Smart Obstacle Detection System: An AI-IoT Powered Assistive System for the Visually Impaired

The millions of people who are visually challenged in the world almost invariably have to grapple with the three problems: navigating an environment, recognizing visual content, and social interaction. The use of traditional aids such as white canes and guide dogs, no matter how helpful, is devoid of real-time contextual awareness. This paper presents the Smart Obstacle Detection System, an innovative AI-IoT integrated assistive system that helps the visually impaired be more independent, safe, and socially interactive. Smart Obstacle Detection System provides real-time feedback to users via voice output by performing obstacle detection, facial recognition, emotion analysis, OCR, and scene description. The system was built using Python modules, namely ESP32-CAM for image capturing, ultrasonic sensors for object detection, and the use of AI models such as YOLO and ConvNeXt for smart interactions. Reversible data hiding was included in the project to ensure privacy and integrity. Smart Obstacle Detection System symbolizes the true potential of AI-IoT fusion in creating accessibility.