A Study of Intelligent Stadiums: the City of Manchester Stadium

This paper provides a case study of the City of Manchester Stadium based on relevant literatures, based on a comprehensive description of multidisciplinary, cross-sectoral and future-oriented requirements and operations in the design of modern intelligent sports buildings. The successfulness of the City of Manchester Stadium gives constructive experience and knowledge for the building professions including architecture, building structure, building services, construction, and facilities management, etc. In addition, this paper is valuable for developing intelligent sports buildings in China

Local Positioning Systems in (Game) Sports

Position data of players and athletes are widely used in sports performance analysis for measuring the amounts of physical activities as well as for tactical assessments in game sports. However, positioning sensing systems are applied in sports as tools to gain objective information of sports behavior rather than as components of intelligent spaces (IS). The paper outlines the idea of IS for the sports context with special focus to game sports and how intelligent sports feedback systems can benefit from IS. Henceforth, the most common location sensing techniques used in sports and their practical application are reviewed, as location is among the most important enabling techniques for IS. Furthermore, the article exemplifies the idea of IS in sports on two applications

MAAIG: Motion Analysis And Instruction Generation

Many people engage in self-directed sports training at home but lack the real-time guidance of professional coaches, making them susceptible to injuries or the development of incorrect habits. In this paper, we propose a novel application framework called MAAIG(Motion Analysis And Instruction Generation). It can generate embedding vectors for each frame based on user-provided sports action videos. These embedding vectors are associated with the 3D skeleton of each frame and are further input into a pretrained T5 model. Ultimately, our model utilizes this information to generate specific sports instructions. It has the capability to identify potential issues and provide real-time guidance in a manner akin to professional coaches, helping users improve their sports skills and avoid injuries.Comment: Accepted to the ACM Multimedia Asia 2023 Workshop on Intelligent Sports Technologies (WIST

The Fusion and Construction Strategy of Smart Sports and Traditional Sports Teaching Mode in College and Universities

Use expert interviews, literature and other methods to summarize and analyze the pros and cons of smart sports and traditional sports, combine traditional sports with smart education, and create a more scientific and effective smart education model for colleges and universities, so as to promote the joint participation or supervision of schools, teachers, parents, and students to improve the quality of physical education, so as to achieve physical education for students and enhance the time and intensity of students’ physical fitness