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International Net-Zero Standards Integration
Enterprise Carbon Emissions & Energy Management
Energy Usage and Efficiency Management
Helps enterprises gain full visibility into electricity and energy consumption across equipment, production lines, and sites—identifying high-energy-use areas and optimization opportunities to reduce waste and carbon emissions at the source.
Aligned with international standard: ISO 50001 | Energy Management Systems
IoT-Based Building Management Systems
Incorporates environmental factors such as temperature, humidity, and equipment operation into analysis—helping enterprises identify hidden energy waste caused by overcooling, excessive HVAC use, or improper settings, and further optimize operational efficiency.
Aligned with international standard: ISO 50001 | Energy Management Systems
Enterprise Carbon Accounting and Management
Conducts organization-level greenhouse gas inventories based on international accounting principles, covering direct and energy-related emissions to establish a consistent and verifiable carbon management foundation.
Aligned with international standard: ISO 14064-1 | Organizational GHG Inventory
From Measurement to Management: Building Actionable Decarbonization Pathways
Carbon and Energy Monitoring System
Intelligent Decarbonization Workflow
Data Collection
Collects time-series data—such as electricity usage, indoor temperature, and equipment operation—via smart meters and IoT devices to establish a foundation for energy efficiency.
Model Inference
LLM-based semantic analysis transforms language understanding into actionable energy behavior decision models.
Intelligent Reporting
Automatically generates decarbonization analysis reports and action recommendations, supporting emissions tracking and continuous optimization to effectively execute sustainability strategies.
AI Model Training
LLM Model Applications
Foundational Understanding
Builds core semantic understanding from large-scale textual data such as energy-saving guidelines, consumption patterns, and government policies.
Task Fine-Tuning
Enhances model capabilities in energy efficiency, carbon behavior prediction, and recommendation generation.
Feedback Calibration
Refines outputs based on real-world or preferred feedback to generate more actionable and context-appropriate recommendations.
Real-World Deployment
Deploys trained models into live environments to automatically generate site-specific decarbonization recommendation reports based on prompt-driven workflows.
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