Consumption Characterization via Sensor Relay and Server
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Solution Overview
Problem
Existing solutions for monitoring fluid consumption, such as electricity, water, or gas, using intelligent meters provide coarse information and raise privacy concerns due to the collection of detailed usage patterns by third-party operators.
Innovation Solution
A system comprising a sensor affixed to a metrological meter with radio frequency communication capabilities, a local relay for data processing, and a remote server that applies machine learning to timestamped data to characterize equipment consumption, providing detailed and privacy-respecting usage profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If intelligent meters collect detailed consumption data for analysis, then information on equipment consumption patterns is improved, but user privacy is compromised
Solution Approach 1:
The patent extracts only the necessary consumption data (power, time, date) from the meter readings while leaving detailed usage patterns private. The system processes this extracted data locally or on secure servers to identify equipment consumption patterns without exposing granular behavioral information, thus providing useful consumption information while protecting user privacy.
Solution Approach 2:
The patent introduces an intermediary processing layer between the meter and the end user. This intermediary (the processing system with algorithms) anonymizes and aggregates the data, transforming raw consumption readings into equipment-level insights without revealing personal usage patterns. The intermediary acts as a buffer that protects privacy while enabling useful analysis.
2Object-affected harmful factors
If coarse consumption information is provided by existing meters, then privacy is protected, but detailed equipment characterization is lost
Solution Approach 1:
The patent segments the overall consumption data into equipment-specific consumption patterns using analysis algorithms. By dividing the total consumption into attributable portions for different equipment types (heating, lighting, appliances), the system recovers detailed equipment characterization information from aggregated meter readings without exposing personal usage behavior, thus maintaining privacy while providing detailed equipment insights.
Solution Approach 2:
The patent transforms one-dimensional total consumption data into multi-dimensional equipment-level information by adding temporal, power, and equipment-type dimensions through algorithmic processing. This dimensional transformation allows detailed equipment characterization without requiring direct access to granular usage patterns, preserving privacy while enriching the information content.
3Loss of information
If third-party operators collect load curve data, then consumption analysis capability is improved, but trust and privacy concerns increase
Solution Approach 1:
The patent enables users to perform consumption analysis themselves through provided tools and algorithms that process their own meter data. By giving users control over their own data analysis and allowing them to run local processing or choose secure servers, the system builds trust by eliminating the need for third-party operators to access and analyze sensitive load curve data, thus maintaining both analytical capability and user trust.
4Device complexity
If simple meter reading systems are used, then device complexity is reduced, but measurement precision and equipment identification capability deteriorate
Solution Approach 1:
The patent replaces complex hardware measurement systems with software-based analysis algorithms that process simple meter readings. Instead of installing sophisticated sensors and measurement devices, the system uses computational methods to extract precise equipment consumption information from standard meter data, thus achieving high measurement precision while keeping the physical system simple and the added complexity primarily in the software domain.
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
The system delivers accurate and reliable information on equipment consumption patterns while ensuring user privacy by processing data to identify usage profiles and alerting users to potential inefficiencies, thereby aiding in optimization and supervision.
Implementation Method 1
the known sensors operate with a light source (visible or invisible) and a photoelectric sensor. The light source is intended to illuminate the rotating disk while the photoelectric sensor receives the light reflected by the disk.
Data Source
Figure 1~3
AI summary
The present invention concerns a system for characterising electrical consumption of a set of equipment powered by a local grid equipped with an energy counter (2) providing visual consumption information, comprising: a) a sensor (1) suitable for being affixed on said counter, comprising: - a means for acquiring said visual information (6), and - a radiofrequency communication means (9) with a local relay; b) a local relay comprising: - receiving means (11) and preprocessing means (10) for data coming from said sensor (1), and - a communication means (13) with a remote server for transmitting timestamped data; and c) a remote server performing processing of data transmitted by said local relay in order to calculate characterisation information and the transmission of said information to a remotely connected piece of equipment.