Automated Customer Movement Tracking via Color Sensor Image Processing
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Solution Overview
Problem
Current methods for tracking customer movements in Quick-Service Restaurants (QSR) are inefficient and prone to human error, requiring manual data collection that can distort transaction flows and is not economically viable for continuous monitoring, especially during peak hours.
Innovation Solution
An automated system using colour sensors to capture image frames, process them to isolate individual images, generate descriptors, and track customer movements across multiple frames, allowing for accurate and anonymized data collection and analysis of transaction states and durations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data collection by employees is used, then measurement precision is improved, but productivity deteriorates and loss of time increases
Solution Approach 1:
The patent replaces the mechanical manual data collection system with an automated image processing system using colour sensors and computer vision algorithms. The system captures images of customers, isolates individuals from frames, generates descriptors, and tracks movements automatically, eliminating the need for manual observation while maintaining high measurement precision through algorithmic analysis.
2Measurement precision
If multiple employees are deployed for data gathering, then measurement precision is improved, but device complexity and loss of substance increase
Solution Approach 1:
The patent merges multiple data collection functions into a single automated system. Instead of deploying multiple employees to track different aspects of customer behavior, the system uses image processing to simultaneously capture location, calculate waiting times, and monitor transaction states of all customers in the service area, reducing system complexity while improving tracking accuracy.
3Reliability
If manual tracking is used, then reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The system implements self-service automation where the image processing system independently performs data collection, analysis, and tracking without requiring human operators. The automated descriptor generation and customer movement tracking maintain reliable data while dramatically simplifying operation, as the system runs autonomously without manual intervention.
4Productivity
If automated image processing is used, then productivity is improved, but measurement precision may deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-processing images to isolate individuals and generate descriptors before tracking. This preliminary segmentation and feature extraction enables the automated system to maintain high measurement precision by establishing accurate customer identifiers and location data upfront, which then supports reliable real-time tracking and waiting time calculation throughout the service process.
Data Source
AI summary
System and methods for tracking transaction flow through a customer service area. The present invention provides automated, non-intrusive tracking of individuals, based on a series of still image frames obtained from one or more colour sensors. Images of individuals are extracted from each frame and the datasets resulting from the cropped images are compared across multiple frames. The datasets are grouped together into groups called “tracklets”, which can be further merged into “customer sets”. Various pieces of metadata related to individuals' movement (such as customer location and the duration of each transaction state) can be derived from the customer sets. Additionally, individual images may be anonymized into mathematical representations.