Apparatus, computer implemented method, and computer program product for improving selection and provision of operational support data objects

Abstract

An embodiment of the present disclosure provides predicted operational support data object selection and provisioning functionality. The predicted operational support data objects may be selected and provided to address a particular fault classification affecting a network-connected device on a dynamic home communication network. Some embodiments include identifying, in real time, a device identification dataset associated with a set of network-connected devices capable of communicating with the dynamic home communication network, retrieving a device activity dataset associated with the set of network-connected devices, applying a fault classification data model to the device activity dataset to select predicted operational support data objects from a device operational support management repository, and outputting the predicted operational support data objects to a client device communicating with the dynamic home communication network. The fault classification data model is trained based on training data, external aggregated activity data, and faulty device history data.

Description

[Technical field]

[0001] Embodiments of the present disclosure relate generally to automatically providing operational support data objects to assist in resolving faults in one or more devices, and specifically to applying at least device activity data, and optionally external aggregated device activity data and faulty device history data, to a fault classification data model to select at least predicted operational support data objects for output via a client device. [Background technology]

[0002] For any of a number of reasons, devices, systems, networks, and / or other configurations of computing devices may experience any number of technical problems that affect their operation. Such problems may include slow performance, crashes, lack of connectivity, software bugs, and the like. Users of such devices or associated with such devices may seek resources, methods, processes, and other means to diagnose and resolve such technical problems. Applicant has discovered problems with current systems for identifying and resolving technical problems that arise among devices, systems, networks, and other configurations of computing devices. Through exerted effort, ingenuity, and innovation, Applicant has solved many of these identified problems by developing the solutions embodied in the present disclosure, which are described in detail below. Summary of the Invention

[0003] In general, the embodiments of the disclosure provided herein provide improved operational support data objects that address specific faults. Other implementations for providing improved operational support data objects that address specific faults will be, or become, apparent to one of ordinary skill in the art upon review of the following figures and detailed description. It is intended that all such additional implementations be included herein within the scope of this disclosure and protected by the following claims.

[0004] According to a first aspect of the present disclosure, a computer-implemented method is provided for selecting predicted operational support data objects from a device operational support management repository using diverse device activity data from a dynamic home communication network. In some exemplary embodiments of the computer-implemented method, the computer-implemented method is executed by a specially configured computing device embodied in hardware, software, firmware, and / or any combination thereof. The computer-implemented method of one exemplary embodiment includes identifying, in real time, a device identification dataset associated with a set of network-connected devices capable of communicating with the dynamic home communication network. The exemplary computer-implemented method further includes retrieving a device activity dataset associated with the set of network-connected devices. The exemplary computer-implemented method further includes applying a fault classification data model to the device activity dataset to select predicted operational support data objects from the device operational support management repository, the fault classification data model being trained based on training data from the dynamic home communication network, external aggregated device activity data from one or more external dynamic home communication networks, and faulty device history data from the device operational support management repository. The exemplary computer-implemented method further includes outputting the predicted operational support data objects to a client device in communication with the dynamic home communication network.

[0005] Additionally or alternatively, in some embodiments of the exemplary computer-implemented method, the predicted operational support data object includes a data link to a solution page associated with correcting the fault classification data associated with the set of network-connected devices.

[0006] Additionally or alternatively, in some embodiments of the exemplary computer-implemented method, the exemplary computer-implemented method further includes determining fault classification data associated with the set of network-connected devices by at least identifying a first device identification data from the device identification set, where the first device identification data is associated with a first device of the set of network-connected devices, and determining fault classification data corresponding to the first identification data and the device activity data set.

[0007] Additionally or alternatively, in some embodiments of the exemplary computer-implemented method, the exemplary computer-implemented method further includes determining fault classification data associated with the set of network-connected devices by at least identifying a plurality of device identification data from a device identification dataset, where the plurality of device identification data are associated with a plurality of network-connected devices of the set of network-connected devices, and determining fault classification data corresponding to the plurality of device identification data and the device activity dataset.

[0008] Additionally or alternatively, in some embodiments of the exemplary computer-implemented method, the exemplary computer-implemented method further includes determining fault classification data associated with the set of network-connected devices by determining at least that the device activity data set indicates a first fault classification represented by the fault classification data.

[0009] Additionally or alternatively, in some embodiments of the exemplary computer-implemented method, the device operations management repository includes at least predicted operations support data objects associated with the set of device types and at least one fault classification identifier in fault classification data associated with the set of network-connected devices, and the device identification data set indicates that the set of network-connected devices includes one or more network-connected devices of the set of device types.

[0010] Additionally or alternatively, in some embodiments of the exemplary computer-implemented method, the exemplary computer-implemented method further includes identifying a first fault classification associated with the set of device types; storing first fault classification data representative of the first fault classification associated with the set of device types; and determining fault classification data associated with the network connected device set by identifying a device type of each of the one or more network connected devices of the network connected device set based at least in part on the device identification set, and determining that the set of device types associated with the first fault classification data includes the device type of each of the one or more network connected devices of the network connected device set.

[0011] Additionally or alternatively, in some embodiments of the exemplary computer-implemented method, the exemplary computer-implemented method further includes identifying historical activity data, determining that the historical activity data indicates a first fault, and storing a first fault classification identifier representing the first fault associated with the historical activity data.

[0012] According to a second aspect of the present disclosure, an apparatus is provided for selecting predicted operational support data objects from a device operational support management repository using diverse device activity data from a dynamic home communication network. In some exemplary embodiments of the apparatus, the apparatus includes at least one processor and at least one non-transitory memory having computer-coded instructions stored therein, the computer-coded instructions, upon execution on the at least one processor, cause the apparatus to perform any one of the exemplary computer-implemented methods described herein. In still some other exemplary embodiments of the apparatus, the apparatus includes means for performing each step of any one of the exemplary computer-implemented methods described herein.

[0013] According to a third aspect of the present disclosure, a computer program product is provided for selecting predicted operational support data objects from a device operational support management repository using diverse device activity data from a dynamic home communications network. In some exemplary embodiments of the computer program product, the computer program product includes at least one non-transitory computer-readable storage medium having computer-coded instructions stored thereon, the computer-coded instructions, upon execution by at least one processor, configuring the computer program product to perform any one of the exemplary computer-implemented methods described herein.

[0014] Having thus described embodiments of the present disclosure in general terms, reference is now made to the accompanying drawings, which are not necessarily drawn to scale. [Brief description of the drawings]

[0015] [Figure 1] 1 illustrates a block diagram of a system specially configured to enable embodiments of the present disclosure. [Diagram 2] 1 illustrates a block diagram of an exemplary fault support apparatus configured in accordance with an exemplary embodiment of the present disclosure. [Diagram 3] 1 illustrates a schematic visualization of example device activity data associated with various network-connected devices on a dynamic home communication network, in accordance with at least some example embodiments of the present disclosure. [Figure 4] 1 illustrates a schematic visualization of example device activity data associated with various network-connected devices embodying a dynamic home communications network, in accordance with at least some example embodiments of the present disclosure. [Diagram 5] FIG. 1 is a schematic illustration of an exemplary fault support system disposed in communication with various exemplary dynamic home communication networks, in accordance with an embodiment of the present disclosure. [Figure 6] 1 illustrates an example data representation of operational support data objects stored within a system operational support management repository, in accordance with at least some embodiments of the present disclosure. [Figure 7] 1 illustrates an example data representation of an operational support data object associated with a fault classification identifier, according to at least some embodiments of the present disclosure. [Figure 8] 1 illustrates an example visualization of predicted operational resource selection utilizing a fault classification data model, in accordance with at least some embodiments of the present disclosure. [Figure 9] 1 illustrates a flowchart showing example operations of an example process for selecting and outputting forecasted operational support data objects, in accordance with at least some example embodiments of the present disclosure. [Figure 10] 1 illustrates a flowchart showing example operations of an example process for determining fault classification data based at least in part on particular device identification data, according to at least some example embodiments of the present disclosure. [Figure 11] 1 illustrates a flowchart showing example operations of an example process for determining fault classification data based at least in part on a plurality of device identification data, according to at least some example embodiments of the present disclosure. [Figure 12] 1 illustrates a flowchart showing example operations of an example process for determining fault classification data based on a set of device types, according to at least some example embodiments of the present disclosure. [Figure 13] 1 illustrates a flowchart showing an example operation of an example process for storing fault classification data associated with one or more faults, according to at least some example embodiments of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will now be described more fully hereinafter with reference to the accompanying drawings in which some, but not all, embodiments of the present disclosure are illustrated. Indeed, the present disclosure may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout.

