Plant Health Monitor Project with AI

• newEditor

Plant Health Monitor Project with AI

By: Hala Alaa Aldin Zaidan 11H

What do you already know about using AI in plant health monitoring?

Learning Objective

At the end of the lesson you will understand how to design a plant health monitoring system using CNN AI, ESP32-CAM, and sensors, and explain how STEM concepts are integrated into this project.

Project Overview

The plant health monitor project uses AI (Convolutional Neural Networks) to detect and diagnose plant health. This solution automates monitoring and ensures healthy growth.

STEM Integration

This project merges Science (biology of plants), Technology (use of AI and sensors), Engineering (system design), and Mathematics (data analysis) for a comprehensive learning experience.

Key Hardware Components

The main hardware includes the ESP32-CAM microcontroller for image capturing, and various sensors for measuring soil moisture, temperature, and light intensity.

System Workflow

Sensors collect environmental data and the ESP32-CAM captures plant images. Data is analysed by the CNN model to predict plant health and send alerts if issues are detected.

Advantages of the System

Benefits

Useful in greenhouses, farms, research labs, and educational projects.

Applications

Early detection of plant diseases, reduced labour, increased crop yield, and real-time monitoring.

Reflection

Think about how AI can be combined with sensors and microcontrollers to solve real-world environmental problems like plant health.

Write down 3 things you learned in this lesson.

Write down 2 things you want to know more about.

Ask 1 question about something you haven't quite understood yet.