Utility Meter Data Storage Using Event-Based Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current utility metering systems face challenges in efficiently storing and transferring high-resolution data on electricity, gas, and water consumption due to data volume and communication interruptions, which limits detailed analysis and behavioral efficiency improvements for consumers and suppliers.
Innovation Solution
A method and apparatus for storing and transmitting utility consumption data by making series of measurements at predetermined intervals, processing these to identify events, generating further measurements with timestamps, and storing and transmitting only event-based data, reducing data volume and improving communication efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution metering is used to measure power consumption at one second intervals, then measurement precision is improved, but data volume increases making storage and transfer problematic
Solution Approach 1:
The patent extracts only the essential information from continuous high-resolution measurements by identifying and storing only event-based data points (when consumption patterns change or exceed thresholds) rather than storing all continuous measurement data. This maintains measurement precision for critical events while dramatically reducing overall data volume.
Solution Approach 2:
The patent segments the continuous stream of high-resolution measurements into discrete event-based records. Instead of storing every second of consumption data, the system divides the data stream into meaningful segments based on detected events such as appliance activation, consumption spikes, or pattern changes, thereby reducing storage requirements while preserving analytical value.
2Loss of information
If continuous high-resolution data is stored and transferred to remote devices, then analysis capability is improved, but communication bandwidth and time are consumed excessively
Solution Approach 1:
The patent extracts only the most informative data points for remote analysis - namely event-based records that capture meaningful consumption patterns - rather than transmitting the entire continuous data stream. This maintains sufficient analysis capability for identifying consumption behaviors while minimizing transfer time and bandwidth usage.
Solution Approach 2:
The patent performs preliminary processing and event identification at the local meter before data transfer to remote devices. By pre-processing the continuous measurement stream to extract and filter only meaningful events, the system reduces the amount of data that needs to be transmitted, thereby decreasing transfer time while preserving analytical value.
3Reliability
If all continuous measurement data is stored locally, then data completeness is improved, but storage capacity requirements become excessive
Solution Approach 1:
The patent extracts only the essential event-based information from continuous measurements for local storage, maintaining data completeness for analytical purposes while eliminating redundant continuous data. This approach ensures that storage capacity is sufficient for retaining meaningful consumption patterns without requiring excessive storage space.
Solution Approach 2:
The patent changes the data representation parameters from continuous time-series values to discrete event-based records with timestamps and consumption values. This parameter transformation maintains the reliability of consumption data for analysis while significantly reducing the volume of data that needs to be stored locally.
4Reliability
If communication between meter and remote device is interrupted, then system reliability is improved, but data transfer becomes problematic when connection is restored
Solution Approach 1:
The patent performs preliminary event identification and data preparation at the meter continuously, so that when communication is restored after an interruption, the system can immediately transfer pre-processed event data without needing to re-process continuous streams. This maintains ease of operation during connection restoration while preserving communication reliability.
Solution Approach 2:
The patent segments data transfer into discrete event-based packets rather than continuous streams. This segmentation allows the system to send only meaningful event records when communication is restored, making the transfer operation simpler and more reliable compared to attempting to resume continuous data transmission after interruptions.
Data Source
AI summary
A method and apparatus for storing data regarding parameter values by making a series of measurements of parameter values at times separated by predetermined time intervals, processing the series of measurements of parameter values made at predetermined time intervals to identify events at different times, generating a further series of measurements of parameter values at each of said different times, and storing each of said further series of measurements of parameter values in association with said respective different time.