Building Twin Function Processing With Context-Aware Event Triggers
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Solution Overview
Problem
The existing building data processing systems require users to manually review and identify necessary data elements from retrieved data sets, leading to inefficiencies and potential errors in processing building data.
Innovation Solution
A building system that receives queries with context parameters, automatically retrieves relevant data, performs processing operations based on the context, and generates a response without requiring user input, utilizing a data storage system like a building graph to identify processing operations and execute twin functions dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually review and identify necessary data elements from retrieved data sets, then data processing accuracy can be maintained, but processing efficiency deteriorates and user workload increases
Solution Approach 1:
The system performs self-service by automatically identifying and executing necessary processing operations on retrieved data without requiring user intervention. The building system autonomously determines what processing is needed based on the query context and automatically performs those operations, eliminating the manual review step while maintaining accuracy through systematic automated processing logic
Solution Approach 2:
The system performs preliminary action by pre-defining and storing multiple processing operations that can be automatically selected and executed. These processing operations are prepared in advance and can be triggered automatically based on query parameters and context, eliminating the need for users to manually identify and execute operations at query time
2Reliability
If users manually identify and trigger processing operations, then processing accuracy is maintained, but time consumption increases
Solution Approach 1:
Processing operations are defined and prepared in advance within the system. When a query is executed, the system automatically selects and triggers the appropriate pre-defined operations based on the query context, eliminating the time users would spend identifying and manually triggering operations while maintaining reliability through systematic selection logic
Solution Approach 2:
The system uses feedback from query parameters and context to automatically determine which processing operations to execute. This closed-loop approach ensures that the correct operations are selected based on the specific query requirements, maintaining processing reliability while eliminating manual intervention time
3Productivity
If the system automatically performs processing operations without user input, then processing efficiency improves, but system complexity increases
Solution Approach 1:
The system implements a universal query processing framework that can handle multiple types of processing operations through a single automated mechanism. The same infrastructure supports retrieving data, selecting operations, executing processing, and returning results, reducing the need for separate complex systems for each function while maintaining high processing efficiency
4Ease of operation
If the system requires user input to identify processing operations, then ease of operation is maintained, but productivity deteriorates
Solution Approach 1:
The system performs self-service by automatically determining and executing necessary processing operations based on query context. Users simply need to submit their data retrieval queries, and the system handles all processing decisions autonomously, maintaining ease of operation while dramatically improving productivity through eliminated manual steps
Data Source
AI summary
One implementation of the present disclosure is a building system of a building including one or more memory devices having instructions stored thereon, that, when executed by one or more processors, cause the one or more processors to receive a selection including a context and a twin function and generate an operation to monitor a building graph based on the context, the operation identifying whether one or more new events are added to the building graph, the one or more new events affecting a processing result. The instructions cause the one or more processors to cause the twin function to execute responsive to identifying the one or more new events added to the building graph that affect the processing result, execute the twin function based on the one or more new events and the context to generate the processing result.