Glossary

Involves the use of historical data, statistical algorithms, and machine learning techniques to forecast future navigational scenarios and conditions. By analyzing patterns in maritime data, predictive analytics can improve route planning, enhance safety measures, and optimize operational efficiencies, ultimately leading to better decision-making and resource management.

Machine Learning is a subset of artificial intelligence (AI) that enables systems to gain insights from data, identify patterns, and make decisions with minimal human intervention. In maritime navigation, machine learning algorithms can analyze vast amounts of data to improve predictive capabilities, optimize routes, and enhance situational awareness, thereby contributing to safer and more efficient operations.

Decision Support Systems  are interactive software-based systems that assist decision-makers in analyzing data and making informed choices. In the maritime context, DSS can integrate various data sources, including weather conditions, traffic patterns, and vessel performance metrics, to support navigational decisions, enhance operational efficiency, and ensure safety.

MASS are vessels designed to operate with varying degrees of autonomy, ranging from partial to fully autonomous operations. These ships leverage advanced technologies such as AI, sensor systems, and automation to navigate and perform tasks without continuous human oversight, enhancing operational efficiency and safety in maritime operations.

Human-Machine Interfaces allow humans to interact with machines or automated systems. In maritime navigation, effective HMIs facilitate communication (for example, via a touch-screen or control panel linked to a display) between the crew and navigation systems, enhancing situational awareness, decision-making, and operational efficiency while reducing the risk of human error.

Real-Time Data Analytics refers to the continuous analysis of data as it is generated, allowing for immediate insights and informed decision-making. In navigation, real-time analytics can enhance situational awareness, improve response times to changing conditions, and optimize route adjustments based on current information.

Sensor Fusion is the  process of integrating data from multiple sensors to create a comprehensive and accurate representation of the surrounding environment. In maritime navigation, Sensor Fusion combines inputs from various devices, such as Radar, AIS, and cameras, to enhance situational awareness and improve decision-making capabilities.

The use of advanced algorithms and technologies enable computers to interpret and understand visual information from the environment. In maritime operations, this technology utilizes high-end cameras to assist in obstacle detection, monitor traffic, and enhance situational awareness by processing detailed images. By leveraging high-resolution visual input, Computer Vision systems can accurately identify potential hazards and provide crucial information for safe navigation.

This refers to the process of tagging or annotating data (such as images, text, or audio) with relevant labels to train machine learning models. This step is crucial for supervised learning, as it provides the necessary information for algorithms to learn patterns and make predictions based on labeled datasets.

Data management is a multi-tier process that includes collecting, storing, organizing, and analyzing data to ensure its accuracy and accessibility. In maritime navigation, effective data management is crucial for optimizing operational efficiency, enhancing safety, and enabling data-driven decision-making.

A Digital Twin is a virtual representation of a physical asset, system, or process that mirrors its real-time performance and behavior. In maritime navigation, Digital Twins can be used to simulate vessel operations, predict performance under various conditions, and inform decision-making for maintenance and operational efficiency.

The process of estimating the intrinsic and extrinsic parameters of a camera, facilitating accurate 3D computer vision and the removal of lens distortion. This calibration is essential for ensuring accurate representation of the environment, which is crucial for applications like obstacle detection and navigation in maritime operations.

A Thermal Camera (or Heat Camera) is a device that captures images based on infrared (IR) radiation emitted by objects, allowing for visualization in low-light or obscured conditions. In maritime navigation, thermal cameras enhance situational awareness by detecting heat signatures from vessels, obstacles, and environmental features, thereby improving safety during operations.

LOU (or Digital Watchkeeper Unit) refers to the camera system installed on the upper deck or mast of ships to enhance visual monitoring of the surrounding environment. This unit assists in identifying potential hazards and improving situational awareness for the crew during navigation.

A Berthing Assistance System is an advanced solution designed to aid vessels during the berthing process by providing guidance and support for safe and efficient docking. These systems typically utilize sensors, real-time data, and predictive analytics to optimize maneuvering and reduce the risk of accidents during berthing.

A Navigation Assistance System is a set of tools and technologies that support mariners in navigating complex waterways. NAS may include real-time data feeds, predictive analytics, and decision-support tools to enhance situational awareness and improve the safety and efficiency of navigation.

Computer Based Training is an educational approach that utilizes digital  technology and simulators to deliver training programs and instructional materials. In the maritime sector, CBT can be employed to enhance crew training in navigation, safety protocols, and operational procedures, providing interactive and engaging learning experiences.

A Deep Learning Distance Estimator  is a machine learning model designed to estimate distances based on visual input and other sensor data. In maritime navigation, DLDE can improve situational awareness and assist in safe maneuvering by accurately determining distances to nearby vessels and obstacles.

A Bounding Box is a rectangular frame used in computer vision to identify and locate objects within an image. In the context of navigation, BBoxes can assist in detecting and tracking vessels and hazards, thus facilitating improved situational awareness and safety in maritime operations.