Cashierless Shelf Tracking With Battery-Free Displays and WCC
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Solution Overview
Problem
Current devices require network connections and power to exchange data, which complicates their setup and operation, especially in retail environments where seamless data exchange is needed for cashier-less transactions.
Innovation Solution
The use of wireless coded communication (WCC) devices with energy harvesting capabilities, integrated sensors, and machine learning algorithms to track item interactions and user behavior, enabling cashier-less transactions by detecting item takes and returns, and predicting shopping lists without the need for traditional network setups or continuous power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional network connections and power sources are used for data exchange devices, then reliable data communication is achieved, but device complexity and setup requirements increase
Solution Approach 1:
The patent replaces traditional mechanical/electrical network connections and power sources with wireless coded communication technology. WCC devices transmit data through acoustic signals in the ultrasonic frequency range, eliminating the need for physical network cables and power outlets. This substitution maintains communication reliability while dramatically reducing setup complexity, as devices can exchange data wirelessly through sound waves without requiring infrastructure installation.
Solution Approach 2:
The patent introduces an intermediary medium (acoustic waves in the ultrasonic frequency range) to transfer data between devices. Instead of direct electrical or radio frequency communication, the system uses sound waves as a carrier to encode and transmit information. This intermediary approach enables reliable data exchange through a physical medium that is already present in the environment (air), avoiding the need for specialized communication infrastructure.
2Measurement precision
If sensors and tracking systems are deployed to monitor item interactions, then transaction accuracy improves, but energy consumption increases
Solution Approach 1:
The patent implements self-service tracking where items equipped with WCC devices automatically transmit their own location and interaction data without requiring continuous power from external sources. The items use incidental mechanical forces (such as being picked up, moved, or placed) to trigger wireless data transmission, eliminating the need for continuous energy consumption. The system serves itself by converting physical interaction events into data transmission opportunities.
Solution Approach 2:
Instead of continuous monitoring that would consume constant energy, the system uses periodic action triggered by specific events. Sensors and WCC devices transmit data only when an interaction event occurs (item picked up, returned, misplaced), rather than continuously. This event-driven periodic transmission maintains measurement precision for all interactions while dramatically reducing overall energy consumption compared to continuous monitoring.
3Duration of action of stationary object
If continuous power supply is provided to tracking devices, then uninterrupted monitoring is achieved, but power requirements and infrastructure needs increase
Solution Approach 1:
The patent applies preliminary action by equipping items with WCC devices and power sources (such as batteries or energy harvesting components) before deployment. These pre-loaded power sources enable the items to autonomously transmit data whenever interactions occur, without requiring connection to external power infrastructure during operation. The preliminary preparation of power capacity ensures uninterrupted monitoring capability throughout the item's lifecycle in the store.
Solution Approach 2:
The system transitions from static continuous power consumption to dynamic event-triggered operation. Power is consumed dynamically only when interaction events occur, rather than continuously. The monitoring system adapts its energy usage to the actual activity level, maintaining monitoring continuity through event-driven transmissions while reducing overall power requirements through this dynamic operational mode.
Data Source
AI summary
A method for providing real-time recommendations to user in a shopping environment involves sampling a shopping environment using video cameras to generate video features related to a shopper in connection to an item, the sampling input to a machine learning model to create labels related to a state of a scenario, the scenario including the shopper handling the item. Supplemental information is provided to the shopper in connection with the item. The makeup of the supplemental information may be sourced from online service or device associated with the shopper. The supplemental information may be delivered to the shopper, or to a shopper-aware display in the store, or elsewhere. A processing entity associated with the store detects a scenario to identify the shopper as having finished shopping, and causing a charge of the item to a cashierless shopping cart associated with the shopper. In one example, passive, wireless weight sensors may be used to supplement input features for inferences made by the machine learning model. In another example, wireless, battery-free displays may be coupled to shelves to provide information related to supplemental information relating the item held by the shopper.