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Digital Twins

Explore the Infinite Possibilities of Future Buildings

We took the lead in introducing the digital twin framework into the construction industry, creating a fast and precise digital twin simulation engine for buildings. Our system encompasses all data throughout a building’s lifecycle. By inputting physical data such as building materials, spatial design, and environmental factors, customers can visualize the entire lifecycle of the building, from conceptual design to end-of-life phases. The integrated AI models enable rapid deployment and pre-training, allowing customers to predict future events and proactively prevent incidents through carbon reduction assessment, analytics, and long-term building energy-efficiency strategies and suggestions.

DATA&INTELLIGENCEOPTIMIZATIONPHYSICALBUILDINGDIGITALTWINUSER
一窺「未來建築」的無限可能

The Benefits of Digital Twins

數位雙生帶來的好處 改善客戶體驗

Enhanced Customer Experience

數位雙生帶來的好處 優化營運流程

Optimized Operational Processes

數位雙生帶來的好處 減少時間花費

Reduced Time Expenditure

數位雙生帶來的好處 AI節能最佳化

Optimized AI-driven Energy Efficiency

Identify Embodied Carbon in Buildings

Embodied carbon refers to the carbon emissions throughout the lifecycle of a building, from the production of building materials, manufacturing, construction to the final demolition and recycling stages. It is worth-noting that embodied carbon emissions account for 28% of a building’s total carbon footprint.

The Carbon Emission Process throughout a Building's Lifecycle

建築生命週期碳排放流程
建築生命週期碳排放流程

Decarbonize Buildings
with Digital Twins

Implementing Real-world Physical Simulation

Develops a dedicated digital twin model using real-world physical data for fast calculations and analysis of various outcomes

Optimizing Design and Management Processes

Simulating building heat transfer and analyzing airflow during the building design phase to meet high performance and comfort indicators

Predicting Building Operational Risks

Forecasting equipment failures and maintenance needs and using AI to detect anomalies to provide early warning alerts

CO2

Predictive Control of HVAC Equipment to Achieve Near-Zero Carbon Emissions

Integrating real-time weather conditions into calculation to determine the best equipment operation strategies. Connecting the equipment directly to the central control system for large-scale calculations and control to enable long-term energy efficiency and near-zero carbon management for buildings

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Enhanced Decision-Making and Reduced Additional Costs

Integrating smart building data with environmental monitoring devices to improve management efficiency and save time and costs

Applications of Digital Twins

Fault Detection and Diagnosis (FDD) of Equipment /

Evaluating equipment’s environmental control efficiency and energy performance while predicting potential equipment issues such as aging, failures, and other issues

數位雙生的應用 設備錯誤偵知診斷(FDD)
數位雙生的應用 智慧控制(空間舒適度、預冷控制、新風引入控制)

Smart Control (Spatial Comfort, Pre-Cooling, Fresh Air Intake) /

 Creating AI-specific models for scenario-based calculations and optimizing control through remote management of HVAC, outdoor air, and shading equipment

Carbon Management System (Future Carbon Emissions) /

Calculating past, current, and future carbon emissions in various areas of a building by inputting its historical data, including predicting carbon emissions related to materials, activities and energy consumption.

數位雙生的應用 碳排管理系統(未來碳)

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