Central Event Management System for Utility Meter Data
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Solution Overview
Problem
Utility meter data management systems face challenges in processing and utilizing the vast amount of data generated by utility meters, particularly in identifying and quantifying changes in utility monitoring systems in real-time, which affects the effectiveness of infrastructure and consumer-level monitoring.
Innovation Solution
A computer-implemented system and method that utilizes a central event management system to analyze streamed meter data from utility meters, identifying changes and their effects by monitoring sequential reads, allowing for real-time detection of anomalies and adjustments in utility usage, such as water usage violations and irrigation system effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If meter data is processed and stored in massive information databases for later use, then data volume capacity is improved, but data access speed and real-time utilization deteriorate
Solution Approach 1:
The patent segments the data management system into multiple components: a streaming data processing system for real-time analysis and a database system for historical storage. The central event management system processes meter data streams in real-time, separating urgent real-time processing from batch historical analysis, thereby achieving both high-speed access and large-capacity storage.
Solution Approach 2:
The patent introduces an intermediary streaming data processing layer between the meter data sources and the database storage. This intermediary system includes event detection modules that filter, aggregate, and pre-process data before storing it, enabling real-time data utilization without overwhelming the database system.
2Device complexity
If manual methods are used to identify and quantify changes in utility monitoring systems, then system complexity is reduced, but productivity and detection speed deteriorate
Solution Approach 1:
The patent implements self-service automation where the system automatically detects, identifies, and quantifies changes in utility monitoring systems. The central event management system autonomously monitors meter data streams, detects anomalies, and generates change notifications without manual intervention, significantly improving productivity while managing complexity through standardized algorithms.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors meter data, compares it against baseline patterns, and automatically adjusts when changes are detected. This closed-loop feedback system enables rapid change detection and quantification, improving productivity through automated real-time analysis.
3Speed
If real-time monitoring of streamed meter data is implemented to identify changes, then detection speed is improved, but data processing complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-configuring event detection rules, thresholds, and patterns in the central event management system before real-time monitoring begins. Baseline meter usage patterns are established in advance, enabling the system to rapidly detect deviations without complex real-time calculations, thus improving detection speed while managing processing complexity.
Data Source
AI summary
A computer-implemented system for determining the effect of a change is a utility system based on streamed meter data is described. The system includes a metering analytics system configured to receive a stream of meter data received from sensors in or in proximity with utility meters in a utility monitoring system, the meter data being generated by the sensors and a central event management system for identifying an effect of modification to the utility monitoring system in the streamed meter data based on a plurality of sequential meter reads in the streamed meter data. The central event management system is configured to receive a change notification including change time, identify a meter associated with the change notification, monitor read messages in the streamed meter data to identify a first read message for a watched meter received following the change time, and determine a change effect for the meter based on at least a second read message in the streamed meter data.