Connected Building Equipment Monitoring for Fleet-Wide Interventions
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Solution Overview
Problem
Current building management systems lack an efficient method to monitor and manage the performance of connected equipment across multiple geographic locations, leading to inefficiencies in energy usage and fault detection, particularly in systems like chillers, rooftop units, and cooling towers.
Innovation Solution
A system utilizing processors and computer-readable media to collect and categorize performance data from connected building equipment, generating dashboards for visualization, identifying interventions by comparing performance across entities, and executing updates to improve equipment performance, including energy management through web-based interfaces and cellular communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If building management systems monitor equipment across multiple geographic locations, then fault detection capability is improved, but system complexity increases
Solution Approach 1:
The system segments the fleet management functionality into modular components: data collection modules at individual equipment sites, categorization modules that organize data by entity/location/equipment type, and analysis modules that process segmented data independently before aggregation. This modular segmentation enables monitoring of multiple geographic locations while keeping each module's complexity manageable.
Solution Approach 2:
The system introduces intermediate data structures and processing layers between raw equipment data and final analysis results. Performance data is first categorized by entity, location, and equipment type, then aggregated into fleet-wide metrics. These intermediate categorization layers act as mediators that simplify the complexity of directly managing raw data from multiple geographic sources.
2Loss of energy
If performance data from multiple entities is collected and analyzed, then energy efficiency improvement is achieved, but data management complexity increases
Solution Approach 1:
The system applies local quality by maintaining distinct data categorizations for different entities, locations, and equipment types while applying uniform analysis methods. Each entity's performance data is processed with entity-specific parameters and constraints, allowing energy efficiency optimization tailored to local conditions while managing data complexity through structured categorization.
Solution Approach 2:
The system creates universal data structures and analysis frameworks that can handle multiple entity types simultaneously. The same categorization and analysis methodology is applied across diverse equipment (chillers, rooftop units, cooling towers), enabling energy efficiency improvements across the entire fleet while managing data complexity through a unified multi-functional approach.
3Loss of information
If detailed performance data is visualized across geographic regions, then operational insight is improved, but information processing load increases
Solution Approach 1:
The system adds categorical dimensions (entity, location, equipment type) to the performance data, transforming raw time-series data into multi-dimensional categorized datasets. This dimensional organization enables efficient filtering, aggregation, and visualization by different criteria without requiring processing of all raw data, reducing information processing load while maintaining operational insight.
Solution Approach 2:
The system implements selective data visualization and analysis by allowing users to filter and focus on specific subsets of the fleet data based on entity, location, or equipment type. Rather than processing and displaying all data simultaneously, the system enables partial action where only relevant data subsets are actively processed and visualized, reducing overall information processing load.
Data Source
AI summary
Systems and methods for monitoring and controlling building equipment are provided. A connected equipment system is configured to obtain performance data from a fleet of connected building equipment associated with a plurality of customer entities, tag the performance data with categorizations associating subsets of the performance data with different equipment models, different locations, and different entities of the plurality of customer entities, generate, based on the categorizations, a dashboard comprising visualizations of the performance data, identify, using a subset of the performance data associated with multiple different entities of the plurality of customer entities, an intervention for a particular unit of the connected building equipment associated with an entity of the plurality of customer entities, and execute the intervention to affect performance of the particular unit of the connected building equipment from the fleet of connected building equipment.