Supply Network Sensor Time Stamping for Gapless Data Reconstruction
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Solution Overview
Problem
Current methods for collecting and processing data from consumption meters in supply networks are limited in terms of depth and amount of information, requiring complex and energy-intensive computations at the local sensor level, which can lead to gaps and inaccuracies in data transmission.
Innovation Solution
A method that uses a correlation model to generate time stamps for raw measurement data, allowing for dynamic changes in conditions and transmission, enabling continuous and gapless data reconstruction at the head-end system, reducing computational load on local sensors and improving data resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If complex computations are performed at the local sensor level to process raw measurement data, then data processing capability is improved, but energy consumption increases and device complexity increases
Solution Approach 1:
The patent extracts the complex computation tasks from the local sensor and relocates them to the head-end system. The sensor only performs minimal local processing to generate time stamps, while the head-end system performs the complex computations for reconstructing raw measurement data streams and generating consumption data, thereby reducing energy consumption and complexity at the sensor level.
Solution Approach 2:
Instead of the conventional approach where sensors perform complex computations locally, the patent inverts the processing hierarchy: sensors generate only time stamps, and the head-end system performs the complex data reconstruction and computation, reversing the traditional computational burden distribution.
2Productivity
If complex computations are performed at the local sensor level to process raw measurement data, then data processing capability is improved, but device complexity increases
Solution Approach 1:
The patent extracts complex computation functions from the local sensor and relocates them to the head-end system. The sensor is simplified to only generate time stamps based on local measurements, while the head-end system handles complex data reconstruction, stream generation, and consumption data computation, thereby reducing sensor complexity.
Solution Approach 2:
The patent inverts the conventional processing architecture by placing minimal processing at the sensor level (time stamp generation only) and complex processing at the head-end level (data reconstruction and analysis), reversing the traditional complexity distribution.
3Ease of operation
If data are collected at defined times using conventional methods, then data transmission is simplified, but data resolution and information depth are reduced
Solution Approach 1:
The patent applies preliminary action by generating time stamps at the sensor level that encode measurement resolution information before transmission. These time stamps are used at the head-end to reconstruct high-resolution raw measurement data streams, allowing both simple transmission and high data resolution to coexist.
Solution Approach 2:
The patent changes the parameter being transmitted from raw measurement values to time stamps that encode temporal and resolution information. This parameter transformation enables the system to maintain simple transmission while preserving high data resolution through the correlation model that uses time stamps to reconstruct detailed measurement streams.
4Measurement precision
If time stamps are generated continuously at high resolution, then data accuracy is improved, but data transmission volume and energy consumption increase
Solution Approach 1:
The patent extracts only the essential time stamp information from the full measurement data and transmits only these compressed time stamps to the head-end system. The high-resolution measurement data is reconstructed computationally at the head-end using the correlation model, thereby maintaining data accuracy while minimizing transmission volume and associated energy consumption.
Solution Approach 2:
Instead of transmitting the actual high-resolution measurement data, the patent transmits time stamps that serve as references for reconstructing the measurement data stream at the head-end. This copying approach preserves measurement precision while dramatically reducing the amount of data that needs to be transmitted and processed at the sensor level.
Data Source
AI summary
A method for collecting data of a consumption, a physical or physico-chemical parameter and/or an operating state in a supply network for consumables. A measuring element of a local sensor provides elementary measuring units, which correspond to at least one physical or physico-chemical variable or at least one physical or physico-chemical parameter, as raw measurement data. In order to determine the measurement resolution of the sensor, the conditions for generating time stamps are determined in advance using a correlation model, time stamps of successive raw measurement data are generated in the sensor on the basis of the correlation model, and the time stamps are transmitted via a wired connection and/or via a radio path. The raw measurement data are reconstructed and evaluated based on the time stamps with the correlation model. The conditions for generating time stamps can be changed dynamically within the framework of the correlation model.