<![CDATA[General Background: Welding activities pose significant risks to eye safety due to exposure to intense light and radiation. Specific Background: Conventional welding glasses rely on manual operation, which often leads to inconsistent use and reduced safety compliance. Knowledge Gap: Existing solutions have not fully integrated automated control with voice-based interaction for real-time operation. Aims: This study aims to design and develop an Arduino-based automatic welding glasses system controlled by voice commands to improve operational safety. Results: The system achieved 100% command recognition accuracy with an average response time of 1.1 seconds, an effective voice recognition distance up to 50 cm, and stable operation for 60 minutes without performance degradation. Novelty: The integration of voice recognition technology with automatic lens control and cooling system provides a practical approach to hands-free safety equipment operation. Implications: This system offers a reliable solution to improve compliance in the use of protective equipment and supports safer welding practices in real working environments. Keywords: Voice Control, Arduino Uno, Welding Glasses, Voice Recognition, Safety System Key Findings Highlights Command detection achieves full recognition under controlled testing conditions System response remains consistent within short reaction time intervals Operational stability maintained during continuous usage period]]>
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