Monitoring, Predicting, and Optimizing Energy Consumptions

Author:

Cardoso Pedro J. S.1ORCID,Monteiro Jânio2ORCID,Cabrita Cristiano3,Semião Jorge2ORCID,Cruz Dario Medina4ORCID,Pinto Nelson4ORCID,Ramos Célia M.Q.5ORCID,Oliveira Luís M. R.6,Rodrigues João M. F.1ORCID

Affiliation:

1. Universidade do Algarve, Portugal & LARSyS, Institute for Systems and Robotics, Lisbon, Portugal

2. Universidade do Algarve, Portugal & INESC-ID, Lisbon, Portugal

3. Universidade do Algarve, Portugal & Centre of Intelligent Systems, IDMEC, Portugal

4. Universidade do Algarve, Portugal

5. Universidade do Algarve, Portugal & CIEO, Portugal

6. Universidade do Algarve, Portugal & CISE, Portugal

Abstract

Energy consumption and, consequently, the associated costs (e.g., environmental and monetary) concern most individuals, companies, and institutions. Platforms for the monitoring, predicting, and optimizing energy consumption are an important asset that can contribute to the awareness about the ongoing usage levels, but also to an effective reduction of these levels. A solution is to leave the decisions to smart system, supported for instance in machine learning and optimization algorithms. This chapter involves those aspects and the related fields with emphasis in the prediction of energy consumption to optimize its usage policies.

Publisher

IGI Global

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Measures to Improve Health Performing of an Accommodation Building. A Study Case;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2023

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