ML Based Strategy for Optimal Power Prediction in IoT

Internet of Things (IoT) enabled sensors are extensively used for industrial, agriculture, health care and many more application. The primary concern of IoT devices are energy consumption in data gathering and forwarding over Internet due to heterogeneous nature of sensing information. This is because of IoT sensors are often deployed in the monitoring area for several years where human intervention is extremely difficult subject to analyze the environment. In this paper, we predict the energy consumption using various Machine Learning (ML) strategies based on regression model and predict the abnormalities and power usage of inside building or company or inaccessible area. Further, performance is analyzed for heterogeneous resources of data over different version of machine learning algorithm. Furthermore, sophisticated predictive version of machine learning algorithm is selected for different application.