Methods and systems for deterring suspicious behavior in retail establishments

Abstract

Systems and methods are disclosed for alerting suspicious activity in an establishment, including detecting, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring in the establishment, and displaying, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.

Description

039636.07714 METHODS AND SYSTEMS FOR DETERRING SUSPICIOUS BEHAVIOR IN RETAIL ESTABLISHMENTS CLAIM OF PRIORITY

[0001] The present Application for Patent claims priority to U.S. Provisional Patent Application No. 63 / 532,813, entitled “METHODS AND SYSTEMS FOR DETERRING SUSPICIOUS BEHAVIOR IN RETAIL ESTABLISHMENTS” filed August 15, 2023, which is assigned to the assignee hereof and hereby expressly incorporated by reference herein in its entirety for all purposes. BACKGROUND

[0002] The present disclosure relates to monitoring retail locations, and more particularly to detecting and deterring suspicious behavior in a retail establishment.

[0003] Retailers can have security systems deployed within retail establishments for detecting various activities within the retail establishments, such as movement of goods, movement or actions of consumers, etc. A security system may include one or more cameras or other sensors for recording consumer activity. The cameras can record video that can be viewed or reviewed by security personnel to detect theft or potentially suspicious behavior. In addition, retailers can employ public view monitors for various purposes, such as displaying advertisements, offers, product information, retail establishment information, etc., at various locations throughout the establishment.

[0004] In some cases, however, the security personnel may not be able to apprehend theft in a suitable time or before the suspect exits the retail establishment. In addition, cameras alone may not be a sufficient deterrent to theft in the retail establishment. SUMMARY

[0005] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the DETAILED DESCRIPTION. This summary is not intended to identify key features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

[0006] In an aspect, a method of alerting suspicious activity in an establishment is provided that includes detecting, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring039636.07714 in the establishment, and displaying, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.

[0007] In another aspect, an apparatus for alerting suspicious activity in an establishment is provided. The apparatus includes one or more memories, and one or more processors coupled to the one or more memories. The one or more processors are configured to execute instructions stored on the one or more memories to detect, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring in the establishment, and display, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.

[0008] In another aspect, one or more computer-readable media storing instructions, executable by one or more processors, for indicating occupancy of a point of interest in a room are provided. The instructions include instructions for detecting, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring in the establishment, and displaying, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.

[0009] In another aspect, a security system is provided that includes various hardware, software, or other components for alerting suspicious activity in an establishment using one or more methods described herein. In another aspects, a security system is provided that includes means for alerting suspicious activity in an establishment using one or more methods described herein. In another aspect, a computer-readable medium is provided herein that stores computer executable instructions for alerting suspicious activity in an establishment using one or more methods described herein.

[0010] Further aspects of the present disclosure are described in more details below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The disclosed aspects will hereinafter be described in conjunction with the appended drawings, provided to illustrate and not to limit the disclosed aspects, wherein like designations denote like elements, and in which:039636.07714

[0012] FIG. 1 is a block diagram of an example of a security system, according to implementations of the present disclosure;

[0013] FIG. 2 is a block diagram of an example of a control system implemented by the security system of FIG.1, according to implementations of the present disclosure;

[0014] FIG.3 is a flowchart of an example of a method implemented by the security system of FIG.1, according to implementations of the present disclosure; and

[0015] FIG. 4 is a block diagram of examples components of a computer device that may implement one or more of the features of the security system of FIG.1. DETAILED DESCRIPTION

[0016] The detailed description set forth below in connection with the appended drawings is intended as a description of various configurations and is not intended to represent the only configurations in which the concepts described herein may be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of various concepts. However, it will be apparent to those skilled in the art that these concepts may be practiced without these specific details. In some instances, well known components may be shown in block diagram form in order to avoid obscuring such concepts.

[0017] In many retail establishments, there is a need of deterring theft of articles. Retail establishments typically include security systems with cameras for capturing video of consumer behavior throughout the retail establishment. Retail establishments also can include public view monitors for displaying advertisements, offers, product information, retail establishment information, etc.

