设计说明书
总字数：24000+
基于STM32的智能绿植种植系统设计
摘要
传统绿植人工种植养护模式存在环境参数监测单一、水肥光照调控滞后、养护标准同质化、适配绿植生长阶段性差等问题，人工管护方式难以精准匹配绿植不同生长周期的环境需求，极易出现灌溉不当、光照不足、生长环境失衡等情况，导致绿植存活率低、生长状态不佳，无法实现绿植养护的智能化、精细化、全天候管控。本文提出一种基于STM32F103C8T6单片机与物联网技术的智能绿植种植系统设计方案。系统集成多环境参数采集、智能水肥灌溉、自动光照补光、水位监测预警、生长期模式切换、本地数据显示、无线数据传输与移动端远程控制等核心功能。通过DHT11温湿度传感器、YL69土壤湿度检测模块、5516光照检测模块、SGP30气体检测模块、YW-J水位监测模块，实时采集绿植生长环境的温湿度、土壤湿度、光照强度、CO₂浓度以及水箱水位数据。系统可根据绿植生长需求预设参数阈值，当土壤湿度低于设定最小值时，系统结合水箱水位状态智能启停灌溉功能，水位达标时自动开启灌溉，直至土壤湿度达到上限阈值后关闭灌溉；当环境光照强度低于设定最小值时，自动启动补光设备，保障绿植光照供给。系统支持通过本地按键切换育苗期、生长期、结果期三种绿植生长模式，不同生长期匹配对应的土壤湿度与光照强度标准，实现分阶段精准养护。搭载的OLED显示屏可实时本地展示各项环境监测数据与绿植当前生长阶段；同时通过ESP8266 WiFi模块将全部监测数据实时上传至手机移动端，移动端可远程设置绿植生长周期，还支持手动操控灌溉与补光设备开关。当监测到水箱水位低于最小阈值时，手机端自动弹窗震动预警，提醒用户及时补水。本系统有效解决了传统绿植人工养护粗放化、调控不及时、适配性差等痛点，实现绿植生长环境多参数实时监测、分生长阶段智能调控、异常状态主动预警与移动端远程管控，大幅提升绿植种植养护的智能化与精细化水平，适用于家庭、室内园艺等多种绿植种植场景，具备较高的实用价值与推广前景。
关键词：STM32单片机；智能绿植种植；环境参数监测；智能调控；物联网远程控制
The traditional manual maintenance mode of green plant planting has problems such as single environmental parameter monitoring, lagging water, fertilizer and light regulation, homogenized maintenance standards, and poor adaptability to plant growth stages. Manual maintenance cannot accurately match the environmental needs of green plants in different growth cycles, which is prone to improper irrigation, insufficient light and unbalanced growth environment, resulting in low survival rate and poor growth state of green plants, and failing to realize intelligent, refined and all-weather management of green plant maintenance. This paper proposes a design scheme of an intelligent green plant planting system based on STM32F103C8T6 single-chip microcomputer and Internet of Things technology. The system integrates core functions such as multi-environment parameter collection, intelligent water and fertilizer irrigation, automatic light supplement, water level monitoring and early warning, growth period mode switching, local data display, wireless data transmission and mobile terminal remote control. DHT11 temperature and humidity sensor, YL69 soil humidity detection module, 5516 light intensity detection module, SGP30 gas detection module and YW-J water level monitoring module are adopted to real-timely collect the temperature and humidity of the green plant growth environment, soil humidity, light intensity, CO₂ concentration and water tank water level data. The system can preset parameter thresholds according to the growth needs of green plants. When the soil humidity is lower than the set minimum value, the system intelligently starts and stops the irrigation function combined with the water tank water level state. When the water level reaches the standard, irrigation is automatically turned on, and the irrigation is turned off until the soil humidity reaches the upper limit threshold. When the ambient light intensity is lower than the set minimum value, the light supplement equipment is automatically started to ensure the light supply for green plants. The system supports switching three green plant growth modes including seedling stage, growth stage and fruiting stage through local keys, and different growth stages are matched with corresponding soil humidity and light intensity standards to realize accurate phased maintenance. The equipped OLED display screen can locally display all environmental monitoring data and the current growth stage of green plants in real time. Meanwhile, all monitoring data are real-timely uploaded to the mobile terminal through the ESP8266 WiFi module. The mobile terminal can remotely set the growth cycle of green plants and support manual control of the switches of irrigation and light supplement equipment. When the water tank water level is monitored to be lower than the minimum threshold, the mobile terminal will automatically pop up a window and vibrate for early warning to remind users to replenish water in time. This system effectively solves the pain points of extensive traditional manual maintenance of green plants, untimely regulation and poor adaptability. It realizes real-time monitoring of multiple parameters of the green plant growth environment, intelligent regulation by growth stage, active early warning of abnormal states and remote management and control via mobile terminals, which greatly improves the intelligence and refinement of green plant planting and maintenance. It is suitable for a variety of green plant planting scenarios such as families and indoor gardening, and has high practical value and promotion prospects.
Keywords: STM32 Microcontroller; Intelligent Green Plant Planting; Environmental Parameter Monitoring; Intelligent Regulation; IoT Remote Control
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