Measurement Apparatus Using Temporal-Spatial Constraints to Filter Noise
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Solution Overview
Problem
Existing measurement technologies struggle to extract required data in noisy environments due to measurement errors and unintended objects, limiting analysis sites and complicating data selection.
Innovation Solution
A measurement apparatus and method that utilizes a processor to extract and analyze measurement data based on temporal-spatial constraints, determining whether an object satisfies these constraints to identify it as an analysis target, thereby filtering out noise and unintended objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If measurement data is collected in everyday life environments, then the quantity of measurement data increases, but noise due to measurement errors and unintended objects increases
Solution Approach 1:
The patent extracts and removes noise components from measurement data by identifying and eliminating data points that do not satisfy temporal-spatial constraints. The processor separates valid measurement data from noise by applying constraint-based filtering, thereby extracting required measurement data while removing harmful noise elements.
Solution Approach 2:
The patent introduces temporal-spatial constraints as an intermediary mechanism to mediate between raw measurement data and analysis results. These constraints act as a filtering layer that distinguishes valid data from noise, enabling the system to handle everyday life measurement data effectively without being affected by measurement errors or unintended objects.
2Object-affected harmful factors
If conventional noise removal methods are applied, then measurement error noise is reduced, but analysis sites are limited or data selection becomes difficult
Solution Approach 1:
The patent creates a universal noise removal framework based on temporal-spatial constraints that can be applied across multiple analysis sites and measurement types. The constraint-based approach is not limited to specific measurement scenarios, enabling flexible data selection and analysis in various environments while maintaining effectiveness in noise removal.
Solution Approach 2:
The patent changes the parameters used for noise identification from fixed thresholds to dynamic temporal-spatial constraints. By evaluating whether measurement data satisfies time and space constraints rather than using predetermined thresholds, the system maintains adaptability across different analysis sites while effectively removing measurement error noise.
3Quantity of substance
If measurement data from public places is collected, then the quantity of data increases, but uniform determination of analysis targets becomes difficult due to noise
Solution Approach 1:
The patent implements a feedback mechanism where measurement data is evaluated against temporal-spatial constraints, and the results of this evaluation feed back into the selection of analysis targets. This closed-loop approach ensures uniform determination by continuously verifying whether data points satisfy the constraints, thereby maintaining measurement precision even when processing large quantities of public place data.
Solution Approach 2:
The patent applies preliminary filtering using temporal-spatial constraints before the actual analysis process. By pre-evaluating measurement data against time and space constraints, the system prepares clean, validated data for subsequent analysis, ensuring uniform determination of analysis targets even when processing large volumes of data from public places.
Data Source
AI summary
Provided is a measurement apparatus including a processor and a storage unit. The storage unit holds measurement data of each time point which is obtained by a photographing apparatus, and temporal-spatial constraints. The processor extracts a position of an object from the measurement data of each time point, determines whether the object satisfies the temporal-spatial constraints, and determines, based on a result of the determination on whether the object satisfies the temporal-spatial constraints, whether the object is an analysis target.