certain reference value for agricultural planting management.A multi-sensor fusion which used to solve the comprehensive analysis of plant growth is proposed in this thesis based on the study of the effects of plant leaf moisture,chlorophyll content,temperature,humidity,light intensity and CO2 concentration on plant growth.The construction of the sensor network and the design of the control framework which based on the principle of information acquisition are completed.The main controller STM32F103 is used to complete the timing design of the signal acquisition,and the Wifi-based data transmission method is determined.Aiming at the problem that traditional agricultural planting can not provide reliable planting guidance,an expert system construction method based on fuzzy mathematics is discussed.In the research of the fuzzy expert system,firstly,the input and output of the system are determined.Secondly,considering that the implementation measures in the output may have contradictory situations for a specific case,the analytic hierarchy process is used to obtain the important coefficients of each implementation measure.Thirdly,the appropriate quantization function and membership function are combined to fuzz the input and output,then the fuzzy expert system rule is designed.Finally,a set of intelligent analysis and decision system for plant planting management is given.In order to make agricultural management more convenient,a mobile APP is developed by combining Tomcat,MyEclipse,MySQL,and Android Studio.Finally,the construction of a small-scale agricultural information diagnosis platform which integrates acquisition,analysis and guidance is realized.In this thesis,the system is evaluated by using strawberries in the greenhouse as the research object to realize the reliability verification of the system.Firstly,the reliability of the acquisition system is verified by calibrating the collected data.Secondly,the necessity of multi-sensor fusion method for strawberry growth research and the reliability of fuzzy expert system are analyzed,and the expert rules are tested and correced by experiments.The research shows that the fuzzy expert system designed in this thesis is reliable;at the same time,it is necessary to correct the expert system rule through a large number of experiments.Through the research on the plant growth information acquire and analysis system,it is shown that the multi-sensor fusion technology combined with fuzzy reasoning in agricultural planting management can achieve accurate detection of crop information and reasonable evaluation of growth status,and then the planting guidance can be given.In addition,the development of mobile APP based on the Android platform has greatly improved the efficiency of agricultural management.Therefore,the analysis method for agricultural planting management proposed in this thesis has certain rationality and feasibility,and can provide reference for future research.