KPI-Based Building Management Platform for Energy Usage Intensity
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Solution Overview
Problem
Existing building management systems require significant manual effort and technical expertise to compare key performance indicators (KPIs) across different buildings, making it challenging to identify best and worst performers and pinpoint areas for improvement.
Innovation Solution
A KPI-based building management platform that allows users to select multiple buildings for comparison, automatically calculates and displays KPIs, identifies root causes for underperforming buildings, and sends notifications for immediate attention, thereby streamlining the process and providing a single view of building performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual comparison of KPIs across buildings is performed, then detailed analysis is possible, but significant manual effort and time are required
Solution Approach 1:
The system enables automatic self-service by having buildings report their own KPI data through integrated sensors and meters. The platform automatically collects, processes, and compares KPIs across multiple buildings without requiring manual data gathering, thereby eliminating time loss while maintaining measurement precision through automated data validation and normalization procedures.
Solution Approach 2:
The system performs preliminary actions by pre-configuring KPI measurement protocols, data collection templates, and comparison methodologies before actual building performance assessment. This preliminary setup includes defining KPI thresholds, normalization factors, and comparison criteria in advance, enabling rapid automated comparison without manual intervention during the actual analysis phase.
2Loss of information
If detailed data navigation is required to analyze building performance, then comprehensive insights are obtained, but technical expertise is needed
Solution Approach 1:
The platform introduces an intermediary layer that automatically processes raw building data and translates it into meaningful performance insights. This intermediary includes automated analytics engines that normalize data across different building types, apply industry standards, and generate comparative reports. The system acts as a mediator between complex building systems and users, eliminating the need for technical expertise while preserving comprehensive performance information.
Solution Approach 2:
The system segments building performance data into standardized KPI categories (energy efficiency, water usage, occupancy, maintenance) that can be independently analyzed and compared. This segmentation allows the platform to present comprehensive insights in organized, digestible formats without requiring users to navigate complex raw data structures, thereby improving ease of operation while maintaining information completeness.
3Adaptability or versatility
If multiple building types are compared, then broader performance benchmarks are available, but data normalization becomes more complex
Solution Approach 1:
The system dynamically adjusts normalization parameters based on building type characteristics. It employs building-specific correction factors for energy usage, water consumption, and occupancy metrics that account for differences between office buildings, residential complexes, retail spaces, and industrial facilities. The platform automatically selects and applies appropriate normalization parameters based on the building classification, enabling versatile multi-type comparison while managing normalization complexity through automated parameter selection.
Data Source
AI summary
The present disclosure is directed to a method for managing performance indicators of a number of buildings. The method includes providing a user interface to select at least a first physical premise and a second physical premise to be compared from a plurality of physical premises of an organization. The method includes identifying one or more performance indicators associated with an entity of the organization. The method includes collecting data that associates the first and second physical premises with the one or more performance indicators. The method includes displaying, through the user interface, one or more comparison results of the one or more performance indicators among the first and second physical premises.