Green AI Framework Metrics for Energy and Carbon Management

176.5 KB of data underpins a proposed Green AI framework integrating blockchain and IoT for sustainable energy systems. Author Di Wu published this conceptual model and its associated metrics in March 2026. The framework aims to enhance energy efficiency and reduce carbon emissions through intelligent technology.

Use Cases

• Analyze energy_efficiency metrics from smart grid data to benchmark Green AI framework performance.
• Model carbon_emissions reductions based on renewable_energy_integration and demand_estimation algorithms.
• Validate blockchain_secured data transparency using real-time IoT sensor readings from environmental_monitoring networks.

Strengths

• Framework proposes integration of three major technologies: AI, blockchain, and IoT.
• Clear focus on specific sustainability outcomes: energy efficiency and carbon emission reduction.

Limitations

• Dataset scale is limited at 176.5 KB, indicating a conceptual or small-scale proof-of-concept.
• No sample data or column details are provided to validate the proposed metrics or models.
• Temporal and geographic coverage of the underlying data is unspecified.

Provenance

Source

Di Wu via figshare.

Collection Method

Conceptual framework proposal; specific data collection method not detailed.

Freshness

Last updated March 2026.