AI Drive-Through Ordering With Computer Vision Menu Preselection
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Solution Overview
Problem
Existing drive-through transactions are inefficient due to the limitations of human interaction, leading to slower service speeds and reduced profitability for establishments.
Innovation Solution
An AI-driven computing system that utilizes computer vision, facial recognition, and natural language processing to identify vehicle occupants, retrieve customer profiles, and predict menu items based on historical data, providing a customized and accelerated ordering experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human interaction is used in drive-through transactions, then service can be personalized, but transaction speed decreases and profitability is reduced
Solution Approach 1:
The system enables self-service by using computer vision to automatically identify customers, retrieve their profiles, and present personalized menus without human cashier intervention. The AI system independently completes tasks that previously required human workers, thereby increasing transaction speed while maintaining personalization.
Solution Approach 2:
The patent replaces the mechanical system of human interaction with an AI-based computer vision system. The AI agent performs customer identification, profile retrieval, and menu presentation functions that previously required human cashiers, thereby eliminating the trade-off between personalization and speed.
2Productivity
If AI automation is implemented in drive-through transactions, then transaction speed increases, but system complexity increases
Solution Approach 1:
The AI agent is designed as a universal system that performs multiple functions: customer identification via computer vision, profile retrieval from databases, personalized menu generation, and transaction processing. By consolidating these diverse functions into a single multi-functional AI system, the patent manages complexity while achieving high productivity.
3Adaptability or versatility
If computer vision and facial recognition are used to identify customers, then service personalization is enhanced, but data privacy concerns increase
Solution Approach 1:
The system uses the vehicle as an intermediary identifier rather than directly processing biometric data. The computer vision system captures images of the vehicle and its occupants, but the vehicle serves as the primary key for retrieving customer profiles from the database, thereby reducing direct reliance on sensitive biometric data while maintaining personalization capabilities.
Data Source
AI summary
Mechanisms are provided for performing an artificial intelligence (AI) based drive-through transaction. A digital image capturing device, in response to a vehicle entering a drive-through, captures a digital image of the vehicle. A computer vision operation is executed on the digital image to analyze data patterns and identify an identity of individual(s) within the vehicle. User profile(s) are retrieved that correspond to the individual(s) within the vehicle. A customized menu of products and/or services is generated based on user profile information and one or more menu items are pre-selected from the customized menu based on contextual information derived from at least one of audio or digital image data received during the drive-through transaction. A menu presentation computing device, located in the drive-through, is controlled to present the pre-selected menu item(s) and the customized menu.