Facial User Recognition Platform for Personalized In-Store Identification
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Solution Overview
Problem
Existing systems fail to provide an efficient and personalized user experience for individuals entering a business establishment, often requiring significant human and computing resources to identify and cater to customer needs, while also lacking in security against malicious intent.
Innovation Solution
A user recognition platform that utilizes facial recognition and other biometric techniques to identify individuals entering a business, providing personalized user data to employee devices for enhanced customer experience and security, thereby reducing the need for extensive computing and human resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual identification methods are used to identify customers entering a business, then human resources and computing resources are consumed, but the system becomes inefficient and unable to provide personalized experiences at scale
Solution Approach 1:
The system uses automatic facial recognition to identify customers without requiring manual intervention. The camera captures images, the recognition system automatically identifies customers based on their facial features, and the system autonomously retrieves and provides personalized information, eliminating the need for manual customer identification processes
Solution Approach 2:
The patent replaces manual mechanical identification processes with automated optical and computational systems. Instead of manual recognition, the system uses camera-based image capture, facial recognition algorithms, and automated data retrieval mechanisms to identify customers and provide personalized experiences
2Adaptability or versatility
If comprehensive user data collection and processing is implemented, then personalized user experience is enhanced, but computing resources and data processing requirements increase significantly
Solution Approach 1:
The system performs preliminary actions by capturing customer images and storing them in a database before actual identification occurs. When a customer enters, the system quickly matches the captured image against the pre-existing database of registered customers, enabling rapid identification without requiring real-time processing of all historical data
Solution Approach 2:
The system extracts only the necessary facial feature data from customer images for identification purposes, rather than processing complete customer profiles or all available data. This selective extraction approach reduces computing resource consumption while maintaining personalized experience capabilities
3Speed
If automatic facial recognition system is deployed, then customer identification speed increases, but security risks and malicious intent detection become more challenging
Solution Approach 1:
The system incorporates feedback mechanisms where the results of facial recognition are verified and cross-referenced with additional data sources. The system can detect anomalies in recognition results and seek verification through alternative methods, providing a feedback loop that mitigates security risks while maintaining high identification speed
Solution Approach 2:
The system performs preliminary security checks and risk assessments before completing the identification process. By evaluating potential security threats in advance and preparing countermeasures, the system prevents malicious actors from exploiting the rapid identification capability while maintaining normal operational speed
Data Source
AI summary
A device may receive, from a camera device, an image that includes a person. The device may provide the image to a user recognition device and receive, from the user recognition device, a user identifier based on the person included in the image. In addition, the device may obtain user data based on the user identifier, the user data relating to prior activity relating to the person associated with the user identifier. The device may identify a user device based on a first physical location associated with the camera device and a second physical location associated with the user device, and provide the user data to the user device.