Water Usage Profiling for Multi-Consumer Leak Attribution
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Solution Overview
Problem
Distributed water infrastructure systems face challenges in detecting leaks and abnormal water usage efficiently, leading to unnoticed waste and potential damage, as users often fail to recognize leaks until significant water loss occurs, and existing methods lack precision in tracking water usage across multiple appliances and consumers.
Innovation Solution
A system comprising sensors, processors, and communication components that aggregate and analyze water usage data to construct time-based profiles, compare current usage to baseline profiles, and initiate remedial actions such as automatic valve closure or alerting administrators for potential leaks or abnormal consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distributed water infrastructure systems monitor water usage across multiple appliances and consumers, then water waste detection capability is improved, but system complexity increases
Solution Approach 1:
The system segments water usage monitoring by creating separate usage profiles for different appliances and consumers. Each appliance (toilet, shower, sink, washing machine) has its own baseline usage profile, allowing the system to detect anomalies at the appliance level rather than treating the entire infrastructure as a single unit. This segmentation enables precise leak detection while managing complexity through modular profile management.
Solution Approach 2:
The monitoring system serves multiple functions: it detects leaks, identifies abnormal usage patterns, tracks water consumption by appliance and consumer, and provides early warning systems. By consolidating these diverse functions into a single multi-functional platform, the system improves detection capability without proportionally increasing complexity, as the same infrastructure supports multiple objectives.
2Loss of substance
If the system continuously monitors and analyzes water usage data to detect leaks early, then water waste reduction is improved, but data processing requirements increase
Solution Approach 1:
The system performs preliminary action by establishing baseline usage profiles for each appliance during normal operation. These profiles are created in advance and stored for comparison. When monitoring, the system compares current usage against pre-established baselines rather than performing complex real-time analysis, significantly reducing data processing requirements while maintaining effective leak detection capability.
Solution Approach 2:
The system applies partial monitoring by focusing computational resources on detecting deviations from baseline patterns rather than analyzing every data point in detail. It uses threshold-based anomaly detection that triggers detailed analysis only when usage patterns exceed predetermined limits, reducing overall data processing energy consumption while maintaining effective water waste detection.
3Reliability
If the system automatically initiates remedial actions such as valve closure upon detecting abnormal usage, then water damage prevention is improved, but system automation complexity increases
Solution Approach 1:
The system implements feedback loops where detected anomalies trigger automated responses. When usage patterns deviate from baselines beyond threshold limits, the system automatically initiates remedial actions such as closing valves or sending alerts. This feedback mechanism enables reliable damage prevention through automation while managing complexity by using simple threshold-based decision rules rather than complex algorithms.
Solution Approach 2:
The system provides self-service by automatically detecting leaks and initiating corrective actions without requiring constant human intervention. The automated monitoring and response system serves itself by comparing data against stored profiles and executing pre-programmed remedial actions, reducing the need for manual system management while maintaining high reliability in damage prevention.
Data Source
AI summary
A system is provided for differentiating between water usage of multiple water consumers using a common distributed water infrastructure. The system receives from a water sensor that is upstream of a plurality of appliances, signals indicative of water usage, and constructs from the signals a plurality of water event profile signatures. The system associates, based on differences between similar water event profiles, at least one water event profile signature with a first water consumer and associates a second water event profile signature with a second water consumer, and stores the water event profile signatures for the first water consumer and the second water consumer. The system constructs current water event profiles reflecting subsequent water usage in the distributed water infrastructure, and attributes a first current water event profile to the first water consumer and attributes a second current water event profile to the second water consumer.