Real-Time Composite Utility Data Correlation for Consumption Change Isolation
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Solution Overview
Problem
Existing utility consumption tracking systems fail to provide a comprehensive, real-time assessment of composite utility consumption due to disparate data formats, missing information, and varying protocols, limiting users' ability to manage and understand their energy usage effectively.
Innovation Solution
A system that integrates local devices and central process capabilities to collect, correlate, and visualize utility data from multiple sources, including sensors and external data, generating accurate composite utility consumption information in real-time, even filling in missing data through estimation and historical information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual utility providers capture and store their own data in different formats and time intervals, then each provider maintains data accuracy for their specific utility type, but the system cannot generate a comprehensive real-time composite picture of total utility consumption
Solution Approach 1:
The patent introduces an intermediary system comprising a data collector, data correlator, and composite utility cost generator that acts as a mediator between disparate utility providers and the user. This intermediary collects data from multiple utility providers using different protocols and time intervals, correlates the data in real-time, and generates a unified composite cost indication, thereby preserving the accuracy of individual measurements while synthesizing comprehensive information.
Solution Approach 2:
The system employs a universal data collection and correlation mechanism that can handle multiple utility types (electricity, gas, water, etc.) with different data formats, protocols, and time intervals through a single integrated platform. The data correlator universally processes various input formats and converts them into a unified composite cost indication, enabling multi-functional utility monitoring without requiring separate systems for each utility type.
2Productivity
If utility data is collected at different time intervals and in different formats from various providers, then each data source maintains its own collection efficiency, but the system cannot provide real-time composite cost information
Solution Approach 1:
The system performs preliminary actions by pre-configuring multiple data collection routines that are tailored to each utility provider's specific data format and time interval requirements. These routines are established in advance and continuously execute, allowing the system to proactively gather data from all sources simultaneously and correlate them in real-time, eliminating delays associated with sequential data collection.
Solution Approach 2:
The data collection and correlation system is dynamically adaptive, automatically adjusting to different data arrival times and formats from various utility providers. The correlator dynamically processes incoming data streams at their native intervals and synthesizes real-time composite cost indications, maintaining productivity while ensuring timely information availability despite varying data collection schedules.
3Adaptability or versatility
If the system integrates multiple disparate utility data sources with different protocols and formats, then comprehensive utility monitoring is achieved, but the system complexity increases significantly
Solution Approach 1:
The patent segments the complex data integration task into distinct functional modules: a data collector that interfaces with individual utility providers, a data correlator that processes and synchronizes the data, and a composite utility cost generator that produces the final cost indication. This segmentation allows each module to handle specific protocols and formats independently, reducing overall system complexity while maintaining versatility.
Solution Approach 2:
The system employs intermediary components including standardized data interfaces and correlation algorithms that mediate between disparate utility data sources and the final composite output. These intermediaries translate and harmonize different protocols and formats without requiring direct integration between all data sources, thereby achieving adaptability while controlling system complexity through layered architecture.
4Loss of information
If utility consumption data is aggregated from multiple sources, then a complete picture of total consumption is obtained, but the ability to identify specific changes in consumption patterns is reduced
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor and compare utility consumption data against historical patterns and thresholds. The correlator analyzes changes in consumption patterns for each utility type and provides feedback signals that highlight significant deviations, enabling the system to maintain comprehensive aggregation while preserving the ability to detect specific consumption changes through comparative analysis.
Solution Approach 2:
The patent applies local quality by maintaining detailed, high-precision consumption data for each individual utility type and location within the aggregated system. While the overall system provides comprehensive total consumption visibility, each local data point retains its specific characteristics and change patterns, allowing the system to simultaneously achieve complete aggregation and precise change detection through differentiated data retention.
Data Source
AI summary
Presented are methods and systems to universally assess composite utility consumption (1) in which a plurality of real-time and batch sensor readings such as from multiple disparate utility sensor data inputs (3) may be acquired and stored such as into a local device (2) or a central data warehouse (6). A composite utility estimated cost generator (9) can generate missing or uncorrelated data and a collected composite utility data information correlator (11) can correlate the data so it can be applied to determine some type of composite utility cost information. For real-time calculation, a disparate utility rate information accessor (8) can obtain multiple items of disparate rate information and this can use with correlated data to create a composite utility consumption and spend so a user can manage and control utility usage for a home, building, facility, plant, specific equipment, or the like. Cost information, such as a rate of spend or spend amount(s) to date or for a period may be presented to user in a variety of visualizations and reporting formats including specific time usage and spend information, specific time range usage and spend, and “time-of-use” billing information for specific real-time data points. The visualization and reporting may be used to answer a plurality of usage questions along with specific characterizations of utility spend across time of day domains and specific equipment usage domains thus affording more effective utility cost management.