Measurement Selection Strategy for Multi-Device Physical Quantities
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Solution Overview
Problem
Existing data collecting systems face challenges in automatically and dynamically selecting the best measurement for physical quantities from multiple sources, as measurement devices can change over time, leading to inconsistencies and inefficiencies in data management.
Innovation Solution
A data processing arrangement that collects and characterizes measurement data from multiple electronic measuring devices, calculates multiple measurements for each physical quantity, and selects the best measurement based on predetermined measuring characteristics, such as accuracy, precision, and granularity, while adapting to changes in the status and number of devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple measurement devices are used to measure the same physical quantity, then measurement reliability and data redundancy are improved, but device complexity and data management difficulty increase
Solution Approach 1:
The data collecting arrangement automatically performs selection of the best measurement without external intervention. The system self-manages the complexity by autonomously evaluating measurements from multiple devices and selecting the optimal one based on predefined criteria, eliminating the need for manual data management while maintaining high reliability through redundant measurements.
2Adaptability or versatility
If measurement devices are dynamically added or removed, then system adaptability is improved, but measurement consistency and selection reliability worsen
Solution Approach 1:
The selection strategy is designed to be dynamic rather than static. When measurement devices are added or removed, the data collecting arrangement automatically re-evaluates the available measurements and adjusts its selection based on the current set of devices. This dynamic adaptation maintains measurement consistency by always selecting from the currently available devices using the same evaluation criteria.
Solution Approach 2:
The system continuously monitors the status and performance of measurement devices, using this feedback to dynamically adjust which measurement is selected. When devices are added or removed, the feedback mechanism triggers a re-evaluation of all available measurements, ensuring that the selected measurement remains reliable and consistent with the system's current state.
3Productivity
If automatic selection of best measurement is implemented, then data processing efficiency is improved, but computational complexity and selection strategy complexity increase
Solution Approach 1:
The selection criteria and evaluation rules are predetermined and configured in advance. Rather than performing complex real-time analysis, the system applies pre-defined rules to select the best measurement from available options. This preliminary configuration reduces computational complexity during operation while maintaining high data processing efficiency through automated selection.
Data Source
AI summary
A system is disclosed comprising: a plurality of electronic measuring devices adapted to provide measurement data of a set of physical quantities; wherein the measurement data from each measuring device are characterized by at least one respective measuring characteristic;a data processing arrangement, configured to calculate at least two measurements for each physical quantity based on said measurement data; and further configured to select a best measurement for each physical quantity based on said measuring characteristics.