Building Management Workflow Automation with AI
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Solution Overview
Problem
Existing building management systems face challenges in generating precise data for service operations due to the loss and separation of data across the building lifecycle phases, leading to difficulties in identifying appropriate response actions and sequences for equipment maintenance, technical issues, and timely data availability.
Innovation Solution
A method that collects building lifecycle data from multiple sources, uses AI models to augment workflows by incorporating up-to-date enterprise data and equipment history, and generates insights to modify workflows dynamically, providing a knowledge set for building management systems that anticipates user requests and supports physical operations through a graphical user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If building lifecycle data is collected from multiple sources over time, then the completeness and accuracy of service operation data is improved, but the complexity of data management and processing increases
Solution Approach 1:
The patent segments the building lifecycle data into distinct phases (commissioning, operation, maintenance, decommissioning) and organizes it in a structured workflow format. This segmentation allows the system to manage complex data from multiple sources by breaking it down into manageable chunks that can be processed systematically through the AI model, reducing overall data management complexity while maintaining completeness and accuracy.
Solution Approach 2:
The patent introduces an AI model as an intermediary between the collected building lifecycle data and the workflow generation process. This intermediary automatically processes, contextualizes, and transforms raw data from multiple sources into actionable workflow instructions, thereby managing data complexity while improving data accuracy for service operations.
2Measurement precision
If AI models are used to augment workflows with additional content, then the precision of service operation responses is improved, but the computational resources and processing time required increase
Solution Approach 1:
The patent performs preliminary actions by pre-collecting and structuring building lifecycle data from multiple sources before service operations are needed. The AI model processes and contextualizes this pre-available data to generate augmented workflows, reducing the computational burden during actual service operations while maintaining high precision in response actions.
Solution Approach 2:
The patent applies partial action by selectively processing only the portions of building lifecycle data that are relevant to the current service operation through the AI model. Rather than processing all historical data, the system identifies and processes only the necessary subsets, thereby reducing computational resource consumption while maintaining sufficient precision for accurate service responses.
3Adaptability or versatility
If workflows are dynamically modified based on real-time data and enterprise data, then the adaptability of service operations is improved, but the complexity of workflow management increases
Solution Approach 1:
The patent implements feedback mechanisms where the AI model continuously monitors service operation progress and compares it against the augmented workflow. Based on this feedback and real-time building data, the workflow is dynamically adjusted to accommodate changing conditions, improving service adaptability while the systematic feedback loop manages workflow complexity through automated adjustments.
Solution Approach 2:
The patent makes the workflow dynamic by enabling it to automatically adapt to real-time building data and service conditions through AI-driven modifications. The workflow transitions from a static plan to a living document that continuously updates based on actual service progress and changing building conditions, improving adaptability while the automated nature of the changes manages management complexity.
4Quantity of substance
If data is collected and processed across all building lifecycle phases, then the availability of comprehensive service information is improved, but the time required for data gathering and processing increases
Solution Approach 1:
The patent performs preliminary data collection and processing actions during the commissioning and operation phases of the building lifecycle. By gathering and structuring essential service information early when systems are most accessible, the system reduces the time needed for data gathering during maintenance and decommissioning phases, while still achieving comprehensive service information availability.
Solution Approach 2:
The patent maintains continuous data collection and processing actions throughout the building lifecycle, ensuring that service information is always available and up-to-date. This continuous approach, combined with automated AI processing, eliminates gaps in data availability while the automation reduces the time investment required for data gathering across all phases.
Data Source
AI summary
A method of servicing a building can include creating a workflow for a service by stitching building lifecycle data together with enterprise data from a plurality of sources, augmenting the workflow by stitching, into the workflow using at least one AI model, specific information associated with an object involved in the service, and facilitating completion of the service in accordance with the augmented workflow by guiding a user through the augmented workflow.