设计说明书
总字数：14000+
摘要
随着骑行运动的普及与城市通勤需求的增长，传统骑行头盔仅能提供基础物理防护，难以应对复杂环境下的安全挑战。本设计聚焦基于 STM32F103C8T6 单片机的智能骑车头盔系统，通过多传感器融合与智能控制技术，构建集环境适应、运动监测、生理预警、应急救援于一体的综合防护方案。硬件上，集成 MPU6050 运动传感器实现转向、刹车动作识别与摔倒判定，光敏电阻自适应控制照明灯，MLX90614 与 MAX30102 分别监测体温与心率，GPS+GSM 模块保障应急定位通信，OLED 显示屏实时呈现数据。软件上，开发运动状态识别算法（准确率达 96%）、生理参数异常判断逻辑及分级应急响应机制，支持按键阈值设置与整点报时功能。系统经测试验证，光照响应时间≤0.5 秒，摔倒判定误报率＜3%，应急短信发送成功率 100%，有效解决传统头盔夜间可视性差、生理状态监测缺失、摔倒后救援延迟等问题，为骑行安全提供全场景智能化保障，具有显著的实用价值与推广前景。
关键词：智能头盔；运动识别；生理监测；摔倒报警；STM32 单片机
ABSTRACT
With the continuous improvement of modern living standards, traditional shoe cabinets face persistent problems such as moisture-induced mold, odor accumulation, and bacterial growth, which have become critical concerns for household health management. This project focuses on the development of an intelligent drying shoe cabinet system, aiming to provide a comprehensive smart storage solution through the synergy of hardware and software innovations.Hardware Design:The system employs a DHT11 humidity sensor for real-time monitoring of internal cabinet humidity, automatically activating PTC heating elements and silent fans for rapid dehumidification when thresholds are exceeded. An MQ-135 ammonia sensor precisely detects odor concentrations, triggering dual-action purification via UV sterilization lamps and activated carbon fans. An infrared obstacle avoidance module enables automatic door opening upon human approach, with a servo motor ensuring smooth cabinet door operation. An OLED display provides real-time visualization of key parameters including humidity and ammonia levels, offering an intuitive user interface.Software Design:Powered by the STM32F103C8T6 microcontroller, the system implements intelligent control logic with real-time environmental parameter monitoring, threshold-based decision making, and device coordination. The RTC module supports scheduled operation intervals with automatic energy-saving during off-hours. WiFi connectivity enables remote monitoring via a mobile application, allowing users to adjust thresholds and manually activate dehumidification/odor removal functions from anywhere.Performance Verification:Physical testing confirms the system achieves 60% improved dehumidification efficiency, 99% sterilization rate, and over 90% odor elimination. These results effectively address traditional shoe cabinet challenges while providing households with an intelligent, health-focused storage solution. The system demonstrates significant market potential and broad application prospects for modern smart home environments.
Keywords: Intelligent shoe cabinet; humidity monitoring; ammonia purification; UV sterilization; human presence detection; remote control
目录
第1章 绪论
1.1 研究背景与意义
1.2 国内外研究现状
1.3 本文主要研究内容
第2章 设计思路与方案论证
2.1 主要元器件选择
2.1.1 主控芯片方案选择
2.1.2 运动状态检测方案
2.1.3 心率检测模块方案选择
2.1.4 定位与通信方案
2.1.5 体温检测模块方案选择
2.1.6 显示与交互方案
2.2整体设计方案
第3章 硬件设计
3.1 主控电路模块
3.2 光照检测模块
3.3 姿态检测模块（MPU6050）
3.4 体温检测模块（MLX90614）
3.5 心率检测模块（MAX30102）
3.6 RTC 模块
3.7 GPS + 北斗定位模块
3.8 按键与显示模块
3.9 OLED 显示模块
第4章 系统程序设计
4.1 编程软件介绍
4.2 系统主流程设计
4.3 独立按键
4.4 温湿度检测模块子流程
4.5 A/D模数转换子流程
4.6 定时器模块子流程
4.7 蓝牙模块子流程
4.8 LCD1602液晶显示子流程
第五章 实物测试
5.1 整体实物测试
5.2 光照检测与照明系统测试
5.3 姿态检测与提示系统测试
5.4 体温与心率监测系统测试
5.5 时间与定位系统测试
5.7 总结
第6章 总结与展望
一、总结
二、展望
致谢
参考文献
附录
附录一：原理图
附录二：PCB
附录三：主程序
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