Goal:
Enable heavy industrial plants (steel, cement, chemicals, mining) to monitor emissions, cut energy waste, and meet ESG commitments — without disrupting production.
Impact Keywords:
Approach:
LunarTech Lab deployed an integrated analytics platform to quantify emissions, predict process inefficiencies, and recommend optimal control actions.
Real-Time Emissions Monitoring:
Combined sensor streams with external climate data to quantify CO₂ and particulate output per production unit.
Process Optimization Models:
Built AI models that fine-tune furnace, kiln, and boiler parameters to minimize energy waste while maintaining product quality.
Material Substitution Simulation:
Developed a “green materials simulator” that tests alternative input mixes (e.g., green cement additives) for lower carbon intensity.
Predictive Energy Forecasting:
Linked AI forecasting with energy procurement systems to shift high-energy tasks during low-tariff hours or renewable surplus.
ESG Automation:
Generated compliance-ready reports aligned with global frameworks (EU ETS, ISO 14064, Saudi Green Initiative).
Summary:
This solution transformed industrial plants into data-driven, low-carbon operations — cutting emissions up to 20%, energy use by 15%, and aligning ESG performance with investor expectations.