[0018] The present disclosure addresses one or more shortcomings of security systems for retail establishments by using machine learning (ML) for detecting potential suspicious activities by suspects within the retail establishment and / or using public view monitors or other display devices for deterring theft within the retail establishment. For example, video or other data captured by one or more cameras or other sensors in a retail establishment can be provided as input to a ML model to detect whether potentially suspicious activity is occurring at a location in a retail establishment. For example, the video can be compared to other videos identified as theft or other suspicious activities to determine whether a threshold probability of suspicious activity is identified in the videos. In an example, captured videos may be039636.07714 evaluated (e.g., input to the ML model) to detect if one or multiple items are removed from a shelf in an aisle or other display at the established, if a sequence of multiple items are removed, etc., which may be received as output from the ML model (e.g., including or based on a probability score or confidence score) and may be indicative of theft or other suspicious behavior. In another example, articles in the retail establishment can have other mechanisms for tracking movement thereof, removal from a shelf, etc., such as radio frequency identifier (RFID) tags. This information can be used (e.g., with the captured video or otherwise and / or as input to the ML model) to detect movement or removal of certain products from the shelf, for detecting whether possible theft or other suspicious activity is occurring.

[0019] In an example, based on the security system detecting possible theft or suspicious activity in this regard, a public view monitor can be used as a deterrent to the theft or suspicious activity. For example, based on detecting the suspicious activity, the security system can cause the public view monitor, or other display device, to display an indication of, or other deterrent for, the theft or suspicious activity. The public view monitor can typically be used to display advertisements, offers, product information, retail establishment information, etc. Multiple public view monitors can be deployed at various locations throughout the establishment. In an example, the security system can interrupt the video being displayed to instead (or in addition) display the indication of the theft or suspicious activity on one or more of the public view monitors. For example, the indication can include at least a portion of the video analyzed to detect, or otherwise determined as including (e.g., by the ML model), the potential theft or suspicious activity. In another example, the indication can include a visual or audio alert of the theft or suspicious activity. In yet another example, the indication can include adjusting a brightness level of the public view monitor. In an example, a public view monitor at a certain location can be selected relative to the location of the potential theft or suspicious activity (e.g., a public view monitor in closest proximity to the theft or suspicious activity), a location of the suspect of the potential theft or suspicious activity (and / or the public view monitor displaying the indication may change as the suspect moves throughout the retail establishment), etc. In accordance with the aspects described herein, displaying the indication on the public view monitor for the potential suspect, and / or other people in the vicinity of the potential theft or other suspicious activity, to see can have a deterrent effect.039636.07714

[0020] Turning now to the figures, example aspects are depicted with reference to one or more modules or components described herein, where modules or components in dashed lines may be optional.

[0021] Referring to FIG.1, an example of a security system 100 deployed at an establishment 102 (e.g., a retail establishment, such as store) is depicted. The security system 100 may include, for example, one or more cameras 104 installed within (or outside of) the establishment 102. For example, the one or more cameras 104 can be fixed cameras attached to a structure within the establishment 102, such as a ceiling or wall, attached to another structure in the parking lot, etc., and / or can be attached to a drone or other unmanned aerial system (UAS), robot, or other device that can move throughout the establishment 102. In yet another example, the one or more cameras 104 can be part of a mobile device (e.g., a cellular phone) carried by an employee of the establishment, or worn by the employee (e.g., an outward facing camera on a body of the employee). In any case, the one or more cameras 104 can be communicatively coupled with the control system 120 via a wired or wireless communication medium to provide images or videos 106 to the control system 120.

[0022] The security system 100 may also include an item tracker 108 for tracking items throughout the establishment 102. For example, the items can include tags (e.g., RFID tags) that can be read and / or tracked by various item trackers 108 installed throughout the establishment 102. Item trackers 108 can send item information 110 to the control system 120 to facilitate tracking location or movement of items in the establishment 102. For example, item trackers 108 can track removal of an item from a shelf, table, or other construct in the establishment.

[0023] The security system 100 may also include, or be able to operate, one or more public view monitors (PVMs), or other display devices, in the establishment 102. The PVMs can be operated to display advertisements, offers, product information, retail establishment information, etc., at various locations throughout the establishment. For example, the PVMs can be deployed near different aisles 114 within the establishment 102 (e.g., at aisle end caps), locations within the aisles 114, etc. An individual 116 can travel throughout the establishment 102, and activity of the individual can be tracked by the security system 100 to detect potential theft or other suspicious behavior. For example, cameras 104 can record video within the establishment, item trackers 108 can track item movement throughout the establishment 102, etc. The images / videos 106 from the one or more cameras 104039636.07714 and / or item information 110 from the item trackers 108 can be provided to the control system 120.

