<![CDATA[Purpose - This study aims to develop and evaluate an edge-based early warning prototype for monitoring the stability of high-speed boats using real-time motion data. Design/methods/approach – The study employs an engineering prototype validation design consisting of system requirement analysis, architecture design, implementation, and validation. The system integrates an IMU (MPU-6050) for motion sensing, a Raspberry Pi-based edge computing unit for real-time processing, rule-based classification (Normal/Warning/Critical), and an MQTT-based communication framework connected to the SHISTAMO dashboard. Prototype validation includes functional testing, platform integration, and operational monitoring using controlled scenarios and expert-labeled events. Findings - The results show that the prototype successfully performs end-to-end integration from sensing to visualization. The system achieved 90.4% classification accuracy, with high recall in detecting critical conditions (96.7%), ensuring reliable identification of high-risk events. The local alarm response time was 182 ms, while the dashboard update delay averaged 1.24 s, indicating near-real-time performance. Communication reliability was also high, with 98.8% data delivery success and 97.2% offline synchronization. Research implications/limitations – The findings demonstrate prototype-level feasibility; however, validation is limited to controlled scenarios and does not yet represent diverse sea conditions. The rule-based thresholds and comfort proxy require further calibration and validation through extended sea trials and reference instrumentation. Originality/value – This study contributes an integrated edge-based maritime monitoring prototype that combines motion sensing, offline-capable alarming, real-time telemetry, and fleet-level logging in a single system, specifically tailored to the operational needs of high-speed boats.]]>
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