Design And Implementation Of Air Conditioning Monitoring And Early Warning System In Cigarette Factory Based On SpringBoot

In the new round of development trend of the integration of information technology and manufacturing,the wave of digitization has penetrated rapidly in the industrial field,generating massive amounts of industrial digital production data,and effectively promoting the application and promotion of artificial intelligence-related technologies in the industrial field.Thanks to the rapid development of artificial intelligence technology,great progress has been made in the research of air conditioning monitoring systems in cigarette factories.However,the existing air-conditioning monitoring system has problems such as data dispersion,poor data quality,and large data affected by equipment.On the other hand,the production workshops of cigarette factories have extremely high requirements for the accuracy of the temperature control of the air-conditioning system.The existing air-conditioning monitoring and early warning system It is difficult to meet actual application requirements.Therefore,how to achieve accurate control of the air-conditioning temperature in a complex and changeable monitoring environment is a core problem to be solved in this field.In this paper,a set of air conditioning monitoring and early warning systems for cigarette factories based on the RF-LSTM(random forest-long short term memory)model is constructed in response to the current deficiencies of cigarette factories.The model first uses random forest regression to filter data.Then use the selected optimal feature subset to train the LSTM model,and then realize the accurate warning of the temperature of the packaging workshop.Through the systematic analysis,design and realization of the business requirements of the cigarette factory’s package workshop,the research and development of a management system that integrates data collection,monitoring and early warning suitable for the air-conditioning system of the tobacco industry’s package workshop is researched and developed.The system structure is a three-tier architecture system in the B/S mode.The Spring Boot framework and Spring Data JPA’s ORM persistence layer framework are used to build the system business architecture;the front-end page construction is realized through front-end technologies such as Node.js and Vue,and the database system uses SQL Server,And realize the air conditioning sensor data collection and preprocessing function based on OLEDB(Object Linking and Embedding,Database)through C#.The development of this system strictly abides by the software development process and specifications,and has undergone software development processes such as demand analysis,outline design,detailed design and implementation,and system testing.The designed and implemented air conditioning monitoring and early warning system for the cigarette factory roll package workshop adopts the current cutting-edge technology in the development of Java Web.The system functions are basically complete,the interface is very friendly,the response speed is fast,and the operability is good.The need for monitoring and early warning.