An Intelligence Donation System using CNN and KNN | ||||
| Journal of the ACS Advances in Computer Science | ||||
| Volume 16, Issue 1, 2025 PDF (641.5 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/asc.2025.367249.1035 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Tarek Salah Sobh 1; Alaa Hassan2
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| 1The Higher Institute of Computer and Information Technology, El Shorouk Academy, , Cairo, Egypt | ||||
| 2Higher Institute of Computers and Information Technology, Computer Depart., El. Shorouk Academy, Cairo, Egypt | ||||
| Abstract | ||||
| The growing concern over clothing waste and its environmental impact has motivated the development of reliable solutions for managing donation surplus garments. This work plays an important role to ensure a constant supply of clothes without waste. In addition, it supports both donor and donation warehouse by applying intelligent techniques. This paper introduces a smart clothing donation system leveraging Artificial Intelligence (AI). The system facilitates efficient collection, classification, and distribution of donated clothes. Utilizing Convolutional Neural Networks (CNN) for image-based classification achieving an accuracy of 92%, and K-Nearest Neighbors (KNN) for text-based classification with an accuracy of 93%, the system ensures accurate sorting of clothing items. The proposed approach aims to reduce textile waste while enhancing accessibility to clothing for underprivileged communities. Experimental results demonstrate the system's efficiency, achieving high accuracy in classification and significant reductions in processing time. This AI-driven solution represents a significant step forward in promoting sustainable clothing donation practices worldwide. | ||||
| Keywords | ||||
| Convolutional Neural Networks (CNN); K-Nearest Neighbors (KNN); clothes quality assurance | ||||
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