Smart Object Recognition with Audio-Visual Feedback for Enhanced Accessibility Using ESP32

Vision loss presents substantial barriers to autonomy, employment, and routine activities. With over 2.2 billion individuals globally affected by some form of visual impairment, even basic tasks like navigation or reading become difficult. This study introduces a smart object recognition system tailored for visually impaired users, utilizing real-time image processing. The framework leverages Python with OpenCV for image analysis and an ESP32 microcontroller for system coordination. Auditory feedback is delivered via the DFPlayer Mini, while an OLED display provides on-screen visual cues. Upon detecting an object with the camera module, the system identifies it and communicates the result through synchronized voice and text outputs. Efficient integration between components is achieved through the ESP32, ensuring smooth operation. The system combines artificial intelligence and IoT to create a responsive, affordable, and portable assistive device, aiming to enhance independence and accessibility for users with visual challenges.