Ethan Zhang¹ and Tyler Boulom², ¹Fairmont Preparatory Academy, USA, ²California State Polytechnic University, USA

This research presents a combined mechanical and artificial intelligence solution designed to assist individuals with learning or physical disabilities in reading books more effectively [3]. The system consists of a low-cost book flipper, a camera for page capture, a Raspberry Pi for text extraction, and an AI module for summarization and explanation. Experiments evaluated two potential blind spots: mechanical accuracy of page flipping and the effect of lighting on OCR performance [4]. The page-flipping mechanism averaged 1.6 errors per trial, while OCR accuracy peaked at 91% under moderate exposure, highlighting the importance of environmental conditions. Comparisons with existing methodologies showed that previous systems emphasized digitization and preservation but did not address comprehension or accessibility. By contrast, this project enhances accessibility by not only digitizing books but also tailoring content through summarization. Ultimately, the system provides both a functional and educational tool, bridging the gap between traditional books and adaptive learning technologies.

Servo, Arduino, Raspberry Pi, Flutter