Supervisory Data Selection for Automated Learning Model Sharing
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Solution Overview
Problem
Existing techniques for sharing supervisory data among apparatuses with learning functions do not provide methods for selecting desired supervisory data or cameras with which to share it, requiring additional manual work.
Innovation Solution
An information management apparatus with a communication unit and control unit that automatically selects and transmits supervisory data to appropriate external apparatuses with learning functions, enabling automated selection and sharing of supervisory data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If supervisory data is shared among multiple apparatuses without automatic selection, then data sharing can occur, but additional manual work is required for selecting desired supervisory data and cameras
Solution Approach 1:
The system enables automatic selection and sharing of supervisory data through the control unit, which autonomously determines which external apparatus should receive supervisory data based on learning model compatibility without requiring manual user intervention for each data sharing decision
Solution Approach 2:
The control unit changes the parameter of data sharing by automatically adjusting which supervisory data is transmitted to which external apparatus based on matching learning models, transforming the manual selection process into an automated parameter-driven process
2Productivity
If all supervisory data is transmitted to all external apparatuses, then data sharing is maximized, but transmission efficiency decreases due to irrelevant data being shared
Solution Approach 1:
The control unit extracts only the relevant supervisory data that matches the learning models of external apparatuses, separating useful data from unnecessary data before transmission, thereby improving efficiency and reducing energy waste
Solution Approach 2:
The system applies local quality by tailoring the supervisory data transmission to each specific external apparatus based on its learning model characteristics, ensuring that each apparatus receives data specifically suited to its needs rather than a universal dataset
3Loss of time
If manual selection of supervisory data and cameras is performed, then data sharing can occur, but time consumption increases
Solution Approach 1:
The control unit performs preliminary action by automatically determining and preparing the appropriate supervisory data for sharing before transmission, eliminating the need for users to manually select data and cameras at the time of sharing operations
Data Source
AI summary
An information management apparatus comprises a communication unit configured to communicate with a plurality of external apparatuses having learning functions, and a control unit configured to control the communication with the plurality of external apparatuses performed by the communication unit. The control unit, if supervisory data generated when a predetermined external apparatus executes a learning function is received from the predetermined external apparatus via the communication unit, selects, from among the plurality of external apparatuses, an external apparatus, other than the predetermined external apparatus, with which the supervisory data is to be shared, and performs control so that the supervisory data is transmitted to the selected external apparatus.