[0017] overview Modern homes have evolved into complex technology hubs that are vital to the global economy. Such technology hubs are expected to seamlessly enable rapidly changing and dynamically expanding remote work, gaming, e-commerce, media and entertainment, and Internet of Things platforms. These technology hubs are typically organized into dynamic home communication networks that, given their complexity, can be difficult to maintain and support to ensure that all aspects of such networks continue to function.

[0018] A dynamic home communication network is mutable and constantly changing in that new devices are frequently connecting while previously connected network-connected devices are frequently disconnected. Such connections and disconnections must be managed flawlessly or network degradation errors may occur. Additionally, any network-connected device of a dynamic home communication network, whether considered alone or within the broader context of the dynamic home communication network, may experience a malfunction that affects the network connectivity of the network-connected device, the interoperability of the network-connected device with other network devices, and / or the intended operation of the network-connected device.

[0019] Given the complex and rapidly changing nature of dynamic home communication networks, it can be particularly difficult to identify, isolate, and resolve device or system malfunctions. Homeowners are not trained IT professionals and therefore do not have the ability to identify and trace the source of device or system malfunctions. In addition, devices operating on dynamic home communication networks are typically not configured to operate specifically with other devices that may be added to the network or in close proximity to nearby interference sources that may be present in the home environment, which can result in errors or malfunctions that are difficult to identify and resolve.

[0020] Although various resources may help to resolve the fault, searching for useful resources from a vast assortment of fault-related content often requires a reasonable understanding of the real-time status of each network device and having some idea of ​​the interference landscape present in the home environment. The dynamic nature of home communication networks may also render fault resolution resources outdated, especially in situations where such resources embody static content that is printed or downloaded and stored in some network repository. It is important that fault resolution content is continually refreshed and updated as may be necessary in response to the changing real-time conditions of a particular home communication network.

[0021] Embodiments of the present disclosure provide for the automatic provision of operational support data objects. Specifically, operational support data objects are identified and provided to resolve specific faults that are affecting or may affect one or more network-connected devices identified on a dynamic home communication network, such as a dynamic home communication network. In some contexts, the operational support data objects are associated with the most likely faults and / or embody resources determined as most likely to assist in resolving the likely faults.

[0022] Some embodiments of the present disclosure utilize fault classification data models that are specially trained and / or otherwise configured to determine predicted operational support data objects based at least in part on particular input data. Such input data may include device activity data, external aggregated device activity data, faulty device history data, etc. The predicted operational support data objects identified and / or otherwise determined by the fault classification data model may be output to one or more client devices, network-connected devices, etc. for use in resolving one or more faults.

[0023] In a particular example context, embodiments of the present disclosure select and output predicted operational support data objects for network-connected devices on or associated with a dynamic home communications network (e.g., active network-connected devices currently connected to the dynamic home communications network, or inactive network-connected devices previously detected on the dynamic home communications network but no longer connected). Such predicted operational support data objects may be specific to network-connected devices that are experiencing system malfunctions, are likely to experience malfunctions, and / or are otherwise likely to be of interest to users focused on optimizing device or network performance. Predicted operational support data objects may also be specific to network malfunctions caused by device interoperability issues, environmental interference, or other system or network factors.

[0024] As the topology of the dynamic home communications network changes (e.g., by the attachment of new or previously inactive network-connected devices and / or by the disconnection of previously active network-connected devices), such selected and output predicted operational support data objects may be similarly updated to account for the updates in the topology. For example, if a newly introduced network-connected device is experiencing or is about to experience one or more faults, predicted operational support data objects may be selected and / or output to aid in resolving such faults. Alternatively or additionally, if one or more network-connected devices contribute to or are likely to contribute to one or more faults affecting the dynamic home communications network, predicted operational support data objects may be identified, selected, and / or output to resolve such faults even in situations where such faults have not yet manifested themselves.

[0025] Some embodiments maintain and / or otherwise provide access to one or more third-party operational support data objects. The third-party operational support data objects may be made accessible as corresponding to a particular malfunction. Such third-party operational support data objects may be maintained and / or updated by systems external to the embodiments described herein. The third-party operational support data objects may be updated to ensure that the content embodied in the operational support data objects remains current and is not outdated with respect to a particular malfunction. As new or updated third-party operational support data objects are created or otherwise made available, such embodiments of the present disclosure are similarly updated to enable selection and / or output of such third-party operational support data objects in situations where a particular corresponding malfunction has been identified and / or is likely to be present within a particular dynamic home communications network.

[0026] Embodiments of the present disclosure provide numerous technical improvements in various technical fields. For example, some embodiments of the present disclosure provide predicted operational support data objects that enable proactive resolution of specific faults affecting devices, systems, networks, and / or interoperability therebetween. In this regard, embodiments improve the overall operational functionality of individual network-connected devices and / or the communications network itself (e.g., a dynamic home communications network) based, at least in part, on providing relevant predicted operational support data objects that accurately identify and resolve faults of interest (actual or potential) based on the configuration and / or topology of the communications network. Some embodiments achieve such advantages automatically (e.g., in situations where automatically executed operational support data objects, such as software applications, instructions, etc., are provided). Other embodiments achieve such advantages by facilitating various user-initiated fault resolution actions.

[0027] Additionally or alternatively, embodiments of the present disclosure provide various technical advantages to network-connected devices on a dynamic home communication network and / or the dynamic home communication network itself, as well as to fault support systems that assist in maintaining the functionality of such network-connected devices and / or the dynamic home communication network. For example, embodiments of the present disclosure improve the uptime of individual devices, systems, and networks by assisting in the rapid resolution of technical faults with greater efficiency and accuracy. Additionally or alternatively, embodiments of the present disclosure reduce wasteful network load affecting a dynamic home communication network by reducing and / or minimizing error-related inefficiencies affecting the dynamic home communication network. Additionally or alternatively, embodiments of the present disclosure reduce the computing resources required to store operational support data objects for provisioning, and thus reduce storage space that would otherwise be dedicated to locally storing complete operational support data objects. In this regard, embodiments of the present disclosure improve the functionality of both the devices and / or systems that provide such operational support data objects for network-connected devices, as well as the functionality of both the network-connected devices and / or systems that embody or are connected to the dynamic home communication network itself.

[0028] The embodiments of the present disclosure provide further technical improvements in the functioning of individual network-connected devices themselves (e.g., by improving the operational functionality of network-connected devices). Additionally or alternatively, the embodiments of the present disclosure provide technical improvements in the functioning of dynamic home communication networks themselves (e.g., by improving the interoperability and / or functionality of dynamic home communication networks and / or enabling configuration of communication networks to meet specific user-defined goals and / or preferences). Additionally or alternatively, the embodiments of the present disclosure provide improvements (e.g., technical improvements) in the accuracy of operational support data objects provided within the technical field of preventing and / or resolving failures. Furthermore, additionally or alternatively, the embodiments of the present disclosure provide technical improvements within the field of resource storage and maintenance by enabling the provision of third-party operational support data objects without the active update steps performed by the embodiments described herein.

[0029] definition The term "user" refers to an entity that controls one or more devices. Non-limiting examples of a user include an individual, an organization, or a group of people that control client devices that have access to a communications network.

[0030] The term "requesting client device" refers to a computing device embodied in hardware, software, firmware, and / or combinations thereof that enables access to one or more client devices, systems, and / or supporting functionality associated with one or more communications networks. A client device may execute a browser application configured to access web-based applications that provide such supporting functionality, and / or execute native applications that provide the supporting functionality and / or communicate with web-based applications as well.

[0031] The term "user input" refers to any user interaction with a client device that initiates a process through the client device. Non-limiting examples of user input include user gestures via a touch screen or interactive display (e.g., taps, swipes, pinches, multi-touch, multi-taps, and custom gestures), voice commands, peripheral input, keyboard keystrokes, mouse clicks or mouseovers, scrolling input, video detection actions, and data input.

[0032] The term "communications network" refers to one or more interconnected computing devices, embodied in hardware, software, firmware, and / or combinations thereof, that enable the transmission of data between such one or more computing devices. Non-limiting examples of communication networks include public networks (e.g., the Internet), private networks (e.g., home networks, enterprise networks), cellular networks, and hybrid networks.

