Abstract

Mobility remains one of the greatest challenges faced by visually impaired individuals, with conventional white canes offering limited protection against head-level or distant obstacles. This project addresses that gap by providing a low-cost, Arduino Nano–based smart cane that detects obstacles in real time and alerts users through progressive haptic and auditory feedback. The system integrates an HC-SR04 ultrasonic sensor for obstacle detection, a vibration motor with cubic PWM mapping for smooth intensity control, and an active buzzer with dynamic cadence that tightens as proximity decreases, culminating in an emergency mode (maximum vibration + continuous tone) at very close range (<8 cm). To ensure accuracy and reliability, the firmware employs a 5-sample moving average filter, millis()-based non-blocking timing, and timeout handling to maintain stability even under noisy conditions. The hardware is powered by dual 3.7 V Li-ion batteries regulated to 5 V, achieving 6–8 hours of continuous operation. Extensive indoor and outdoor tests confirmed over 95% detection accuracy, a response time of 80–100 ms, and robust performance across multiple obstacle types, with minimal false triggers. This project contributes to the body of knowledge by providing an affordable, replicable framework for developing assistive mobility devices that combine smooth, real-time feedback with long battery life, making it an ideal blueprint for future enhancements such as multi-sensor coverage, machine-learning-based obstacle classification, and IoT connectivity for caregiver support

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