Image Processor User Notification Segmentation
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Solution Overview
Problem
Existing methods for informing users of changes in image processors, such as the addition of new functions or consumable item supplementation, are inefficient, often notifying all users regardless of relevance, and struggle to determine the correct user for notifications.
Innovation Solution
An image processor with a storage portion for user identification information, a status change detection mechanism, and a notification target determination system that identifies and notifies only the users who need to know about changes, such as added functions or consumable item replenishments based on their usage history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all users are notified of every status change in the image processor, then users are informed of all changes, but information overload occurs and notification efficiency decreases
Solution Approach 1:
The notification system segments users into different groups based on their usage history and job types. Instead of notifying all users uniformly, the system divides the user base into segments that are relevant to specific status changes, such as users who have executed specific job types or have particular execution conditions recorded. This segmentation ensures that only relevant users receive notifications, reducing information overload while maintaining completeness for affected users.
Solution Approach 2:
The notification system applies local quality by tailoring notifications to specific user groups based on their local characteristics and usage patterns. Different user segments receive different types of notifications based on their historical job execution patterns and relevance to the status change. This ensures that each user receives appropriate information without unnecessary noise, improving overall notification efficiency.
2Loss of information
If conventional notification methods are used, then all users receive status change information, but it is difficult to determine which user should be informed of newly added functions
Solution Approach 1:
The system performs preliminary action by pre-recording execution condition information for each job type in the storage portion before status changes occur. User identification information and execution conditions are stored in advance, allowing the notification target determination portion to quickly identify relevant users when a status change occurs. This preliminary preparation eliminates the need for complex real-time analysis and ensures accurate user identification.
Solution Approach 2:
The system uses feedback from historical job execution data to improve notification accuracy. By analyzing recorded execution conditions and user patterns, the system learns which users are most likely to be affected by specific status changes. This feedback mechanism enables the notification target determination portion to accurately identify users who should be informed of newly added functions or other status changes.
Data Source
AI summary
An image forming device includes a user job history database for storing execution condition information that indicates an execution condition of the job in relationship with user identification information for distinguishing a user who made the instruction for each executed job, a device structure detection portion for detecting a change in a state of the image processor, a notification target determination portion for determining a notification target user who is a user to be notified of the change in accordance with the execution condition information and the user identification information stored in the user job history database, and a new function notification portion for notifying the change to the determined notification target user.