Information Processing Apparatus for Action State Estimation
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Solution Overview
Problem
Existing techniques for detecting user actions and states using motion sensors struggle to accurately estimate specific, long-duration actions from short-duration action patterns, and fail to integrate additional information sources effectively.
Innovation Solution
An information processing apparatus and method that combines action pattern recognition from motion sensors with other information sources, such as text data, to generate state information using a contribution level analysis, enabling the extraction of higher-level insights into user actions and intentions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If action pattern recognition is performed using only motion sensors for short periods, then processing speed and simplicity are improved, but measurement precision and reliability of long-duration action estimation deteriorate
Solution Approach 1:
The patent combines multiple information sources including motion sensor data, text information from social networking services, and other contextual data to estimate user actions and states. This merging of diverse data sources compensates for the limitations of short-duration sensor data alone, enabling accurate estimation of long-duration actions while maintaining processing efficiency through modular architecture.
Solution Approach 2:
The patent introduces text information and other contextual data as intermediary elements that bridge the gap between short sensor readings and long-duration action estimation. These intermediaries provide additional context that helps infer sustained actions without requiring continuous long-term sensor monitoring, thus maintaining both speed and precision.
2Loss of information
If multiple information sources are integrated for comprehensive analysis, then information completeness is improved, but device complexity increases
Solution Approach 1:
The patent segments the information processing system into distinct functional modules: a text information acquiring unit, a sensor information acquiring unit, an action pattern specifying unit, and a state analyzing unit. Each module handles specific tasks independently, which reduces overall system complexity while enabling comprehensive integration of multiple information sources. This modular architecture allows for easier maintenance and scalability.
Data Source
AI summary
There is provided an information processing apparatus including a matter extracting unit extracting a predetermined matter from text information, an action pattern specifying unit specifying one or multiple action patterns associated with the predetermined matter, an action extracting unit extracting each of the action patterns associated with the predetermined matter, from sensor information, and a state analyzing unit generating state information indicating a state related to the matter, based on each of the action patterns extracted from the sensor information, using a contribution level indicating a degree of contribution of each of the action patterns to the predetermined matter, for a combination of the predetermined matter and each of the action patterns associated with the predetermined matter.