AIApr 17, 2024

A Survey on Semantic Modeling for Building Energy Management

arXiv:2404.11716v13 citationsh-index: 1
Originality Synthesis-oriented
AI Analysis

It addresses energy efficiency in buildings, a major global energy consumer, by surveying existing methods without introducing new techniques, making it incremental.

This survey examines semantic modeling techniques for building energy management to address interoperability challenges from diverse device data representations, aiming to guide researchers in selecting appropriate models for various use cases.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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