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Visual impairment presents significant challenges in safe navigation and independent mobility due to limited environmental awareness. Existing assistive tools, such as white canes, are restricted to contact-based detection and lack real-time hazard identification. This study presents the development of an Intelligent Auto Supervision System, a wearable assistive solution designed to enhance safety and mobility for visually impaired individuals through sensor-based technology. The system integrates ultrasonic sensors and a heat sensor into wearable components, namely intelligent glasses and intelligent shoes, controlled by an Arduino microcontroller. The ultrasonic sensors detect obstacles at both upper and ground levels, while the heat sensor identifies nearby heat sources. A buzzer provides real-time audio feedback to alert users of potential hazards. The system was developed using an experimental design approach and tested in controlled environments to evaluate detection accuracy, response time, and reliability. Results indicate high effectiveness in obstacle detection, achieving 100% accuracy for front-level detection and 90% for ground-level detection. Heat detection achieved an accuracy of 80%, with reduced sensitivity for weaker heat sources. The system demonstrated rapid response time and consistent performance, confirming its capability to improve environmental awareness and user safety. In conclusion, the Intelligent Auto Supervision System offers a practical, low-cost, and innovative solution for assistive mobility. Although limitations such as environmental sensitivity and lack of waterproofing exist, the system shows strong potential for further development and real-world application.

Keywords: assistive technology, visually impaired, ultrasonic sensor, heat sensor, Arduino, obstacle detection, wearable system, smart mobility