Utility Usage Apportioning via Non-Invasive Water Flow Sensing
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Solution Overview
Problem
In multi-unit buildings, individual metering of utility usage is often impractical, leading to arbitrary apportionment based on unit size or occupancy, which lacks accuracy and incentivizes conservation.
Innovation Solution
Installation of non-invasive sensor units on unit feed pipes and water outlets to monitor water flow, correlating this data with main feed pipe measurements to accurately apportion utility usage to each unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual metering is installed in each unit, then measurement precision of utility usage is improved, but device complexity and installation difficulty increase
Solution Approach 1:
The patent introduces a correlation engine as an intermediary component that processes data from non-invasive sensors and main feed pipe meters to infer individual unit usage. Instead of directly installing meters in each unit, the system uses sensor data from common areas and correlates it with main feed pipe measurements to calculate individual usage, thereby avoiding the complexity of individual meter installation while achieving accurate measurement.
Solution Approach 2:
The patent replaces physical mechanical meters with non-invasive sensors that detect usage through vibration, acoustic, or flow measurements. These sensors can be installed on external surfaces without penetrating pipes or requiring internal access, substituting complex mechanical metering infrastructure with simpler electronic detection systems that achieve comparable or superior measurement precision.
2Ease of manufacture
If non-invasive sensors are used on unit feed pipes, then ease of installation is improved, but measurement precision may be compromised
Solution Approach 1:
The patent combines data from multiple non-invasive sensors with measurements from main feed pipe meters to achieve accurate individual unit usage measurement. By merging sensor data from common areas (hallways, stairwells, exterior walls) with overall building consumption data, the system compensates for the limitations of individual non-invasive sensors and achieves precision comparable to or exceeding traditional metering while maintaining installation ease.
Solution Approach 2:
The system implements a feedback mechanism where the correlation engine continuously processes sensor data and compares it with main feed pipe measurements to validate and refine usage calculations. This feedback loop ensures measurement precision by cross-verifying sensor readings against actual consumption data, correcting for any drift or inaccuracies in non-invasive sensor measurements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables fair and incentive-driven conservation by accurately measuring individual water usage, reducing the burden on tenants and promoting efficient resource management.
Implementation Method 1
non-invasive sensor units on unit feed pipes and water outlets to monitor water flow
Implementation Method 2
non-invasive sensor units on unit feed pipes and water outlets to monitor water flow
Implementation Method 3
correlating this data with main feed pipe measurements to accurately apportion utility usage to each unit
Data Source
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AI summary
Usage of a utility in a multi-unit building is apportioned to a single unit by measuring the total usage of the utility using a meter unit to produce a total usage measurement, then positioning at least one sensor unit in a single unit of the multi-unit building and monitoring usage of the utility by the single unit using the at least one sensor unit to produce monitoring data. Then a processor unit receives the total usage measurement and the monitoring data and correlates them to generate correlated data. Finally, the processor unit apportions the total usage measurement to the single unit based on the correlated data.