Task Content Identification via Priority-Based Model Comparison
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Solution Overview
Problem
Existing systems for identifying task content in workers based on sensor information are inefficient due to random comparison of sensor data with determination models, leading to wasted calculations and reduced efficiency.
Innovation Solution
A task content identifying system that includes an information acquisition unit for sensor data, a storage unit for determination models, a task identifying unit for comparing sensor data with models, and a priority setting unit to prioritize model comparisons based on probability values, allowing for efficient identification of task content by matching sensor information with high-priority models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sensor information is compared with determination models in random order, then all element tasks can be identified, but calculation waste occurs and identification efficiency is poor
Solution Approach 1:
The system performs preliminary actions by pre-calculating probability values for each element task based on historical data and task sequences. These probability values are stored in advance and used to guide the comparison process, eliminating the need for random ordering and reducing unnecessary calculations.
Solution Approach 2:
The system changes the parameter of comparison order from random to priority-based on probability values. By dynamically adjusting the comparison sequence according to calculated probabilities, the system identifies tasks faster and reduces computational waste while maintaining accurate identification.
2Measurement precision
If sensor information is compared with all determination models, then accurate task identification is achieved, but calculation time increases
Solution Approach 1:
The system performs preliminary calculations of probability values for each element task before the actual comparison process. This preliminary action enables the system to prioritize comparisons based on likelihood, reducing the number of models that need to be compared while maintaining high identification accuracy.
Solution Approach 2:
The system applies partial action by comparing sensor information with determination models in priority order based on probability values. Instead of exhaustively comparing with all models, the system stops when a match is found among the high-probability candidates, reducing calculation time while maintaining sufficient accuracy.
3Productivity
If determination models are compared in priority order based on probability values, then calculation efficiency is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary calculation of probability values using historical task data and sensor information patterns. This pre-computation simplifies the main identification process by providing ready-to-use priority rankings, reducing the complexity of real-time decision-making while improving calculation efficiency.
Solution Approach 2:
The system introduces probability values as an intermediary parameter between sensor information and determination models. This intermediary enables priority-based comparison without requiring complex real-time analysis, simplifying the system architecture while enhancing calculation efficiency through guided search.
Data Source
AI summary
In a series of tasks consisting of a plurality of consecutive element tasks, a task content identifying system for identifying task contents performed by a worker includes: an information acquisition unit that acquires sensor information indicating a state of a worker when the worker performs the element task; a storage unit that stores a determination model of each element task for identifying each element task; a task identifying unit that specifies an element task performed by the worker by comparing the sensor information of the worker acquired by the information acquisition unit with a determination model of each element task stored by the storage unit; and a priority setting unit that sets a priority of the determination model of each element task when the task identifying unit performs a comparison.