[0024] The control system 120 can utilize an artificial intelligence (AI) module 122, via a network 124 or a locally executing AI module, to assess whether recorded video 106 and / or item information 110 is indicative of potential theft, fraud, or other suspicious activities. In an example, AI module 122 can use a ML model, such as a neural network of images, videos, or other inputs, to compare captured images, videos, or other inputs to detect whether activity in the captured images, videos, or other inputs, is indicative of potential theft or other suspicious activity. For example, the ML model can be trained with images, videos, etc. indicated as associated with theft or other activities for which detection is desired, and the ML model can accordingly receive images, videos, etc. as input, and provide an output as to whether the input images, videos, etc. include theft or other activities on which the ML model is trained, provide a confidence score as to whether the input images, videos, etc. include theft or other activities, or other output from which a determination can be made as to whether the input images include (or likely include) theft or other activities of interest.

[0025] In another example, AI module 122 can use a ML model of, and / or trained on, item tracking information to detect whether item tracking information is indicative of potential theft or other suspicious. For example, movement of certain items, movement of multiple items of the same brand or type, movement of items from their original aisle to another part of the store, etc., may be indicative of potential theft. This movement of items and analysis via the AI module 122 can be based on the image / video 106 input and / or the item information 110 received from one or more item trackers 108.

[0026] In one example, AI module 122 can use a generative adversarial network (GAN), which can include a ML model in which two neural networks (a generator and a discriminator) that compete with each other by using deep learning methods to become more accurate in their predictions. In other examples, AI module 122 can bypass the GAN (e.g., for a different neural network used), or can bypass one of the generator or discriminator (e.g., assuming they are well trained) in detecting potential theft or other suspicious activity based on provided inputs.

[0027] In accordance with aspects described herein, when the control system 120 detects potential theft or suspicious activity, the control system 120 can control one or more of the PVMs 112 to display or otherwise alert an indication of the potential theft or039636.07714 suspicious activity. For example, the control system 120 can interrupt a video displaying on at least one of the PVMs 112 to display the indication of the potential theft or suspicious activity. One of multiple PVMs 112 can be selected based on a location of the detected potential theft or suspicious activity. In an example, the indication can include the video captured by the cameras 104 that the control system 120 detected to be potential theft or suspicious activity, or a current video being captured of the individual 116 by one or more cameras 104. In another example, the indication displayed on at least one of the PVMs 112 can include a text indication overlaid on video of the PVM(s) 112, such as “Recording in Progress”, “Theft Detected”, or other deterring language. In yet another example, control system 120 can cause one or more PVMs 112 to increase a brightness level so the indication is more noticeable. Displaying the indication of potential theft or other suspicious activity on the PVMs 112 may catch the attention of the individual 116 (and / or other individuals), which may deter the individual 116 from continuing the potential theft or other suspicious activity.

[0028] Referring to FIG. 2, details of the control system 120 for detecting and deterring potential theft or other suspicious activity are illustrated. In an example, the control system 120 may optionally include a video receiving module 202 for receiving video or images from one or more cameras to analyze for detecting potential theft or other suspicious activity, an item tracking module 204 for tracking item information or movement throughout an establishment, an event generating module 206 for generating an event based on identifying potential theft or other suspicious activity based on received videos, images, or item information, an event locating module 208 for determining a location of the potential theft or other suspicious activity, and / or a PVM operating module 210 for operating one or more PVMs to display or otherwise render a video or audio indication of the potential theft or other suspicious activity.

[0029] For example, the various modules 202, 204, 206, 208, 210 of the control system 120 can be provided or implemented by one or more processors, one or more memories, instructions stored on the one or more memories and executable by the one or more processors, etc., of the control system 120, as described further herein. In addition, control system 120 can include a communications module for communicating with one or more other devices, such as the one or more cameras 104 to receive the images or video, the item trackers 108 to receive item information, the AI module 122 to provide the video or item information input to the AI module 122 and / or receive an039636.07714 output therefrom, etc. In some examples, the AI module 122 may be part of (e.g., provided by) the control system 120, such that the control system 120 may store the ML model and / or interact with the ML model to provide image, video, etc. input and receive an output indicating whether potential theft or other suspicious activities are detected.

