Remote Meter Data Analysis with Cartographic Context
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Solution Overview
Problem
Current methods for analyzing water and energy consumption data are limited in their ability to fully understand and manage consumption patterns, particularly on a collective scale, as they rely on technology-oriented and descriptive statistical techniques that do not adequately account for contextual and socio-economic factors.
Innovation Solution
A method that integrates cartographic and socio-economic data with remotely collected consumption data to determine user profiles, reference consumption models, and provides feedback mechanisms for users, allowing for targeted adjustments in consumption patterns and resource supply.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional descriptive statistical techniques are used for consumption data analysis, then the analysis process remains simple and technology-oriented, but the ability to understand consumption patterns and provide actionable insights is insufficient
Solution Approach 1:
The patent merges multiple data sources including consumption data, cartographic data, and socio-economic data into a unified analysis system. This combination allows the system to capture comprehensive consumption patterns by integrating previously separate information streams, thereby reducing information loss while managing complexity through systematic data fusion
Solution Approach 2:
The patent introduces an intermediary processing layer that transforms raw data from multiple sources into meaningful consumption patterns and insights. This intermediary system handles the complexity of data integration while presenting simplified, actionable results to users, effectively mediating between complex data sources and user needs
2Productivity
If remote meter reading operations are implemented, then consumption data collection becomes automated and efficient, but the quality of information for supporting sustainable management remains insufficient without advanced analysis
Solution Approach 1:
The patent implements feedback mechanisms where consumption data is continuously collected, analyzed, and used to generate insights that feed back into consumption management. This closed-loop system transforms automated data collection into actionable information by providing feedback on consumption patterns, enabling users to make informed decisions for sustainable management
Solution Approach 2:
The patent performs preliminary analysis and pattern recognition on collected consumption data before presenting results to users. By pre-processing and interpreting data in advance, the system transforms raw automated readings into meaningful insights about consumption patterns, reducing the information gap between data collection and actionable intelligence
3Measurement precision
If statistical techniques are applied to raw consumption data, then descriptive analysis is achieved, but the ability to provide targeted recommendations and monitor consumption trends is limited
Solution Approach 1:
The patent enables the system to automatically perform complex analysis, pattern recognition, and insight generation without requiring manual intervention. The system serves itself by autonomously processing consumption data, identifying patterns, and providing recommendations, thereby maintaining high measurement precision while preserving ease of operation through automation
Data Source
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AI summary
The invention relates to a computer-implemented method for determining a profile of a user of a water and/or energy resource, the method comprising the steps that consist of receiving initial data on consumption of the resource by a plurality of users; determining consumption levels of the resource, determining user groups and determining at least one user profile. Developments describe the use of additional data, in particular cartographic data, corresponding to the determined user profile; the determination of consumption trends; the determination of a reference consumption model; and the comparison of the remotely read consumptions with the reference model. System and software aspects are also described, in particular for remotely consulting information relating to the consumption data, to the groups of users, to the user profiles, to the consumption trends or to the reference consumption models.