Computer Vision Guest Tracking for Passive Order Delivery
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Solution Overview
Problem
Existing systems for delivering orders in dining environments often rely on visual searches for cards with printed numbers or use of output devices like buzzers, which can be inefficient and require guests to actively monitor for their orders.
Innovation Solution
A delivery system that uses computer vision to identify attributes of users in images captured by cameras, associate these attributes with orders, and track movement within the environment to determine the location for order delivery without the need for visual indicators or notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If visual search for cards with printed numbers is used to deliver orders, then guests can be identified and orders can be delivered, but the process becomes inefficient and requires guests to actively monitor for their orders
Solution Approach 1:
The patent replaces the mechanical visual search system with an automated computer vision system using cameras and image processing algorithms. The system automatically captures images, identifies guest attributes, and matches them with order information, eliminating the need for manual visual searching and guest monitoring of order status.
Solution Approach 2:
The system enables passive order delivery where guests do not need to actively monitor for their orders. The computer vision system autonomously tracks guests, determines their locations, and delivers orders without requiring guest intervention or attention, allowing guests to simply receive their orders at their tables.
2Reliability
If output devices like buzzers are used to notify guests of ready orders, then guests can be notified, but guests must actively monitor for notifications
Solution Approach 1:
The patent replaces acoustic notification devices (buzzers) with an automated computer vision-based notification system. The system uses image processing to automatically identify guests, determine their locations, and deliver orders directly to their tables, replacing the need for active acoustic notifications and guest monitoring.
Solution Approach 2:
The system implements continuous feedback through automated image capture and processing. Cameras continuously monitor the dining area, the system processes images to track guest locations, and automatically delivers orders when guests are identified at their tables, creating a closed-loop notification system that does not require guest attention.
3Productivity
If computer vision tracking is implemented to automatically deliver orders, then delivery efficiency improves and guest monitoring is eliminated, but system complexity increases
Solution Approach 1:
The patent divides the computer vision system into modular components: image capture devices (cameras), image processing units that extract guest attributes, attribute matching systems that link guests to orders, and delivery coordination systems. This segmentation makes the complex system more manageable and easier to implement.
Solution Approach 2:
The computer vision system performs multiple functions simultaneously: it captures images for guest identification, tracks guest movement throughout the dining area, determines current guest locations, and coordinates order delivery. This multi-functionality reduces the need for separate systems and manages overall complexity.
Data Source
AI summary
A delivery system may include one or more processors and memory storing instructions executable by the one or more processors to cause the one or more processors to identify one or more attributes of a user in one or more images and associate the one or more attributes of the user with an order placed by the user. The delivery system may also track the one or more attributes of the user in the one or more images over time to identify movement of the user within an environment and in response to the one or more attributes of the user in the one or more images remaining at a location for more than a threshold time, create an association between the one or more attributes of the user and the location. The delivery system may then provide an instruction to deliver items in the order to the location.