[0033] The term "dynamic home communication network" refers to a communication network associated with one or more user identifiers that defines network access within the home environment of a user associated with the user identifier. The dynamic home communication network embodies an internal network and / or sub-network (e.g., a sub-network of the Internet) that includes any number of network-connected devices of various device types. In some embodiments, the dynamic home communication network includes one or more routers, modems, gateways, signal repeaters, smart devices, mesh networking devices, and / or wired or wireless access points that communicate with the network-connected devices via any of a number of home networking protocols, including, but not limited to, Internet Protocol (IP), IEEE 802.11 (Wi-Fi), Bluetooth, Zigbee, Wireless Universal Serial Bus (USB), Ethernet Category 5, Matter, and / or other wired or wireless transmission protocols. At a given time, the dynamic home communications network includes an "active network-connected device set" that includes all network-connected devices that are currently connected to the dynamic home communications network for communication purposes, and an "inactive network-connected device set" that includes all network-connected devices that are capable of connecting to the dynamic home communications network and / or that have previously been connected to the dynamic home communications network, but are not currently connected to the dynamic home communications network.

[0034] The term "network-connected device" refers to a computing device that is connected to, authorized by, or otherwise a part of a communications network. Non-limiting examples of network-connected devices include client devices for one or more end users of a communications network, routers, switches, relays, base stations, intracontinental and / or transcontinental network wiring, communications satellites, and cellular communications towers. The term "set of network-connected devices," when used with respect to a particular communications network, refers to two or more network-connected devices of that communications network.

[0035] The term "fault" refers to a state of reduced, erroneous, or otherwise abnormal operation of a computing device, multiple computing devices, and / or connectivity between two or more computing devices associated with a particular communications network.

[0036] The term "device identification data" refers to data and / or metadata that uniquely identifies a network-connected device. The device identification data of a particular network-connected device may be generated by and obtainable from the network-connected device itself, or may be assigned to the network-connected device by another system external to the particular network-connected device and retrievable from that external system. A network-connected device associated with device identification data may be actively connected to or otherwise associated with a communications network, or may be inactive on the communications network. Non-limiting examples of device identification data include a device International Manufacturer Equipment Identifier (IMEI), Internet Protocol address (IP), Media Access Control address (MAC address), hardware identifier, user-entered unique device name, and / or an automatically generated device identifier from a central system. In some embodiments, device identification data is retrieved and / or received by a fault support system monitoring a communications network via direct communication with each network-connected device on that communications network and / or indirectly from one or more particular network-connected devices of that communications network that aggregate such data. The device identification data can be used by one or more computing devices, including the fault support system, to identify the particular identities and / or device types of network-connected devices embodying and / or connected to the communications network.

[0037] The term "device activity data" refers to electronically managed data received from a network-connected device or generated based at least in part on monitoring one or more characteristics of a network-connected device. The device activity data represents system-initiated and / or user-initiated actions indicative of attempts to modify configuration data of a network-connected device associated with a communications network or to resolve one or more faults (e.g., as represented by one or more fault classification identifiers) associated with a network-connected device associated with a communications network. In some embodiments, the particular device activity data associated with a particular network-connected device depends on the particular device type of the network-connected device, such that different device types are associated with different data characteristics represented by the device activity data. In some embodiments, the device activity data is retrieved and / or received by a fault support system monitoring a communications network via direct communication with each network-connected device on that communications network and / or indirectly from one or more particular network-connected devices of that communications network that aggregate such device activity data by directly communicating with the network-connected devices. The device activity data can be used by one or more computing devices, including the fault support system, to determine data values ​​currently representative of the configuration of various data characteristics of one or more of the network-connected devices embodying and / or connected to the communications network, and / or to process such data values ​​to perform one or more determinations and / or apply one or more models, as described herein. In some embodiments, the device activity data includes device brands and / or device models identified from data received from or otherwise associated with network-connected devices on a particular communications network.

[0038] The term "support activity data" refers to electronically managed data representing user-initiated actions associated with initiating and / or receiving technical support for a fault represented by a fault classification identifier. Support activity data is generated via one or more client devices interacting with a fault support system and is retrievable from one or both of the client devices and / or the fault support system. Non-limiting examples of support activity data include one or more search queries entered by a user for operational support data objects associated with a fault classification identifier, data representing user interactions with a support user interface, chat log data (e.g., describing the fault) of a fault support session between a user utilizing a client device and a technician utilizing a technician device, and user interactions with an automated system for providing technical support data and / or help. In some embodiments, the support activity data includes device brands and / or device models identified from one or more user communications, user inputs, and the like. Additionally or alternatively, in some embodiments, the support activity data includes data indicative of the length of time a fault has been affecting one or more devices, systems, communication networks, and the like. The support activity data can be used by one or more computing devices including the fault support system to provide context to faults being encountered by network-connected devices associated with the user and / or to actions the user has already taken in an attempt to resolve the fault. In some embodiments, the fault support system processes such support activity data to make such determinations and / or apply one or more models as described herein.

[0039] The term "operational support data object" refers to electronically managed data that embodies or is utilized to retrieve data that remediates, resolves, and / or troubleshoots faults that affect one or more computing devices and are represented by fault classification identifiers. The operational support data object provides access to data files stored locally and / or external to the fault support system, including, but not limited to, text content data, web page data, video data, audio data, data instructions, or software applications for remediating, resolving, and / or troubleshooting one or more faults that are represented by corresponding fault classification identifiers associated with one or more computing devices. The operational support data object is generated and stored by the fault support system to provide access to the data files. Non-limiting examples of operational support data objects include text files, web pages, PDFs, and links to hosted web resources. "Third-party operational support data object" specifically refers to operational support data objects that are maintained on a data system separate from the fault support system and made accessible via links or other resource identifiers stored in the fault support system. The fault support system maintains access to any number of operational support data objects.

[0040] The term "predicted operational support data object" refers to a particular operational support data object identified to assist in resolving an identified fault corresponding to a particular fault classification identifier. The fault support system utilizes the fault classification data model to determine that the operational support data object is associated and predicted as likely to assist in resolving a particular fault that has been determined to affect or likely to affect one or more network-connected devices. In some embodiments, the fault support system generates a confidence score associated with the operational support data object that indicates the likelihood that the operational support data object will assist in resolving a fault that affects one or more network-connected devices associated with a particular user profile identifier, and determines that the operational support data object should be provided if the confidence score is above a particular minimum confidence threshold.

[0041] The term "operational support data object set" refers to one or more data objects that embody and / or store any number of operational support data objects. When used in reference to a particular fault classification identifier, an operational support data object set refers to any number of operational support data objects that may be utilized to improve or otherwise resolve the fault classification identifier.

[0042] The term “fault classification data model” refers to a statistical, algorithmic, and / or machine learning model specifically trained to identify associations between data indicative of possible faults corresponding to fault classification identifiers of one or more network-connected devices on a communications network and any number of third-party operational support data objects that may be used to resolve or improve the possible fault classification identifiers.

[0043] The term "fault classification identifier" refers to electronically managed data or unique identifiers that uniquely represent a fault in the technical operation of a particular computing device or system including multiple computing devices, a fault in the technical operation of a communications network, and / or a fault in the interoperability between two or more computing devices. Non-limiting examples of fault classification identifiers include data representing problems with connecting a computing device to a communications network, interoperability problems between a first computing device and a second computing device, interoperability problems or connectivity failures between a computing device and a peripheral device, performance hardware components of a computing device below a particular threshold, degradation in performance of a hardware component of a computing device over a particular time interval or upon the occurrence of a particular event represented in device activity data, software application crashes, unexpected shutdown of a computing device, loss of network connectivity of a computing device, and the presence of malware, spyware, computer viruses, etc. In some embodiments, there are system operational support classification identifiers that identify multiple levels of granularity, such that a first system operational support classification identifier includes one or more subsystem operational support classification identifiers. In a non-limiting exemplary context, a system operations support classification identifier embodying a “printer problem” class of technical problem is associated with various sub-identifiers embodying particular problem types (e.g., “printer connectivity problem”, “printer printing problem”, “printer ink problem”, etc.) and / or problems for particular instances of devices and / or systems (e.g., “printer brand A printing problem” and “printer brand B printing problem”, and / or “printer brand A model 1 printing problem” and “printer brand A model 2 printing problem”).The term "fault classification data" refers to electronically managed data representing one or more fault classification identifiers that have been determined to affect or have a high likelihood of affecting a computing device, a group of computing devices, and / or a communications network embodying two or more computing devices.

