Systematic Maritime Automated Reporting Technology (SMART)

The Systematic Maritime Automated Reporting Technology (SMART) system is designed to modernize and enhance problem reporting within the U.S. Navy’s Aegis Combat System (ACS) by leveraging artificial intelligence (AI) and machine learning (ML). Current manual reporting processes rely on operator expertise, leading to inconsistencies, inefficiencies, and human error. Variability in documentation quality and incomplete issue descriptions hinder test and maintenance efforts, increasing operational costs and prolonging issue resolution timelines. The SMART system aims to address these challenges by automating problem identification, documentation, and reporting using advanced AI-driven techniques.  SMART's architecture consists of key components, including an Automated Data Collection Framework to capture system data and operator observations, an Intelligent Analysis Engine that utilizes ML algorithms for anomaly detection and specification matching, and a Natural Language Generation Pipeline that transforms technical findings into standardized, human-readable reports. Additionally, a Specification Compliance Validator ensures reports align with system requirements, and an Integration Interface facilitates seamless connectivity with existing ACS components. This modular and scalable approach allows SMART to adapt across different platforms while maintaining reporting accuracy and efficiency.  By automating data collection, analysis, and report generation, SMART significantly improves efficiency by reducing reporting time, enhances accuracy through AI-driven standardization, and provides explainable AI capabilities for traceable decision-making. The system’s scalable design ensures compatibility across ACS testing environments, supporting rapid issue identification and resolution. With a projected 10% improvement over existing performance metrics, SMART represents a transformative advancement in ACS problem reporting, improving operational effectiveness, maintenance workflows, and overall system reliability.