Shelf-Level Inventory Counting via RFID Antenna Segmentation
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Solution Overview
Problem
Current RFID solutions can only reliably identify assets within a room, making manual and time-consuming processes necessary for inventory tracking at shelf-level granularity, which requires identifying assets at specific rack, shelf, and depth locations.
Innovation Solution
Implementing a system with strategically placed RFID antennas along storage racks, connected to readers, and a process to determine XYZ positions and confidence levels of detected assets, allowing for automated shelf-level inventory counting by analyzing RFID tags and selecting the most accurate location based on relative detection locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional RFID solutions are used, then asset identification within a room is reliable, but shelf-level inventory counting requires manual processes that are time-consuming
Solution Approach 1:
The patent segments the storage space into discrete shelf-level locations by placing RFID antennas at specific rack, shelf, and depth positions. Each antenna is assigned a unique XYZ location that corresponds to a specific storage slot, enabling precise shelf-level identification rather than just room-level identification.
Solution Approach 2:
The patent introduces RFID antennas as intermediary detection points positioned at various shelf locations throughout the storage room. These antennas act as mediators between the RFID tags on assets and the central system, enabling automated detection of asset locations at shelf granularity without requiring manual counting.
2Measurement precision
If manual inventory counting is performed at shelf-level granularity, then precise location tracking is achieved, but the process becomes extremely time-consuming
Solution Approach 1:
The system enables self-service automated inventory counting where RFID readers automatically query antennas and detect RFID tags without human intervention. The system autonomously determines asset locations by analyzing which antenna detects which tag, eliminating the need for manual shelf-level counting while maintaining precise location tracking.
Solution Approach 2:
The patent replaces the mechanical manual counting process with an automated RFID-based detection system. Instead of physically inspecting each shelf location, the system uses electromagnetic field-based RFID communication between readers, antennas, and tags to automatically identify asset positions at shelf-level granularity.
3Extent of automation
If RFID readers are placed throughout the storage room, then shelf-level detection is enabled, but the system complexity increases
Solution Approach 1:
The system segments the storage room into a grid of rack-shelf-depth locations, with each location potentially having one or more RFID antennas. This segmentation allows the complex three-dimensional storage space to be managed through discrete, addressable units, simplifying the overall system architecture despite the distributed nature of the antennas.
Solution Approach 2:
The patent introduces a three-dimensional XYZ coordinate system to map RFID antenna locations to physical shelf positions (rack number, shelf level, depth). This dimensional mapping transforms the complex spatial arrangement of antennas into a structured coordinate framework that simplifies location tracking and system management.
4Measurement precision
If multiple RFID antennas are positioned at different shelf locations, then precise asset location determination is possible, but the system complexity and cost increase
Solution Approach 1:
The system uses partial coverage by placing RFID antennas only at strategic shelf locations rather than every possible position. The patent determines that sufficient location precision can be achieved with antennas positioned at key racks and shelves, without requiring complete coverage of every single storage slot, thus reducing system complexity while maintaining adequate precision.
Solution Approach 2:
The patent creates a virtual copy of the physical storage layout through the XYZ coordinate system that maps antenna positions to shelf locations. This digital representation allows the system to determine asset locations by identifying which virtual location corresponds to the detecting antenna, simplifying the interpretation of RFID data without requiring physical markers or complex positioning hardware.
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 automates the inventory tracking process at shelf-level granularity, significantly reducing the time required for inventory counts and improving accuracy by determining the precise location of assets within complex storage configurations.
Implementation Method 1
track each asset as it moves through the storage room by detecting RFID tags on the assets using radio-frequency identification (RFID) readers
Data Source
AI summary
A radio frequency identification tag at a plurality of detection locations is detected and an expected location of the radio frequency identification tag is determined. A confidence level for each of the detection locations that detected the radio frequency identification tag is determined based on a relative location of the corresponding detection location as compared to the expected location. The determined confidence levels of the detection locations is analyzed to select at least one of the detection locations and an action based on the at least one selected detection location is performed.