Green AI Framework Data For Sustainable Energy Systems

Green AI is a framework integrating AI, blockchain, and IoT to address sustainability issues in energy systems. The dataset, 2.4 MB in size and authored by Di Wu, was last updated in March 2026. It supports a scalable architecture for enhancing energy efficiency and reducing carbon emissions.

Use Cases

• Model energy demand estimation using historical and real-time data from smart grids.
• Analyze carbon emission reductions by correlating data from environmental sensors and energy market transactions.
• Train algorithms for renewable energy integration optimization using IoT device streams.
• Audit energy transaction transparency and accountability via blockchain-managed data logs.

Strengths

• Framework integrates three distinct technologies (AI, blockchain, IoT) for a unified approach.
• Data is shared under a permissive CC-BY-4.0 license for broad reuse.

Limitations

• The dataset is small at 2.4 MB, suggesting limited scope or a proof-of-concept scale.
• Specific data volume (row count) and granular features like column names are unknown.
• Recency of the underlying source data is unclear, potentially limiting temporal analysis.

Provenance

Source

Di Wu via figshare.

Collection Method

Proposed framework data; likely synthesized or simulated from smart grids, environmental sensors, and energy markets.

Freshness

Metadata indicates a last update in March 2026, suggesting forward-looking or projected data.