Design And Implementation Of Io T Training System Based On Front-end And Back-end Separation

In recent years,the Internet of Things industry in China has developed rapidly.It is expected that during the 14 th Five-Year Plan period,the development of the IoT industry in China will be further upgraded,which will bring greater demand for the cultivation of IoT talents.The traditional IoT training method is relatively fixed,which mainly consists of classroom explanation and practical operation of fixed training box.In order to achieve better IoT training effects,embedded development programs based on different software and hardware platforms have emerged in recent years.The IoT training system is mainly realized through the C/S architecture.However,due to the closeness of the system,the training scene is usually single,and there is a lack of reusable training project development scheme,which is not conducive to the expansion of the training scene.At the same time,the system has problems such as high coupling,complex development,and poor maintainability.In order to solve the above problems,this thesis proposes a hierarchical software architecture of the training system based on the analysis of the software architecture of the IoT,and designs a front-end and back-end separation of the training system,so as to reduce the coupling between the system modules.The system is developed based on unified programming language,and the front and back end are deployed independently,which reduces the implementation complexity of the training system.Based on the actual needs of the training system,the thesis divides the structure and business functions of the system,and realizes the back-end service layer and front-end application layer.The main work is as follows:(1)The back-end service layer is built based on Node.js.Firstly,the edge service module is designed to realize the access and extension of different sensor devices and solve the heterogeneity problem of the sensing layer.Secondly,the platform service layer is designed to achieve a unified rest style interface through the express server framework,so as to shield the heterogeneity of the system interface and enhance the scalability of the training system.The back-end service layer can flexibly open the interface of IoT devices,so as to meet the needs of advanced practical training of IoT and solve the single content problem of traditional practical training system.(2)This thesis builds the front-end application layer based on the MVVM framework Vue,and proposes a component-based reusable development plan,which realizes the rapid development of basic training,smart home,industrial production and other multi-scene training applications through component reuse,effectively reducing training Complexity of application development,and support for later training function expansion.In order to overcome the disadvantages of single interaction mode and poor intuitiveness of traditional practical training system,the visual practical training business components were realized by Raphael,which provided diversified and interactive friendly basic practical training interface for trainees and improved the teaching experience of practical training of IoT.(3)In order to further improve the practical application experience,this thesis proposes a front-end rendering performance optimization method based on IOT components.The experimental results show that the optimized page component can reduce the rendering time by more than 30%,and the more component data,the greater the performance improvement,which can effectively reduce the device rendering pressure of the user end of the training system and meet the multi terminal deployment requirements of the system.(4)Finally,the system verification work is performed to test the system's business functions,compatibility,interface performance,and rendering performance.The test results meet the expected indicators and the system meets the initial design goals and requirements.