Digital Signage Content Scheduling via Linear Programming
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Solution Overview
Problem
Existing outdoor advertising systems using digital signages lack an effective scheduling algorithm to optimize content exposure based on varying target customer populations across time zones, making it difficult to maximize advertisement effectiveness due to constraints such as different play rates for different content types.
Innovation Solution
A content scheduling method utilizing a linear programming model that determines optimal play counts for target content across time slots by assigning weight values indicating preference, considering total play counts and floating populations, and prioritizing content based on contract costs to maximize exposure and profit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If content scheduling is performed without considering target customer population variations, then the scheduling process is simple, but the exposure effect of advertisement content deteriorates
Solution Approach 1:
The patent applies parameter changes by introducing weight values that represent target customer population variations across different time slots. The linear programming model uses these weight values as parameters to optimize content scheduling, transforming the scheduling problem from a simple time-based allocation to a population-weighted optimization problem that maximizes exposure effect
Solution Approach 2:
The patent adds a new dimension to content scheduling by incorporating target customer population data as a weighting factor. Instead of scheduling content based solely on time slots, the system creates a multi-dimensional optimization space that includes population density, content type preferences, and time slot characteristics, solved through linear programming
2Productivity
If content scheduling considers various constraints such as different play rates for different content types, then the exposure effect is maximized, but the scheduling complexity increases
Solution Approach 1:
The patent achieves universality by designing a linear programming-based scheduling system that can handle multiple content types with different constraints through a unified mathematical framework. The system accommodates various play rates, time slot restrictions, and population variations using a single optimization model, eliminating the need for separate scheduling mechanisms for different content types
Solution Approach 2:
The patent manages scheduling complexity by transforming multiple content-specific constraints into standardized parameters within the linear programming model. Play rates, time slot preferences, and population weights are converted into mathematical parameters that the optimization algorithm processes uniformly, simplifying the system architecture while handling diverse constraints
3Ease of operation
If uniform play count is assigned to advertisement content across all time slots, then the scheduling process is straightforward, but the exposure effect deteriorates due to ignoring floating population variations
Solution Approach 1:
The patent applies local quality by assigning different play counts to advertisement content based on the specific characteristics of each time slot. Instead of uniform distribution, the system calculates optimal play counts for each time slot by considering local population density, target customer presence, and content type preferences, thereby maximizing exposure effect in each specific time zone
Data Source
AI summary
A content scheduling method is provided. The content scheduling method, which is performed by a content scheduling apparatus, comprises acquiring a total play count of target content, determining a plurality of weight values of the target content with respect to a plurality of time slots, each weight value of the plurality of weight values indicating a first preference for the target content with respect to each time slot of the plurality of time slots, generating a linear programming model using the acquired total play count and the plurality of weight values and determining, via a processor, a play count of the target content in the each time slot of the plurality of time slots based on the linear programming model.