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This study presents Q-GRID SMART, a decentralized, blockchain-enabled residential energy management platform integrating IoT-based monitoring, predictive analytics, and an interactive user dashboard. In a one-month pilot across 4,196 households in Doha, Qatar, machine learning models (GRU, Bi-LSTM) forecasted energy consumption, cost, and CO 2 emissions with RMSE = 160.9 kWh and MAE = 120.3 kWh. Post-deployment surveys (n = 312) indicated a Net Promoter Score of +42 and 87% reported improved energy awareness. The platform achieved an average 16.8% electricity reduction and 145.4 kg CO 2 savings per household per month. We further analyze how blockchain latency and confirmation times affect real-time control and user experience, proposing mitigation via edge control loops, batching, and Layer-2 solutions (state channels, rollups). These results demonstrate Q-GRID SMART's potential to deliver scalable, secure, and user-centric energy management solutions for utilities and households. • Blockchain-enabled secure smart home energy trading. • Achieved 16.8% energy use cut in 4,000+ real houses. • Real-time cost, CO2 forecasts with dashboard feedback. • Comparative validation with existing smart grid systems.
Ameni Boumaiza (Thu,) studied this question.
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