Spatially Selective Air Sampling via Unified Data Mapping
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Solution Overview
Problem
Existing air sampling devices require multiple installations across different spaces to diagnose fine suspended materials in air, leading to complexity and inefficiency in data management and contextual translation across independent data spaces.
Innovation Solution
An apparatus and method for controlling spatially selective air sampling that maps multimodal sensing values, including image, voice, and environmental data, to a unified data space, using a processor to generate color palette data, perform inference with a learning model, and control air sampling devices for each space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple air sampling devices are installed in each space to diagnose fine suspended materials, then diagnostic coverage is improved, but device complexity and data management burden increase
Solution Approach 1:
The patent applies universality by designing a single air sampling device capable of serving multiple spaces through spatially selective air sampling. The device can be configured to sample air from different spaces sequentially or simultaneously, eliminating the need for separate devices in each space while maintaining comprehensive diagnostic coverage across multiple locations
Solution Approach 2:
The patent applies segmentation by dividing the air sampling function into spatially selective sampling capabilities. The system segments the sampling process to target specific spaces individually, allowing one device to perform the work of multiple devices by selectively directing air sampling to different locations based on diagnostic needs
2Adaptability or versatility
If multimodal sensing data from independent data spaces is collected, then comprehensive sensing capability is improved, but data management complexity increases
Solution Approach 1:
The patent applies merging by integrating multiple independent data spaces into a unified data space. The system combines image data, environmental sensing data, and air sampling data from different spaces into a single coordinated data framework, enabling comprehensive sensing while simplifying data management through unified storage and processing structures
Solution Approach 2:
The patent applies the intermediary principle by introducing a unified data space as a mediator between multiple independent sensing systems. This intermediary structure enables different modalities of data from various spaces to be translated into a common format, facilitating integrated analysis without requiring direct complex interactions between all sensing systems
3Adaptability or versatility
If contextual translation is performed to map multimodal sensing data to unified data space, then data integration is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-establishing the unified data space structure and translation protocols before actual data collection. The system prepares the framework for contextual translation in advance, enabling rapid mapping of multimodal sensing data to the unified space during operation without time-consuming on-the-fly structural setup
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
Facilitates efficient data management and contextual translation by mapping diverse sensing data to a unified space, allowing for effective air sampling and diagnosis across multiple spaces with a single device, thereby improving economic feasibility and air quality monitoring.
Implementation Method 1
an air adjuster configured to suction the air of the space and transfer the suctioned air to the diagnostic module
Data Source
AI summary
Provided are an apparatus and a method of controlling spatially selective air sampling, the apparatus including a sensing unit configured to detect a multimodal sensing value for at least one space, a diagnostic module configured to collect fine suspended materials in air of the space and diagnose composition of the fine suspended materials, an air adjuster configured to suction the air of the space and transfer the suctioned air to the diagnostic module, and a processor configured to generate color palette data of a unified data space having pixel brightness corresponding to signal intensity of the multimodal sensing value, map the color palette data to a diagnostic result of the diagnostic module, perform inference through a learning model based on the color palette data and the diagnostic result, and control the air adjuster for each space according to an inference result to transfer the air to the diagnostic module.