Prediction of Quality and Lifetime of Fruit using Deep Learning

This proposed system focuses on developing a predictive model "Prediction of Quality and Lifetime of Fruits Using Deep Learning" is to create a reliable system for predicting fruit shelf life and evaluating fruit quality in real time. The system examines fruit photos to determine surface flaws, maturity levels, and general quality using Deep Learning-based object detection. It predicts how long fruits will last on the shelf by taking into account environmental factors like temperature and humidity. A Deep Learning model is trained using the preprocessed dataset, which comes from Roboflow, to ensure precise detection and classification. By decreasing fruit waste and empowering farmers, distributors, and retailers to make well-informed decisions, this technology aims to maximize supply chain management. In order to improve food quality monitoring and guarantee efficiency, sustainability in the agricultural industry. The suggested solution integrates computer vision and Deep Learning algorithms. The proposed work performs better when compared with the existing algorithms.