arXiv:2606.17637v1 Announce Type: new Abstract: Building Management Systems (BMS) are essential for optimizing energy efficiency and operational performance in modern buildings. However, the lack of standardization across BMS points from different manufacturers creates significant barriers to integration and data utilization. While the Brick schema offers a standardized ontology for building systems, mapping BMS points to appropriate Brick classes presents three critical challenges: (i) the extensive number of Brick classes (936 in the latest version), (ii) limited domain-specific knowledge in
The proliferation of Building Management Systems and the increasing complexity of smart buildings necessitate automated solutions for data standardization, making this development timely.
This development addresses a critical barrier to efficient building management and data utilization by automating the mapping of diverse BMS points to a standardized schema, enhancing operational efficiency and energy optimization.
The prior manual and error-prone process of standardizing BMS data is now significantly automated and improved through dynamic in-context learning.
- · Smart building operators
- · Building Management System providers
- · Energy efficiency companies
- · AI/ML solution providers
- · Manual data mapping consultancies
- · Legacy BMS integration methods
Automated integration of diverse building control systems becomes significantly easier and more cost-effective.
Improved data standardization enables advanced analytics and AI applications for predictive maintenance and optimized resource allocation across entire building portfolios.
The widespread adoption of standardized building ontologies could accelerate the development of autonomous building operations and a more interconnected urban infrastructure.
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Read at arXiv cs.AI