[0030] Referring to FIG. 3, an example of a method 300 of displaying an indication of potential theft or other suspicious activity on a PVM in an establishment is depicted. The operations of the method 300 may be performed by one or more modules or components of the security system 100, control system 120, etc., as described herein.

[0031] At 302, the method 300 may include detecting potential suspicious activity occurring in an establishment. For example, the control system 120 can detect potential suspicious activity occurring in the establishment. In an example, detecting the potential suspicious activity at 302 can optionally include, at 304, detecting, based on using ML to process video received from one or more cameras in the establishment, the potential suspicious activity. For example, video receiving module 202 of the control system 120 can receive the video from the one or more cameras 104 and can provide the video as input to an ML model (e.g., via AI module 122) to receive an indication, such as a probability score or confidence score, of whether activity in the video is indicative of potential theft or other suspicious activity. For example, the AI module 122 can compare the video to other videos stored in the ML model to generate the probability score, confidence score, or other output of whether (or an extent to which) the video includes activity related to potential theft or suspicious activity.

[0032] In an example, detecting the potential suspicious activity at 302 can optionally include, at 306, detecting, based on item tracking information, the potential suspicious activity. For example, item tracking module 204 of the control system 120 can receive the item information from the one or more item trackers 108 and can provide the item information as input to an ML model (e.g., via AI module 122) to receive the indication, such as a probability score or confidence score, of whether item information (e.g., in conjunction with the video or otherwise) is indicative of potential theft or other suspicious activity. For example, the AI module 122 can compare the item information to other item information stored in the ML model to generate the probability score, confidence score, or other output of whether (or an extent to which) the item information (e.g., the pattern of movement of the item through the establishment, time or velocity associated with movement of the item through the039636.07714 establishment, etc.) indicates activity related to potential theft or suspicious activity. In one example, AI module 122 can consider the video and the item tracking information together (and / or other information) to determine whether potential theft or other suspicious activity is detected.

[0033] The AI module 122 can provide an output (e.g., the probability score or confidence score) to the control system 120. In an example, event generating module 206 can compare the output to a threshold (e.g., compare the probability score or confidence score to a threshold) to detect the potential theft or other suspicious activity. In another example, AI module 122 can provide the indicator of potential theft or other suspicious activity (e.g., as a binary indicator, an indication of a type of activity, etc.). In any case, event generating module 206 can detect potential suspicious activity and / or generate a corresponding event based on the output from the AI module 122.

[0034] At 308, the method 300 can optionally include determining a location associated with the potential suspicious activity. For example, event locating module 208 can determine the location (within or outside of the establishment 102) associated with the potential suspicious activity. In an example, event locating module 208 can determine the location based on a location, position (e.g., pan, tilt, direction), etc., of a camera capturing the associated video, based on a location associated with item information, etc. For example, the location can include a global positioning system (GPS) location, a coordinate location on a map of the establishment, a zone within which the video is captured, etc.

[0035] At 310, the method 300 can include displaying, on a PVM near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity. For example, PVM operating module 210 can operate a PVM 112 near the potential suspicious activity to display the indication of the potential suspicious activity. In an example, PVM operating module 210 can determine which of multiple PVMs 112 to control to display the indication by selecting one or more PVMs 112 that are within a proximity to (or at a closest proximity to) the detected potential suspicious activity. In an example, PVM operating module 210 can interrupt a video being displayed on the PVM 112 to instead display the video based on which the potential suspicious activity is detected (e.g., as a delayed video, a video loop for a period of time, a video zoomed on the portion detected to include the potential suspicious activity, etc.).039636.07714

[0036] In another example, PVM operating module 210 can interrupt the video to display, or overlay on the current video being displayed, a visual indicator of the potential suspicious activity, such as a text notification (e.g., “Recording in Progress”, “Theft Detected”, etc.), a logo, a video or hologram projection, etc. In one example, PVM operating module 210 can select one of multiple PVMs 112 on which to display the indication based on the determined location of the potential suspicious activity (e.g., to be a PVM 112 in a zone or otherwise nearest to the determined location). In an example, PVM operating module 210 can also operate the one or more PVMs 112 to sound an audio alert or play some audio clip based on detecting the potential suspicious activity to alert the suspect or other nearby individuals of the potential suspicious activity.

