区域（县市区）小学生BMI体质健康数据

1、通过区域智慧教育大脑和教育大模型云平台（简称教育大脑、教育大模型）智慧体质健康评价系统和学校部署的相应物联网环境智能终端设备，不定期对所在区域每个小学生身高、体重数据进行测量和统计，并通过教育大脑相关模型自动计算出每个学生的BMI体质健康指标，学生、家长、教师和管理部门可以通过智慧评价系统（APP）实时查看学生的BMI（体质健康）指标情况。2、为教育管理人员和师生家长管理和预警各年级段不同年龄阶段孩子的体质健康发展情况提供决策数据支撑。3、数据应用场景：对小儿肥胖症、青春期肥胖、顽固性肥胖、体重减轻等健康状况提出数据参考和预警预防。4、更好实现新时代教育德智体美劳新型五育发展的身体和体质健康评价，为建设区域教育大脑和人工智能教育大模型，实施个性化健康成长提供重要的数据支撑。（1）数据采集：通过智慧教育云平台系统和相关的物联网健康检测设施，不定期对区域每个小学生身高、体重数据进行测量和统计。（2）数据处理：智慧教育云平台系统将采集到的身高、体重数据进行模型计算【模型核心公式：体质指数（BMI）=体重（kg）÷身高^2（m）】。（3）根据国际BMI体质健康指数的亚洲统计分类标准：<18.5为体重过低，18.5～23.9为正常范围，24～26.9为过重或肥胖前期，27～29.9为Ⅰ度肥胖，≥30为Ⅱ肥胖，≥40.0为Ⅲ肥胖。（4）为教育管理人员和师生家长管理和预警各年级段不同年龄阶段孩子的体质健康发展情况提供决策数据支撑。（4）数据应用场景：相关健康疾病的预防预警数据参考，青少年营养摄入、身体发育、体质健康检测反馈、跟踪管理等。

1. Via the Smart Physical Health Evaluation System of the Regional Smart Education Brain and Educational Large Model Cloud Platform (referred to as Education Brain and Educational Large Model for short) and the corresponding IoT intelligent terminal devices deployed by schools, height and weight data of every primary school student in the region are measured and counted irregularly. The relevant models of the Education Brain will automatically calculate the BMI (Body Mass Index) physical health index for each student. Students, parents, teachers and management departments can view their students' BMI (physical health) indicators in real time through the smart evaluation system (APP).
2. This dataset provides decision-making data support for education administrators, teachers, students and parents to manage and conduct early warning on the physical health development of children of different ages in each grade.
3. Data application scenarios: Provide data references and early warning prevention for health conditions such as childhood obesity, adolescent obesity, refractory obesity and weight loss.
4. It better realizes the physical fitness and health evaluation for the development of the new "Five Educations" (moral, intellectual, physical, aesthetic and labor education) in education in the new era, and provides important data support for the construction of regional education brains and artificial intelligence educational large models, as well as the implementation of personalized healthy growth.
(1) Data Collection: Height and weight data of every primary school student in the region are measured and counted irregularly via the smart education cloud platform system and relevant IoT health detection facilities.
(2) Data Processing: The smart education cloud platform system performs model calculation on the collected height and weight data [Core model formula: Body Mass Index (BMI) = Weight (kg) ÷ Height² (m)].
(3) According to the Asian statistical classification standard of the international BMI physical health index: <18.5 is underweight, 18.5–23.9 is the normal range, 24–26.9 is overweight or pre-obesity, 27–29.9 is Grade I obesity, ≥30 is Grade II obesity, and ≥40.0 is Grade III obesity.
(4) Provide decision-making data support for education administrators, teachers, students and parents to manage and conduct early warning on the physical health development of children of different ages in each grade.
(4) Data application scenarios: Provide data references for prevention and early warning of relevant health diseases, adolescent nutrition intake, physical development, physical health detection feedback, tracking management, etc.

搜集汇总

数据集介绍

特点

该数据集包含2795条区域（县市区）小学生的BMI体质健康数据，每学期更新一次。数据通过智慧教育云平台和物联网设备采集，涵盖学生基本信息及BMI指数，主要用于智慧体质健康评价、教育管理和健康预警等场景。