RF Asset Tag Tracking with Mobile Device Mediator
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Solution Overview
Problem
Current tracking systems in brick and mortar stores face challenges in associating consumer movement data with individual users across multiple visits, as existing RF tracking systems can only track assets like shopping carts and not specifically link the movement data to the consumer using them.
Innovation Solution
A system comprising RF-enabled nodes and a back end server that tracks RF-enabled asset tags within a space, determines their location, and associates this data with user identification information using predetermined correspondence criteria to link asset tag movement history with the relevant user in a database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If RF tracking systems are used to track assets like shopping carts, then movement data can be collected, but the data cannot be associated with specific consumers across multiple visits
Solution Approach 1:
The patent introduces a mobile device as an intermediary between the consumer and the RF tracking system. The mobile device contains both the consumer's identification information and an RF tag for tracking. This mediator enables the system to associate movement data with consumers without requiring direct authentication steps between the consumer and the tracking system, thereby resolving the contradiction by maintaining accurate consumer identification while reducing system complexity.
Solution Approach 2:
The mobile device serves multiple functions simultaneously: it acts as the consumer's identification carrier, the RF tracking tag, and the data collection interface. By making the mobile device universal for these purposes, the system eliminates the need for separate authentication mechanisms and RF tags, thereby reducing device complexity while maintaining the ability to identify consumers across multiple visits.
2Reliability
If consumers are tagged via their personal smartphone, then consumer tracking is possible, but several authentication steps and hardware compatibility development are required
Solution Approach 1:
The system leverages the consumer's existing mobile device to perform tracking functions. The mobile device already contains necessary components (processor, display, RF capabilities) and operates autonomously without requiring additional authentication steps or specialized hardware. This self-service approach maintains tracking accuracy while eliminating complex system development requirements.
Solution Approach 2:
The patent changes the operational parameters by utilizing the mobile device's existing RF capabilities and processing power rather than requiring dedicated tracking hardware. By adapting the mobile device's existing parameters (battery power, RF transmission, processor) for tracking purposes, the system achieves reliable tracking without the need for specialized hardware development or complex authentication protocols.
3Measurement precision
If sensors are used to track RF tags through a store, then positional data can be generated, but tagging every item and consumer is dauntingly expensive
Solution Approach 1:
The patent extracts the RF tracking functionality from the environment and places it in the mobile device itself. Instead of requiring sensors throughout the store to track every item, the system uses the mobile device's RF capabilities to perform tracking. This extraction reduces the number of tags and sensors needed while maintaining positional data accuracy, thereby reducing costs.
Solution Approach 2:
The system replaces expensive, permanent installation of RF sensors and tags with the consumer's existing mobile device, which is inexpensive and portable. The mobile device serves as a disposable-like component that doesn't require permanent installation or high upfront costs, enabling accurate tracking without the daunting expense of tagging every item or installing sensors throughout the store.
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
Enables the collection and analysis of consumer movement data across multiple visits, providing insights into store design improvements and shopping habits by accurately associating asset tag movement with individual users, enhancing data-driven decision-making for retailers.
Implementation Method 1
one or more radio frequency-enabled nodes located within a space, each radio frequency-enabled nodes being configured to communicate with a radio frequency (RF)-enabled asset tag within the space
Data Source
AI summary
In an example, a method comprises communicating with a radio frequency (RF)-enabled asset tag within a space, tracking a location of the RF-enabled asset tag within the space, determining location estimates of the asset tag as the asset tag moves within the space, and accepting identifying information from or about a selected user. The method additionally comprises determining, based on a predetermined correspondence criteria, a correspondence between the asset tag location and a position estimate of an electronic hardware device within the space. Further, in response to determining the correspondence between the asset tag and the electronic hardware device and based at least in part on the identifying information accepted via the electronic hardware device, the method includes associating tracked asset tag location information corresponding to the location estimates of the asset tag as the asset tag moved within the space to identification of the selected user.