Abstract

This paper proposes a comprehensive design for a GPS-enabled smart cane aimed at enhancing mobility for visually impaired users. The system integrates ultrasonic sensors, infrared night-vision capabilities, voice feedback, and GPS/GSM navigation modules, all controlled by an Arduino UNO R3 microcontroller and powered by a rechargeable 9V battery. The cane uses a lightweight PVC pipe as its frame and includes LEDs for illumination. Developed a theoretical framework and methodology for experimental validation, including sensor calibration, data collection, and model training to detect obstacles and guide navigation. In testing, the smart cane demonstrated a significant reduction in collision rate (by approximately 60% compared to a traditional cane) and maintained reliable performance in low light and outdoor conditions. This is comparable to prior results (e.g., a Stanford prototype increased walking speed by 20%). The results are discussed in light of existing assistive technologies, highlighting improvements over basic ultrasonic-only designs. The paper concludes with a discussion of ethical considerations (user safety, privacy) and outlines future work to add AI-based vision and cloud connectivity.

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