[0037] In an example, displaying the indication at 310 can optionally include, at 312, increasing brightness of the PVM based on detecting the potential suspicious activity. For example, PVM operating module 210 can increase the brightness of the PVM based on detecting the potential suspicious activity.

[0038] At 314, the method 300 can optionally include storing the video in a case file for an incident corresponding to the potential suspicious activity. For example, event generating module 206 can store an indication of the event and the corresponding video, item information, etc., in the case file (e.g., in memory). The case file can be used for further study to determine if theft occurred, suspect identification, etc. In one example, the case file can be merged with other case files having the same identified suspect. For example, the case file can be retrieved for providing to law enforcement personnel or related systems for use as evidence, etc. In addition, for example, the generated event can influence different behaviors of the security system 100. For example, the security system 100 may be equipped to track items and / or individuals, and notify or alarm at an exit of the establishment when the items and / or individuals reach the exit (e.g., where the item is suspected to be part of the suspicious activity, based on the generate event, and / or where payment is not received for the item being tracked). For example, the generated event may correspond to a more likely incident of theft, and the security system 100 may sound an alarm with higher probability, take more forceful action to prevent the individual from exiting the establishment with the item, etc.

[0039] At 316, the method 300 can optionally include controlling one or more sensors to record a journey of a suspect of the potential suspicious activity throughout the039636.07714 establishment. For example, event generating module 206 can cause, based on detecting the potential suspicious activity, the one or more sensors (e.g., cameras 104, microphones, drones, robots, etc.) to track movement of the suspect throughout the establishment. The movement and / or activity of the suspect during movement throughout the establishment can further be indicative of the suspicious activity, and can be used in generating the event and / or in generating other events in the security system 100. For example, if the suspect takes items in a way that triggers potential suspicious activity, and moves to a certain location in the establishment (e.g., a restroom or well hidden location), event generating module 206 can track and detect such movement and can accordingly determine to trigger the event to cause the PVMs to display the indication of potential suspicious activity, trigger additional PVMs to display the indication as the suspect moves throughout the establishment, and / or can trigger other events in the security system 100, which may increase the probability or confidence score of the potential suspicious activity.

[0040] Referring to FIG. 4, a computing device 400 may implement all or a portion of the functionality described in FIGS.1-3. For example, the computing device 400 may be or may include at least a portion of the control system 120, or any other module or component described herein with reference to FIGS.1-3. The computing device 400 may include one or more processors 402 which may be configured to execute or implement software, hardware, and / or firmware modules that perform some or all of the functionality described herein with reference to FIGS. 1-3. For example, the processor(s) 402 may be configured to execute or implement software, hardware, and / or firmware modules that perform some or all of the functionality described herein with reference to the control system 120, or any other module or component described herein with reference to FIGS.1-3.

[0041] The processor(s) 402 may be a micro-controller, an application-specific integrated circuit (ASIC), or a field-programmable gate array (FPGA), and / or may include a single or multiple set of processors or multi-core processors. Moreover, the processor(s) 402 may be implemented as an integrated processing system and / or a distributed processing system. The computing device 400 may further include memory / memories 404, such as for storing local versions of applications being executed by the processor(s) 402, related instructions, parameters, etc. The memory / memories 404 may include a type of memory usable by a computer, such as random access memory (RAM), read only memory (ROM), tapes, magnetic discs,039636.07714 optical discs, volatile memory, non-volatile memory, and any combination thereof. Additionally, the processor(s) 402 and the memory / memories 404 may include and execute an operating system executing on the processor(s) 402, one or more applications, display drivers, etc., and / or other modules or components of the computing device 400.

[0042] Further, the computing device 400 may include a communications module 406 that provides for establishing and maintaining communications with one or more other devices, parties, entities, etc. utilizing hardware, software, and services. The communications module 406 may carry communications between modules on the computing device 400, as well as between the computing device 400 and external devices, such as devices located across a communications network and / or devices serially or locally connected to the computing device 400. In an aspect, for example, the communications module 406 may include one or more buses, and may further include transmit chain modules and receive chain modules associated with a wireless or wired transmitter and receiver, respectively, operable for interfacing with external devices.

