Facial Recognition Visitor Profile System for Retail Personalization

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Solution Overview

Problem

Retailers and shopkeepers face challenges in identifying and accessing personal information of customers due to the increasing size and transient nature of populations, making it difficult to provide personalized customer interactions.

Innovation Solution

A system utilizing image sensors, local visitor profile databases, and input/output devices for facial recognition, which detects individuals, identifies known and unknown visitors, generates new profiles for unknowns, and updates existing profiles based on actions, allowing for personalized information retrieval and sharing across a decentralized network.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If shopkeepers maintain personal relationships with customers to know their names and personal information, then customer service quality improves, but this becomes impossible with increasing population size and transient nature

Engineering Contradiction:

Improvecustomer service qualityVSAvoidability to handle large transient populations

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system creates digital copies of customer profiles containing personal information, facial recognition data, and purchase history. These profile copies are stored in databases and can be quickly retrieved to provide personalized service without requiring shopkeepers to personally know each customer.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent replaces the mechanical system of human memory and personal recognition with automated facial recognition technology and database systems. Image sensors capture facial images, which are then matched against stored profiles using pattern recognition algorithms, eliminating the need for human shopkeepers to manually remember customer details.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If shopkeepers manually track and remember customer information, then personalized marketing can be provided, but this becomes inefficient and impossible at scale

Engineering Contradiction:

Improvepersonalized marketing efficiencyVSAvoidtime to identify and access customer information

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-capturing facial images during customer visits and pre-storing detailed customer profiles in databases before subsequent visits. This advance preparation enables instant identification and retrieval of personalized marketing information on future visits, eliminating the need for real-time data collection.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback loops where customer interactions, purchase behavior, and preferences are continuously monitored and fed back into the profile database. This ongoing feedback refines the stored information, enabling increasingly accurate personalized marketing recommendations over time.

Inventive Principle:

Principle #23Feedback

3Loss of information

If centralized databases are used to store all customer information, then comprehensive data access is achieved, but network bandwidth and processing demands increase

Engineering Contradiction:

Improvecompleteness of customer data accessVSAvoidnetwork bandwidth and processing demands

Core Design Contradiction:

Loss of informationVSUse of energy by moving object

Solution Approach 1:

The patent segments the centralized database architecture into distributed local databases at multiple retail locations. Each location maintains a local copy of relevant customer profile data, allowing shopkeepers to access customer information without requiring continuous communication with a central server, thereby reducing network bandwidth consumption.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements local quality by storing and processing customer data at the local retail location rather than requiring all operations to access a centralized database. This localization enables faster access to customer information and reduces the energy and bandwidth requirements for data transmission across the network.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS20240289820A1Systems and methods using facial recognition for detecting previous visits of a plurality of individuals at a location

Publication Date: 2024.08.29 CAPITAL ONE SERVICES LLC

AI summary

Systems and methods for enhancing customer service are disclosed. The system can perform operations including detecting individuals and performing facial recognition on the individuals using visitor profiles stored by a local database. The operations can further include determining known visitors and unknown visitors among the individuals. The operations can further include generating new visitor profiles for the unknown visitors, obtaining identity information for the unknown visitors, and associating the identity information of the unknown visitors with the new visitor profiles. The operations can further include accessing identify information of the known visitors, obtaining personalized information for the known visitors from a central database, and providing the personalized information to the known visitors. The operations can further include updating the existing visitor profiles and new visitor profiles based on actions of the known visitors and actions of the unknown visitors and providing the updated visitor profiles to the central database.