Energy consumption prediction methods for embedded systems

Evaldas Zulkas, Edgaras Artemciukas, Dale Dzemydiene, Eleonora Guseinoviene

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publication2015 10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781467367844
DOIs
Publication statusPublished - Jun 11 2015
Externally publishedYes
Event10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015 - Monte-Carlo, Monaco
Duration: Mar 31 2015Apr 2 2015

Other

Other10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015
CountryMonaco
CityMonte-Carlo
Period3/31/154/2/15

Fingerprint

Embedded systems
Energy utilization
Time series analysis
Time series
Statistical Models

Keywords

  • ARMA model
  • Data acquisition
  • Energy consumption
  • Energy forecasting
  • Kalman filter

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Automotive Engineering
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

Zulkas, E., Artemciukas, E., Dzemydiene, D., & Guseinoviene, E. (2015). Energy consumption prediction methods for embedded systems. In 2015 10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015 [7112932] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EVER.2015.7112932

Energy consumption prediction methods for embedded systems. / Zulkas, Evaldas; Artemciukas, Edgaras; Dzemydiene, Dale; Guseinoviene, Eleonora.

2015 10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7112932.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zulkas, E, Artemciukas, E, Dzemydiene, D & Guseinoviene, E 2015, Energy consumption prediction methods for embedded systems. in 2015 10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015., 7112932, Institute of Electrical and Electronics Engineers Inc., 10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015, Monte-Carlo, Monaco, 3/31/15. https://doi.org/10.1109/EVER.2015.7112932
Zulkas E, Artemciukas E, Dzemydiene D, Guseinoviene E. Energy consumption prediction methods for embedded systems. In 2015 10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7112932 https://doi.org/10.1109/EVER.2015.7112932
Zulkas, Evaldas ; Artemciukas, Edgaras ; Dzemydiene, Dale ; Guseinoviene, Eleonora. / Energy consumption prediction methods for embedded systems. 2015 10th International Conference on Ecological Vehicles and Renewable Energies, EVER 2015. Institute of Electrical and Electronics Engineers Inc., 2015.
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