Digital Signage Campaign Optimization Using Mathematical Solvers

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Solution Overview

Problem

Existing digital signage management systems lack automation in adjusting active campaigns to accommodate new campaigns, and legacy availability engines struggle to support new use cases efficiently.

Innovation Solution

A method and computing device that utilize a mathematical solver to generate optimal configuration data for deploying new digital signage campaigns by processing screen data, requirements of active and candidate campaigns, and constraints, replacing legacy availability engines with a mathematical solver for dynamic campaign optimization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If a proprietary availability engine is used to manage digital signage campaigns, then pre-defined use cases are supported, but the system cannot automatically adapt to new use cases and requires manual adjustment of active campaigns

Engineering Contradiction:

Improveability to support new use casesVSAvoidautomatic adjustment of active campaigns

Core Design Contradiction:

Adaptability or versatilityVSExtent of automation

Solution Approach 1:

The patent replaces the proprietary availability engine (a rigid, rule-based system) with a mathematical solver that uses optimization algorithms to automatically determine campaign configurations. This substitution enables the system to handle new use cases by formulating them as mathematical optimization problems rather than requiring manual programming of rules for each scenario

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the approach from fixed rule-based parameters to dynamic mathematical parameters that can be adjusted automatically. The mathematical solver optimizes parameters such as campaign scheduling, screen allocation, and configuration data based on objective functions and constraints, allowing automatic adaptation to new use cases without manual intervention

Inventive Principle:

Principle #35Parameter changes

2Ease of operation

If manual adjustment of active campaigns is performed to accommodate new campaigns, then configuration data can be modified, but the process requires user intervention and is time-consuming

Engineering Contradiction:

Improvemanual campaign configurationVSAvoidtime for manual adjustments

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system implements self-service by automatically adjusting active campaigns through mathematical optimization. The solver independently determines optimal configurations for new and existing campaigns without requiring user intervention, thereby eliminating the time loss associated with manual adjustments while maintaining operational simplicity

Inventive Principle:

Principle #25Self-service

3Reliability

If legacy availability engines are used for campaign deployment, then existing campaigns are managed, but the system lacks processing power and flexibility for complex optimization scenarios

Engineering Contradiction:

Improvecampaign deployment stabilityVSAvoidprocessing capability for optimization

Core Design Contradiction:

ReliabilityVSPower

Solution Approach 1:

The patent replaces legacy availability engines with advanced mathematical solvers that utilize optimization algorithms (such as linear programming, integer programming, or heuristic methods). This substitution significantly enhances processing capability while maintaining deployment stability through mathematically guaranteed optimal or near-optimal solutions

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Ease of manufacture

If proprietary software is used to determine campaign deployment, then pre-defined scenarios are handled, but the system is difficult to adapt and lacks flexibility

Engineering Contradiction:

Improvesoftware adaptabilityVSAvoidsystem rigidity

Core Design Contradiction:

Ease of manufactureVSDevice complexity

Solution Approach 1:

The mathematical solver provides a universal framework that can handle diverse campaign deployment scenarios through a single optimization engine. By formulating different use cases as variations of optimization problems with different objective functions and constraints, the system achieves multi-functionality without requiring separate proprietary software for each scenario, thereby reducing system rigidity

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250225552A1Method and computing device for performing dynamic digital signage campaign optimization

Publication Date: 2025.07.10 BROADSIGN INTELLECTUAL PROPERTY INC

AI summary

Method and computing device for performing dynamic digital signage campaign optimization. Screen data associated to screens controlled by the computing device and requirements of active campaigns are stored at the computing device. The screen data comprise characteristics of the screens and screen activity data defining the activity the screens for the active campaigns. The computing device receives requirements of a candidate campaign and generates a mathematical model based on the requirements of the candidate campaign, the requirements of the active campaigns, and at least some of the screen data. The mathematical model is transmitted to a mathematical solver and a mathematical solution generated by the mathematical solver is received. The computing devices generates configuration data for the candidate campaign based on the mathematical solution. The configuration data define a configuration for displaying a content of the candidate campaign on selected screens among the screens controlled by the computing device.