LIU Xinran,ZENG Jiahong,LUO Sen,et al.Design and Development of Intelligent Twin Classroom System[J].Journal of Chengdu University of Information Technology,2024,39(06):665-675.[doi:10.16836/j.cnki.jcuit.2024.06.004]
智慧化孪生教室系统设计与开发
- Title:
- Design and Development of Intelligent Twin Classroom System
- 文章编号:
- 2096-1618(2024)06-0665-11
- Keywords:
- smart classroom; digital twin; deep learning; smart campus
- 分类号:
- TP399
- 文献标志码:
- A
- 摘要:
- 智慧教室作为智慧校园建设的重要环节,为教学信息化、数字化、智能化提供重要支撑。目前智慧教室建设过程中存在教室智能化程度低、获取教室环境信息不及时、教学资源利用不足等问题。因此设计开发了一套智慧化孪生教室原型系统,旨在高效提高教室环境监控和智能化监管能力。系统综合采用数字孪生、深度学习、传感器检测等技术,设计并实现了数据检测模块、智能计算模块、可视化模块3个功能模块。数据检测模块通过摄像头和传感器采集课堂环境信息,并通过UDP和TCP通讯协议将数据传输到计算机,供智能计算模块使用。智能计算模块主要使用YOLOv5算法对摄像头实时视频进行检测并智能计算,识别学生性别、统计人数、检测位置等功能。最后通过构建教室的孪生模型,并与物理教室进行数字映射,实现数据的可视化显示。结果表明,系统可以实时检测教室温湿度、识别学生人数、性别比例和位置信息,并可将检测到的数据实时可视化展示。整个系统的延迟在1 s以内,帧率在30 FPS左右,能满足智慧教室的应用需求,能用于教师实时管理课堂、合理利用课堂资源、提高课堂的智慧化程度,为智慧校园提供技术支撑,对推进智慧校园建设具有积极意义。
- Abstract:
- As an important part of the construction of a smart campus, smart classrooms provide important support for teaching informatization, digitalization, and intelligence. At present, in the process of building smart classrooms, there are problems such as low degree of classroom intelligence, untimely access to classroom environmental information, and insufficient utilization of teaching resources. Therefore, this paper designs and develops a prototype system of intelligent twin classrooms, aiming to efficiently improve the classroom environment monitoring and intelligent supervision capabilities. The system comprehensively adopts digital twin, deep learning, sensor detection, and other technologies, and designs and realizes three functional modules:data detection module, intelligent computing module, and visualization module. The data detection module collects classroom environment information through cameras and sensors and transmits data to the computer through UDP and TCP communication protocols for use by the intelligent computing module. The intelligent computing module mainly uses the YOLOv5 algorithm to detect the real-time video of the camera and intelligently calculate, identify the gender of students, count the number of people, detect the location, and other functions. Finally, by building a twin model of the classroom and digitally mapping it with the physical classroom, the data is visualized and displayed. The final results show that the system can detect classroom temperature and humidity in real-time, identify the number of students, gender ratio and location information, and visualize the detected data in real-time. The delay of the whole system is less than 1 s, and the frame rate is about 30 FPS, which can meet the application requirements of smart classrooms, and can be used for teachers to manage classrooms in real time, rationally use classroom resources, and improve the degree of intelligence of classrooms. So as to provide technical support for smart campus, which is of positive significance to promote the construction of smart campus.
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备注/Memo
收稿日期:2023-08-07
项目基金:四川省自然科学基金资助项目(2022NSFSC0934); 四川省科技计划资助(2023YFG0122)
通信作者:罗德宁.E-mail:loening@foxmail.com