IoT Energy Consumption of Appliances
Catalog Summary
"Telemetry from smart plugs monitoring individual household appliances. Used for identifying energy-hungry devices and predictive load balancing."
Catalog Notes
Residential Energy Efficiency
This dataset tracks the energy consumption of kitchen appliances, HVAC systems, and lighting over a period of 4.5 months. It is essential for building Non-Intrusive Load Monitoring (NILM) systems.
Feature Set
- Power Metrics: Real power (Watts) and reactive power (VAR).
- External Factors: Outside temperature and humidity which drive HVAC usage.
- Time Factors: Weekday vs. weekend behavioral patterns.
Data Preview
| Date | Appliances_W | Lights_W | T_out | RH_out |
|---|---|---|---|---|
| 2024-01-11 17:00 | 60 | 30 | 6.60 | 92.0 |
| 2024-01-11 17:10 | 60 | 30 | 6.48 | 92.0 |
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Provided Citation
Candanedo, L. (2017). Appliances Energy Prediction [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5VC8G.
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Source metadata: External (2026)
Indexed by IoTDataset.com on Jan 14, 2026
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