Energy consumption prediction methods for embedded systems

Abstract

Human surrounding environment parameters are gathered regularly from electrical signals which are converted to digital signal using ADC converters and performing necessary data transformations. The gathered environment data can be estimated as a time series to apply standard statistical models. In this study, there are analyzed statistical models that help understand data and find consistent patterns-trends to make predictions depending on all previous data. Energy consumption data processing prediction methods were analyzed and presented. Dependency on time series analysis' results when using task management with prediction parameters is the special feature of designed measurement system. Transition from one state to another includes not only estimates of the previous and current states, but also a prediction state.