Abstract
Abstract: This project introduces a new educational service that uses machine learning algorithms in Python and the OpenCV library to detect and prevent tampering, providing blind people with better freedom and personal security. Thanks to the integration of real-time detection equipment, the system can identify various hazards in different locations without using conventional equipment. Topics covered include optimizing algorithms for immediate use and maximizing efficiency for portable devices. Python supports rapid development, while OpenCV's modularity enables scalable development. This approach performs existing processes accurately, quickly and efficiently, using flexible methods for continuous improvement. Future developments include the integration of advanced learning models and user insights to provide more accurate feedback and pave the way for new products.
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