[0043] Additionally, the computing device 400 may include a data store 408, which can be any suitable combination of hardware and / or software, that provides for mass storage of information, databases, and programs. For example, the data store 408 may be or may include a data repository for applications and / or related parameters not currently being executed by processor(s) 402. In addition, the data store 408 may be a data repository for an operating system, application, display driver, etc., executing on the processor 402, and / or one or more other modules of the computing device 400.

[0044] The computing device 400 may also include a user interface module 410 operable to receive inputs from a user of the computing device 400 and further operable to generate outputs for presentation to the user (e.g., via a display interface to a display device). The user interface module 410 may include one or more input devices, including but not limited to a keyboard, a number pad, a mouse, a touch-sensitive display, a navigation key, a function key, a microphone, a voice recognition module, or any other mechanism capable of receiving an input from a user, or any combination thereof. Further, the user interface module 410 may include one or more output devices, including but not limited to a display interface, a speaker, a haptic feedback mechanism, a printer, any other mechanism capable of presenting an output to a user, or any combination thereof.039636.07714

[0045] One or more aspects of the present disclosure may be implemented according to one or more of the following clauses.

[0046] Clause 1. A method of alerting suspicious activity in an establishment, comprising: detecting, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring in the establishment; and displaying, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.

[0047] Clause 2. The method of clause 1, wherein displaying the indication of the potential suspicious activity includes interrupting a video playing on the public view monitor to play the indication of the potential suspicious activity.

[0048] Clause 3. The method of any preceding clause, wherein the indication of the potential suspicious activity includes at least a portion of the video received from the one or more cameras based on which the potential suspicious activity is detected.

[0049] Clause 4. The method of any preceding clause, wherein the indication of the potential suspicious activity includes a visual or audio alert indicating the potential suspicious activity.

[0050] Clause 5. The method of any preceding clause, wherein the indication of the potential suspicious activity includes information regarding the location of the potential suspicious activity.

[0051] Clause 6. The method of any preceding clause, further comprising increasing a brightness of the public view monitor for displaying the indication of the potential suspicious activity.

[0052] Clause 7. The method of any preceding clause, further comprising storing the video in a case file for an incident corresponding to the potential suspicious activity.

[0053] Clause 8. The method of any preceding clause, further comprising controlling one or more sensors to record a journey of a suspect of the potential suspicious activity throughout the establishment.

[0054] Clause 9. The method of any preceding clause, further comprising selecting the public view monitor from multiple public view monitors configured at the establishment based on a proximity of the potential suspicious activity to the public view monitor.

[0055] Clause 10. An apparatus for alerting suspicious activity in an establishment, comprising: one or more memories; and one or more processors coupled to the one or more memories and configured to execute instructions stored on the one or more039636.07714 memories to: detect, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring in the establishment; and display, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.

[0056] Clause 11. The apparatus of any preceding clause, wherein the one or more processors are configured to execute instructions stored on the one or more memories to display the indication of the potential suspicious activity including interrupting a video playing on the public view monitor to play the indication of the potential suspicious activity.

[0057] Clause 12. The apparatus of any preceding clause, wherein the indication of the potential suspicious activity includes at least a portion of the video received from the one or more cameras based on which the potential suspicious activity is detected.

[0058] Clause 13. The apparatus of any preceding clause, wherein the indication of the potential suspicious activity includes a visual or audio alert indicating the potential suspicious activity.

[0059] Clause 14. The apparatus of any preceding clause, wherein the indication of the potential suspicious activity includes information regarding the location of the potential suspicious activity.

[0060] Clause 15. The apparatus of any preceding clause, wherein the one or more processors are configured to execute instructions stored on the one or more memories to increase a brightness of the public view monitor for displaying the indication of the potential suspicious activity.

[0061] Clause 16. The apparatus of any preceding clause, wherein the one or more processors are configured to execute instructions stored on the one or more memories to store the video in a case file for an incident corresponding to the potential suspicious activity.

