Context-Aware Ad Display Using Neural Network Object Recognition

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Solution Overview

Problem

Current targeted advertising systems in public spaces lack real-time adaptability, effective object recognition, and context-aware ad display, while also raising privacy concerns.

Innovation Solution

A system utilizing neural networks and object recognition software, integrated with cameras and display screens, to identify specific objects and display relevant advertisements in real-time, with optional facial recognition and online data analysis for enhanced targeting.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional digital footprint-based advertising methods are used, then advertising can be delivered through websites and social media, but the system fails to account for real-time physical interactions and preferences

Engineering Contradiction:

Improvereal-time adaptability to physical environmentVSAvoidphysical context information

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The system segments the advertising delivery process into digital and physical components, using camera devices to capture physical environment data separately from digital footprint data, then integrates both through server processing to deliver contextually relevant advertisements that account for real-time physical interactions

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The server acts as an intermediary that receives and processes both digital footprint information and physical environment data from camera devices, combining these data sources to determine contextually appropriate advertisements that bridge the digital and physical advertising realms

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If basic sensors or QR codes are used in billboards, then advertising can be displayed in public spaces, but the system lacks real-time adaptability to dynamic public spaces

Engineering Contradiction:

Improvereal-time adaptation to public space dynamicsVSAvoidsystem sophistication

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system transitions from static billboard advertising to dynamic advertising by continuously capturing images with camera devices, processing these images in real-time to identify objects and people, and adjusting advertisement content dynamically based on current environmental conditions and detected targets

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system replaces basic mechanical sensors and QR code scanning with advanced image recognition technology using neural networks, enabling the billboard to automatically identify and target specific people and objects without requiring manual interaction or simple sensor detection

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If cameras and display screens are used in public places, then advertising content can be displayed, but the system lacks sophistication to identify specific objects or attributes for ad targeting

Engineering Contradiction:

Improveobject recognition precisionVSAvoidrecognition system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system replaces rudimentary camera-based detection with sophisticated image recognition technology utilizing trained neural networks that can automatically identify and classify specific objects, people, and attributes in captured images, providing precise targeting capabilities without requiring complex manual analysis

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the operational parameters of the camera system by integrating it with image recognition software that analyzes visual data for specific object characteristics, enabling the identification of detailed attributes such as object type, person demographics, and contextual information for refined advertising targeting

Inventive Principle:

Principle #35Parameter changes

4Measurement precision

If facial recognition technologies are used, then individual identification can be achieved, but ethical and privacy concerns arise and individual context understanding is limited

Engineering Contradiction:

Improveindividual identification precisionVSAvoidprivacy concerns

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The system applies different levels of identification precision to different advertising contexts, using full facial recognition only when necessary and appropriate, while relying on object recognition and contextual analysis for other cases, thereby balancing identification precision with privacy protection based on local requirements

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The server acts as an intermediary that processes facial recognition data through ethical guidelines and privacy filters, determining whether and how to use individual identification information for advertising purposes, thereby mediating between identification capabilities and privacy protection requirements

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentEP4538953A1System and related methods for real-time context-aware targeted advertising system using neural networks and object recognition in public spaces

Publication Date: 2025.04.16 BOBROV ANTON

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AI summary

The invention provides a system for real-time, context-aware targeted advertising in public spaces. Utilizing a combination of neural networks, object recognition software, and a hardware setup of cameras and display screens, the system identifies specific objects in the vicinity. Based on this real-time data, the system selects and displays advertisements that are most relevant to the individuals present. Advanced versions integrate facial recognition and online data analysis for more precise targeting. The system offers advertisers the ability to reach their intended audience more effectively while minimizing intrusion on those not interested in the displayed content.