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Methods, systems, and computer readable media for tracking consumer interactions with products using modular sensor units

  • US 10,083,453 B2
  • Filed: 12/31/2013
  • Issued: 09/25/2018
  • Est. Priority Date: 03/17/2011
  • Status: Active Grant
First Claim
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1. A system for tracking interactions with products, comprising:

  • a merchandising unit;

    a plurality of sensors configured to detect signals that change over time in response to a plurality of product items being removed or returned from the merchandising unit;

    a daisy-chain system, for incremental electrical connection of the plurality of sensors to upstream and downstream wiring segments joined by multi-conductor wires transmitting power to the plurality of sensors;

    a database containing allowable and non-allowable patterns of the plurality of product items; and

    a signal processor connected to the daisy-chain system configured to;

    receive and log the signals detected by the plurality of sensors;

    communicate with the database containing the allowable and non-allowable patterns; and

    execute a pattern matching algorithm by;

    identifying a pickup event, of at least one of the product items, detected as a peak in at least one of the detected signals indicating that a shopper has pressed down on the at least one of the product items prior to removing the at least one of the product items, followed by a period, detected by a lower signal level at a tail of the at least one of the detected signals, when the at least one of the product items weighs less than prior to the pickup event,identifying a vibration event when the at least one of the product items is jolted,generating a percentage best pattern match using a plurality of identified pickup and vibrations events for the at least one of the product items within the database,applying an acceptance percentage threshold to the generated percentage best pattern match to classify the plurality of identified pickup events into an allowable pattern,applying a rejection percentage threshold to the generated percentage best pattern match to classify the vibrations events into a non-allowable pattern,identifying un-assignable events that do not meet the acceptance percentage threshold or the rejection percentage threshold, anddetermining from the acceptance percentage threshold, the rejection percentage threshold, and newly discovered patterns, valid signals produced by the plurality of identified pickup events of the at least one of the product items and invalid signals produced by the vibrations events, andupon determination of the valid signals further identifying a position and an associated facing of the at least one of the product items that was identified as being removed or returned from the merchandising unit.

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