In the paper,a urban household energy efficiency management system is proposed that can provide both energy efficiency and meet residents' needs.Three prediction mechanisms are proposed for deriving comfortable temperatures,predicting sleep without devices,and predicting going out based on occupancy probability.Based on these mechanisms,four intelligent heater control strategies are proposed:going out,occupancy,comfort,and sleep-based control.Finally,an experiment test platform is constructed and evaluated,and over a 48-day evaluation period,the system achieved an energy saving rate of approximately 14% and a resident satisfaction rate of approximately 91%.The results show that the system can save energy while maintaining high satisfaction levels.
Key words
IoT /
smart home /
AI-HEMS
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