DT Platform: Core Engine for 3D Modeling & VR Integration

Amid digital & intelligent transformation, 3D modeling is key to integrating physical & information spaces. We provide high-precision, full-element, interactive 3D digital bases for smart cities, industrial IoT, and smart parks, enabling visual-to-manageable transition and supporting closed-loop business-driven DT systems.

I. Reshaping Digital Platform Architecture with 3D Modeling

Traditional 2D management systems struggle with multidimensional, complex modern business scenarios. Information silos, poor visibility, and difficult data integration hinder digital transformation. Based on 3D modeling, we build 1:1 mapped digital twins to fully digitize physical objects, relationships, and business processes, upgrading digital platforms from "management tools" to "decision engines".

II. Full-Element, Multi-Resolution, Interactive 3D Digital Twins

We provide multi-level modeling capabilities covering "macro-meso-micro" scales, deeply integrating business data and real-time dynamics to enable full-scenario support from city-level management to equipment-level maintenance.

1. Multi-Level Modeling for Business Granularity

• City/Campus Level: Uses oblique photography and GIS data to quickly build geographic environment and building outline models for regional planning and macro-analysis.

• Building/Workshop Level: Employes BIM and reality modeling to restore structures, pipelines, and layouts, supporting integrated management of energy, security, and other systems.

• Equipment/Component Level: High-precision modeling of key equipment for real-time status monitoring, disassembly simulation, and fault prediction.

2. Multi-Source Data Fusion for Models as Dashboards

• Integrates IoT real-time data and business system info with dynamic 3D model binding for visualized display of device parameters, energy consumption, alerts, etc.

• Supports attribute query, spatial search, and data drilling (e.g., "filter all abnormal devices in a region") to improve operational efficiency.

3. High Compatibility & Lightweight for Cross-Platform Embedding

• Models are professionally lightweighted with over 80% compression ratio, supporting smooth loading of tens of millions of components.

• Offers standard APIs for quick integration with mainstream digital platforms like Huawei Cloud, Alibaba Cloud, Azure, and multi-terminal access.

III. Key Tech Implementation: End-to-End Digital Twin Capabilities

1. Intelligent Acquisition & Reconstruction

• Uses laser point cloud scanning and UAV oblique photography for millimeter-level restoration of large-scale scenes.

• Supports BIM forward design and reverse modeling, compatible with multi-format data import (Revit, AutoCAD, etc.).

2. Visualization & Business Integration

• Develops visual components based on engines like Three.js, Cesium, Unity for model interaction, scene roaming, and simulations.

• Provides spatial analysis (visibility, sunlight, measurement), dynamic labeling, simulation, and other extended tools.

3. Continuous Model Lifecycle O&M

• Establishes version management and collaborative update mechanisms for full-cycle digital twin management from design to O&M.

• Offers model hosting and iteration services to ensure alignment with business changes.

IV. Typical Application Scenarios

V. Core Advantages

• High Precision & Strong Restoration: Supports multi-level accuracy from cm to mm, truly reproducing physical details.

• Fast Response & Optimal Experience: Loads models with tens of millions of polygons in under 15s, smoothly supporting multi-end interaction.

• Open Integration & Easy Expansion: Provides standard interfaces and development support for flexible adaptation to various business systems.

• Full-Cycle Service: From requirement alignment to model O&M, offering sustainable digital twin asset management.

VI. Implementation Process: 5 Steps to Build a Digital Twin Base

1. Requirement Alignment (1-2 weeks): Define modeling scope, precision levels, and core business scenarios.

2. Data Integration (2-4 weeks): On-site collection and multi-source data governance.

3. Model Construction (4-8 weeks): Hierarchical modeling, attribute mapping, and coordinate calibration.

4. System Integration (2-3 weeks): API development, business linkage, and UI embedding.

5. Delivery & O&M (1 week): Training, documentation handover, and after-sales support.

VII. Outlook: Beyond Visualization Towards Intelligent Decision-Making

Digital twins are not just mirrors of the real world but core infrastructure for simulation, prediction, and optimization. We will further integrate AI simulation and real-time control to build an intelligent twin ecosystem with integrated "perception-analysis-decision-execution", helping clients achieve true closed-loop management and business innovation.

Let's collaborate to move from digital mapping towards an intelligent future.