Method and tactical passive RFID transponder gloves with morphological actuation

A method comprising:

• receiving, via an external interface, (i) an RFID tag reading of an inventory object and (ii) an action sequence classification from an apparatus, wherein the apparatus comprises (i) a glove comprising two or more force sensors configured to measure resistance, (ii) an RFID reader, (iii) one or more antennas, and (iv) a controller coupled to the glove to evaluate the resistance measured from the glove and to read and/or tally RFID tags, wherein the controller is configured to determine the action sequence classification based on the measured resistance;
• and
• generating and storing a new field for an inventory database for an object identified by the RFID tag reading with an updated status associated with the action sequence classification and a position determined from the RFID tag reading, including an additional tally of the object,
• wherein the determination of the action sequence classification is performed by one or more machine learning classification and prediction algorithms configured to interpret the measured resistance, and other RFID readings, as action sequences for real-time movements of a person to be classified.

A non-transitory computer-readable medium having instructions stored thereon, wherein execution of the instructions by a processor causes the processor to:

• receive, via an external interface, (i) an RFID tag reading of an inventory object and (ii) an action sequence classification from an apparatus, wherein the apparatus comprises (i) a glove comprising two or more force sensors configured to measure resistance, (ii) an RFID reader, (iii) one or more antennas, and (iv) a controller coupled to the glove to evaluate the resistance measured from the glove and to read and/or tally RFID tags, wherein the controller is configured to determine the action sequence classification based on the measured resistance;
• and
• generate and store a new field for an inventory database for an object identified by the RFID tag reading with an updated status associated with the action sequence classification and a position determined from the RFID tag reading, including an additional tally of the object,
• wherein the determination of the action sequence classification is performed by one or more machine learning classification and prediction algorithms configured to interpret the measured resistance, and other RFID readings, as action sequences for real-time movements of a person to be classified.