Smart Cane for Visually Impaired Persons

. Time, safety, and navigation are critical challenges for visually impaired individuals, yet many assistive tools remain limited in capability, accuracy, or affordability. The objective of this project is to design and develop a Smart Cane Assistive System that enhances mobility, ensures safety, and provides real-time environmental awareness through a combination of sensor-based obstacle detection, computer vision, and emergency communication technologies. The system incorporates an IR sensor for short-range ground obstacle detection and an ultrasonic sensor for mid- and upper- level obstacle identification, both interfaced with an Arduino Uno that alerts the user through a buzzer. An ESP32-CAM module enables object identification and OCR, activated via dedicated switches, with results processed through a Python application and provided as audio feedback. An RFID reader supports automatic bus route identification without user input. For emergency situations, a second Arduino Uno is paired with a SIM800L GSM and NEO-6M GPS module, powered by a 3.7V Li-ion battery, to send an SMS containing the user’s live location when the panic button is pressed. The system follows a modular design covering core functions such as sensing, vision processing, RFID-based alerts, and emergency communication. Multi-level testing validated the system’s accuracy, performance, and user comfort. The results indicate that the smart cane significantly improves obstacle detection accuracy, enhances situational awareness, and provides reliable emergency communication support compared to conventional assistive devices. Future developments may include AI-based path prediction, Bluetooth connectivity for mobile integration, and onboard audio processing for fully offline operation