Building Blocks of Autonomous Ship?

This presentation will focus on the topic of the Building Blocks of an Autonomous Ship. That consist of some key building blocks that should be considered to make autonomous shipping a reality. The subtopics of this presentation consist of Vessel & Ship System, Automation System, Vessel Behavior, Navigation System, Environmental Conditions, Human Navigator Actions, Advanced Ship Predictor, Digital Ship Route, Digital Navigator, Training Process, Execution Process, Decision Support, Information Sources, Support Services & Authorities, and The Framework.

Key Pillars in Autonomous Shipping ?

This presentation will focus on the topic of Key Pillars in Autonomous Shipping. That consist of some key concepts that should be considered to make autonomous shipping a reality and that includes the human navigator, technology, rules and regulations, and digital navigator. The subtopics of this presentation consist of Human Navigator, Human-Technology Interactions, Information Visualization, Regulatory Compliance, Behavior Cloning and Creation of Digital Navigator, AI-Technology Interactions, Information Visualization for AI, Regulatory Compliance of AI, Trustworthiness of AI, and AI-Human Interactions.

Digital Twin as System of Systems?

This presentation will focus on the topic of Digital Twin as a System of Systems. That consists of an overview of developing the digital twin as a system of systems (SoS) for complex systems by utilizing extreme data. The development a digital twin for an ocean going vessel, as a vessel hull and ship systems to improve ship energy efficiency has also been discussed in this presentation. The subtopics of this presentation consist of SoS from Extreme Data, Marine Engine Data Clusters, Marine Engine Data Super Clusters, SoS Data Space, Extreme Data, Ship Energy Efficiency, Engine Super Cluster, Other Super Clusters, and Operation Modes.

Covariance & Correlation in Digital Twin (Part II)? 

This presentation will focus on the topic of Covariance & Correlation in Digital Twin. The subtopics of this presentation consist of One Parameter Data Cluster, Histogram of the Parameter, Histogram under a Probability Distribution, What is a Gaussian Distribution, Gaussian Distribution as a Probability Density, Kernel Density Estimation of a Data Cluster, Histogram vs Kernel Density Estimation, Two Parameter Data Cluster, Zero Mean Value, Kernel Density Estimation of a Data Cluster, Mean, Covariance & Correlation Matrices, Covariance & Correlation, and Python Codes.

What is Extreme Data?

This presentation may answer the questions of What is Extreme Data, What is Big Data, What is Data, Big Data Solutions from Data Management, Big Data Solutions from Data Analytics, Modeling in Extreme Data, Anomaly of Extreme Data and Outliers of Extreme Data? Outliers of Extreme Data.

What is a Digital Twin?

This presentation may answer the questions of What is a Digital Twin, What is Not a Digital Twin, Main Components of a Digital Twin, Utilization of Extreme Data, Model Development by ML, Model Objectives in Digital Twin, Physical Laws can be Used in Digital Twin, Model Assumptions in Digital Twin, Digital Twin is a Superior Approach and Digital Twin Limitations.