区域（县市区）高中生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高中学生身高、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，不定期对所在区域每个高中学生身高、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. Through the smart physical health evaluation system of the Regional Smart Education Brain and Education Large Model Cloud Platform (referred to as Education Brain and Education Large Model) and corresponding IoT-enabled intelligent terminal devices deployed by schools, the platform irregularly measures and collects height and weight data of every high school student in the local area, and automatically calculates each student's BMI physical health index via the relevant models of the Education Brain. Students, parents, teachers and management departments can real-time view their students' BMI (physical health) indicators through the smart evaluation system (APP).
2. Provide decision-making data support for education administrators, teachers, students and parents to manage and conduct early warning of physical health development of children of different ages across all grade levels.
3. Data Application Scenarios: Provide data references and early warning prevention for health conditions including pediatric obesity, adolescent obesity, refractory obesity and weight loss.
4. Better realize the physical health evaluation for the development of the new era's Five Educations (moral, intellectual, physical, aesthetic and labor education), and provide critical data support for the construction of regional Smart Education Brain and AI education large models, as well as the implementation of personalized healthy growth for students.
(1) Data Collection: Via the smart education cloud platform system and related IoT health detection facilities, the platform irregularly measures and collects height and weight data of every high school student in the local area.
(2) Data Processing: The smart education cloud platform system conducts model-based calculations 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 for the international BMI physical health index: <18.5 is classified as underweight, 18.5–23.9 falls within the normal range, 24–26.9 is classified as 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 of physical health development of children of different ages across all grade levels.
(4) Data Application Scenarios: Provide data references for prevention and early warning of related health diseases, adolescent nutrition intake, physical development, physical health detection feedback and tracking management.

搜集汇总

数据集介绍

特点

该数据集包含595条区域高中生BMI体质健康数据，每学期更新一次，用于智慧体质健康评价和健康预警。数据涵盖学校、学生基本信息及BMI指标，通过物联网设备采集并依据国际标准计算分类。