Embedded Smart Pen for Real-Time Word Recognition and Meaning Search

This paper presents a smart embedded pen system designed for real-time text recognition and semantic interpretation. The proposed system uses an embedded camera module to capture textual content, which is then transmitted via a wireless interface to a processing server. Optical Character Recognition (OCR) is performed using Tesseract OCR to extract text from the captured images. To enhance accuracy and usability, a custom preprocessing pipeline is introduced, including error correction using string similarity measures, sentence importance ranking based on frequency analysis, and rule-based detection of basic literary devices. This preprocessing layer improves the quality of the input before further semantic analysis.

The processed text is then passed to a language model for generating simplified meanings, contextual explanations, and key insights. The system follows a distributed architecture where the embedded device is responsible for data acquisition and user interaction, while computationally intensive tasks are handled by the server. This approach ensures efficient performance despite hardware constraints. Experimental results demonstrate that the system can effectively extract and interpret textual information in near real-time, making it suitable for educational assistance and accessibility applications. Future enhancements include improving OCR robustness, expanding linguistic analysis capabilities, and integrating more advanced on-device processing.