<![CDATA[This study presents the design and development of a smart helmet system for detecting impact levels and monitoring accident locations in real time. The system utilizes an MPU6050 sensor to measure three-axis acceleration, which is processed using the Signal Vector Magnitude (SVM) method to determine G-Force values. Based on the calculated G-Force, impacts are classified into light, moderate, and severe categories. Experimental results show that the proposed system successfully classified impacts with average G-Force values of 1.08 g, 3.26 g, and 3.92 g for light, moderate, and severe impacts, respectively. Furthermore, GPS evaluation conducted at five outdoor locations produced an average positioning error of 2.31 m, demonstrating reliable real-time location tracking for accident monitoring applications. Keywords: Smart Helmet, Impact Detection, MPU6050, ESP32, G-Force, Signal Vector Magnitude (SVM), GPS Neo-6M, Real-Time Monitoring, Accident Detection]]>
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