Digital Signage Screening for Inappropriate Customer Profile Images

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Solution Overview

Problem

Quick service restaurants face challenges in delivering fresh orders on time and preventing inappropriate imagery or language from being displayed on digital signage, leading to customer dissatisfaction and potential misdelivery.

Innovation Solution

A system utilizing machine-learning models to analyze customer profile images and language for appropriateness, preventing inappropriate content from being displayed on digital signage, and optimizing order preparation and delivery through geofencing and customer management systems.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If customer user profile images are displayed on digital signage to personalize customer experience, then customer satisfaction is improved, but inappropriate imagery may be displayed causing reputational harm

Engineering Contradiction:

Improvecustomer experienceVSAvoidinappropriate imagery display

Core Design Contradiction:

Ease of operationVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary analysis of customer profile images using machine learning models before displaying them on digital signage. The image appropriateness detection occurs in advance, allowing the system to pre-approve or reject images before they reach the display stage, thus preventing inappropriate content from being shown while maintaining personalized customer experience

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The machine learning model acts as an intermediary between the customer profile image source and the digital signage display. This intermediary layer automatically filters and evaluates images for appropriateness, blocking inappropriate content without requiring manual review, thus resolving the contradiction between displaying personalized content and preventing harmful imagery

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If orders are prepared in advance to improve service speed, then customer wait time is reduced, but food freshness deteriorates

Engineering Contradiction:

Improveorder preparation speedVSAvoidfood freshness

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The order preparation system dynamically adjusts timing based on real-time customer arrival predictions and order complexity. Rather than static advance preparation, the system flexibly schedules preparation to start at optimal times, ensuring food is ready when customers arrive while maintaining freshness by avoiding premature preparation

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system uses feedback from customer arrival data, order history, and kitchen capacity to continuously optimize preparation timing. This feedback loop allows the system to learn from past performance and adjust preparation schedules to balance speed and freshness, preparing orders early enough to ensure speed but not so early that freshness is compromised

Inventive Principle:

Principle #23Feedback

3Adaptability or versatility

If digital signage displays customer information to enhance personalization, then customer engagement is improved, but system complexity increases

Engineering Contradiction:

Improvepersonalization capabilityVSAvoidimage analysis system

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The machine learning system automatically performs image analysis and appropriateness determination without requiring manual intervention. The system serves itself by autonomously evaluating customer profile images, making the complexity hidden from users while delivering simple, reliable personalization functionality on the digital signage

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual image review processes are replaced with automated machine learning models. This substitution eliminates the need for human operators to manually check each customer profile image, reducing operational complexity while maintaining or improving personalization capabilities through automated, consistent evaluation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12517689B2Detection of inappropriate language and/or imagery for prevention of display on quick service restaurant signage

Publication Date: 2026.01.06 INSIGHT DIRECT USA INC

AI summary

A method of detecting inappropriate imagery in a customer user profile image intending to be displayed on digital signage at a quick service restaurant can include identifying the presence of a customer adjacent a digital sign; associating the customer with a customer user profile; analyzing, by a computer processor, the customer user profile image for inappropriate imagery in the customer user profile image; in response to the detection of inappropriate imagery, displaying on the digital sign either no image or a different image that does not contain inappropriate imagery; and, in response to the detection of inappropriate imagery, displaying on the digital sign the customer user profile image.