Server Setting Screen for Cloud Image Transmission
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Solution Overview
Problem
Existing multi-function peripherals (MFPs) require significant time and effort to set up file names and storage rules for transmitting image data to cloud services, and existing solutions may inadvertently extract incorrect character strings from scanned images, leading to inconvenience.
Innovation Solution
A server system that presents setting screens to users for configuring image data transmission settings, allowing users to select pre-stored settings for similar image types, reducing the need for repetitive setup and minimizing errors by reflecting previous settings for similar image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually set file names and storage rules for each image data transmission, then transmission accuracy and user control are improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary actions by automatically extracting character strings from scanned images and pre-setting file names and storage rules based on image content analysis. This preliminary processing eliminates the need for users to manually configure each transmission, reducing setup time while maintaining accuracy through automated image recognition and content-based rule generation.
Solution Approach 2:
The system enables self-service by autonomously analyzing image data, extracting relevant character strings, and automatically generating transmission settings without user intervention. The automated system serves itself by configuring file names, selecting storage destinations, and managing transmission parameters based on image content, thereby reducing both time consumption and operational complexity.
2Productivity
If automated character string extraction is used for file naming, then setup time is reduced, but error rate in extracting correct character strings increases
Solution Approach 1:
The system implements feedback mechanisms where extracted character strings are validated against image content, user preferences, and predefined rules. The system learns from extraction results and adjusts its analysis parameters to improve accuracy. Feedback loops ensure that automated extraction maintains high reliability by correcting errors and refining character string selection based on continuous performance monitoring.
Solution Approach 2:
The system dynamically changes extraction parameters such as character string length, position weighting, and confidence thresholds based on image type and content characteristics. By adjusting these parameters adaptively, the system optimizes extraction accuracy for different image formats and content types, maintaining high reliability while preserving fast automated setup speed.
3Productivity
If pre-stored settings are automatically applied to similar image data, then operational efficiency is improved, but flexibility in managing different storage rules is reduced
Solution Approach 1:
The system dynamically adapts pre-stored settings based on image content analysis and user-specific requirements. Rather than rigidly applying fixed rules, the system adjusts transmission parameters, file naming conventions, and storage destinations according to the specific characteristics of each image and the user's preferences. This dynamic approach maintains operational efficiency while preserving flexibility for different storage scenarios.
Solution Approach 2:
The system applies local quality by customizing transmission settings for different image types, users, and storage destinations. Each user can have personalized storage rules, and settings are tailored to specific image characteristics such as content type, size, and sensitivity. This localized customization ensures that pre-stored settings remain flexible and adaptable to diverse storage requirements while maintaining high transmission efficiency.
Data Source
AI summary
A server presents a first setting screen for entering settings relating to target image data for transmission, transmits the target image data to a cloud service in accordance with the settings, stores the settings associated with a type of the target image data and information of a user, and presents a second setting screen for selecting whether or not to use settings identical to any stored settings for new target image data. When presenting the first setting screen, the server presents it in a state in which, from the stored settings which the user selected to use settings identical to, a type of image data is omitted and settings required for transmission have been reflected. The server stores a type of the new target image data added to and associated with the selected stored settings.