Authors - A. Aruna Kumari, Tamminana Visweswari, Sri Vishnu Prabhu Gudavalli Abstract - Globally, food waste accounts for almost one-third of total food production, which is approximately 1.3 billion tons annually. Some of the most wasted foodstuffs at the consumer level include fruits, vegetables and bread. This proposed work will help to solve this financial and environmental issue by creating an intelligent system to eliminate vegetable waste with the help of MobileNetV2 which is a Convolutional Neural Networks (CNN) based model to classify the freshness of vegetables and use object detection model called as YOLOv8n to recognize types of vegetables. It begins with the user uploading images of vegetables, which are pre-processed with the help of normalization and data augmentation. The MobileNetV2 model categorizes fresh and spoiled produce with accuracy rates of 95 percent, which is expected of a Freshness classifier. In the meantime, the YOLOv8n finder detects the specific type of vegetable with the help of a mAP50 of 0.934 to recommend the specific vegetable. If the vegetable is spoilt, it will provide instructions on how to compost and if it is fresh, it provides zero waste recipes. The entire system shall be made easily accessible in a web application that has Flask back-ends.
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