AI Based Predictive Carbon Footprint Reduction System for Household Electronic Devices

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Key Points

The aim is to develop an AI-based system for predicting and reducing carbon footprints from household electronic devices.
Developed a predictive modeling system using AI for household energy consumption analysis.
Implemented the system across various household scenarios to evaluate effectiveness.
Analyzed data to assess changes in carbon footprint before and after implementing the AI system.
Achieved an average carbon footprint reduction of 20% in households after AI system integration (p<0.05).
Demonstrated a significant reduction in energy consumption metrics across assessed devices (RR 0.80, 95% CI 0.70-0.90, p=0.001).
Identified key electronic devices contributing to carbon emissions, facilitating targeted interventions.

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Demonstrates carbon footprint reduction in households, suggesting effective AI implementation.

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Bhuvan et al. (2026) studied this question.

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