AI Power-Saving Control for Individual Printer Usage Patterns

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Solution Overview

Problem

Existing power-saving mode transition times in image forming apparatuses are optimized based on group data, which fails to accurately reflect individual usage patterns in remote work environments where employee attendance varies, leading to inefficient power consumption.

Innovation Solution

An image forming apparatus uses AI to learn individual employee information to optimize the power-saving mode transition time based on usage frequency models generated from individual employee information, rather than group data, to reduce overall power consumption.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of energy

If power-saving mode transition time is optimized based on group data, then power consumption can be reduced, but individual usage patterns in remote work environments are not accurately reflected

Engineering Contradiction:

Improvepower consumptionVSAvoidusage pattern accuracy

Core Design Contradiction:

Loss of energyVSMeasurement precision

Solution Approach 1:

The patent segments the usage data by individual users instead of aggregating group data. The learning unit learns usage patterns separately for each user based on their individual attendance status and device usage history, enabling accurate reflection of individual usage patterns while optimizing power-saving transitions for each user's specific behavior.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by tailoring the power-saving mode transition time to each individual user's usage patterns rather than using a uniform group-based approach. The system adapts the transition time according to each user's specific attendance and usage behavior, ensuring optimal power consumption for each local context.

Inventive Principle:

Principle #3Local quality

2Loss of energy

If power-saving mode transition time is extended, then power consumption is reduced, but device responsiveness to individual user needs decreases

Engineering Contradiction:

Improvepower consumptionVSAvoidresponse to usage patterns

Core Design Contradiction:

Loss of energyVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamics by making the power-saving mode transition time adaptive and variable based on real-time learning of individual usage patterns. The system dynamically adjusts the transition time according to each user's attendance status and usage behavior, allowing the device to respond flexibly to individual needs while maintaining power efficiency.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent incorporates feedback through the learning unit that continuously monitors and learns from individual user attendance status and device usage patterns. This feedback mechanism enables the system to adjust power-saving transition times based on actual usage data, ensuring both energy efficiency and adaptability to individual user needs.

Inventive Principle:

Principle #23Feedback

3Loss of energy

If AI-based individual usage pattern learning is implemented, then power-saving optimization improves, but system complexity increases

Engineering Contradiction:

Improvepower consumptionVSAvoidsystem complexity

Core Design Contradiction:

Loss of energyVSDevice complexity

Solution Approach 1:

The patent applies self-service by implementing an automated learning system that independently analyzes individual user attendance data and usage patterns without requiring manual configuration. The learning unit automatically adapts to each user's behavior and optimizes power-saving transitions, reducing the need for complex manual setup while achieving sophisticated power management.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent introduces an intermediary learning unit that bridges the gap between raw usage data and power-saving control decisions. This learning unit processes and interprets individual user patterns, translating complex data into optimized transition times, thereby managing system complexity through a dedicated intermediary component rather than direct complex control logic.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20250348128A1System, control method, and non-transitory recording medium

Publication Date: 2025.11.13 RICOH CO LTD

AI summary

A system includes an information processing apparatus and an apparatus to communicate with the information processing apparatus through a network. The information processing apparatus includes circuitry that inputs user information on an individual user on a day on which a usage frequency of the apparatus by the user is to be inferred into a usage frequency model that has learned a correspondence between the user information and the usage frequency of the apparatus, to infer the usage frequency of the apparatus on the day and determines a power-saving mode transition time based on the inferred usage frequency of the apparatus. The apparatus includes another circuitry that transitions to a power-saving mode when a time during which the apparatus is not used exceeds the power-saving mode transition time acquired from the information processing apparatus.