[0044] The term "system operational support management repository" refers to one or more electronically maintained databases embodied in hardware, software, firmware, and / or combinations thereof that store any number of operational support data objects and / or associations between operational support data objects and operational support classification identifiers. In one non-limiting exemplary context, a system operational support management repository includes operational support data objects each stored with a fault classification identifier that the operational support data object has been determined to resolve.

[0045] The term "problem support session" refers to an authorized connection between a client device and a technician device that allows a technical support technician to be provided to a user of the client device via the technician device. The problem support session allows data transfer between the client device and the technician device that provides text data, video data, access control to the client device, and / or configuration of one or more network devices that can communicate via the client device.

[0046] The term "fault text description data" refers to text data transmitted as part of a fault support session by a client device and / or technician device associated with the fault support session. Fault text description data includes text data entered by a user, including free-form text data and / or text data selected from a predefined set of available text elements. The fault text description data is stored on and / or processed by the client device and / or technician device, and / or in some embodiments, processed by an intermediate device facilitating the fault support session, such as a fault support system or associated subsystem specialized in maintaining such fault support sessions. In some embodiments, the fault support system identifies and / or receives fault text description data and stores such fault text description data associated with a particular user profile identifier as support activity data for processing as described herein, such as input to a fault classification data model.

[0047] The term "support search data" refers to electronically managed data entered via a client device associated with a user search for technical support associated with one or more fault classification identifiers. In some embodiments, the support search data includes text data entered by a user representing a user's description of a fault represented by a fault classification identifier. The support search data is stored in and / or processed by the client device and / or, in some embodiments, an intermediate device that facilitates searching operational support data objects and / or data associated with a particular fault, such as a fault support system and / or associated subsystems specialized in facilitating such searches. In some embodiments, the fault support system identifies and / or receives support search data and stores such support search data associated with a particular user profile identifier as support activity data for processing as described herein, e.g., as input to a fault classification data model.

[0048] The term "support user interface" refers to a user interface that includes one or more interface elements associated with providing access to a problem support session. In some embodiments, the support user interface includes multiple sub-interfaces, each of which provides access to various data and / or functionality associated with providing technical support functionality.

[0049] The term "main support transmission process" refers to a computer-driven process for initiating, maintaining, and engaging in a fault support session. The main support process runs separately from one or more secondary support processes that operate in parallel with the main support process. The main support transmission process may be maintained in parallel with any number of side processes, such as one or more side processes that facilitate identification of predicted operational support data objects in order to provide and / or display such predicted operational support data objects. Non-limiting examples of secondary support processes include processes that provide operational support data objects dynamically associated with one or more identified fault classification identifiers as a user engages in the main support transmission process.

[0050] The terms "training data" and "set of training data" refer to electronically managed data used to train a particular fault classification data model to identify fault classification identifiers corresponding to faults likely to affect a particular communication network (e.g., a dynamic home communication network) and / or to identify predicted operational support data objects determined as likely to assist in resolving the faults. The training data represents all or at least a portion of available historical data associated with particular operations, configurations, and / or interactions associated with the dynamic home communication network and / or one or more other dynamic home communication networks, and / or user profile identifiers associated with the dynamic home communication network and / or multiple dynamic home communication networks. In some embodiments, the training data is processed during training such that trends, patterns, data-driven indicators, and / or other predictive decisions are learned from such data by the fault classification data model. In some embodiments, the training data includes various data received, extracted, normalized, and / or aggregated from the particular dynamic home communication network and / or one or more dynamic home communication networks external to the particular dynamic home communication network.Non-limiting examples of data for the training data include past device activity data associated with a particular dynamic home communications network, past device activity data associated with one or more external dynamic home communications networks, past support activity data associated with a particular dynamic home communications network, past support activity data associated with one or more external dynamic home communications networks, faulty device history data (e.g., device activity data, support activity data, particular network topology data such as a dynamic home communications network) representing past faults affecting a network-connected device with particular other data associated with the network-connected device stored by the fault support system via a device operational support management repository, external data indicative of device fault trends and / or occurrences (e.g., web articles and / or web scraping data indicative of an increase in users reporting a particular fault of a particular device type), and / or other available data from which faults associated with the dynamic home communications network may be identified and / or from which it may be determined whether a particular operational support data object is likely to assist in resolving one or more faults affecting the dynamic home communications network.

[0051] A set of training data includes any desired portion of available data associated with one or more dynamic home communication networks and from which such trends, patterns, data-driven indicators, and / or other predictive decisions are to be learned. In some embodiments, the training data set utilized to train a particular model includes a selected subset of the desired portion of historical device activity data, support activity data, other data indicative of previous operational support data objects associated with network-connected devices of the dynamic home communication network, interactions with such operational support data objects, external system data (e.g., blog data, article data, and / or other web data from one or more predefined or determined external sources). For example, in one embodiment, the set of training data may include one or more of data representative of the make and / or model of the device, data representative of a description of the problem, any search terms to resolve a perceived problem, data representative of the duration of an ongoing problem, and / or historical data related to a fault / problem (e.g., malfunction). In some contexts, the training data includes a subset of data associated with one or more dynamic home communication networks with which the trained model is to be utilized. In some contexts, the training data includes data associated with all available dynamic home communication networks. During training, the training data set is processed by the fault classification data model, enabling the fault classification data model to identify data trends, patterns, and / or other links in the training set of device activity data.

[0052] Exemplary Systems and Apparatus of the Disclosure FIG. 1 illustrates a block diagram of a system specifically configured to enable embodiments of the present disclosure. Specifically, FIG. 1 illustrates an exemplary system 100 configured to enable the selection and provision of predicted operational support data objects. The system 100 includes any number of network-connected devices, including a fault support system 102, an external data system 112, a client device 104, a printer represented by a network-connected device 106A, a smartphone represented by a network-connected device 106B, a tablet represented by a network-connected device 106C, and one or more other network-connected devices 106D (the network-connected devices 106A-106D are collectively referred to as "network-connected devices 106"). The network-connected devices 106 can communicate with each other and / or with one or more other devices, such as the client device 104, via a first dynamic communication network 110. The fault support system 102 can communicate with the external data system 112 and / or with one or more other devices, such as the client device 104, via a second communication network 108.

[0053] The fault support system 102 includes one or more computing devices embodied in hardware, software, firmware, and / or combinations thereof that provide predicted operational support data object selection and provision functionality. For example, in some embodiments, the fault support system 102 embodies or is otherwise included in a system that provides user automated support and / or technician-based support associated with one or more network-connected devices and / or dynamic home communication networks associated with those network-connected devices. The fault support system 102 trains and / or otherwise maintains a fault classification data model, utilizes the fault classification data model to select one or more predicted operational support data objects, and / or outputs the predicted operational support data objects. In some embodiments, the fault support system 102 provides such functionality via a client device, such as client device 104, associated with any number of computing devices, such as one or more of the network-connected devices 106. In some embodiments, the fault support system 102 maintains one or more repositories that store operational support data objects, data links for accessing operational support data objects (including third-party operational support data objects), and / or associations between operational support data objects and fault classification identifiers.

[0054] The external data systems 112 include any number of data systems external to the fault support system 102. Each external data system of the external data systems 112 includes one or more computing devices embodied in hardware, software, firmware, and / or combinations thereof that host, store, and / or otherwise provide access to one or more operational support resources. For example, in some embodiments, the external data systems 112 include one or more third-party web servers that host content associated with a particular fault. Such content may include web pages, videos, images, articles, manuals, and / or other textual content, applications that attempt to diagnose and / or resolve a particular fault, etc. It should be appreciated that in some embodiments, each external data system is controlled by a different entity and / or each external data system maintains operational support data objects associated with a particular fault. For example, in some embodiments, each external data system controlled by a particular entity embodying a device manufacturer maintains operational support data objects associated with devices and / or systems made available by the device manufacturer. Alternatively or additionally, for example, an external data system embodying a technical support forum platform may include operational support data objects associated with various faults that may affect different types, makes, models, and other variations of devices, or combinations thereof.

