Anastasios Vafeiadis, T. Vafeiadis, Stelios Zikos, S. Krinidis, K. Votis, Dimitrios Giakoumis, D. Ioannidis, D. Tzovaras, Liming Luke Chen, R. Hamzaoui
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Energy-based decision engine for household human activity recognition
We propose a framework for energy-based human activity recognition in a household environment. We apply machine learning techniques to infer the state of household appliances from their energy consumption data and use rule- based scenarios that exploit these states to detect human activity. Our decision engine achieved a 99.1% accuracy for real-world data collected in the kitchens of two smart homes.
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