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AI system disaggregates smart meter data to identify appliance energy use

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a novel system to break down domestic smart meter electricity usage data into specific appliance categories. This method combines event detection for high-power appliances with questionnaire-guided estimation, offering a label-free approach. Evaluations on multiple datasets, including a large Irish consumer dataset, show this hybrid method outperforms existing systems in accuracy and provides actionable advice for energy consumption patterns and cost reduction. AI

IMPACT Enables more granular energy consumption insights for consumers and utilities, potentially driving efficiency and cost savings.

RANK_REASON This is a research paper detailing a new AI methodology for energy data analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI system disaggregates smart meter data to identify appliance energy use

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This is a research paper detailing a new AI methodology for energy data analysis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Achal Nanjundamurthy, Rupam Misra, Suzanne Little, Alan F. Smeaton ·

    Questionnaire-Guided Disaggregation of Energy Appliance Use for Domestic Smart Meter Data

    arXiv:2610.01297v1 Announce Type: new Abstract: Ireland's smart metering programme records electricity use at 30-minute resolution, with smart meters installed in over 80\% of households as of late 2025. While this is useful for billing of smart, time-of-use tariffs, it is too co…

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