Automatic Hydroponic Farming System with Image Processing based on Nutrients System

Automatic Hydroponic Farming System with Image Processing based on Nutrients System

Porf.P.A.Khade*1, Rutuja Shinde*2, Pranav Sirsat *3, Gauri Yadav*4

*2,3,4, Student, Zeal College Of Engineering And Research Narhe, Pune, India.

*1 Faculty of Zeal College Of Engineering And Research Narhe, Pune, India

ABSTRACT
This project introduces an advanced automated hydroponic farming system that integrates image processing and precise nutrient management to support optimized plant growth. In hydroponics, plants grow without soil, relying instead on a nutrient-rich water solution. The core of the system involves real-time image analysis to assess plant health and detect nutrient deficiencies. Using computer vision image processing techniques, images of the plants are analyzed to identify key indicators of health, including leaf colour, size, shape, and texture. Based on these assessments, the system can send alerts messages to user and can automatically adjust the concentration of nutrients in the solution to maintain optimal plant health. Additionally, it monitors and automatically adjusts other crucial parameters like pH level, temperature and humidity, and light intensity, which are essential for nutrient uptake and overall growth.

Keywords- Raspberry Pi, Hydroponics, Automated system, Mobile Application, Sensors