Pipe Leak Detection Using Home Telematics and Irregular Usage
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Solution Overview
Problem
Homeowners often fail to detect leaks or bursts in pipes due to infrequent checks, leading to extensive damage, especially in less frequently used buildings, and conventional methods are inefficient.
Innovation Solution
A system using home telematics data, including weather forecasts and smart home sensors, to detect potential pipe leaks or bursts and initiate corrective actions such as temperature adjustments or shutting off water valves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If homeowners check pipes frequently to detect leaks early, then detection reliability improves, but time consumption and operational burden increase
Solution Approach 1:
The system enables automatic leak detection through telematics devices that continuously monitor water flow, temperature, and pressure without requiring homeowner intervention. The system self-monitors pipe conditions and automatically detects anomalies, eliminating the need for manual checking while maintaining high detection reliability.
Solution Approach 2:
Manual pipe inspection is replaced by electronic sensing systems. Telematics devices with sensors automatically detect leaks through electronic monitoring of water flow patterns, temperature changes, and pressure variations, substituting human mechanical inspection with automated electronic detection.
2Reliability
If homeowners check pipes frequently to detect leaks early, then detection reliability improves, but operational complexity increases
Solution Approach 1:
The monitoring system operates autonomously without requiring homeowner action. Sensors continuously detect pipe conditions and the system automatically processes data to identify leaks, making the complex monitoring task self-executing and simple for the user.
Solution Approach 2:
The system creates a virtual model of the plumbing system through continuous sensing and data collection. By monitoring telemetry data from multiple sensors and creating a digital representation of pipe conditions, the system simplifies complex physical monitoring into manageable electronic data analysis.
3Reliability
If the system takes preventive actions such as shutting off water valves, then damage prevention effectiveness improves, but system complexity increases
Solution Approach 1:
The system pre-positions control mechanisms (automatic shut-off valves, temperature control devices) that can be activated immediately upon detecting a leak or freeze condition. This preliminary preparation enables rapid response without requiring complex real-time decision-making or additional components.
Solution Approach 2:
The system continuously monitors pipe conditions and provides feedback to control mechanisms. When sensors detect anomalies such as unusual flow patterns or temperature changes, the feedback loop automatically triggers appropriate responses like shutting off valves or adjusting heating, creating a self-regulating system.
4Measurement precision
If the system monitors multiple parameters continuously, then detection accuracy improves, but energy consumption increases
Solution Approach 1:
Instead of continuous monitoring of all parameters, the system uses periodic sampling at strategically chosen intervals. Sensors take measurements at regular intervals and only trigger alerts when anomalies are detected, reducing overall energy consumption while maintaining detection accuracy through targeted monitoring.
Solution Approach 2:
The system monitors all relevant parameters but processes data selectively, focusing computational resources only on analyzing combinations of parameters that indicate potential leaks. By applying partial analysis to the full data set, the system maintains high detection accuracy while minimizing energy expenditure on data processing.
Data Source
AI summary
Systems and methods are described for detecting a leak based upon home telematics data. The method may include: (1) receiving home telematics data from one or more sensors associated with one or more pipes (or piping systems) in a structure, wherein the home telematics data is indicative of the frequency with which the one or more pipes are being used; (2) determining, using a trained machine learning algorithm, pipe activity associated with the one or more pipes is occurring at an irregular frequency; (3) determining, based upon at least the determination that the pipe activity associated with the one or more pipes is occurring at the irregular frequency, that the one or more pipes are leaking; and (4) transmitting an indication to a user associated with the home that the one or more pipes are leaking.