SYSTEM AND METHOD FOR IMPROVING SITE OPERATIONS BY DETECTING ABNORMALITIES
First Claim
1. A system for improving site operations by detecting abnormalities, comprising:
- a first sensor;
a first sensor abnormality detector connected to the first sensor, and configured to learn a first normal behavior sequence based on detected data sent from the first sensor, the first sensor abnormality detector comprising a first scorer configured to assign a normal score to first sensor data corresponding to the learned normal behavior sequence and an abnormal score to first sensor data having a value outside of the value of the first sensor data corresponding to the learned normal behavior sequence;
a second sensor;
a second sensor abnormality detector connected to the second sensor, and configured to learn a second normal behavior sequence based on detected data sent from the second sensor, the second sensor abnormality detector comprising a second scorer configured to assign a normal score to second sensor data corresponding to the learned normal behavior sequence and an abnormal score to second sensor data having a value outside of the value of the second sensor data corresponding to the learned normal behavior sequence;
an abnormality correlation server configured to receive abnormally scored first sensor data and abnormally scored second sensor data, the abnormality correlation server further configured to correlate the received abnormally scored first sensor data and abnormally scored second sensor data sensed at the same time by the first and second sensors and determine an abnormal event; and
an abnormality report generator configured to generate an abnormality report based on the correlated received abnormally scored first sensor data and abnormally scored second sensor data.
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Accused Products
Abstract
A system for improving site operations by detecting abnormalities includes a first sensor abnormality detector connected to a first sensor and configured to learn a first normal behavior sequence, a second sensor abnormality detector connected to a second sensor and configured to learn a second normal behavior sequence, an abnormality correlation server configured to receive abnormally scored first sensor data and abnormally scored second sensor data, the abnormality correlation server further configured to correlate the received abnormally scored first sensor data and abnormally scored second sensor data sensed at the same time by the first and second sensors and determine an abnormal event; and an abnormality report generator configured to generate an abnormality report based on the correlated the received abnormally scored first sensor data and abnormally scored second sensor data.
305 Citations
27 Claims
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1. A system for improving site operations by detecting abnormalities, comprising:
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a first sensor; a first sensor abnormality detector connected to the first sensor, and configured to learn a first normal behavior sequence based on detected data sent from the first sensor, the first sensor abnormality detector comprising a first scorer configured to assign a normal score to first sensor data corresponding to the learned normal behavior sequence and an abnormal score to first sensor data having a value outside of the value of the first sensor data corresponding to the learned normal behavior sequence; a second sensor; a second sensor abnormality detector connected to the second sensor, and configured to learn a second normal behavior sequence based on detected data sent from the second sensor, the second sensor abnormality detector comprising a second scorer configured to assign a normal score to second sensor data corresponding to the learned normal behavior sequence and an abnormal score to second sensor data having a value outside of the value of the second sensor data corresponding to the learned normal behavior sequence; an abnormality correlation server configured to receive abnormally scored first sensor data and abnormally scored second sensor data, the abnormality correlation server further configured to correlate the received abnormally scored first sensor data and abnormally scored second sensor data sensed at the same time by the first and second sensors and determine an abnormal event; and an abnormality report generator configured to generate an abnormality report based on the correlated received abnormally scored first sensor data and abnormally scored second sensor data. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. At least one non-transitory computer-readable medium readable by a computer for improving site operations by detecting abnormalities, the at least one non-transitory computer-readable medium comprising:
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a first sensor abnormality detecting code segment that, when executed, learns a first normal behavior sequence based on detected data sent from a first sensor, the first sensor abnormality detecting code segment comprising a first scoring code segment configured to assign a normal score to first sensor data corresponding to the learned first normal behavior sequence and an abnormal score to first sensor data having a value outside of the value of the first sensor data corresponding to the learned first normal behavior sequence; a second sensor abnormality detecting code segment that, when executed, learns a second normal behavior sequence based on detected data sent from a second sensor, the second sensor abnormality detecting code segment comprising a second scoring code segment configured to assign a normal score to second sensor data corresponding to the learned second normal behavior sequence and an abnormal score to second sensor data having a value outside of the value of the second sensor data corresponding to the learned second normal behavior sequence; an abnormality correlation code segment that, when executed, receives abnormally scored first sensor data and abnormally scored second sensor data, the abnormality correlation code segment further configured to correlate the received abnormally scored first sensor data and abnormally scored second sensor data sensed at the same time by the first and second sensors and determine an abnormal event; and an abnormality report generating code segment that, when executed, generates an abnormality report based on the correlated the received abnormally scored first sensor data and abnormally scored second sensor data. - View Dependent Claims (9, 10, 11, 12, 13)
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14. A method for improving site operations by detecting abnormalities, comprising:
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learning a first normal behavior sequence based on detected data sent from a first sensor; assigning a normal score to first sensor data corresponding to the learned normal behavior sequence and an abnormal score to first sensor data having a value outside of the value of the first sensor data corresponding to the learned first normal behavior sequence; learning a second normal behavior sequence based on detected data sent from a second sensor; assigning a normal score to second sensor data corresponding to the learned normal behavior sequence and an abnormal score to second sensor data having a value outside of the value of the second sensor data corresponding to the learned second normal behavior sequence; receiving abnormally scored first sensor data and abnormally scored second sensor data; correlating the received abnormally scored first sensor data and the received abnormally scored second sensor data sensed at a same time by the first and second sensors and determining an abnormal event; and generating an abnormality report based on the correlated received abnormally scored first sensor data and the abnormally scored second sensor data. - View Dependent Claims (15)
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16. A method of processing an order from a mobile device, the method comprising:
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detecting at least one nearest facility based on a location of the mobile device; communicating the detected at least one more nearest facility to a user; selecting a detected facility of the at least one nearest facility; selecting at least one item from items available for purchase at the selected detected facility; sending an order for the at least one item to a site for order processing; and receiving a confirmation of the ordered at least one item. - View Dependent Claims (17)
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18. A method of verifying an identity of a customer picking up an order at a site, the method comprising:
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receiving an order from a mobile device, the order including customer identification data; generating an order confirmation for the customer; and associating the customer identification data with the order confirmation. - View Dependent Claims (19, 20, 21)
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22. A method for preventing merchandise loss at a site, the method comprising:
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storing video recordings of a plurality of videos, each video of the plurality of videos including video images and metadata of the video image, the metadata including data corresponding to a face value of a unique face; comparing face values of the plurality of videos; obtaining a degree of correlation between a face value of one video of the plurality of videos and a face value of another video of the plurality of videos; and generating a report when a predetermined correlation threshold is reached between the one video and the another video. - View Dependent Claims (23)
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24. A method of managing a workforce at a site, the method comprising:
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monitoring the location of at least one employee at the site; monitoring the location of at least one customer at the site; determining a positional relationship between the at least one employee and the at least one customer; determining that the at least one customer is being assisted by the at least one employee when the determined positional relationship is within a predetermined value range; determining that the at least one customer is not being assisted by the at least one employee when the determined positional relationship is outside of the predetermined value range; and generating a report when the determined positional relationship is outside of the predetermined value range. - View Dependent Claims (25, 26)
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27. A method of determining an identity of a customer at a site, the method comprising:
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detecting, using at least one video imager, a unique customer based on a customer face at the site based on face data corresponding to a face value of a unique face; obtaining unique customer data at a point of sale terminal of the site, the unique customer data including at least customer name and previously stored face data; and comparing the detected face data with the previously stored face data and determining whether the identity of the unique customer corresponds to the unique customer data.
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Specification