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A Survey on Semantic Modeling for Building Energy Management

Miracle Aniakor, Vinicius V. Cogo, Pedro M. Ferreira

TL;DR

The paper addresses the challenge of heterogeneous building data hindering scalable energy management by surveying semantic modeling approaches in the building operation domain. It analyzes core ontologies—BOT, SAREF, SSN/SOSA, Brick, and PH—and their extensions, and categorizes use cases into single-, two-, and multiple-ontology scenarios to illustrate practical interoperability gains. Key findings show that while these ontologies enable modular, interoperable representations and enable data-driven energy analysis, fragmentation and lack of a unified modeling philosophy hinder broader adoption. The work highlights the need for coordinated ontology development, standardized practices, and energy-flexibility modeling to advance practical, context-aware BEM solutions with real-world impact.

Abstract

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.

A Survey on Semantic Modeling for Building Energy Management

TL;DR

The paper addresses the challenge of heterogeneous building data hindering scalable energy management by surveying semantic modeling approaches in the building operation domain. It analyzes core ontologies—BOT, SAREF, SSN/SOSA, Brick, and PH—and their extensions, and categorizes use cases into single-, two-, and multiple-ontology scenarios to illustrate practical interoperability gains. Key findings show that while these ontologies enable modular, interoperable representations and enable data-driven energy analysis, fragmentation and lack of a unified modeling philosophy hinder broader adoption. The work highlights the need for coordinated ontology development, standardized practices, and energy-flexibility modeling to advance practical, context-aware BEM solutions with real-world impact.

Abstract

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.
Paper Structure (22 sections, 6 figures, 1 table)

This paper contains 22 sections, 6 figures, 1 table.

Table of Contents

  1. Introduction
  2. Research Methodology
  3. Context and Background
  4. Digitization of Building Data
  5. The Advent of Semantic Modeling Technologies in Building's Operation Phase
  6. Ontologies and Semantic Web
  7. Identifying Core Concepts in Building Operational Ontologies
  8. Semantic Models
  9. Core Semantic Models
  10. BOT---Building Topology Ontology
  11. SAREF---Smart Applications REFerence Ontology and its Extensions
  12. SSN---Semantic Sensor Network and SOSA---Sensor, Observation, Sample, and Actuator
  13. Brick
  14. PH---Project Haystack
  15. Others
  16. ...and 7 more sections

Figures (6)

  • Figure 1: BEM Applications Framework
  • Figure 2: Key components of semantic data modeling and interoperability in smart environments.
  • Figure 3: Representation of Building Topology by BOT (image from botOntology).
  • Figure 4: Overview of core SAREF ontology (image from sarefcore.
  • Figure 5: Integrating Building Data with Observation and Sensor Data Utilizing SOSA/SSN (image from haller2019modular).
  • ...and 1 more figures