Light-Signal Cart Tracking for Lower-Resource Frictionless Shopping
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Solution Overview
Problem
Conventional frictionless shopping systems require significant computing and hardware resources to track shoppers, making them difficult to implement and maintain, especially in large spaces.
Innovation Solution
A frictionless shopping system utilizing light emission and detection features, where shopping carts and baskets emit light signals detected by ceiling-mounted cameras, reducing the reliance on resource-intensive computer vision techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computer vision techniques are used to continuously monitor and track shoppers, then shopping tracking accuracy is improved, but hardware and computing resources increase significantly
Solution Approach 1:
The patent introduces light-emitting tags attached to shopping carts and baskets as intermediary objects. These tags emit light signals that are detected by cameras, serving as a mediator between the shopper and the tracking system. This approach replaces direct computer vision analysis of shoppers with indirect light signal detection, significantly reducing computing resources while maintaining tracking accuracy.
Solution Approach 2:
The patent replaces the mechanical/computational system of continuous computer vision processing with an optical system using light-emitting tags and light detection. This substitution transforms the tracking mechanism from resource-intensive image processing to simpler light signal detection and processing.
2Reliability
If computer vision systems continuously monitor store videos to track shopper movements, then shopper tracking reliability is improved, but system complexity increases
Solution Approach 1:
Light-emitting tags attached to shopping carts and baskets serve as intermediaries that simplify the tracking system. Instead of complex computer vision algorithms analyzing video feeds to identify and track shoppers, the system directly detects light signals from these tags, significantly reducing system complexity while maintaining reliable tracking.
Solution Approach 2:
The patent uses light-emitting tags that act as simplified copies or representations of shoppers for tracking purposes. Rather than processing complex visual information about actual shoppers, the system tracks these simpler light signal sources, reducing computational complexity while preserving tracking functionality.
3Area of stationary object
If a large number of cameras are deployed to cover large store spaces, then detection coverage is improved, but hardware costs and maintenance difficulty increase
Solution Approach 1:
The light-emitting tags attached to shopping carts and baskets act as mobile intermediaries that extend detection coverage without requiring additional fixed cameras. As shoppers move throughout the store with their tagged carts or baskets, the light signals travel with them, enabling tracking across large areas with a reduced camera infrastructure.
Solution Approach 2:
The patent transitions from a static camera-based coverage model to a dynamic tracking model where coverage follows the shopper. By attaching light-emitting tags to mobile shopping carts and baskets, the system effectively moves the detection point to the shopper's location, eliminating the need for extensive camera coverage of the entire store space.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces the hardware and computing resources needed for tracking shoppers by using light signals, allowing fewer cameras and less continuous monitoring, thus simplifying implementation and maintenance.
Implementation Method 1
shopping carts and shopping baskets in a store are equipped with a light (e.g., a light emitting diode) that emits light signals (e.g., infrared light signals) that identify the shopping cart or basket
Data Source
AI summary
The present disclosure provides a system and method for providing a frictionless shopping experience. The method includes detecting that an item was removed from a first area and detecting, by a camera, a light signal emitted from a cart. The method also includes identifying the cart based on the light signal and determining, based on the identified cart, a shopper linked to the cart. The method further includes determining, based at least in part on a location of the camera in the space, that the shopper removed the item from the first area and assigning the item to the shopper.