National Security
Explore maritime defense strategies, naval operations, and coastal protection.
Recognising Indigenous Knowledge as a Working Input to Underwater Domain Awareness: Insights from the Indian Ocean Region
This research note examines the importance of integrating indigenous knowledge and traditional ecological practices into the Underwater Domain Awareness (UDA) framework in the Indian Ocean Region. It highlights how coastal communities, fishing populations, and maritime indigenous groups possess valuable knowledge of marine ecosystems, ocean conditions, and maritime activities that can complement technology-driven surveillance. The study advocates a more inclusive, community-centred approach to maritime security, sustainability, and ocean governance.
The Indian Ocean Region (IOR) in the Indo-Pacific: A Tropical Perspective Through the UDA Framework
This research note emphasises the utility of the UDA framework, underscoring the need for a context-specific approach and its ability to integrate policy, technology, community, and other stakeholders. It also notes that. A tropical maritime analysis is essential toward a comprehensive understanding of the Indo-Pacific region to secure maritime governance and sustainable development.
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 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.
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.