WiMi Built Digital-Twin Visualization Architecture

BEIJING, Oct. 10, 2023

In order to build a digital twin model, data collection and data processing of the entity or system are first required. The collected data are then processed and transformed in order to correspond and match with the digital twin model. The next step is to build the digital twin model, which is the basis of the digital-twin visualization architecture and is an accurate digital model of the actual entity or system. The digital twin model includes geometry, physical properties, and motion behavior information. By modeling and simulating the data of the entity or system, a digital twin model is created that corresponds to the actual situation.

In addition, the system includes the visualization engine, which is the core component of the digital-twin visualization. It is responsible for presenting the digital twin model and actual data in a visualized form to the user or decision maker. This can be achieved through charts, images, animations, virtual reality, etc., providing realistic visualization. Meanwhile, the user can interact with the visualization engine to observe and analyze the digital twin model and can explore different scenarios, parameters, and decisions in order to make more accurate predictions and optimizations. The user interface, on the other hand, is the interface through which the user interacts with the digital-twin visualization system, providing various operations and controls that enable the user to freely navigate and manipulate the digital twin model.

WiMi's digital-twin visualization architecture is in real-time and is capable of collecting and processing data from various entities in real-time. The real-time data is collected and transmitted to the digital model for analysis and visualization, enabling decision makers to understand the state and performance of entities and make adjustments accordingly. The core of the digital-twin visualization architecture is to connect physical entities with their digital copies, and the feedback of real-time data allows users to accurately understand the state and performance of physical entities. Through sensors and monitoring devices, real-time data can be captured and synchronized with the digital twin for updates. This real-time feedback allows users to identify problems and take action in a timely manner, improving efficiency and safety. Moreover, the digital-twin visualization architecture not only reflects the current real-time state of physical entities, but also allows for simulation and prediction through modeling. Based on historical data and algorithmic models, the digital twin can predict the future behavior and performance of physical entities. This capability allows users to identify potential problems in advance and take appropriate preventive measures, thereby reducing losses and risks.

The digital-twin visualization architecture can fuse information from multiple data sources, including sensor data, historical data, market data, and more. By integrating these data together, a more comprehensive understanding of an entity's operation can be obtained and more accurate predictions and decisions can be made, as well as the data can be intelligently analyzed and optimized using AI and machine learning technologies. For example, by learning from historical data and pattern recognition, the system can automatically identify problems and anomalies, and propose appropriate solutions. This intelligent analysis and optimization capability can greatly improve the efficiency and performance of the entity.

WiMi uses 3D visualization technology to present digital models realistically. Through virtual reality technology, decision makers can observe and manipulate the digital model as if they were there to better understand the structure and behavior of the entity. This intuitive visualization can help decision makers better understand and analyze problems, and can also help users discover hidden correlations and patterns and make more accurate decisions. At the same time, the digital-twin visualization architecture can also facilitate multi-party collaboration. By sharing digital twin models and real-time data, different partners can work together on the same platform. For example, in the industrial sector, manufacturers, suppliers, and maintenance personnel can collaborate on design, process optimization, and troubleshooting through digital twins, which can greatly improve efficiency and operational accuracy.

In the future, with the continuous development of artificial intelligence, IoT and big data technologies, digital-twin visualization technology will also be further improved and applied. Digital-twin visualization technology will become an important tool for the intelligent transformation of various industries, which will bring more efficient and intelligent solutions to various industries, provide more accurate and comprehensive information to decision makers, and help them make more informed decisions. At the same time, digital-twin visualization technology will also promote collaboration between different industries and accelerate technological innovation and industrial development.