Casino Chip Tracking and Inventory Aggregation via Edge Patterns
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Solution Overview
Problem
Casino gaming environments face challenges in accurately tracking and managing casino chip inventories across multiple tables due to variations in lighting and perspective, leading to inefficiencies in data integration and inventory management.
Innovation Solution
A system utilizing light sensors and machine learning models to detect and classify casino chips by edge patterns, integrated with a central server for real-time inventory management and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple cameras take pictures of casino chips from different perspectives to track chip inventory, then chip tracking coverage is improved, but image analysis complexity and computational resources increase significantly
Solution Approach 1:
The patent extracts only the essential feature (chip edge pattern) from the complete image data, eliminating the need to process entire images from multiple camera perspectives. By focusing solely on edge patterns, the system achieves accurate chip denomination identification with minimal computational resources.
Solution Approach 2:
The system creates a simplified representation (copy) of the chip edge pattern rather than processing the full original images. This edge pattern copy contains sufficient information for chip identification while dramatically reducing the data volume and processing complexity compared to analyzing complete camera images.
2Measurement precision
If detailed images of chips are captured to identify visible features for determining chip values, then chip value identification accuracy is improved, but computing resources required increase significantly
Solution Approach 1:
The patent extracts only the essential feature (chip edge pattern) from the complete image data, eliminating the need to process entire images from multiple camera perspectives. By focusing solely on edge patterns, the system achieves accurate chip denomination identification with minimal computational resources.
Solution Approach 2:
The system creates a simplified representation (copy) of the chip edge pattern rather than processing the full original images. This edge pattern copy contains sufficient information for chip identification while dramatically reducing the data volume and processing complexity compared to analyzing complete camera images.
3Measurement precision
If chip tracking systems are implemented at multiple gaming tables to monitor chip inventories, then inventory monitoring coverage is improved, but data integration complexity increases
Solution Approach 1:
The patent uses a uniform edge pattern detection methodology across all gaming tables, ensuring consistent data collection standards. This homogeneity in the tracking approach simplifies the aggregation and integration of chip inventory data from multiple tables, as all data points follow the same detection and classification protocol.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate, real-time tracking and aggregation of casino chip inventories across multiple tables, enhancing management capabilities and reducing computational resources.
Implementation Method 1
detecting, for at least one column of the chip tray based on a detected level of ambient light at a plurality of light sensors positioned inside the at least one column
Data Source
AI summary
A casino chip inventory management system and method are disclosed. The system includes a plurality of chip tracking apparatuses, each comprising a chip tray with light sensors in at least one column and a tracking controller. Each controller computes a total value of, in one example, the at least one column, or in another example, a total tray value for all columns in a tray by determining chip denominations based on ambient light detection at the sensors and machine learning analysis of chip edge patterns. A central server, networked to these apparatuses, receives the total values, aggregates them to determine a casino-wide chip inventory status, and generates related reports or alerts. This enables centralized monitoring and management of chip inventories across multiple gaming tables, supporting auditing and operational efficiency.