Facility Resource Usage Query Ranking for ESG Data Analysis
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Solution Overview
Problem
Companies face challenges in effectively monitoring and understanding comprehensive facility resource usage data for decision-making in the context of environmental, social, and governance (ESG) contexts, particularly in integrating and analyzing data from a large group of diverse facilities.
Innovation Solution
A computerized method and system for analyzing facility resource usage data via a graphical user interface (GUI), enabling users to input facility feature queries, obtaining and ordering data from a facility resource usage data store, and presenting the results in a visually digestible format to facilitate better decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive facility resource usage data is collected and stored for ESG monitoring, then data completeness and measurement precision are improved, but data complexity and difficulty of understanding increase
Solution Approach 1:
The patent segments comprehensive facility resource usage data into multiple hierarchical levels: facility-level data, building-level data, and portfolio-level data. This segmentation allows the system to maintain complete detailed data while presenting information in manageable, organized segments that reduce complexity for users making ESG decisions.
Solution Approach 2:
The patent introduces an intermediary processing layer between raw data collection and user presentation. This layer includes data normalization, aggregation, and analysis components that transform comprehensive raw data into standardized, easily interpretable metrics, thereby maintaining data completeness while reducing the perceived complexity for end users.
2Reliability
If detailed resource usage data from multiple facilities is analyzed, then decision-making quality is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary data processing, normalization, and aggregation operations before data is requested for analysis. By pre-processing and organizing facility resource usage data in advance, the system reduces the computational burden during actual query and analysis operations, thereby maintaining high decision-making quality while reducing processing time when data is needed.
3Productivity
If resource usage data is stored centrally for comprehensive analysis, then data accessibility and productivity are improved, but memory costs and infrastructure complexity increase
Solution Approach 1:
The patent implements a hierarchical data storage architecture where data is organized with different levels of detail stored in different locations. Frequently accessed aggregated metrics are stored centrally for quick access, while detailed raw data is stored locally or in distributed storage systems. This approach maintains high data accessibility for common queries while reducing central memory requirements.
Data Source
AI summary
A computerized method analyzes and presents facility resource usage data. A facility feature query is received via a graphical user interface (GUI). A data category to be analyzed is determined using the facility feature query. Resource usage data of the determined data category is obtained from a facility resource usage data store. A plurality of facilities represented in the obtained resource usage data are identified and recorded in a response data structure. The plurality of facilities are recorded in an order according to a degree to which each facility satisfies a requirement of the facility feature query. Facility data of the plurality of facilities is presented from the response data structure in the order in which the plurality of facilities are arranged in the response data structure using the GUI, whereby facility data of a facility that best satisfies the requirement is prioritized in the GUI.