[0062] Clause 17. The apparatus of any preceding clause, wherein the one or more processors are configured to execute instructions stored on the one or more memories to control one or more sensors to record a journey of a suspect of the potential suspicious activity throughout the establishment.

[0063] Clause 18. The apparatus of any preceding clause, wherein the one or more processors are configured to execute instructions stored on the one or more memories to select the public view monitor from multiple public view monitors configured at the039636.07714 establishment based on a proximity of the potential suspicious activity to the public view monitor.

[0064] Clause 19. One or more computer-readable media storing instructions, executable by one or more processors, for alerting suspicious activity in an establishment, the instructions comprising instructions for performing the method of any one of clauses 1 to 9.

[0065] The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein, but is to be accorded the full scope consistent with the language claims, wherein reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.” The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects. Unless specifically stated otherwise, the term “some” refers to one or more. Combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” include any combination of A, B, and / or C, and may include multiples of A, multiples of B, or multiples of C. Specifically, combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” may be A only, B only, C only, A and B, A and C, B and C, or A and B and C, where any such combinations may contain one or more member or members of A, B, or C. All structural and functional equivalents to the elements of the various aspects described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. The words “module,” “mechanism,” “element,” “device,” and the like may not be a substitute for the word “means.” As such, no claim element is to be construed as a means plus function unless the element is expressly recited using the phrase “means for.”039636.07714

[0066] As used in this application, the terms “component,” “module,” “system” and the like are intended to include a computer-related entity, such as but not limited to hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and / or a computer. By way of illustration, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and / or thread of execution and a component can be localized on one computer and / or distributed between two or more computers. In addition, these components can execute from various computer readable media having various data structures stored thereon. The components can communicate by way of local and / or remote processes such as in accordance with a signal having one or more data packets, such as data from one component interacting with another component in a local system, distributed system, and / or across a network such as the Internet with other systems by way of the signal.

[0067] As used herein, a processor, at least one processor, and / or one or more processors, individually or in combination, configured to perform or operable for performing a plurality of actions is meant to include at least two different processors able to perform different, overlapping or non-overlapping subsets of the plurality actions, or a single processor able to perform all of the plurality of actions. In one non-limiting example of multiple processors being able to perform different ones of the plurality of actions in combination, a description of a processor, at least one processor, and / or one or more processors configured or operable to perform actions X, Y, and Z may include at least a first processor configured or operable to perform a first subset of X, Y, and Z (e.g., to perform X) and at least a second processor configured or operable to perform a second subset of X, Y, and Z (e.g., to perform Y and Z). Alternatively, a first processor, a second processor, and a third processor may be respectively configured or operable to perform a respective one of actions X, Y, and Z. It should be understood that any combination of one or more processors each may be configured or operable to perform any one or any combination of a plurality of actions.

[0068] As used herein, a memory, at least one memory, and / or one or more memories, individually or in combination, configured to store or having stored thereon instructions executable by one or more processors for performing a plurality of actions is meant to include at least two different memories able to store different, overlapping039636.07714 or non-overlapping subsets of the instructions for performing different, overlapping or non-overlapping subsets of the plurality actions, or a single memory able to store the instructions for performing all of the plurality of actions. In one non-limiting example of one or more memories, individually or in combination, being able to store different subsets of the instructions for performing different ones of the plurality of actions, a description of a memory, at least one memory, and / or one or more memories configured or operable to store or having stored thereon instructions for performing actions X, Y, and Z may include at least a first memory configured or operable to store or having stored thereon a first subset of instructions for performing a first subset of X, Y, and Z (e.g., instructions to perform X) and at least a second memory configured or operable to store or having stored thereon a second subset of instructions for performing a second subset of X, Y, and Z (e.g., instructions to perform Y and Z). Alternatively, a first memory, and second memory, and a third memory may be respectively configured to store or have stored thereon a respective one of a first subset of instructions for performing X, a second subset of instruction for performing Y, and a third subset of instructions for performing Z. It should be understood that any combination of one or more memories each may be configured or operable to store or have stored thereon any one or any combination of instructions executable by one or more processors to perform any one or any combination of a plurality of actions. Moreover, one or more processors may each be coupled to at least one of the one or more memories and configured or operable to execute the instructions to perform the plurality of actions. For instance, in the above non-limiting example of the different subset of instructions for performing actions X, Y, and Z, a first processor may be coupled to a first memory storing instructions for performing action X, and at least a second processor may be coupled to at least a second memory storing instructions for performing actions Y and Z, and the first processor and the second processor may, in combination, execute the respective subset of instructions to accomplish performing actions X, Y, and Z. Alternatively, three processors may access one of three different memories each storing one of instructions for performing X, Y, or Z, and the three processor may in combination execute the respective subset of instruction to accomplish performing actions X, Y, and Z. Alternatively, a single processor may execute the instructions stored on a single memory, or distributed across multiple memories, to accomplish performing actions X, Y, and Z.

