Sensor Data Reconstruction via Time Stamping Correlation
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Solution Overview
Problem
Existing consumption data acquisition systems in supply networks for goods like gas, water, and electricity are limited in depth and scope of information, requiring more advanced methods for data collection and processing to enhance network monitoring and customer transparency.
Innovation Solution
A method that uses sensors with measuring elements to generate time stampings based on a correlation model, allowing for the reconstruction and evaluation of raw measurement data, reducing the need for local computing and energy consumption, and enabling continuous, high-resolution data transmission for network monitoring and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If raw measurement data are transmitted continuously from sensors to the head-end system, then the depth and scope of information is improved, but the energy consumption and computing load increase significantly
Solution Approach 1:
The patent extracts only the essential temporal information (time stampings) from the complete raw measurement data and transmits only these extracted elements to the head-end system. The correlation model stored at the head-end reconstructs the full measurement data from these time stampings, thereby reducing transmission energy while preserving information depth and scope.
Solution Approach 2:
The correlation model is pre-stored in the head-end system before data transmission occurs. This preliminary preparation enables the system to reconstruct complete measurement data from minimal time stamping information, reducing the energy required for continuous data transmission while maintaining full information availability.
2Productivity
If computing operations are performed locally at the sensor to process and evaluate raw measurement data, then the information processing capability is improved, but the device complexity and energy consumption increase
Solution Approach 1:
Instead of performing complex computing operations at the sensor level, the patent inverts the architecture by storing the correlation model at the head-end system and transmitting only simple time stamping data from sensors. The computationally intensive reconstruction and evaluation operations are performed centrally rather than locally, reducing sensor complexity while maintaining processing capability.
3Device complexity
If measurement data are collected at predefined intervals, then the device complexity is reduced, but the measurement precision and time resolution deteriorate
Solution Approach 1:
The patent creates a virtual copy of the continuous measurement data stream through mathematical reconstruction using the correlation model. Instead of physically collecting data at high resolution intervals, the system generates accurate intermediate values by reconstructing the measurement curve from time stampings, achieving high time resolution without the complexity of continuous high-frequency sampling.
Data Source
AI summary
A method collects data in a network by operation of a local sensor of a consumption meter where the network is part of a supply network. The network distributes a consumable good. The sensor has a measuring element providing raw measurement data corresponding to a physical or physicochemical value or parameter. The sensor has a wired and/or radio communication device and a memory. For the determination of the measurement resolution of the sensor the conditions for generating time stampings using a correlation model are determined in advance, on the basis of the correlation model time stampings of successive raw measurement data in the sensor are generated. The time stampings are transmitted over a wired connection and/or a radio link so that on the basis of the time stampings using the correlation model the raw measurement data collected by the measuring element are reconstructed and evaluated and used for network monitoring.