Plant growth monitoring using image processing with automatic irrigation system

Author

Mhosva, Omega

Title

Plant growth monitoring using image processing with automatic irrigation system

Abstract

As global food demands rise, the agricultural sector requires advanced technologies to improve productivity and resource efficiency. Traditional methods of plant monitoring and irrigation are often labor-intensive, time-consuming, and prone to human error. This project presents the design and implementation of an intelligent plant growth monitoring and automated irrigation system that leverages image processing and Internet of Things (IoT) technologies. The system aims to remotely monitor plant health and optimize water usage by creating a closed-loop solution for smart farming.
The hardware architecture integrates an ESP32-CAM for computer vision tasks—analyzing leaf color, size, and density to detect health status—and an ESP32 NodeMCU/ESP8266 controller to manage sensor data. Ultrasonic and infrared sensors are employed to measure plant height and leaf spread, while a soil moisture sensor regulates the automated irrigation system, activating a submersible pump when moisture levels drop below 40%. Real-time status updates and alerts are transmitted to the user via a GSM module and displayed locally on an LCD, with captured images stored in a cloud-integrated database for further analysis. Experimental results demonstrate the system's capability to successfully monitor growth parameters, detect moisture deficiencies, and automate irrigation, offering a sustainable and efficient alternative to manual agricultural practices.

Date

June 2024

Publisher

BUSE

Keywords

Plant Growth Monitoring

Image Processing

Automatic Irrigation System

Smart Agriculture

Supervisor

Not Specified