Precipitation Aware Irrigation Monitoring via Streamed Meter Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Utility meter management systems face challenges in efficiently processing and utilizing the vast amount of data generated by sensors, particularly in determining the effectiveness of rain-aware irrigation systems, which requires real-time monitoring and analysis of precipitation and water usage data.
Innovation Solution
A computer-implemented system that includes a metering analytics system and a central event management system to receive and analyze streamed meter data from utility sensors, identifying precipitation notifications and determining irrigation usage, enabling effective monitoring and notification of water usage violations and system effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional meter management systems process data in batches (e.g., every 4 hours), then data processing load is reduced, but real-time monitoring capability is lost
Solution Approach 1:
The system performs preliminary actions by continuously processing and analyzing meter data as it arrives, rather than waiting for batch processing intervals. The event detection system is pre-configured with rules and thresholds, enabling immediate identification of irrigation events and precipitation anomalies as they occur in the streamed data, thus achieving real-time monitoring without overwhelming processing loads
Solution Approach 2:
The data processing is segmented into discrete event detection tasks within the continuous data stream. Instead of processing all data uniformly, the system segments analysis into specific event types (irrigation events, precipitation anomalies, usage violations) that can be independently detected and handled, improving both real-time responsiveness and processing efficiency
2Loss of information
If comprehensive sensor data is collected and stored in massive databases, then data availability for analysis is improved, but data access and utilization efficiency decreases
Solution Approach 1:
The system extracts only the critical information needed for irrigation effectiveness analysis from the massive streamed data. Instead of accessing and processing entire databases, the event detection system extracts specific metrics such as irrigation event timing, duration, precipitation amounts, and water usage patterns directly from the data stream, significantly improving access efficiency while maintaining data availability
Solution Approach 2:
The patent introduces an intermediary event detection system that sits between the raw data stream and the analysis applications. This intermediary layer pre-processes and structures the data, identifying and flagging relevant events before they reach downstream systems, thus improving both data availability for analysis and access efficiency by reducing the volume of raw data that needs to be processed
3Measurement precision
If manual validation and monitoring of irrigation data is performed, then data accuracy can be verified, but labor costs and processing time increase
Solution Approach 1:
The system implements self-service through automated event detection and validation rules that continuously monitor the data stream for irrigation events, precipitation anomalies, and usage violations. The system automatically validates data accuracy by checking against predefined thresholds and patterns, eliminating the need for manual verification while maintaining high measurement precision and reducing processing time
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors detected events and adjusts its detection parameters based on observed patterns. The automated system provides feedback loops that verify data accuracy by comparing detected events against expected patterns and notifying users of anomalies, thereby maintaining high measurement precision without manual intervention
Data Source
AI summary
A computer-implemented system for detecting water usage violations from 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, the meter data being generated by the sensors and a central event management system for determining the effectiveness of a precipitation aware irrigation system based on a plurality of sequential meter reads in the streamed meter data. The central event management system is configured to receive a notification regarding usage of a precipitation aware irrigation system, identify a meter associated with the notification, receive a precipitation notification indicating precipitation has exceeded a defined threshold in an area specific to the meter, monitor read messages in the streamed meter data to identify a first read message for a watched meter, and determine irrigation usage for the meter based on at least a second read message in the streamed meter data.