Abstract: The global imperative to mitigate food waste and foster sustainable practices has led to the development of innovative solutions, among which the integration of deep learning techniques in an online fruits and vegetables recycling and reuse system stands as a promising approach. This paper outlines the conceptualization and implementation of an intelligent system leveraging deep learning to revolutionize the management of surplus or aesthetically imperfect fruits and vegetables The system's foundation rests upon a robust deep learning model trained to accurately assess and categorize the quality of fruits and vegetables based on visual attributes. Utilizing convolutional neural networks, the model can identify and classify produced items, distinguishing between those suitable for consumption, redistribution, or recycling based on Grade A, B, C. Through a user-friendly online platform, consumers, retailers, and farmers can seamlessly upload images of surplus or imperfect produce. The deep learning model swiftly evaluates the condition of these items, providing real-time assessments and recommendations.

Keywords: CNN, Machine Learning, Deep Learning, Visual Attribute.

Cite:
P. Neelima, K. Sahithi, B. Anusha, B. Lalitha,"Online Fruits and Vegetables Recycling and Reuse System ", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 11, no. 3, 2024, Crossref https://doi.org/10.17148/IARJSET.2024.11338.

| DOI: 10.17148/IARJSET.2024.11338