Claims

039636.07714 CLAIMS WHAT IS CLAIMED IS:

1. A method of alerting suspicious activity in an establishment, comprising: detecting, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring in the establishment; and displaying, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.

2. The method of claim 1, wherein displaying the indication of the potential suspicious activity includes interrupting a video playing on the public view monitor to play the indication of the potential suspicious activity.

3. The method of any preceding claim, wherein the indication of the potential suspicious activity includes at least a portion of the video received from the one or more cameras based on which the potential suspicious activity is detected.

4. The method of any preceding claim, wherein the indication of the potential suspicious activity includes a visual or audio alert indicating the potential suspicious activity.

5. The method of any preceding claim, wherein the indication of the potential suspicious activity includes information regarding the location of the potential suspicious activity.

6. The method of any preceding claim, further comprising increasing a brightness of the public view monitor for displaying the indication of the potential suspicious activity.

7. The method of any preceding claim, further comprising storing the video in a case file for an incident corresponding to the potential suspicious activity.039636.07714 8. The method of any preceding claim, further comprising controlling one or more sensors to record a journey of a suspect of the potential suspicious activity throughout the establishment.

9. The method of any preceding claim, further comprising selecting the public view monitor from multiple public view monitors configured at the establishment based on a proximity of the potential suspicious activity to the public view monitor.

10. An apparatus for alerting suspicious activity in an establishment, comprising: one or more memories; and one or more processors coupled to the one or more memories and configured to execute instructions stored on the one or more memories to: detect, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring in the establishment; and display, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.

11. The apparatus of claim 10, wherein the one or more processors are configured to execute instructions stored on the one or more memories to display the indication of the potential suspicious activity including interrupting a video playing on the public view monitor to play the indication of the potential suspicious activity.

12. The apparatus of any preceding claim, wherein the indication of the potential suspicious activity includes at least a portion of the video received from the one or more cameras based on which the potential suspicious activity is detected.

13. The apparatus of any preceding claim, wherein the indication of the potential suspicious activity includes a visual or audio alert indicating the potential suspicious activity.039636.07714 14. The apparatus of any preceding claim, wherein the indication of the potential suspicious activity includes information regarding the location of the potential suspicious activity.

15. The apparatus of any preceding claim, wherein the one or more processors are configured to execute instructions stored on the one or more memories to increase a brightness of the public view monitor for displaying the indication of the potential suspicious activity.

16. The apparatus of any preceding claim, wherein the one or more processors are configured to execute instructions stored on the one or more memories to store the video in a case file for an incident corresponding to the potential suspicious activity.

17. The apparatus of any preceding claim, wherein the one or more processors are configured to execute instructions stored on the one or more memories to control one or more sensors to record a journey of a suspect of the potential suspicious activity throughout the establishment.

18. The apparatus of any preceding claim, wherein the one or more processors are configured to execute instructions stored on the one or more memories to select the public view monitor from multiple public view monitors configured at the establishment based on a proximity of the potential suspicious activity to the public view monitor.

19. One or more computer-readable media storing instructions, executable by one or more processors, for alerting suspicious activity in an establishment, the instructions comprising instructions for: detecting, based on using machine learning to process video received from one or more cameras in the establishment, potential suspicious activity occurring in the establishment; and displaying, on a public view monitor near a location of the potential suspicious activity and based on detecting the potential suspicious activity, an indication of the potential suspicious activity.039636.07714 20. The one or more computer-readable media of claim 19, wherein displaying the indication of the potential suspicious activity includes interrupting a video playing on the public view monitor to play the indication of the potential suspicious activity.

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