AI-Based Differentiation of Fertilized and Organic Fruits

Abstract: The project "AI-Based Differentiation of Fertilized and Organic Fruits" aims to develop an intelligent system for classifying fruits based on their cultivation methods. Traditional methods of distinguishing organic and fertilized fruits are time-consuming, expensive, and often inaccurate. This project leverages artificial intelligence (AI), image processing, and pH sensor technology to automate the classification process. A machine learning model will analyze fruit images and pH values to determine whether a fruit is organically grown or chemically fertilized. The system will be implemented on a Raspberry Pi, enabling real-time processing and portability. Additionally, a mobile application will be developed to allow users to scan and check fruit quality instantly. This solution aims to enhance transparency in the food industry, assist consumers in making informed choices, and promote organic farming. By providing a cost-effective, efficient, and user-friendly tool, the project addresses the growing need for reliable fruit classification methods.

Keywords: AI-Based Classification, Image Processing, pH Sensor, Raspberry Pi, Organic Fruits, Fertilized Fruits, Real-Time Processing, Mobile Application.