Facility Asset Modeling With Automated Data Contextualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current building management systems rely on manual asset modeling and dashboard configuration by facility managers, which is time-consuming, error-prone, and leads to unoptimized resource utilization and incorrect operations.
Innovation Solution
An automated system that receives asset data, generates asset models, and configures dashboards using data models and contextualization to optimize asset management, reducing human intervention and enhancing resource efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual asset modeling and dashboard configuration is performed by facility managers, then asset models can be created and dashboards can be configured, but it consumes substantial time and human resources
Solution Approach 1:
The system enables automatic asset modeling by having the BMS self-configure asset models, points, and dashboards using sensor data and metadata without requiring manual intervention from facility managers. The system discovers assets automatically, infers their types based on sensor data patterns, and generates appropriate models and dashboards autonomously.
Solution Approach 2:
The patent replaces the manual mechanical process of asset modeling with an automated computational system. Instead of workers manually creating asset models and configuring dashboards, the system uses algorithms to automatically discover assets, contextualize sensor data, generate asset models, and configure dashboards based on the modeled assets.
2Ease of manufacture
If manual asset modeling is performed by workers, then asset models can be created, but errors may occur in assigning points and point roles for sensors
Solution Approach 1:
The system continuously monitors sensor data and uses feedback loops to validate and refine asset models. The BMS compares actual sensor readings against expected patterns for different asset types, automatically corrects misassignments, and updates asset models to maintain accuracy. This feedback mechanism ensures reliable point and point role assignments.
Solution Approach 2:
The patent replaces error-prone manual assignment of points and point roles with an automated computational system that uses sensor data analysis, metadata, and contextual information to accurately assign points to assets and determine their roles. The system cross-validates assignments against multiple data sources to ensure correctness.
3Productivity
If manual asset modeling is performed, then asset models can be created, but it requires substantial human resources and expertise
Solution Approach 1:
The system performs automatic asset discovery, classification, and model generation without requiring human operators. The BMS autonomously scans the facility, identifies assets based on sensor data patterns, determines asset types, and creates appropriate models, thereby eliminating the need for specialized human expertise in the modeling process.
Solution Approach 2:
The patent creates a universal automated system that can handle multiple asset types (HVAC equipment, lighting, security systems, etc.) using the same underlying technology. The system uses general-purpose algorithms for asset discovery, data contextualization, and model generation that work across diverse facility types and asset categories, reducing the need for specialized knowledge.
Data Source
AI summary
Various embodiments described herein relate to systems and methods for modelling assets in a facility. In this regard, data associated with the assets in the facility is initially received from the assets. Also, one or more data models associated with the assets is then retrieved. The data is then contextualized based at least on the one or more data models. Based at least on the contextualized data, an asset model for at least one asset is generated. Further, the one or more data models are also updated with the generated asset model. Additionally, one or more dashboards are also generated based on the one or more updated data models. Also, one or more operations associated with the assets are controlled based at least on the one or more updated data models as well.