Operation of a self-check out surface area of a retail store

A system for operating a plurality of self-checkout (SCO) terminals of a SCO environment, the system comprising:

• one or more video sensors installed in a pre-defined location from each of the plurality of SCO terminals configured to capture a plurality of video frames;
• an SCO unit communicably coupled to each of the plurality of SCO terminals and configured to obtain status data of each of the plurality of SCO terminals,
• wherein the status data identifies each of the plurality of SCO terminals as one of a locked or an active;
• a control unit coupled to the one or more video sensors and the SCO unit, wherein the control unit comprises a processing unit connected to a memory, wherein the memory comprises a set of instructions executed by the processing unit configured to:
• determine one or more frames of interest from the plurality of video frames using a machine learning model, wherein the determination of the one or more frames of interest comprises:
• detect a primary subject of interest using a human classification module, wherein the human classification module is trained based on training data determined based on the plurality of video frames captured using the one or more video sensors;
• classify the detected primary subject of interest based on an age group of the primary subject of interest;
• and
• detect one or more secondary subject of interest using an object detection module, post appearance of the primary subject of interest within a pre-defined distance from each of the plurality of SCO terminals;
• determine location and time of appearance of the primary subject of interest and the secondary subject of interest;
• generate a motion trigger based on detection of change in location data of the primary subject of interest and the secondary subject of interest within the pre-defined distance of one of the plurality of SCO terminals, using a motion detection unit;
• based on the generated motion trigger:
• receive transaction data from the SCO unit, wherein the transaction data comprises transactions received by scanning one or more objects at the respective one of the plurality of SCO terminals;
• compare the transaction data from the SCO unit with the detected secondary subject of interest using a non-scan event detector;
• generate a non-scan event alert based on a mismatch in the comparison of the transaction data and the detected one or more secondary subject of interest;
• the processing unit further configured to initiate a terminal lockdown procedure by identifying a predefined threshold of concurrently locked terminals and, in response to the processing unit determining that a number of concurrently locked terminal is less than said threshold, the processing unit generating an SCO LOCK signal, and sending said SCO LOCK signal to the specific SCO unit of the SCO terminal that is to be locked, and thereby interrupting continuous operation of the SCO terminal coupled to the SCO unit.

A non-transitory computer-readable medium having stored thereon a set of instructions which when executed by a computer causes the computer to perform operations for operating a plurality of self-checkout (SCO) terminals of an SCO environment, comprising:

• receiving a plurality of video frames captured using one or more video sensors installed in a pre-defined location from each of the plurality of SCO terminals;
• obtaining status data of each of the plurality of SCO terminals using an SCO unit communicably coupled to each of the plurality of SCO terminals,
• wherein the status data identifies each of the plurality of SCO terminals as one of a locked or an active,
• wherein a control unit is communicably coupled to the one or more video sensors and the SCO unit, wherein the control unit comprises a processing unit connected to a memory, wherein the memory comprises a set of instructions executed by the processing unit for:
• determining one or more frames of interest from the plurality of video frames using a machine learning model, wherein the determination of the one or more frames of interest comprises:
• detecting a primary subject of interest using a human classification module, wherein the human classification module is trained based on training data determined based on the plurality of video frames captured using the one or more video sensors;
• classifying the detected primary subject of interest based on an age group of the primary subject of interest;
• detecting one or more secondary subject of interest using an object detection module, post the detection of the primary subject of interest and within a pre-defined distance from each of the plurality of SCO terminals;
• determining location and time of detection of the primary subject of interest and the secondary subject of interest;
• generating a motion trigger based on detection of change in the location of the primary subject of interest and the secondary subject of interest within the pre-defined distance of one of the plurality of SCO terminals using a motion detection unit;
• and
• based on the generated motion trigger:
• receiving transaction data from the SCO unit, wherein the transaction data comprises transactions received by scanning one or more objects at the respective one of the plurality of SCO terminals;
• comparing the transaction data from the SCO unit with the detected one or more secondary subject of interest;
• generating a non-scan event alert based on a mismatch in the comparison of the transaction data and the detected one or more secondary subject of interest;
• and
• the processing unit further configured to initiate a terminal lockdown procedure by identifying a predefined threshold of concurrently locked terminals and, in response to the processing unit determining that a number of concurrently locked terminal is less than said threshold, the processing unit generating an SCO LOCK signal, and sending said SCO LOCK signal to the specific SCO unit of the SCO terminal that is to be locked, and thereby interrupting continuous operation of the SCO terminal coupled to the SCO unit.