[0055] The client device 104 includes any number of computing devices embodied in hardware, software, firmware, and / or combinations thereof that provide user access to the functionality of one or more of the fault support system 102 and / or the network-connected devices 106. In some embodiments, the client device 104 is embodied by a user device owned, operated, and / or otherwise controlled by a particular user. Non-limiting examples of the client device 104 include specially configured smartphones, personal computers, tablets, laptops, smart watches, smart TVs, wearables, virtual reality devices, virtual assistant devices, and the like. The client device 104 may be specially configured to provide access to such functionality through one or more software applications (e.g., “apps”) installed on and / or otherwise executable by the client device 104. In some embodiments, the client device 104 includes or is capable of communicating with one or more connected devices that provide processing, communication, network connectivity, display, and / or other functionality. For example, in some embodiments, the client device 104 includes a smartwatch paired with a smartphone, where the smartwatch displays information processed and / or acquired by the smartphone and transmitted from the smartphone to the smartwatch over a short-range communications network (e.g., a Bluetooth connection). In some embodiments, the client device 104 accesses one or more third party applications (e.g., third party messaging, email, and / or other communications applications) that provide data output from the error support system 102.

[0056] The communications network 108 may include any number of computing devices embodied in hardware, software, firmware, and / or combinations thereof, and the communications network 108 may enable the transmission of data to and / or from one or more other devices connected to the computing devices. For example, in some embodiments, as shown, the communications network 108 may enable the transmission of data between the fault support system 102 and / or the external data system 112. Additionally or alternatively, in some embodiments, the communications network 108 may enable the transmission of data between the client device 104 and the fault support system 102. Additionally or alternatively, in some embodiments, the communications network 108 may enable the transmission of data between the client device 104 and some or all of the external data systems 112.

[0057] The communications network 108 may embody any of a number of network configurations. In some embodiments, the communications network 108 embodies a public network (e.g., the Internet). In some embodiments, the communications network 108 embodies a private network (e.g., an internal network between certain devices). In some other embodiments, the communications network 108 embodies a hybrid network (e.g., a network that allows internal communication between certain connected devices and external communication with other devices). The communications network 108 may include one or more base stations, repeaters, routers, switches, cell towers, communications cables, and / or associated routing stations, etc. In some embodiments, the communications network 108 includes one or more user-controlled computing devices (e.g., user-owned routers and / or modems) and / or one or more external utility devices (e.g., Internet service provider communications towers and / or other devices).

[0058] In some embodiments, the first dynamic home communications network 110 embodies a private network that enables communication between various network-connected devices 106 and the client device 104. In some embodiments, for example, the dynamic home communications network 110 embodies a home network that enables communication of various devices on the home network, such as a network-connected printer (network-connected device 106A), the user's smartphone (network-connected device 106B), the user's tablet (network-connected device 106C), other users' smartphones, personal computers, laptops, smart televisions, and / or other Internet of Things-enabled devices, virtual assistant devices, home security systems, etc. A user may utilize one or more such devices independently and / or access it through another device connected to the dynamic home communications network 110, for example, through interaction with the client device 104.

[0059] In some embodiments, the device activity data is detected and / or otherwise received by the fault support system 102 associated with any one or more of the dynamic home communications network 110, the client device 104, and / or the network-connected devices 106. For example, in some embodiments, device activity data associated with each network-connected device connected to the dynamic home communications network 110 and / or associated with component network-connected devices embodying the dynamic home communications network 110 itself is detected, requested, and / or otherwise received by the client device 104 for transmission to the fault support system 102. Alternatively or additionally, in some embodiments, the fault support system 102 directly monitors the dynamic home communications network 110 to identify device activity data associated with the dynamic home communications network 110 and / or the network-connected devices 106 capable of communicating with the dynamic home communications network 110. In one example context, a user may utilize a client device 104 to update the configuration of one or more of the network-connected devices 106 and / or otherwise affect the operation of one or more of the network-connected devices 106, and device activity data (e.g., a configuration log) indicating such configuration updates is included in the device activity data processed by the system 100.

[0060] In some embodiments, the device activity data includes or is associated with device identification data that uniquely identifies one or more network-connected devices. For example, in some embodiments, device identification data is detected and / or otherwise identified for each network-connected device embodying and / or actively connected to the dynamic home communications network 110. Alternatively or additionally, in some embodiments, device identification data is detected, received, and / or determined associated with inactive network-connected devices previously connected to the dynamic home communications network 110. In this regard, any number of devices experiencing and / or contributing to a malfunction (e.g., a malfunction with respect to the operation of the dynamic home communications network 110 overall) may be identified and processed.

[0061] In some embodiments, the device activity data additionally or alternatively includes configuration data and / or logs associated with a network-connected device or combination of network-connected devices. For example, in some embodiments, device activity data is detected, received, and / or otherwise identified that includes current configuration data (e.g., configuration characteristics and corresponding values) for any number of network-connected devices. It should be understood that the particular configuration identified for each network-connected device may differ, for example, based at least in part on the device type of each particular network-connected device. Additionally or alternatively, in some embodiments, device activity data is detected, received, and / or otherwise identified that includes configuration logs of historical configuration data and / or changes in the configuration of the network-connected devices for any number of network-connected devices.

[0062] Additionally or alternatively, in some embodiments, support activity data is generated based on one or more initiated actions associated with diagnosing and / or resolving one or more faults. In some embodiments, support activity data representative of, for example, initiated search queries for support regarding the fault (e.g., performed by a search engine), interactions with one or more support processes of the fault support system 102 and / or associated systems is generated by the fault support system 102 and / or received from the client device 104. The support activity data and / or device activity data may be generated by any of the devices as shown and described herein and received and / or otherwise stored by the fault support system 102 for processing to select one or more predicted operational support data objects as described herein.

[0063] At any point in time, one or more of the network-connected devices 106 may experience a malfunction and / or the dynamic home communication network 110 itself may experience a malfunction due to the network-connected devices 106 embodying and / or contributing to the network-connected devices 106 connected to the dynamic home communication network 110. For example, in one exemplary context, one or more of the network-connected devices 106 operate at a reduced capacity due to any of a number of physical and / or virtual factors, such as (1) incompatibility of hardware, software, firmware, etc., (2) reduction in hardware components, and (3) operation of malicious software such as spyware, malware, viruses, etc. Alternatively or additionally, in another context, one or more of the network-connected devices 106 experience a network connectivity error. For example, the network connected device 106A may lose connection with the dynamic home communications network 110 due to any of a number of malfunctions, such as a loss of signal by the network connected device 106A, a hardware component for connecting the network connected device 106A to the dynamic home communications network 110 that fails, a configuration change that prevents the network connected device 106A from reconnecting to the dynamic home communications network 110, etc. Additionally or alternatively, in some embodiments, the dynamic home communications network 110 itself experiences one or more malfunctions, such as a loss of power by one or more devices embodying the dynamic home communications network 110, a loss of connection by the dynamic home communications network to an external network (e.g., an Internet outage), a reconfiguration of one or more devices of the dynamic home communications network 110 that prevents communication of traffic to and / or from one or more of the network connected devices 106A, etc.

[0064] Additionally or alternatively, each of the network-connected devices 106 may experience different types of malfunctions. For example, a smart printer (e.g., embodied by network-connected device 106A) may experience a particular operational problem that is different from that experienced by a smartphone (e.g., embodied by network-connected device 106B). In this regard, as the number of different types of network-connected devices on a particular dynamic home communications network increases, the complexity of possible malfunctions that may arise and / or that may need to be resolved increases.

[0065] It should be understood, therefore, that as the complexity of network-connected devices increases (e.g., the number increases and / or the variability of devices having different characteristics increases), such technical complexity is particularly prevalent in the context of home networks. For example, in one exemplary context of a home network embodied by dynamic home communication network 110, network-connected devices 106 include any number of network-connected devices, each of various device types, brands, models, operations, etc. Additionally or alternatively, one or more of such devices may actively communicate over the network, while other network-connected devices may be inactive and / or not otherwise communicate over the network. Client device 104, as described herein, utilizes a system operational support data model to enable interaction with the fault support system to accurately identify and / or output predicted operational support data objects to assist in resolving any one or more of the various faults.

