A carbon-aware ML training scheduling system that optimises machine learning workloads using real-time UK grid carbon intensity data. It simulates ML training, finds optimal low-carbon execution windows, and visualises carbon savings through an interactive multi-page Streamlit analytics dashboard.
QField plugin for coordinate conversion and navigation — supports Irish Grid, UK Grid, MGRS, Plus Code, and custom EPSG CRS. Captures screen centre or GPS position, generates/scans geo: QR codes, and adds grid reference search to the QField locator bar.
Live UK grid carbon-intensity forecasting: 48h ML forecast benchmarked against NESO in public, marginal emissions, and a carbon-vs-price 'best time to run' scheduler. Next.js + scikit-learn + Postgres, fully automated at zero cost.
Carbon-aware charging calculator using live UK National Grid data. Built for the MMU Sustainable Computing Hackathon 2026.
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