Facial Recognition Customer Tracking for Amusement Machine Selection
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Solution Overview
Problem
In the amusement industry, particularly in pachinko parlors, it is challenging to accurately understand customer trends and migration patterns, leading to improper removal or replacement of amusement machines, which can result in attracting the wrong customer base and reducing sales.
Innovation Solution
An information processing apparatus that captures and analyzes facial images to identify repeat customers, calculates similarity degrees, and records usage data to determine migration and mobility ratios, enabling the selection of appropriate amusement machines for replacement based on actual customer behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If face recognition technology is implemented to identify customers and calculate mobility ratios, then customer trend analysis accuracy is improved, but device complexity and implementation cost increase
Solution Approach 1:
The patent replaces traditional mechanical identification methods (membership cards, manual registration) with automated face recognition technology. The system uses cameras to capture customer faces, automatically matches them against stored images, and calculates mobility ratios without requiring physical cards or manual data entry, thereby improving accuracy while reducing operational complexity
Solution Approach 2:
The system enables self-service customer identification where customers are automatically recognized and tracked without staff intervention. The face recognition system autonomously captures, stores, and analyzes customer images, automatically determining mobility ratios and providing insights without requiring manual customer registration or staff processing
2Productivity
If amusement machines are removed or replaced based on predicted decreasing trends, then machine management efficiency is improved, but customer migration patterns are not accurately captured leading to potential loss of high-frequency customers
Solution Approach 1:
The patent implements a feedback mechanism where face recognition data continuously monitors customer behavior patterns. The system captures actual migration information by tracking which machines customers visit and calculates mobility ratios that reflect real customer preferences. This feedback loop enables data-driven decisions about machine replacement, preventing the loss of high-frequency customers by identifying them through their consistent visitation patterns across different machines
Data Source
AI summary
A mobile ratio of a customer is obtained to support a marketing strategy related to attracting customers. A population extraction unit extracts the number of persons, in which a game of one of the models of amusement machines installed in past times is recorded, as the number of persons of a population from pieces of information included in a biological information database. A mobile ratio calculation result output unit calculates a ratio of the number of persons, who use a model except the models of the amusement machines in which the population is obtained in the currently-installed amusement machines in the pieces of information included in the biological information database, to the population as the mobile ratio. The present invention can be applied to an apparatus that analyzes a trend of customers.