Facility User Group Estimation and Payment Confirmation

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Solution Overview

Problem

Existing facility management systems, such as unmanned AI stores, struggle with accurately identifying and grouping users for automated payment processing, particularly when unregistered individuals or groups like families and friends shop together, leading to inefficiencies and inaccuracies in payment handling.

Innovation Solution

An information processing apparatus and method that utilizes cameras and a management server to identify individuals, estimate groups based on interaction and attribute data, and present estimation results for user confirmation, allowing for accurate group and payer setting, followed by collective payment processing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If automated payment processing is implemented for unregistered users, then service coverage and user accessibility are improved, but payment accuracy and group identification reliability deteriorate

Engineering Contradiction:

Improveservice coverageVSAvoidpayment accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system performs preliminary actions by estimating user groups and presenting estimation results to users before final payment processing. This allows unregistered users to be preliminarily identified and grouped based on their behavior patterns, then confirms the estimation with the actual user to ensure accuracy before executing the payment.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback by presenting the estimated group information to the user and receiving confirmation or correction. This feedback loop allows the system to verify its estimation against actual user input, thereby improving payment accuracy while maintaining service coverage for unregistered users.

Inventive Principle:

Principle #23Feedback

2Productivity

If group estimation is performed automatically, then processing efficiency and productivity are improved, but measurement precision and identification accuracy worsen

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidgroup identification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system performs partial action by estimating only certain group characteristics automatically based on available data, rather than attempting complete and perfect identification. This allows the system to maintain high processing efficiency while presenting partial estimation results that can be refined with user confirmation.

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If manual group confirmation is implemented, then group identification accuracy is improved, but processing time and operational complexity increase

Engineering Contradiction:

Improvegroup identification accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables self-service by allowing users to confirm or correct their own group estimation through simple interactions. This reduces the need for complex manual verification processes while maintaining high identification accuracy, as users can quickly verify the system's estimation against their actual group composition.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250238779A1Information processing apparatus, information processing method, and storage medium

Publication Date: 2025.07.24 NEC CORP

AI summary

In an information processing apparatus, the person identifying means identifies a person who has entered a facility. The group estimation means estimates a group including a plurality of persons. The group presentation means presents an estimation result of the group to the person. The group setting means sets the group based on a response to the estimation result of the group.