<![CDATA[The Automatic Identification System (AIS) is a vital maritime technology that enhances navigation safety and vessel tracking. This system is integrated with the Internet of Things (IoT) for real-time data transmission. However, due to multiple tasks being employed, the system latency increases. To address this problem, this study proposes an optimized task-scheduling approach using a Round-robin algorithm with an additional task-reshuffling mechanism. The proposed method is implemented on an ESP32 microcontroller, enabling real-time processing of AIS messages while minimizing latency and energy consumption. Experimental results demonstrate that the hybrid Round-robin and Shuffling method achieves the lowest average transmission time of 28.736 seconds, outperforming traditional Priority and standard Round-robin scheduling approaches. The findings of this study contribute to enhancing real-time processing capabilities in embedded vessel tracking systems. Following this, future research should focus on addressing transient fluctuations using adaptive scheduling techniques. ]]>
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