Semantic Space Feature Extraction for Moving Body Behavior Analysis
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Solution Overview
Problem
Existing techniques lack efficiency in recognizing spaces where a moving body exhibits characteristic behavior, leading to increased time and cost in designing comfortable environments for such bodies.
Innovation Solution
An information processing device and method that utilize semantic model information to define specific space features by extracting attribute information of components in and around the space, allowing for the identification of similar spaces in other worlds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to recognize spaces where moving bodies exhibit characteristic behavior, then comprehensive analysis can be performed, but time and cost increase significantly
Solution Approach 1:
The patent segments the complex task of space analysis into distinct components: extracting semantic model information, defining space features through item sets, and identifying characteristic behaviors. This segmentation allows each component to be processed independently and efficiently, reducing overall analysis time while maintaining accuracy.
Solution Approach 2:
The patent creates abstract representations (copies) of spaces through semantic models and space features. Instead of analyzing physical spaces directly, the system works with extracted feature sets that capture essential characteristics, enabling rapid comparison and analysis without requiring detailed examination of actual spaces.
2Measurement precision
If detailed attribute information of multiple components is extracted to define space features, then definition accuracy improves, but processing complexity increases
Solution Approach 1:
The patent extracts only the necessary attribute information from semantic models to define space features. By selectively extracting relevant component attributes and organizing them into structured item sets, the system achieves accurate space feature definition without processing all available data, thereby reducing complexity.
Solution Approach 2:
The patent transforms complex semantic model data into simplified space feature parameters through item sets. This parameter transformation converts detailed component attribute information into a standardized format that is easier to process and compare, maintaining accuracy while reducing computational complexity.
Data Source
AI summary
A world in which a moving body moves is analyzed by using a semantic model of the world. A space feature characterizing a space in the world is defined by an item set that at least includes attribute information of a plurality of components present in and around the space. A specific space is a space where the moving body exhibits a characteristic behavior in the world. A specific space feature is the space feature characterizing the specific space. A plurality of components present in and around the specific space in a first world is extracted, and the specific space feature is defined by the item set. Then, a similar space having the space feature similar to the specific space feature regarding the specific space in the first world is extracted from a second world.