Design And Implementation Of APP Version Upgrade Monitoring System Based On Image Semantic Segmentation

Competitive product analysis is a common means of product design and operation,which means to analyze the existing or potential competitive products in the current market,mainly focusing on product positioning,business distribution,development process,market performance and other aspects,find out product differences through competitive product analysis,and dig out effective information to provide an important basis for enterprises to make scientific and correct decisions.Currently,APP monitoring platforms on the market,such as Qimai data and airy data,can only analyze the download index,search index,Download volume and other indicators of app,but can't collect and analyze the interface data of app.Therefore,a more comprehensive competitive monitoring system is needed to monitor the indicators of competitive products from multiple perspectives,which is conducive to a more comprehensive competitive analysis.Based on the actual needs of the enterprise,this paper designs and implements the app upgrade intelligent monitoring system.It provides efficient and convenient on-line high daily life app interface upgrading and core index monitoring services for enterprise product design and operation personnel.Compared with the traditional competitive product analysis method,the app upgrade intelligent monitoring system in this paper has the following advantages:(1)More functions.It can not only monitor the competitive products from the data,but also from the interface of competitive products,making the analysis more comprehensive.(2)It can remind users of the updated information of competitive products in time.The system provides upgrade alarm service,users can see the upgrade information of competitive products in time.(3)Improve the efficiency of product design and operation personnel.When there are many monitoring applications,the traditional competitive product monitoring means will consume a lot of time and manpower.After the app upgrades the intelligent monitoring system,only the user needs to operate as required,and each user can monitor multiple applications,greatly improving the product design efficiency.This paper firstly introduces the current research status at home and abroad,and then introduces the technical principles involved in the system development process in detail,including web crawler technology,Flask framework,Mongo DB database,and Vue framework.Then the requirements of the system are analyzed in depth,and the way of combining the core functions of each module with the UML diagram is introduced.Finally,functional and non-functional tests were carried out on the system,and the test results reached the expectation of the requirements.At the same time,the project also combines the semantic segmentation algorithm based on deep learning,which greatly improves the system's indicators such as alarm accuracy and recall rate.The system has been tried in baidu,greatly improving the efficiency of operation and product design staff.