Pusan National University Integrated Supply Chain Metaverse Requirements Analysis, Design, and System PoC
Through the Integration of AIS and GPS Data / AI Prediction Models
Providing a Metaverse-based Ship Operation Tracking · Simulation System
| PROJECT | Pusan National University Integrated Supply Chain Metaverse System Expansion Project (3rd Year)
|
PROJECT GOAL
| In accordance with the requirements of the Carbon Neutral Global Supply Chain Research Center (SCSC) at Pusan National University, we implemented a ship route tracking scenario based on actual large-capacity operation history (AIS/GPS). In addition, we completed a data-driven, multifaceted supply chain analysis environment by building a virtual simulation that predicts changes in carbon emissions and costs by adjusting logistics variables such as ship speed and port waiting time. |
| WORK | Planning / System Architecture Design / Data Format Definition / Pixel Streaming
|
| DATE | 2025.03 |
| KEYWORD | #DigitalTwin #SupplyChainOptimization #Metaverse #VARLOS #WebStreaming #Simulation #Port
|
“By intuitively visualizing complex ship operation data in a metaverse environment, we have been able to understand the flow of maritime logistics much more easily.”
We aimed to seamlessly integrate large-capacity operation history (AIS/GPS) data generated during actual maritime movements with the metaverse virtual space. To achieve this, we built a refinement pipeline for massive route data and conducted comprehensive system upgrades to integrate backend API servers.
As a result, based on actual data, it became possible to precisely track the route of specific ships, and carbon emission · cost simulations through the adjustment of variables such as ship speed and waiting time became possible, providing substantial assistance to the research center's scenario analysis and decision-making.
 |
Web-based Data Visualization and Sharing |
Overview
Pusan National University Carbon Neutral Global Supply Chain Research Center (SCSC)'s Real-time Data-driven Metaverse Simulation Platform Advancement
We implemented a real-time ship tracking system by integrating large-capacity operation history (AIS/GPS) data with the metaverse virtual space. Utilizing Samoo Immersion's VARLOS digital twin technology, we advanced the metaverse platform to intuitively visualize spatial data in a virtual environment.
 |
Accessibility Improvement Based on Web Streaming
| Data Visualization in a 3D Environment
|
Immersion Strategy
We provide a spatial-constraint-free analysis infrastructure by applying pixel streaming technology to access a high-quality 3D environment through a web browser. We maximized the effectiveness of data analysis by combining a ship tracking function based on refined AIS/GPS data with a simulation linked to six major AI models.
 |  |
Port Operation Simulation Screen
| Ship Tracking and Route Simulation Screen
|
Global Supply Chain Data Visualization System Configuration
This system is configured to intuitively visualize six major data inquiry scenarios linked to the research center's key AI prediction models, based on ship navigation data.
 |  |  |
Scenario 1:
Route and ETA Prediction
| Scenario 2:
Fuel Consumption Prediction
| Scenario 3: Marine Accident Risk Management (LLM Linked)
|
Visualization of route and estimated time of arrival (ETA) predictions based on real-time operation data (AIS/GPS)
| Linked with weather and ship data,
3D display of expected real-time · segment-specific fuel consumption | Identification of marine accident risks on the route using LLM
and safety management
|
 |  |  |
Scenario 4: Optimal Cruising Route Determination
| Scenario 5: Port Transfer
Equipment Route Prediction
| Scenario 6:
Port Air Pollution Management
|
For maximizing fuel efficiency and
on-time port entry, visualization of optimal cruising speed · route data per ship
| For unloading efficiency, port transfer equipment's real-time movement routes and optimal path prediction | Real-time graph monitoring of ship emissions and port air pollutants (carbon, etc.)
|
VARLOS Integrated Supply Chain Specialized Technology
By combining real-time AIS/GPS data integration, AI prediction simulation, and web-based pixel streaming technology, we provide a high-quality ship operation analysis environment without spatiotemporal constraints.
