• Mrs Ramya KR
• Sarika S
• Shree Harshitha S
• Surya RV
• Tirumala Ganesh Bharadwaj Sharma

The project “AI-Based Differentiation of Fertilized and Organic Fruits” aims to identify whether a fruit is organic or chemically fertilized using AI and image processing techniques. A camera module captures fruit images, which are analyzed through machine learning algorithms for color, texture, and shape features. When image-based detection is uncertain, a pH sensor measures the fruit’s acidity level for accurate classification. The system is implemented on a Raspberry Pi for real-time analysis. This project promotes healthy consumption and sustainable farming practices through smart automation.

This project involves the use of Artificial Intelligence (AI) for accurate fruit classification. It applies Image Processing techniques to analyze visual features of fruits. A pH Sensor is integrated to determine chemical characteristics and support differentiation. The system classifies fruits as organic or fertilized based on combined visual and chemical data. Implementation is done using a Raspberry Pi for real-time detection and analysis.

"AI-BASED DIFFERENTIATION OF FERTILIZED AND ORGANIC FRUITS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.c235-c241, December-2025, Available :http://www.jetir.org/papers/JETIR2512228.pdf

"AI-BASED DIFFERENTIATION OF FERTILIZED AND ORGANIC FRUITS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppc235-c241, December-2025, Available at : http://www.jetir.org/papers/JETIR2512228.pdf