摘要
面向高校学生画像的建设需求,物联网技术作为主要数据支撑手段,急需构建系统化的采集与处理体系。围绕学生行为数据在高校场景下的采集与离线处理,设计多源感知设备的部署方案,建立边缘计算与平台接入的联动机制。在此基础上,提出一套面向学生画像的数据清洗、融合及匿名化处理流程。通过画像聚类建模与标签分类机制,抽取与呈现学生多维特征。结果表明,本系统具备较强的适应性与稳定性,能够为高校学生精准画像提供可靠的数据支撑与技术路径。
In response to the construction needs of college student portraits,Internet of Things technology,as the main data support method,urgently needs to build a systematic collection and processing system.This paper focuses on the collection and offline processing of student behavior data in the university scene,designs the deployment scheme of multi-source sensing devices,and establishes the linkage mechanism between edge computing and platform access.On this basis,a data cleaning,fusion,and anonymization process for student portraits is proposed.By using portrait clustering modeling and label classification mechanism,effective extraction and presentation of multidimensional features of students can be achieved.The results indicate that this system has strong adaptability and stability,and can provide reliable data support and technical paths for accurate profiling of college students.
作者
谢鸿稳
张春燕
韦思飞
杨向前
XIE Hongwen;ZHANG Chunyan;WEI Sifei;YANG Xiangqian(Baise Vocational College,Baise,Guangxi 533000,China)
出处
《智能物联技术》
2025年第4期42-45,共4页
Technology of Io T& AI
基金
2024年度广西高校中青年教师科研基础能力提升项目(2024KY1542)。
关键词
高校学生画像
物联网
数据采集
离线处理
建模验证
portrait of college students
Internet of Things
data collection
offline processing
modeling validation
