Smart Irrigation System For Rice Farming

This dataset can be used to present several key innovations in the development of an AI-IoT-based Smart Drip Irrigation System (SDIS) specifically designed for rice plants by considering local agronomic characteristics. First, this system integrates four key input parameters to ensure precision and adaptability in irrigation management: (1) rice plant growth phase, which determines the adjustment of the dose, irrigation frequency; (2) soil moisture, as the main indicator to activate irrigation only when the soil water content is below the optimal threshold; (3) Light Intensity; (4) air temperature and (5) and air humidity (measured using a DHT22 sensor), which plays a role in mitigating plant stress due to extreme microclimate conditions.

本数据集可用于展示专为水稻作物开发、兼顾当地农艺特性的基于人工智能-物联网（AI-IoT）的智能滴灌系统（Smart Drip Irrigation System, SDIS）研发过程中的多项关键创新成果。
首先，该系统集成了四项关键输入参数，以保障灌溉管理的精准性与适配性：
1. 水稻生育期：用于调整灌水量与灌溉频率；
2. 土壤湿度：作为核心触发指标，仅当土壤含水量低于最优阈值时才启动灌溉；
3. 光照强度（Light Intensity）；
4. 气温与空气湿度（Air Temperature and Air Humidity，通过DHT22传感器采集）：用于缓解极端微气候条件下作物所受的胁迫。