Smart Irrigation System with Remote Plant Health Analysis

Abstract

We focus on developing an Automatic Plant Watering System using Arduino and ESP32 to enhance plant care through automated irrigation and predictive health analysis. The system integrates a soil moisture sensor to monitor moisture levels continuously and activate a water pump when the soil moisture drops below a specified threshold, ensuring optimal watering. In addition to automated irrigation, the system assesses plant health by analyzing environmental parameters such as temperature, humidity, and soil moisture levels. These data are collected in real-time, stored in the cloud, and processed to predict the plant's health status. The real-time data and health predictions are displayed on the Blynk app or website, providing users with a convenient way to monitor their plants remotely. By leveraging IoT technologies, cloud storage, and predictive analytics, this system aims to minimize human intervention, improve plant health management, and offer a sustainable solution for plant care.