[0066] Additionally or alternatively, in some embodiments, the dynamic home communications network 110 is associated with a periodically changing list of actively connected network-connected devices ("active network-connected devices") and inactive network-connected devices that are not connected to the dynamic home communications network 110. For example, in some contexts, a user handheld device may periodically disconnect from the dynamic home communications network 110 as the user handheld device is relocated (e.g., to reach outside the range of the dynamic home communications network 110) and / or dynamically reconnect (e.g., upon re-entering the range of the communications network 110). In this regard, device activity data indicative of active network-connected devices at a particular point in time and / or inactive network-connected devices at any particular point in time may be identified, retrieved, and / or otherwise received. In some embodiments, such data is processable to identify particular network-connected devices of the dynamic home communications network 110. For example, data indicative of inactive and active network-connected devices can be compared over one or more time intervals to determine fixed components of the dynamic home communications network 110, such as routers, modems, etc., that can be configured to address failures associated with one or more network-connected devices and / or network connectivity of the dynamic home communications network 110 itself.

[0067] In some embodiments, the fault support system 102 outputs operational support data objects at certain defined times and / or upon detecting the occurrence of certain events. For example, in some embodiments, the fault support system 102 continuously monitors connections, configuration changes, and / or communications on the dynamic home communication network 110 or associated with the network-connected devices embodying the dynamic home communication network 110. The fault support system 102 in some embodiments monitors the dynamic home communication network 110 directly (e.g., in situations where the fault support system 102 is connected to the dynamic home communication network 110) or indirectly, for example, through communications with the client devices 104. In this regard, the fault support system 102 in such embodiments detects certain occurrences, triggers, satisfaction of predefined criteria, and / or other events that trigger the selection and / or output of predicted operational support data objects. For example, in some embodiments, fault support system 102 monitors such data to determine whether one or more network-connected devices on or embodying dynamic home communications network 110 are experiencing or are likely to experience a fault, and then selects and / or outputs predicted operational support data objects associated with such faults. Alternatively or additionally, in some embodiments, fault support system 102 initiates the selection and / or output of predicted operational support data objects in response to receiving data indicating user initiation of a particular application and / or a request for particular functionality.

[0068] 2 illustrates a block diagram of an exemplary specially configured fault support device according to an exemplary embodiment of the present disclosure. In some embodiments, the fault support system 102 is embodied by one or more computing systems, such as the fault support device 200 as shown and described in FIG. 2. The fault support device 200 includes a processor 202, a memory 204, an input / output circuit 206, a communication circuit 208, and a support providing circuit 210. In some embodiments, the fault support device 200 is configured to perform the operations described herein using one or more of the sets of circuits 202, 204, 206, 208, and / or 210.

[0069] Although these components are described in terms of functional limitations, it should be understood that certain implementations necessarily involve the use of specific computing hardware. It should also be understood that in some embodiments, some of the components described herein include similar or common hardware. For example, two sets of circuits may both leverage the use of the same processor, network interface, storage medium, etc. to perform the associated functions of those sets, thus avoiding the need for duplicated hardware for each set of circuits. Thus, users of the term "circuitry" as used herein with respect to components of an apparatus should be understood to include specific hardware configured to perform the functions associated with the particular circuitry as described herein.

[0070] In particular, the term "circuitry" should be broadly understood to include hardware and, in some embodiments, software for configuring hardware. For example, in some embodiments, "circuitry" includes processing circuitry, storage media, network interfaces, input / output devices, etc. Alternatively or additionally, in some embodiments, other elements of fault support apparatus 200 provide or supplement the functionality of other particular sets of circuits. For example, in some embodiments, processor 202 provides processing functionality for any of the sets of circuits, memory 204 provides storage functionality for any of the sets of circuits, communication circuitry 208 provides network interface functionality for any of the sets of circuits, etc.

[0071] In some embodiments, the processor 202 (and / or a co-processor, or any other processing circuitry that assists or is otherwise associated with the processor) communicates with the memory 204 via a bus for passing information between components of the fault support apparatus 200. In some embodiments, for example, the memory 204 may be non-transitory, for example, including one or more volatile and / or non-volatile memories. In other words, for example, the memory 204 in some embodiments includes or embodies an electronic storage device (e.g., a computer-readable storage medium). In some embodiments, the memory 304 is configured to store information, data, content, applications, instructions, etc., for enabling the fault support apparatus 200 to perform various functions in accordance with exemplary embodiments of the present disclosure.

[0072] Processor 202 may be embodied in a number of different ways. For example, in some embodiments, processor 202 may include one or more processing devices configured to execute independently. Additionally or alternatively, in some embodiments, processor 202 includes one or more processors configured in tandem via a bus to enable independent execution of instructions, pipelines, and / or multithreading. Use of the terms "processor" and "processing circuitry" should be understood to include a single core processor, a multi-core processor, multiple processors internal to defect support apparatus 200, and / or one or more remote or "cloud" processors external to defect support apparatus 200.

[0073] In an exemplary embodiment, the processor 202 is configured to execute instructions stored in the memory device 204 or otherwise accessible to the processor. Alternatively or additionally, the processor 202 is configured to execute hard-coded functionality. Thus, whether configured by hardware or software methods or a combination thereof, the processor 202 represents an entity (e.g., physically embodied in a circuit) that can perform operations according to embodiments of the present disclosure, while being configured accordingly. Alternatively or additionally, as another example, in some embodiments, when the processor 202 is embodied as an executor of software instructions, the instructions specifically configure the processor 202 to execute algorithms embodied in specific operations described herein when such instructions are executed.

[0074] As one particular exemplary embodiment, the processor 202 is configured to perform various operations associated with the selection and provision of improved predicted operational support data objects, for example, as described with respect to the operation of the fault support system 102 and / or as further described herein. In some embodiments, the processor 202 includes hardware, software, firmware, and / or combinations thereof that receive and / or retrieve device activity data associated with a particular client device, user profile, and / or the like. Additionally or alternatively, in some embodiments, the processor 202 includes hardware, software, firmware, and / or combinations thereof that determine that particular data meets trigger criteria to initiate the selection and / or provision of predicted operational support data objects. Additionally or alternatively, in some embodiments, the processor 202 includes hardware, software, firmware, and / or combinations thereof that maintain one or more data repositories of operational support data objects and / or associations with the operational support data objects, e.g., with corresponding fault classification identifiers. Additionally or alternatively, in some embodiments, the processor 202 includes hardware, software, firmware, and / or combinations thereof that maintain a fault classification data model. Additionally or alternatively, in some embodiments, processor 202 includes hardware, software, firmware, and / or combinations thereof that take input data and / or apply it to the fault classification data model. Additionally or alternatively, in some embodiments, processor 202 includes hardware, software, firmware, and / or combinations thereof that output predicted operational support data objects selected by the fault classification data model in real time.

[0075] In some embodiments, the fault support apparatus 200 includes an input / output circuit 206 for providing output to a user, and in some embodiments, receiving an indication of a user input. In some embodiments, the input / output circuit 206 is in communication with the processor 202 to provide such functionality. The input / output circuit 206 may include one or more user interfaces, and in some embodiments includes a display including an interface rendered as a web user interface, an application user interface, a user device, a back-end system, or the like. In some embodiments, the input / output module 206 also includes a keyboard, a mouse, a joystick, a touch screen, a touch area, soft keys, a microphone, a speaker, or other input / output mechanisms. The processor 202 and / or the input / output circuit 206 including the processor may be configured to control one or more functions of one or more user interface elements via computer program instructions (e.g., software and / or firmware) stored in a processor-accessible memory (e.g., memory device 204, etc.). In some embodiments, the input / output circuit 206 includes or utilizes a user-facing application to provide input / output functionality to a client device and / or other display associated with the user.

[0076] The communication circuitry 208 includes any means, such as devices or circuits embodied in either hardware or a combination of hardware and software, configured to receive and / or transmit data to and from a network and / or any other device, circuit, or module in communication with the fault support apparatus 200. In this regard, the communication circuitry 308 includes, for example, in some embodiments, a network interface to enable communication with a wired or wireless communication network. Additionally or alternatively, in some embodiments, the communication circuitry 208 includes one or more network interface cards, antennas, buses, switches, routers, modems, and supporting hardware and / or software, or any other devices suitable for enabling communication over one or more networks. Additionally or alternatively, the communication circuitry 208 includes circuitry for interacting with an antenna and / or other hardware or software to cause transmission of signals via the antenna or process reception of signals received via the antenna. In some embodiments, the communication circuitry 208 communicates with the fault support apparatus 200 to enable transmission of data to and / or reception of data from a client device.

