Abstract: The ability to identify fruits based on their quality is increasingly important in the modern food industry, as consumers are more health conscious and demand high-quality produce. This study presents an automated fruit quality inspection system for banana, orange, and apple, leveraging Python-based image analysis and deep learning techniques. The system extracts key features related to color, texture, and shape, which are used to assess fruit quality accurately. A Convolutional Neural Network (CNN) [1] is trained and optimized in Google Colab using TensorFlow and subsequently converted to TensorFlow Lite for real-time deployment on mobile devices.