The increasing complexity of naval electrical systems and the demand for higher operational reliability necessitate a shift from traditional maintenance methods to data-driven predictive maintenance solutions. This research examines the effectiveness of IoT-based remote monitoring and diagnostic systems in improving system reliability, cost-efficiency, and operational sustainability in naval engineering. A qualitative-empirical approach was applied, utilizing expert interviews, structured surveys, and field observations to assess the impact of IoT-driven predictive maintenance. The findings indicate a significant reduction in system failures (92/100), maintenance costs (89/100), and operational downtime, demonstrating the effectiveness of real-time fault detection and automated diagnostics. Additionally, the study identifies challenges in infrastructure readiness (78/100) and cybersecurity concerns (82/100), which must be addressed for large-scale implementation. While the adoption rate (88/100) reflects strong industry support, skill readiness gaps (80/100) suggest a need for enhanced technical training in maritime education. The research concludes that IoT-based predictive maintenance offers a transformative approach to naval maintenance strategies, ensuring sustainability, efficiency, and enhanced fleet readiness in modern maritime operations.
