The global blue economy is experiencing rapid growth, driving unprecedented investment in marine robotics and autonomous underwater vehicles (AUVs). This expansion is fueled by the imperative for sustainable resource management, climate change monitoring, and the maintenance of vast subsea infrastructure. Concurrently, geopolitical shifts are intensifying the need for advanced maritime surveillance and defense capabilities. Technologies that enhance the precision, safety, and operational efficiency of underwater assets are becoming critical enablers for these strategic global initiatives, with market demand projected to grow at a CAGR of 12.5%.
Reconstructs precise 3D trajectories by integrating operational history and acoustic positioning data, enabling highly accurate vehicle tracking.
Detects real-time deviations and anomalous behavior, potentially reducing accident risks by ~30% and enhancing operational safety.
Establishes a strong market position with a patent validated against 9 prior art documents, ensuring long-term competitive advantage.
This patent protects a method, program, and system for monitoring underwater vehicles by integrating operational history with acoustic positioning data for high-precision 3D trajectory reconstruction and anomaly detection. With 21 claims, it covers broad aspects of the technology, having been granted after thorough examination against 9 prior art documents, indicating a robust and difficult-to-invalidate scope.
This patent primarily covers the fusion of acoustic positioning and operational history for enhanced monitoring. White space exists in integrating novel sensor types (e.g., optical, magnetic) for positioning, or developing advanced AI for autonomous decision-making and mission planning beyond mere anomaly detection.
This technology could reduce re-investigation and accident response costs associated with traditional visual inspection or inaccurate positioning in underwater vehicle monitoring. For example, assuming 500 hours of annual underwater drone operation, implementing this technology could improve anomaly detection rates by 20% and reduce re-investigation and troubleshooting time/costs by 10%. If annual underwater drone operating costs (labor, fuel, repair, etc.) are ~$1.5M (AI est.), a cost reduction of ~$150K/year (AI est.) is projected ($1.5M × 10%).
X: Positioning Accuracy & Stability
Y: Operational Efficiency & Risk Reduction