Design And Implementation Of A Server-side Of A Low-code Development Platform For Competitive Sports Training

Amid the development of the sports powerhouse strategy and digital innovation,precision and scientific training have become inevitable trends for competitive sports.The use of traditional software development methods in the sports professional field faces the problem of large development costs and long lead time due to large gaps in interdisciplinary expertise.In recent years,the development of low-code application development technology has developed rapidly,which has greatly reduced the development threshold of software applications.This paper combines low-code application development technology with the training and management work of competitive sports teams to propose a low-code training platform for competitive sports,focusing on its server-side design and implementation.The platform integrates the advantages of traditional digital platform and low-code application development technology,which enables applications to be developed by sports professionals without computer expertise,which breaks the knowledge barrier of professional fields.It also provides location-based athlete track prediction function based on an excellent pedestrian track prediction model.Combined with data visualization technology,it provides coaches,team doctors and other team members for data analysis,thus enhancing the effectiveness,accuracy and science of decision making.In this paper,following the development process and principles of software engineering,we designed the concepts,data structures,storage schema,and interaction logic for a customizable application and implemented the server-side system of the platform.The paper firstly compares various technical solutions of the system and completes the requirement analysis based on the communication with domestic highlevel sports teams,and then carries out the high-level design of the system based on this,which includes the system architecture design,functional module division and data storage schema design.The entire system uses Node.js as the server-side development language,semi-structured data for data description and storage,and the customizable application is the core of it.The low-level design section describes the internal module interaction logic of the system’s key functions in detail using timing diagrams and analyzes the athlete trajectory prediction method using NBA datasets for training and validation,demonstrating its effectiveness.In addition,we finally performed functional and non-functional tests on the system for software quality assurance.All the development and testing of this system has been completed,and we have built a complete sports team customizable application delivered to Beijing Sports University for testing.The platform is running stably,with positive user feedback and good application value and prospects.