National Security
Explore maritime defense strategies, naval operations, and coastal protection.
Vessel Trajectory Reconstruction Of Missing AIS Data Values Machine Learning.
This study focuses on reconstructing missing AIS data to improve vessel trajectory accuracy for maritime analysis. Various interpolation, filtering, and machine learning methods are explored to restore incomplete AIS records and enhance data quality. The research also highlights challenges like data loss, coverage gaps, and complex vessel movements while suggesting future directions for efficient and accurate trajectory reconstruction.
Underwater Search And Recovery: A Reference To Develop A Regulatory Framework For The Indian Ocean Region.
This study focuses on underwater search and recovery operations for locating and salvaging high-value objects lost at sea. It explores acoustic positioning systems, modeling, and simulation techniques to estimate target trajectories and reduce search areas. The research also addresses challenges like data gaps, tropical littoral conditions, and proposes improvements for search efficiency and maritime safety.
Vessel Path Prediction IWT
This study explores vessel path prediction in Indian Inland Waterways (IWT), a largely under-researched area. Using AIS data, machine learning, and mathematical models, vessel routes can be predicted to improve trade efficiency, detect anomalies like illegal activities or collisions, and protect endangered aquatic species such as the Ganges river dolphin. Challenges include limited data, unique river characteristics, and the need for real-time computation, while opportunities lie in enhancing surveillance, environmental conservation, and safer inland water transport.
Underwater Search And Recovery Its Present Level Of Technology.
This research explores Underwater Search and Recovery (UWSAR) technologies essential for locating and salvaging high-value objects lost at sea. It examines positioning, sensing, and recovery systems such as sonar, ROVs, and acoustic beacons, highlighting current challenges in deep-sea operations. The study also presents emerging solutions like U-GPS, ADS-B tracking, and 3D imaging sonar to enhance underwater recovery efficiency.
Passive Sonar Simulator Design And Development (Effective Detection)
This study focuses on designing a passive sonar simulator to predict effective detection ranges in the Indian Ocean Region. By analyzing Transmission Loss, ambient noise, and Receiver Operating Characteristics (ROC), the simulator quantifies detection probabilities under varying ocean conditions. The work aids tactical decision-making, sonar deployment, and minimizes acoustic impact on marine life.
Effective Deployment Of Passive Sonar Simulator
This study focuses on the effective deployment of passive sonar using simulators to optimize submarine operations in the Indian Ocean. By mapping noise, detection ranges, and vulnerability in 3D, operators can make informed decisions for stealth and threat management. The work also highlights opportunities in real-time simulation, autonomous vehicles, and VR-based training for naval operations.
Automating Static AIS Data
This study explores collision avoidance in inland waterways using AIS data to predict and prevent ship-to-ship and ship-to-shore accidents. It applies models like Collision Risk Index (CRI), fuzzy logic, and neural networks for real-time risk assessment. The research aims to enhance navigation safety and reduce maritime accidents through data-driven solutions.