• Estimation of ‘Time to Failure’ of a machine based on Machine Learning Models
• Detection of anomalies in running machinery
• Classification of different types of faults
• Estimation of “Remaining Useful Life’ of various systems and equipment
• Use of Video Cameras for Object Detection and Classification
•Data fusion of Radar, AIS, and Camera input feeds
• Track Identification (IFF)
• Enhanced Force Protection Measures using AI / ML
• Considerable improvement in ship handling capabilities during Station Keeping, Replenishment at Sea, and Entering/ Leaving Harbour
• Integration of prime movers and other sensors into a consolidated model
• Use of sensors to build domain awareness of the platform in real-time
• Use of AI/ML to predict and recommend a course of action
• Integration of actions with actuators
• Refine and re-orient based on responses and feedback