Automated Building Schema Mapping via Graph Data Structures
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Solution Overview
Problem
Building management systems face difficulties in updating from one schema to another due to the lack of direct mapping between different schemas, requiring excessive user intervention and expert knowledge, which hinders the transition process.
Innovation Solution
A building schema mapping system that receives strings in a first schema, extracts relationships, labels them based on characters, and generates a graph data structure in a second schema, using a dictionary for character mapping and user input to assign tags, facilitating the translation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a building management system is updated to operate on data according to a second schema, then the system can benefit from improved data representation and functionality, but the lack of direct mapping between the first schema and the second schema makes the transition difficult and requires excessive user intervention
Solution Approach 1:
The patent introduces an automated schema mapping system that acts as an intermediary between the first schema (BACnet/METASYS) and the second schema (BRICK/graph schema). This system automatically translates data points, equipment, and spaces from the legacy schema to the new schema using dictionary-based character matching and relationship extraction, eliminating the need for manual expert intervention in the mapping process.
Solution Approach 2:
The patent replaces the manual, expert-knowledge-based schema mapping process with an automated computational system. The system uses algorithms to extract relationships from data strings, match characters to predefined tags using dictionaries, and generate graph data structures automatically, substituting human expertise with machine-based automated translation.
2Measurement precision
If expert knowledge is required to understand what each string represents in the first schema, then accurate interpretation is achieved, but the update process becomes time-consuming and requires excessive user intervention
Solution Approach 1:
The schema mapping system performs self-service by automatically interpreting and translating data strings without requiring external expert knowledge. The system uses predefined dictionaries that map character patterns to semantic tags, enabling autonomous translation of BACnet/METASYS data points into BRICK schema equivalents, thereby eliminating the time cost of manual expert analysis.
Solution Approach 2:
The patent employs preliminary action by pre-defining dictionaries that contain mappings between character patterns in the first schema and semantic tags in the second schema. These dictionaries are prepared in advance, allowing the system to quickly match and translate data strings during the update process without requiring real-time expert interpretation.
3Manufacturing precision
If manual mapping between schemas is performed, then mapping accuracy can be ensured, but processing time increases and productivity decreases
Solution Approach 1:
The patent replaces manual mapping operations with automated computational processes. The system uses algorithmic relationship extraction from data strings, dictionary-based character matching, and automated graph data structure generation, achieving both accuracy through systematic rules and high productivity through automation.
Solution Approach 2:
The patent changes the parameters of the mapping process by transforming it from a manual, expert-driven operation to an automated, rule-based system. The system modifies the translation parameters by using predefined character-to-tag mappings and automated relationship extraction rules, enabling fast and accurate schema translation simultaneously.
Data Source
AI summary
A building schema mapping system, the system including one or more memory devices configured to store instructions, that, when executed by one or more processors, cause the one or more processors to receive strings in a first schema, each string representing at least one of a point, building equipment, or a building space, extract relationships from the strings, each relationship of the relationships indicating a particular relationship between a first string of the strings and a second string of the strings, label each of the strings based on characters of each of the strings, and generate a graph data structure of a second schema based on the relationships and the label of each of the strings.