Development of an ESP32-Based IoT Smart Cane for Multi-Directional Obstacle Detection and Real-Time Monitoring
Visual impairment limits independent mobility due to difficulties in recognizing obstacles and environmental conditions. This study aims to develop an ESP32-based Internet of Things (IoT) smart cane to improve navigation safety and real-time monitoring for visually impaired users. The proposed system integrates three ultrasonic sensors for multi-directional obstacle detection, a water level sensor for puddle detection, a DFPlayer Mini with speaker for audio feedback, a vibration motor for tactile feedback, and a GPS module connected to a Telegram Bot for location monitoring. The prototype was designed and evaluated through functional testing of each subsystem and overall system performance. The results show that the smart cane successfully detects obstacles, provides audio and vibration warnings, and transmits user location information remotely. The developed system demonstrates the potential of IoT-based assistive technology to support safer and more independent mobility for visually impaired users.