1. DB and API-based Data Integration 2. Various Data Visualizations (Numerical Expressions, Charts, etc.)
3. Unreal Engine-based 3D Visualization 4. Simulation Function Provision Based on Specified Conditions
Key Features
Provides real-time ship route search and monitoring functions based on large-capacity AIS/GPS data. Linked with the research center's 6 core AI prediction models, it intuitively displays virtual simulation results and logistics data in a metaverse environment.
 | Ship Information Display Displays and tracks ship information (IMO, latitude, longitude, speed, etc.) by querying past navigation data |
 | Ship Tracking Mode Tracks the ship's route based on stored navigation information, automatically adjusts the viewpoint, and displays it on the screen |
 | Progress Status Display A function that informs the user of the progress status during data inquiry and navigation visualization |
 | Location Message Display While querying or visualizing route data, the ship's location message is displayed on the screen to inform the user of the current latitude and longitude |
The moment you immerse yourself, you grow!
Maximize your capabilities with XR and AI (X-RAI) technology.
Pusan National University Integrated Supply Chain Metaverse Requirements Analysis, Design, and System PoC
Through the Integration of AIS and GPS Data / AI Prediction Models
Providing a Metaverse-based Ship Operation Tracking · Simulation System
In accordance with the requirements of the Carbon Neutral Global Supply Chain Research Center (SCSC) at Pusan National University, we implemented a ship route tracking scenario based on actual large-capacity operation history (AIS/GPS). In addition, we completed a data-driven, multifaceted supply chain analysis environment by building a virtual simulation that predicts changes in carbon emissions and costs by adjusting logistics variables such as ship speed and port waiting time.
“By intuitively visualizing complex ship operation data in a metaverse environment, we have been able to understand the flow of maritime logistics much more easily.”
We aimed to seamlessly integrate large-capacity operation history (AIS/GPS) data generated during actual maritime movements with the metaverse virtual space. To achieve this, we built a refinement pipeline for massive route data and conducted comprehensive system upgrades to integrate backend API servers.
As a result, based on actual data, it became possible to precisely track the route of specific ships, and carbon emission · cost simulations through the adjustment of variables such as ship speed and waiting time became possible, providing substantial assistance to the research center's scenario analysis and decision-making.
Overview
Pusan National University Carbon Neutral Global Supply Chain Research Center (SCSC)'s Real-time Data-driven Metaverse Simulation Platform Advancement
We implemented a real-time ship tracking system by integrating large-capacity operation history (AIS/GPS) data with the metaverse virtual space. Utilizing Samoo Immersion's VARLOS digital twin technology, we advanced the metaverse platform to intuitively visualize spatial data in a virtual environment.
Immersion Strategy
We provide a spatial-constraint-free analysis infrastructure by applying pixel streaming technology to access a high-quality 3D environment through a web browser. We maximized the effectiveness of data analysis by combining a ship tracking function based on refined AIS/GPS data with a simulation linked to six major AI models.
Global Supply Chain Data Visualization System Configuration
This system is configured to intuitively visualize six major data inquiry scenarios linked to the research center's key AI prediction models, based on ship navigation data.
Route and ETA Prediction
Fuel Consumption Prediction
3D display of expected real-time · segment-specific fuel consumption
and safety management
Equipment Route Prediction
Port Air Pollution Management
on-time port entry, visualization of optimal cruising speed · route data per ship
VARLOS Integrated Supply Chain Specialized Technology
By combining real-time AIS/GPS data integration, AI prediction simulation, and web-based pixel streaming technology, we provide a high-quality ship operation analysis environment without spatiotemporal constraints.
1. DB and API-based Data Integration 2. Various Data Visualizations (Numerical Expressions, Charts, etc.)
3. Unreal Engine-based 3D Visualization 4. Simulation Function Provision Based on Specified Conditions
Key Features
Provides real-time ship route search and monitoring functions based on large-capacity AIS/GPS data. Linked with the research center's 6 core AI prediction models, it intuitively displays virtual simulation results and logistics data in a metaverse environment.
Ship Information Display
Displays and tracks ship information (IMO, latitude, longitude, speed, etc.) by querying past navigation data
Ship Tracking Mode
Tracks the ship's route based on stored navigation information, automatically adjusts the viewpoint, and displays it on the screen
Progress Status Display
A function that informs the user of the progress status during data inquiry and navigation visualization
Location Message Display
While querying or visualizing route data, the ship's location message is displayed on the screen to inform the user of the current latitude and longitude
The moment you immerse yourself, you grow!
Maximize your capabilities with XR and AI (X-RAI) technology.