[0077] The support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof to support various functionalities associated with improved selection and / or provision of predicted operational support data objects associated with a communication network or associated with network-connected devices embodying a communication network. For example, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for receiving one or more input data sets for processing by the fault classification data model, such as training data (e.g., previously retrieved device identifiers, other device activity, etc.), external aggregated device activity data, fault device history data, etc. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for identifying in real-time a device identification data set associated with a set of network-connected devices capable of communicating with the dynamic home communication network. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for retrieving a device activity data set associated with a set of network-connected devices. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for applying the fault classification data model to the device activity data set to select predicted operational support data objects from the device operational support management repository. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for outputting the predicted operational support data objects to a requesting client device in real time.

[0078] In some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for performing additional and / or detailed sub-processes embodying such steps. For example, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for determining fault classification data embodying one or more fault classification identifiers corresponding to a particular device identification data and / or a plurality of device identification data. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for identifying fault classification identifiers based at least in part on device types of network-connected devices associated with a particular communication network. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for associating fault classification identifiers with corresponding historical activity data. Additionally or alternatively, in some embodiments, the support providing circuit 210 includes hardware, software, firmware, and / or combinations thereof for training the fault classification data model based on one or more portions of the training data, such as the training data, the external aggregated device activity data, and the faulty device history data.

[0079] It should be understood that in some embodiments, the support providing circuitry 210 may include a separate processor, a specially configured field programmable gate array (FPGA), or a specially programmed application specific integrated circuit (ASIC). Additionally or alternatively, in some embodiments, one or more of the sets of circuits 202-210 may be combined. Alternatively or additionally, in some embodiments, one or more of the sets of circuits perform some or all of the functionality described in association with another component. For example, in some embodiments, one or more of the sets of circuits 202-210 are combined into a single module embodied in hardware, software, firmware, and / or combinations thereof. Similarly, in some embodiments, one or more of the sets of circuits, e.g., the support providing circuitry 210, are combined such that the processor 202 performs one or more of the operations described above with respect to each of these modules.

[0080] Exemplary Computing Environment of the Disclosure Having described exemplary systems and devices according to the present disclosure, exemplary computing environments and data representations according to the present disclosure are now considered. Each of the exemplary computing environments may be represented by a visualization of the data shown in the computing environments. It should be understood that the particular data representations and data types are exemplary and that in other embodiments, such data is otherwise structured and / or represented differently and / or other data is processed. In some embodiments, the particular data is received and / or maintained by the fault support apparatus 200 for processing as described herein.

[0081] 3 illustrates a schematic visualization of example device activity data associated with various network-connected devices operating on a communication network, according to at least some example embodiments of the present disclosure. Specifically, FIG. 3 illustrates a visualization of device activity data for a plurality of network-connected devices associated with a dynamic home communication network, e.g., as active and / or inactive network-connected devices. Various portions of the device activity data shown and described may be received, retrieved, or otherwise obtained from the associated network-connected devices, determined from network traffic communicated through the communication network, etc. In this regard, it will be understood that the device activity data may be received, retrieved, and / or maintained by the fault support apparatus 200.

[0082] As illustrated, the network-connected device 106A is associated with device activity data including configuration change data 302A and network connection data 302B. In some such embodiments, the network-connected device 106A embodies a network-connected printer that is actively connected to a dynamic home communications network. The configuration change data 302A in some embodiments embodies a change log of one or more configuration characteristics of the network-connected device 106A. For example, in some contexts, the configuration change data 302A includes a current value of each configuration characteristic, values ​​of such configuration characteristics at previous time intervals and / or times, and / or indications of other aspects related to the operational functionality of the network-connected printer. Such configuration change data 302A may be maintained by the network-connected device 106A, for example, in a configuration log stored by the network-connected device 106A as values ​​of the configuration characteristics are set and / or updated. In one exemplary context, a user interacts with the network-connected device 106A directly, or indirectly via a client device accessing the same communications network, for example, to update values ​​corresponding to one or more configuration characteristics to desired values. It should be appreciated that in some embodiments, the configuration change data 302A includes detected and / or determined default values ​​identified for one or more configuration characteristics that were set by default upon start-up or initial configuration of the network-connected device 106A.

[0083] The network connection data 302B in some embodiments embodies network authentication credentials and / or connection history logs associated with connecting to a particular communication network. For example, in some such embodiments, the network connection data 302B indicates whether the network connection device 106A is configured to connect to a particular communication network, network security data such as an SSID, hostname, or other network identifier that the network connection device 106A is configured to attempt to access, a password that the network connection device 106A is configured to attempt to utilize to access the communication network, and the like. Additionally or alternatively, in some embodiments, the network connection data 302B includes a connection log indicating periods of network connectivity and / or lack of network connectivity by the network connection device 106A. Alternatively or additionally, in some embodiments, the network connection data 302B includes an indication of received errors associated with attempted network transmissions.

[0084] In some embodiments, the configuration change data 302A and / or the network connection data 302B are embodied chronologically or otherwise to include timestamps indicating when values ​​of such data were changed. In this regard, errors may be correlated to specific changes represented in one or more portions of the device activity data. Additionally or alternatively, in some embodiments, one or more portions of the device activity data are actively monitored (e.g., during a period of active connection with a communications network) by an external device or system, such as the fault support apparatus 200.

[0085] As further illustrated, the network-connected device 106B is associated with device activity data that includes application usage data 304A. In some embodiments, the application usage data 304A includes data identifiers indicative of software applications, packages, and / or other executables installed on or otherwise accessible via the network-connected device 106B. Additionally or alternatively, in some embodiments, the application usage data 304A includes data indicative of actions performed via one or more particular software applications and / or operational data associated with the performance of one or more particular software applications (e.g., processor usage, memory usage, battery depletion, network activity, etc.). Further, additionally or alternatively, in some embodiments, the application usage data 304A includes crash logs, actions attempted and / or performed via one or more particular software applications, and / or other tracked interactions with one or more particular software applications.

[0086] As further illustrated, the network-connected device 106C is associated with device activity data including application usage data 306A, network connection data 306B, and configuration change data 306C. Such data portions in some embodiments are specific to the network-connected device 106C and include data similar to the similarly named configuration change data 302A, network connection data 302B, and application usage data 304A, respectively. In this regard, it should be understood that the data characteristics and / or values ​​of the device activity data associated with each network-connected device may vary based on the individual configuration and use of each network-connected device. Additionally or alternatively, the device activity data associated with each particular network-connected device in some contexts is determined based at least in part on the device type, device characteristics, or other characteristics of the particular network-connected device. Each of the device activity data portions may be stored and / or processed individually or in conjunction with device activity data for one or more other network-connected devices for use in identifying a particular malfunction affecting an individual device, multiple devices, and / or a communications network with which the network-connected device may communicate.

[0087] 4 illustrates a schematic visualization of example device activity data associated with various network-connected devices embodying a communication network, according to at least some example embodiments of the present disclosure. Specifically, FIG. 4 illustrates a visualization of device activity data for a plurality of network-connected devices embodying a dynamic home communication network. As illustrated, the communication network includes a modem 452, a router 454, and a network bridge 456. Various portions of the device activity data shown and described may be received from associated network-connected devices, determined from monitoring network traffic conveyed over the communication network, etc. In some embodiments, a portion of the device activity data is received, retrieved, and / or otherwise maintained by an external device or system, such as the fault support apparatus 200.

[0088] As illustrated, a modem 452 embodying a first network connected device of a dynamic home communication network is associated with device activity data including DNS configuration data 402A and firmware configuration data 402B. In some such embodiments, the modem 452 embodies a user controlled device in a particular environment (e.g., a user's home environment) that facilitates connection to an external communication network, e.g., the Internet. The DNS configuration data 402A embodies configuration of a domain name system and / or configuration for accessing one or more domain name systems. Such DNS configuration data 402A may include DNS host mapping configuration data, IP addresses of such domain name systems, query forwarding configuration data, etc.

[0089] In some embodiments, firmware configuration data 402B embodies firmware that enables interaction between hardware and / or software that configures modem 452. For example, in some embodiments, firmware configuration data 402B includes values ​​of one or more data characteristics that enable connectivity between a modem, other network-connected devices, and / or an external communications network (e.g., the Internet). Firmware configuration data 402B may be updated, replaced, and / or otherwise modified in situations where firmware in modem 452 has been and / or is to be updated to a new version. In some embodiments, firmware configuration data 402B includes a firmware update log that indicates changes in data characteristics between firmware versions.

