A Survey on Semantic Modeling for Building Energy Management
Fuente:
arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913319825178624 |
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| author | Aniakor, Miracle Cogo, Vinicius V. Ferreira, Pedro M. |
| author_facet | Aniakor, Miracle Cogo, Vinicius V. Ferreira, Pedro M. |
| contents | Buildings account for a substantial portion of global energy consumption. Reducing buildings' energy usage primarily involves obtaining data from building systems and environment, which are instrumental in assessing and optimizing the building's performance. However, as devices from various manufacturers represent their data in unique ways, this disparity introduces challenges for semantic interoperability and creates obstacles in developing scalable building applications. This survey explores the leading semantic modeling techniques deployed for energy management in buildings. Furthermore, it aims to offer tangible use cases for applying semantic models, shedding light on the pivotal concepts and limitations intrinsic to each model. Our findings will assist researchers in discerning the appropriate circumstances and methodologies for employing these models in various use cases. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_11716 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Survey on Semantic Modeling for Building Energy Management Aniakor, Miracle Cogo, Vinicius V. Ferreira, Pedro M. Artificial Intelligence I.2.4; C.m; H.m Buildings account for a substantial portion of global energy consumption. Reducing buildings' energy usage primarily involves obtaining data from building systems and environment, which are instrumental in assessing and optimizing the building's performance. However, as devices from various manufacturers represent their data in unique ways, this disparity introduces challenges for semantic interoperability and creates obstacles in developing scalable building applications. This survey explores the leading semantic modeling techniques deployed for energy management in buildings. Furthermore, it aims to offer tangible use cases for applying semantic models, shedding light on the pivotal concepts and limitations intrinsic to each model. Our findings will assist researchers in discerning the appropriate circumstances and methodologies for employing these models in various use cases. |
| title | A Survey on Semantic Modeling for Building Energy Management |
| topic | Artificial Intelligence I.2.4; C.m; H.m |
| url | https://arxiv.org/abs/2404.11716 |