Design And Implementation Of Visual Management System For The Whole Process Of Edible Mushroom Production

China is a major producer of edible mushrooms,currently ranking first in the world in terms of production.However,there is still a certain gap in the quality of edible mushrooms compared to developed countries abroad.The biggest problem is that the production management system in edible mushroom factories is relatively backward.In the initial overall design of the traditional management system,a large number of new Io T devices will be used in the future factory expansion and upgrading,which will lead to the new Io T devices being unable to access the original system and can only develop their own independent management systems,causing the "information silo" effect between management systems.In addition,some data comes from multiple sources,resulting in opaque data,dispersed production management,and asymmetric information transmission,which is not conducive to the overall management requirements of edible mushroom factories.Therefore,using modern and mature technologies such as front and rear end separation,B/S architecture,multisource heterogeneous data collection and processing,and data visualization,a visual management system that can integrate data resources and data visualization in the whole process of edible fungus production has been developed,realizing the unified collection,processing,and storage of data in the whole process of edible fungus production and industry dynamic data,and managing the whole process of production through visualization,The main research content is as follows:(1)Functional requirement analysis and system architecture design.Through investigating the actual production site of the edible fungus factory and consulting relevant literature,this paper analyzes the business requirements,functional requirements and non-functional requirement,and determines the main functions of the system;The system architecture design,user management,data visualization interface and other 13 functional modules were completed.(2)Multi source heterogeneous data collection and processing.It has defined the scope of data collection,developed a focused web crawler based on Java language,and developed picture text recognition and voice text recognition by calling Alibaba Cloud API;Analyze the characteristics of the data,design the process and methods of data cleaning,select data standardization algorithms,data dimensionality reduction algorithms,and data fusion algorithms that meet the requirements of this system,and develop algorithm code through Python language.Successfully call Python algorithm code using Jython library to achieve data collection and processing,and use adaptive weighted average algorithm and grey prediction algorithm to make the data more accurate,And can predict the environmental parameters of mushroom houses.(3)Build backup databases for the main database and cloud platform.In order to prevent data loss,a dual database system is designed,with the main database as the main database and the cloud database as the auxiliary database.My SQL is selected as the main database of the system,and Alibaba Cloud RDS is used as the backup database of the system.Twenty one database tables are designed,and data tables and interconnection between the main database and the cloud database are developed.(4)Implementation of a visual management system for edible mushroom production.Using Vue+Spring Boot framework,a B/S architecture with separated front-end and back-end,using Javascript language,Java language,Python language,Data V technology,Echarts technology,Lay UI technology,etc.The front-end requests data from the back-end interface through Axios,and the back-end project uses Druid Data Source to obtain database connections.According to the functional requirements of the system,a total of 8 front end data visualization pages and 37 background management function modules have been developed.The test results show that this system can effectively solve the "information silo" effect between multi-source heterogeneous data,realize the functions of automatic data collection,real-time statistical analysis,real-time sharing,automatic cloud backup,data visualization display and management,etc.,and introduce the fusion algorithm to make the processed data more accurate and can predict the environmental parameters of the mushroom room,and realize the early warning and alarm functions,Improve the overall level of production decision-making in edible mushroom factories,accurately regulate the production activities of edible fungi,and improve production efficiency and quality of edible fungi.