Method and tactical passive RFID transponder gloves with morphological actuation
Inventors
Maxwell, Erick Niels • David, Eres • Eicholtz, Steven Paul • Finlayson, Samuel • Fullerton, Dean • Kealy, John • Lewis, Cameron • Matthews, Michael • Orlando, Dante Gabriel • Ramirez-Medina, Jacqueline • RIDLEY, Jonathan • Robinson, Kelden • Singh, Rudra Pratap • Terrell, Daniel Andrew • Zaman, Samrin
Assignees
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Publication Number
US-12632110-B2
Publication Date
2026-05-19
Expiration Date
Abstract
Disclosed herein are an exemplary apparatus, system, and methods (e.g., Tactical Passive RFID transponder gloves with Morphological Actuation) comprising a glove made predominately of a resistive fabric that varies resistance per degree of deformation; comprising near field communication RFID tag readers, and a controller coupled to the glove to evaluate the varied resistance. A method of classifying RFID tags is also disclosed.
Core Innovation
The invention describes an inventory management system that receives an RFID tag reading of an inventory object and an action sequence classification from an apparatus comprising a glove, force sensors, an RFID reader, antennas, and a controller. Machine-learning classification and prediction algorithms interpret measured resistance and other RFID readings as action sequences for real-time movements of a person, supporting updates to the inventory object's status, position, and tally.
The described system generates and stores a new field in an inventory database, associating the object identified by the RFID tag reading with an updated status and position and an additional tally. The controller can also disable transmission based on glove morphology. The partial content does not include the background section, so the problem being solved in that section is not explicitly described in patent.
Claims Coverage
The claim coverage encompasses four inventive features across three independent claims, comprising an inventory management system, a method, and a non-transitory computer-readable medium.
Inventory management system
A processor and memory receive, via an external interface, an RFID tag reading and an action sequence classification from an apparatus comprising a glove with two or more force sensors configured to measure resistance, an RFID reader, one or more antennas, and a controller. The system generates and stores a new inventory database field with an updated object status, a position determined from the RFID tag reading, and an additional tally.
Inventory management method
The method receives, via an external interface, an RFID tag reading and an action sequence classification from the glove apparatus, then generates and stores a new inventory database field with the identified object's updated status, position determined from the RFID tag reading, and additional tally.
Non-transitory computer-readable medium
The medium stores instructions that cause a processor to receive an RFID tag reading and an action sequence classification from the glove apparatus and to generate and store a new inventory database field containing the identified object's updated status, position, and additional tally.
Machine-learning action sequence classification
For each independent claim, one or more machine-learning classification and prediction algorithms interpret measured resistance and other RFID readings as action sequences for real-time movements of a person to be classified.
The independent claims cover system, method, and computer-readable-medium forms of inventory updating based on RFID readings and machine-learning action sequence classifications derived from glove resistance measurements and RFID readings.
Stated Advantages
Morphology-based control of RFID transmission is described as reducing power and avoiding unintended operation.
Documented Applications
Ammunition tracking.
Warehouse and package inventory tracking.
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