Multi-Sensor Subject Evaluation Using 2D Reference Images
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Solution Overview
Problem
Existing subject evaluation systems struggle to perform processes appropriate for a variety of sensors at different locations due to limitations in analyzing data from near-infrared cameras.
Innovation Solution
A subject evaluation device and system that utilize multiple sensors, an acquisition unit, a conversion unit, a reference database, and an evaluation unit to convert subject information into a two-dimensional evaluation target image, using machine learning to associate past evaluation target images with reference information for accurate evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If only near-infrared camera data is analyzed, then the system is simple to operate, but it cannot perform processes appropriate for multiple sensor types at various locations
Solution Approach 1:
The evaluation target image generation unit is designed to handle multiple sensor types (near-infrared cameras, visible light cameras, microphones, motion sensors) through a universal processing framework. Each sensor's data is converted into a standardized evaluation target image format, allowing the same evaluation algorithms to process diverse sensor inputs without requiring separate processing pipelines for each sensor type.
Solution Approach 2:
The evaluation target image serves as an intermediary representation that bridges different sensor types. By converting various sensor data (thermal images, visible light images, audio waveforms, motion data) into a unified evaluation target image format, the system enables consistent evaluation processing across heterogeneous sensors while maintaining operational simplicity.
2Measurement precision
If multiple sensors are used at various locations, then evaluation accuracy and adaptability improve, but the system complexity increases
Solution Approach 1:
The system merges data from multiple sensors located at various positions into a single unified evaluation target image. By combining near-infrared images, visible light images, audio data, and motion sensor data into one integrated representation, the system achieves comprehensive evaluation accuracy while presenting a simplified interface that does not require users to manage individual sensor complexities.
Solution Approach 2:
The system transforms multi-dimensional sensor data from various locations and types into a two-dimensional evaluation target image representation. This dimensional transformation allows complex spatial, temporal, and modal information to be consolidated into a format that can be processed by standard evaluation algorithms, reducing system complexity while maintaining measurement precision.
3Loss of information
If data from multiple sensor types is processed, then the evaluation becomes more comprehensive, but the processing difficulty increases
Solution Approach 1:
The evaluation target image generation unit extracts essential information from multiple sensor types and consolidates it into a single evaluation target image. By extracting key features from near-infrared images, visible light images, audio waveforms, and motion data, and combining them into one unified representation, the system maintains information completeness while simplifying the processing required for comprehensive evaluation.
Data Source
AI summary
A subject evaluation device (1) that evaluates the state of a subject (3) includes one or more sensors (2) that measure the state of the subject, an acquisition unit that acquires subject information on the subject and feature information via the sensor, a conversion unit that converts the subject information into an evaluation target image on a two-dimensional plane based on the feature information on the sensor, a reference database that stores an association between a past evaluation target image that has been preliminarily converted and reference information associated with the past evaluation target image, an evaluation unit that refers to the reference database and generates an evaluation result for the evaluation target image, and an output unit that outputs the evaluation result.