RFID Asset Location Sensing with Local Signal Profiles
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Solution Overview
Problem
Existing location sensing technologies are limited in functionality and accuracy, particularly for indoor applications, due to line-of-sight requirements, high infrastructure costs, and assumptions about uniform signal strength, leading to inaccurate asset location predictions.
Innovation Solution
Implementing multiple readers and tags in fixed geographical areas and storage units, with redundancy checks and signal strength comparisons to predict asset location, and employing data cleaning methods that account for varying signal strengths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional location sensing technologies (GPS, triangulation) are used, then location tracking is enabled, but accuracy deteriorates in indoor environments without line-of-sight
Solution Approach 1:
The patent replaces traditional GPS satellite-based electromagnetic triangulation with an RFID-based proximity detection system. Instead of relying on line-of-sight electromagnetic signals from satellites, the system uses RFID readers and tags to detect physical proximity and presence in indoor environments, substituting a mechanical proximity-based system for an electromagnetic triangulation system that fails indoors.
Solution Approach 2:
The patent introduces RFID tags as intermediary objects placed throughout the facility and RFID readers as intermediary detection devices. These intermediaries enable indirect location determination by detecting which reader can communicate with which tag, providing accurate indoor location data without requiring direct line-of-sight satellite signals.
2Measurement precision
If RFID readers and tags are deployed throughout the facility, then location sensing capability is improved, but infrastructure cost increases
Solution Approach 1:
The patent segments the facility into multiple zones, each monitored by dedicated RFID readers. Tags are strategically placed at key locations such as storage units, conveyor belts, and loading docks. This segmentation allows the system to achieve high location precision in critical areas without deploying readers throughout the entire facility, reducing overall infrastructure complexity.
Solution Approach 2:
The RFID tags serve multiple functions: they identify assets, determine location, and track movement through the facility. The same tag infrastructure supports various tracking scenarios including static storage unit location, dynamic conveyor belt tracking, and loading dock asset monitoring, reducing the need for separate systems for different tracking needs.
3Measurement precision
If signal strength comparisons are used to determine specific location, then location precision is improved, but assumption of uniform signal strength causes inaccuracies
Solution Approach 1:
The patent applies local quality by creating location-specific signal strength profiles for each reader-tag pair. Instead of assuming uniform signal strength across all readings, the system learns and stores the characteristic signal strength range for each specific reader-tag combination based on their physical relationship. This allows accurate location determination even when signal strengths vary due to environmental factors, as the system compares against the expected local signal profile rather than a universal standard.
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
Achieves more granular and accurate location sensing with reduced human intervention, improving existing technologies like Active Badge, RADAR, and Cricket Location Support System by enhancing precision and redundancy.
Implementation Method 1
An indication that a set of reader devices have received or read data from a target RFID tag
Data Source
AI summary
Various embodiments employ multiple readers and tags in fixed locations in different geographical areas and/or along different storage units. This allows for more granular or precise location sensing. Particular embodiments employ multiple environment tags in various geographical locations and within multiple storage units. Using this new infrastructure setup, some embodiments can perform new functionality by predicting whether a target asset is in a particular geographical location, predict whether the asset is within a particular storage unit based on the proportion of readers mapped to that shelf which are actually reading the tag on the asset, and/or can predict where an asset's exact location in the located storage unit is based on comparing indications of signal strength values between each reader and tag in the storage unit with other indications of signal strength values between each reader and the tag that is attached to the asset.