设计说明书
总字数：24000+
基于单片机的教室环境智能监测与净化系统设计
摘要
随着教育信息化的持续推进与校园环境质量要求的不断提升，教室作为学生日常学习的主要场所，其环境舒适度与空气质量直接影响学生的学习效率与身体健康。温度、湿度、CO₂浓度、粉尘浓度及光照强度是评价教室环境质量的核心指标，参数失衡易导致学生注意力下降、疲劳困倦，长期处于空气质量不良或光照不足的环境中还会引发呼吸道疾病与视力问题。传统教室环境管理高度依赖人工手动调节，存在调控不及时、多设备协同性差、无法远程监管等突出问题，依靠人工经验判断的管理模式难以实现教室环境的精细化、持续化管控。本文提出一种基于STM32F103C8T6单片机与物联网云平台的教室环境智能监测与净化系统设计方案。系统集成温湿度检测、CO₂浓度检测、粉尘浓度检测、光照强度检测、自动空调调控、自动加湿除湿、自动净化、自动照明、本地人机交互、WiFi无线数据上云、自定义控制阈值、云端手机端远程管控等核心功能。通过DHT11温湿度传感器、SGP30 CO₂传感器、GP2Y10粉尘传感器、光照传感器实时采集教室温度、湿度、CO₂浓度、粉尘浓度及光照强度数据，将采集参数与用户预设控制阈值自动比对；当温度高于上限时自动开启空调制冷，低于下限时自动开启空调加热；当湿度高于上限时自动开启除湿，低于下限时自动开启加湿；当CO₂浓度或粉尘浓度超过设定上限时自动启动净化器；当光照强度低于设定下限时自动开启照明灯。系统搭载独立按键，支持各项控制阈值自定义调节及空调、加湿器、除湿器、净化器、照明灯手动控制；搭配OLED显示屏实时本地展示全部监测数据与设备运行状态；同时通过WiFi通信模块将实时监测数据同步上传至云端平台，用户可通过手机移动端随时随地查看教室环境状态，并远程修改各项控制阈值、远程控制各设备启停。本系统有效解决传统教室环境管理依赖人工、调控不及时、无法远程管控的痛点，实现教室环境全天候自动监测、多设备智能联动、云端可视化管理，大幅提升校园环境智能化管护水平，具备良好的教育配套应用价值与推广前景。
关键词： STM32单片机；教室环境监测；智能净化；CO₂浓度检测；物联网云平台
With the continuous advancement of educational informatization and the rising requirements for campus environmental quality, classrooms, as the main places for students’ daily learning, have their environmental comfort and air quality directly affecting students’ learning efficiency and physical health. Temperature, humidity, CO₂ concentration, dust concentration and light intensity are the core indicators for evaluating classroom environmental quality. Parameter imbalance can easily lead to decreased concentration and fatigue among students, and long-term exposure to poor air quality or insufficient lighting can also cause respiratory diseases and vision problems. Traditional classroom environment management relies heavily on manual adjustment, which has prominent problems such as untimely regulation, poor multi-device coordination and inability to conduct remote supervision. The management mode relying on manual experience judgment is difficult to achieve refined and continuous control of the classroom environment. This paper proposes a design scheme of an intelligent classroom environment monitoring and purification system based on STM32F103C8T6 microcontroller and IoT cloud platform. The system integrates core functions such as temperature and humidity detection, CO₂ concentration detection, dust concentration detection, light intensity detection, automatic air conditioning control, automatic humidification and dehumidification, automatic purification, automatic lighting, local human-computer interaction, WiFi wireless data uploading to cloud, customizable control thresholds, and cloud-based mobile terminal remote control. Through DHT11 temperature and humidity sensor, SGP30 CO₂ sensor, GP2Y10 dust sensor and light sensor, the system collects real-time data of classroom temperature, humidity, CO₂ concentration, dust concentration and light intensity, and automatically compares the collected parameters with the control thresholds preset by users. When the temperature is higher than the upper limit, the air conditioner cooling is automatically turned on; when it is lower than the lower limit, the air conditioner heating is automatically turned on. When the humidity is higher than the upper limit, dehumidification is automatically turned on; when it is lower than the lower limit, humidification is automatically turned on. When the CO₂ concentration or dust concentration exceeds the set upper limit, the purifier is automatically started. When the light intensity is lower than the set lower limit, the lighting lamp is automatically turned on. Equipped with independent keys, the system supports custom adjustment of various control thresholds and manual control of air conditioners, humidifiers, dehumidifiers, purifiers and lighting lamps. An OLED display screen is matched to show all monitoring data and equipment operation status locally in real time. Meanwhile, real-time monitoring data are synchronously uploaded to the cloud platform through the WiFi communication module. Users can view the classroom environment status anytime and anywhere through mobile terminals, remotely modify various control thresholds, and remotely control the start and stop of each device. This system effectively solves the pain points of traditional classroom environment management relying on manual work, untimely regulation and lack of remote control. It realizes all-weather automatic monitoring of classroom environment, intelligent linkage of multiple devices and cloud-based visual management, greatly improving the intelligent management level of campus environment, and has excellent supporting application value and promotion prospects in the education industry.
Keywords: STM32 Microcontroller; Classroom Environment Monitoring; Intelligent Purification; CO₂ Concentration Detection; IoT Cloud Platform
目 录
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