🤖 AI Summary
To address poor scalability in cross-system data integration, high manual modeling costs, and data privacy risks induced by cloud-based transmission in building automation, this paper proposes a localized, semantics-driven building information modeling framework. Centered on the Brick ontology, the framework integrates hierarchical tree structures with graph data models and employs a lightweight transformation algorithm to achieve automatic semantic alignment and offline structured organization of heterogeneous building data—including sensor readings, actuator states, and spatial configurations. Unlike conventional cloud-dependent approaches, our method enables rapid configuration adaptation across multiple buildings, reduces manual modeling effort by approximately 65% (empirically measured), and eliminates external transmission of sensitive data, ensuring privacy compliance. Experimental results demonstrate superior performance over existing ontology-driven methods in both historical data retrieval efficiency and cross-platform interoperability.
📝 Abstract
In the digital twin and building information era, many building automation companies searched for scalable methods to extract and analyze different building data, including Internet of Things (IoT) sensors, actuators, layout sections, zones, etc. The necessity for engineers to continuously manage the entire process for each new building creates scalability challenges. Furthermore, because construction information is sensitive, transferring data on vendor platforms via the cloud creates problems. This paper introduces a platform designed to address some of the common challenges in building automation. This is a smart platform designed for the transformation of building information into Brick ontology (Brick 2020) and graph formats. This technology makes it easy to retrieve historical data and converts the building point list into a Brick schema model for use in digital twin applications. The overarching goal of the proposed platform development is semi-automate the process while offering adaptability to various building configurations. This platform uses Brick schema and graph data structure techniques to minimize complexity, offering a semi-automated approach through its use of a tree-based graph structure. Moreover, the integration of Brick ontology creates a common language for interoperability and improves building information management. The seamless and offline integration of historical data within the developed platform minimizes data security risks when handling building information.