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• W2954790647 abstract "In this paper, we present a concept base novel architecture for intelligent energy efficient applications using Internet of Things. This architecture provides the user-friendly and compatible environment, by predicting the set- point using machine learning techniques. We conduct a real-time implement on the testbed to verify the correctness of the system. Moreover, we have used three machine learning techniques (support vector machine, k-nearest neighbor, and linear regression) to predict the set-point for all the beneficiaries. We found that these techniques give up to 87.41976% accuracy for prediction of set-point. Additionally, we observe that with the use of this mechanism we can save up to 20% electricity consumption." @default.
• W2954790647 created "2019-07-12" @default.
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• W2954790647 date "2019-04-01" @default.
• W2954790647 modified "2023-09-29" @default.
• W2954790647 title "Energy Efficient Smart Working Environment Using Internet of Things" @default.
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• W2954790647 doi "https://doi.org/10.1109/vtcspring.2019.8746355" @default.
• W2954790647 hasPublicationYear "2019" @default.
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