LAPSE:2023.15854
Published Article
LAPSE:2023.15854
A Novel Strategy for Smart Building Convergence Based on the SmartLVGrid Metamodel
March 2, 2023
Smart buildings provide opportunities for technological transformations in building environments to improve resource management, comfort, and efficiency of the systems present in these facilities. For this, Internet of Things (IoT) solutions contribute, with monitoring and remote control features, to automate these environments. However, these solutions can promote the disposal or replacement of outdated but still-needed legacy systems. Thus, a reference model that uses retrofit techniques to update pre-existing systems would be an alternative to enable smart building convergence. The lack of models that advocate this type of strategy provides an opportunity for the emergence of methods capable of filling this gap. Thus, this work presents a strategy for implementing monitoring, control, and communication resources to achieve smart building convergence in legacy building systems. This strategy consists of the use of retrofit techniques based on the adaptation of the SmartLVGrid metamodel. To validate this proposal, we developed hardware platforms and, respectively, their firmware to implement the premises established in a legacy building lighting circuit. The results obtained present a new possibility of implementing smart buildings from the retrofit of legacy infrastructures, as the pre-existing building lighting circuit obtained new functionalities and was preserved as much as possible.
Keywords
embedded platforms, Internet of Things, interoperability, middleware, retrofit, smart buildings, SmartLVGrid
Suggested Citation
Fernandes RA, Gomes RCS, Dias O, Carvalho C. A Novel Strategy for Smart Building Convergence Based on the SmartLVGrid Metamodel. (2023). LAPSE:2023.15854
Author Affiliations
Fernandes RA: Department of Electricity, Federal University of Amazonas, Manaus 69067-005, Brazil; Embedded Systems Laboratory, State University of Amazonas, Manaus 69050-020, Brazil; Programa de Pós-Graduação em Engenharia Elétrica−PPGEE, Federal University of A [ORCID]
Gomes RCS: Embedded Systems Laboratory, State University of Amazonas, Manaus 69050-020, Brazil [ORCID]
Dias O: Department of Electricity, Federal University of Amazonas, Manaus 69067-005, Brazil; Programa de Pós-Graduação em Engenharia Elétrica−PPGEE, Federal University of Amazonas, Manaus 69067-005, Brazil [ORCID]
Carvalho C: Programa de Pós-Graduação em Engenharia Elétrica−PPGEE, Federal University of Amazonas, Manaus 69067-005, Brazil; Departamento de Eletrônica e Computação−DTEC, Federal University of Amazonas, Manaus 69067-005, Brazil; Centro de P&D em Tecnologi [ORCID]
Journal Name
Energies
Volume
15
Issue
3
First Page
1016
Year
2022
Publication Date
2022-01-29
Published Version
ISSN
1996-1073
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Original Submission
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PII: en15031016, Publication Type: Journal Article
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LAPSE:2023.15854
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doi:10.3390/en15031016
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Mar 2, 2023
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