Energy Efficient Smart Working Environment using Internet of Things

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.