This project presents VisionAid, a wearable assistive navigation system designed to enhance the safety and spatial awareness of visually impaired users without replacing the familiar use of a traditional cane. The prototype integrates LiDAR, ultrasonic sensing, a Raspberry Pi AI camera, and Raspberry Pi processing to detect obstacles, classify urgency, and support real-time object recognition. Instead of relying on a single sensor, VisionAid uses a multi-sensor approach with haptic feedback and planned Bluetooth audio output to alert users based on distance, direction, and danger level. The project demonstrates a functional assistive technology platform that prioritizes user control, fail-safe sensing, privacy-conscious local processing, and future refinement through camera-enabled sensor fusion and real-user optimization.
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