Method and system to provide real time interior analytics using machine learning and computer vision
A system may be configured to generate real-time analytics using machine learning and computer vision. In some aspects, the system may receive a storage structure video frame and an interaction video frame, determine a storage structure inference based on the storage structure video frame, and determine an interaction inference based on the interaction video frame. Further, the system may determine that the storage structure inference and the interaction inference correspond to a common time period and common location, and generate analytics information based on the storage structure inference and the interaction inference.
1 . A method comprising:
receiving a storage structure video frame from a first video capture device positioned to capture display activity at a storage structure within a monitored area;
receiving an interaction video frame from a second video capture device positioned to capture interaction activity of customers;
determining a storage structure inference based on the storage structure video frame;
determining an interaction inference based on the interaction video frame;
associating the storage structure inference and the interaction inference based on determining that the storage structure inference and the interaction inference correspond to a common time period and common location; and
triggering an event based on associating the storage structure inference and the interaction inference.
2 . The method of claim 1 , further comprising:
identifying an employee associated with the storage structure, wherein triggering the event includes sending a notification to an employee device associated with the employee, the notification including an instruction.
3 . The method of claim 1 , further comprising:
identifying a third video capture device associated with the storage structure, wherein triggering the event includes sending a notification to the third video capture device, the notification instructing the third video capture device to reposition to capture a potential event at the storage structure.
4 . The method of claim 1 , wherein determining the storage structure inference, comprises determining an available capacity of a portion of the storage structure.
5 . The method of claim 1 , wherein determining the storage structure inference, comprises identifying a sweep event or a restocking requirement at the storage structure.
6 . The method of claim 1 , wherein determining the interaction inference, comprises determining at least one of a wait time or an engagement time of a customer in a zone of the monitored area.
7 . The method of claim 1 , wherein determining the interaction inference, comprises determining a sentiment of a customer in a zone of the monitored area.
8 . The method of claim 1 , wherein determining the interaction inference, comprises determining a demographic attribute of a customer in a zone of the monitored area.
9 . The method of claim 1 , wherein triggering the event comprises:
sending an employee assignment recommendation recommending a type of employee staff a location associated with the storage structure;
sending a loss prevention alert indicating possible unauthorized activity at the location associated with the storage structure;
sending a report including one or more key performance indicators associated with activity within the monitored area; or
sending a schedule for stocking the storage structure.
10 . A non-transitory computer-readable device having instructions thereon that, when executed by at least one computing device, causes the at least one computing device to perform operations comprising:
receiving a storage structure video frame from a first video capture device positioned to capture display activity at a storage structure within a monitored area;
receiving an interaction video frame from a second video capture device positioned to capture interaction activity of customers;
determining a storage structure inference based on the storage structure video frame;
determining an interaction inference based on the interaction video frame;
associating the storage structure inference and the interaction inference based on determining that the storage structure inference and the interaction inference correspond to a common time period and common location; and
triggering an event based on associating the storage structure inference and the interaction inference.
11 . The non-transitory computer-readable device of claim 10 , the operations further comprising:
identifying an employee associated with the storage structure, wherein triggering the event includes sending a notification to an employee device associated with the employee, the notification including an instruction.
12 . The non-transitory computer-readable device of claim 10 , the operations further comprising:
identifying a third video capture device associated with the storage structure, wherein triggering the event includes sending a notification to the third video capture device, the notification instructing the third video capture device to reposition to capture a potential event at the storage structure.
13 . The non-transitory computer-readable device of claim 10 , wherein determining the storage structure inference, comprises determining an available capacity of a portion of the storage structure.
14 . The non-transitory computer-readable device of claim 10 , wherein determining the interaction inference, comprises determining at least one of a wait time or an engagement time of a customer in a zone of the monitored area.
15 . The non-transitory computer-readable device of claim 10 , wherein triggering the event comprises:
sending an employee assignment recommendation recommending a type of employee staff a location associated with the storage structure;
sending a loss prevention alert indicating possible unauthorized activity at the location associated with the storage structure;
sending a report including one or more key performance indicators associated with activity within the monitored area; or
sending a schedule for stocking the storage structure.
16 . A system comprising:
a memory; and
at least one processor coupled to the memory and configured to:
receive a storage structure video frame from at least one video capture device, the storage structure video frame capturing display activity at a storage structure within a monitored area;
receive an interaction video frame from the at least one video capture device, the interaction video frame capturing interaction activity of customers;
determine a storage structure inference based on the storage structure video frame;
determine an interaction inference based on the interaction video frame;
associate the storage structure inference and the interaction inference based on determining that the storage structure inference and the interaction inference correspond to a related time period and a related location; and
trigger an event based on associating the storage structure inference and the interaction inference.
17 . The system of claim 16 , wherein to determine the storage structure inference, the at least one processor is configured to determine an available capacity of a portion of the storage structure.
18 . The system of claim 16 , wherein to determine the storage structure inference, the at least one processor is configured to identify a sweep event or a restocking requirement at the storage structure.
19 . The system of claim 16 , wherein to determine the interaction inference, the at least one processor is configured to determine at least one of a wait time or an engagement time of a customer in a zone of the monitored area.
20 . The system of claim 16 , wherein to trigger the event, the at least one processor is configured:
send an employee assignment recommendation recommending a type of employee staff a location associated with the storage structure;
send a loss prevention alert indicating possible unauthorized activity at the location associated with the storage structure;
send a report including one or more key performance indicators associated with activity within the monitored area; or
send a schedule for stocking the storage structure to determine at least one of a wait time or an engagement time of a customer in a zone of the monitored area.
21 . The system of claim 16 , wherein to determine the interaction inference based on the interaction video frame, the at least one processor is further configured:
determine that a customer is requesting assistance based at least in part on body language detected within the interaction video frame.
22 . The system of claim 16 , wherein to trigger the event, the at least one processor is further configured:
trigger presentation of an anticipated wait time on a visual display at the storage structure;
trigger an audio reproduction indicating the anticipated wait time at the storage structure; or
initialize an audio or text chatbot conversation with a customer at the storage structure.