[0090] As illustrated, a router 454 embodies a second network connected device of the dynamic home communication network. In one exemplary context, the router 454 is connected to a modem 452 to enable traffic routing, wireless transmission functionality (e.g., Wi-Fi), and the like. The illustrated router 454 is associated with QoS configuration data 404A and SSID configuration data 404B. The QoS configuration data 404A may embody data characteristics, values, and the like related to Quality of Service (QoS). In some embodiments, the QoS configuration data 404A embodies values ​​of data characteristics indicative of prioritized network traffic and / or bandwidth allocations for one or more devices, applications, and the like. In some embodiments, the QoS configuration data 404AA includes identifiers of one or more particular network connected devices and a bandwidth or other priority allocation for each identified network connected device. Alternatively or additionally, in some embodiments, the QoS configuration data 404A includes a data log of changes in QoS related characteristics over time.

[0091] In some embodiments, the SSID configuration data 404B embodies data associated with the configuration of a service set identifier (SSID) for the router 454 and / or associated network-connected devices embodying the communication network. In some embodiments, the SSID configuration data 404B includes a data label that identifies the dynamic home communication network (e.g., a "network name" that may be viewed and / or utilized by a user to identify the dynamic home communication network). In some embodiments, the SSID configuration data 404B includes one or more data flags that indicate whether the router broadcasts the SSID for access by other network-connected devices. Alternatively or additionally, in some embodiments, the SSID configuration data 404B includes a past configuration data log that includes previous data values ​​of properties associated with previously configured SSIDs and / or configurations of SSIDs. In some such embodiments, the past configuration data log includes timestamps and / or time intervals during which changes in configuration properties of the router 454 were applied.

[0092] As illustrated, the network bridge 456 embodies a third network connectivity device of the dynamic home communication network. In one exemplary context, the network bridge 456 is a specially configured network connectivity device that bridges two independent networks and / or sub-networks into a single dynamic home communication network. In some embodiments, the network bridge 456 manages a second subset of the network connectivity devices and communicates with the router 454 that manages a first subset of the network connectivity devices to create a single combined dynamic home communication network that includes both the first and second subsets of the network connectivity devices. Alternatively or additionally, in some embodiments, the network bridge 456 embodies a computing device that is specially configured to provide multiple types of network connectivity services including bridging, Internet connection sharing, network address translation (NAT), and the like. In this regard, the network bridge 456 may be configured in one of any number of modes that enable each of these independent types of network connectivity services.

[0093] The illustrated network bridge 456 is associated with IP configuration data 406A and NAT configuration data 406B. In some embodiments, the IP configuration data 406A embodies the configuration of Internet Protocol (IP) addresses utilized to integrate independent communication networks. In some embodiments, the IP configuration data 406A includes currently assigned IP addresses for bridging the network bridge with another network-attached device (e.g., router 454). Additionally or alternatively, in some embodiments, the IP configuration data 406A includes historical configuration data representing previously assigned IP addresses and / or timestamps indicating when the data values ​​for such characteristics were updated.

[0094] In some embodiments, NAT configuration data 406B embodies the configuration of network address translation (NAT) services performed by network bridge 456. In some embodiments, NAT configuration data 406B indicates whether NAT services are to be utilized as an alternative to bridging the network connections of two independent communication networks (or sub-networks). Additionally or alternatively, in some embodiments, NAT configuration data 406B includes the configuration of an address pool of real host IPs utilized by a primary communication network or a host communication network. Additionally or alternatively, in some embodiments, NAT configuration data 406B includes the configuration of virtual addresses utilized for external communications from the communication network. Further, additionally or alternatively, in some embodiments, NAT configuration data 406B includes historical configuration data for one or both of such characteristics, and / or the like, in some embodiments including timestamps and / or time intervals during which values ​​of such configuration characteristics were updated. In this regard, NAT configuration data 406B may include a historical log of such data updates.

[0095] The various configuration characteristics of each network-connected device and the data values ​​associated with those configuration characteristics can be processed to learn situations in which the data values ​​indicate possible, probable, or existing faults. Additionally or alternatively, combinations of data values ​​can be processed to learn situations in which the combinations indicate possible, probable, or existing faults. It should be appreciated that in some embodiments, rule sets are generated that represent manually determined or automatically learned faults indicated from particular data values ​​of configuration characteristics or combinations of configuration characteristics. Alternatively or additionally, in some embodiments, algorithmic, statistical, and / or machine learning models are configured to learn faults indicated by individual data values ​​or combinations of data values ​​for one or more configuration characteristics.

[0096] It should be understood that a communications network may be embodied via and / or including any number of network-connected devices. In this regard, one or more additional and / or alternative network-connected devices may be included in a particular communications network, such as a dynamic home communications network. Each such network-connected device may store and / or be associated with its own independent configuration characteristics and / or data values ​​related to providing the functionality described herein. Accordingly, the characteristics of the particular network-connected devices and configuration data shown and described herein are not intended to limit the scope and spirit of the present disclosure.

[0097] Exemplary Training Data Environment of the Present Disclosure Having described the exemplary systems, apparatus, and data representations and visualizations of the present disclosure, an exemplary training environment is now described that includes visualizations of data elements and visualizations of such interacting data systems. It will be understood that the particular visualizations, data systems, and interactions between such data systems are exemplary, and that in some embodiments, the data systems and interactions between data systems may in fact be embodied utilizing any of numerous devices, systems, processes, and the like. In this regard, the particular visualizations are provided for non-limiting purposes of understanding, and are not intended to limit the scope and spirit of the present disclosure.

[0098] FIG. 5 is a schematic illustration of an exemplary fault support system arranged in communication with various exemplary dynamic home communication networks according to an embodiment of the present disclosure. Specifically, FIG. 5 illustrates a visualization of an exemplary system environment 500 including systems that interact to enable training for accurately predictive operational support data object selection and provision according to the present disclosure. The exemplary system environment 500 includes a plurality of dynamic home communication networks 504A, 504B, 504C, and 504D (collectively, "dynamic home communication networks 504"), each associated with a fault support system 102. The fault support system 102 can communicate with some or all of each of the dynamic home communication networks 504 via a second communication network 502. In some embodiments, the fault support system 102 is embodied by a fault support device 200 as shown and described herein.

[0099] In some embodiments, each of the dynamic home communications networks 504 is embodied by and / or includes any number of connected network-connected devices. Any of such network-connected devices, or combinations of network-connected devices, may experience one or more malfunctions. Such dynamic home communications networks 504 may each include network-connected devices of different device types, different topologies of network-connected devices, different numbers of network-connected devices, etc. Additionally or alternatively, whether the network-connected devices in one or more of the dynamic home communications networks 504 are different or the same, such network-connected devices may nevertheless be configured differently, such that, for example, one or more configuration characteristics of two similar network-connected devices are set to different values. It should be understood that such malfunctions may occur any of a number of times and may be caused by any of a number of underlying configurations, devices, etc.

[0100] In some contexts, each of the dynamic home communication networks 504 is deployed in a different physical and / or virtual environment and / or location. For example, in some embodiments, each of the dynamic home communication networks 504 is deployed in a different home environment. In at least one exemplary context, for example, the dynamic home communication network 504A is embodied by a network-connected device in a first user's home environment, the dynamic home communication network 504B is embodied by a network-connected device in a second user's home environment, the dynamic home communication network 504C is embodied by a network-connected device in a third user's home environment, and the dynamic home communication network 504D is embodied by a network-connected device in a fourth user's home environment. The physical home environments in some contexts are close to each other (e.g., within a particular shared city, zip code, state, country, other region, etc.), or in some contexts are located far away from each other or are otherwise within different location names. It should be understood that in some contexts, the fault support system 102 may be in any location and in any configuration, and thus such a configuration of the dynamic home communication network, which is not constrained by its physical location, network configuration, its network connecting devices, etc., enables a diverse range of dynamic home communication networks to be able to communicate with the fault support system 102.

[0101] The fault support system 102 may be in communication with the fault support system 102 via a second communication network 502. In some embodiments, the second communication network 502 embodies a public communication network, such as the Internet, that enables the transmission of data between each of the dynamic home connectivity networks 504 and the fault support system 102. The dynamic home communication networks 504A in some contexts each include at least one network connectivity device that enables such communication with the fault support system 102. For example, in some embodiments, the client devices of each of the dynamic home communication networks 504 execute one or more software applications that enable the communication of data to and / or from the fault support system 102. The client device in some embodiments includes or embodies a user device (e.g., a specially configured smartphone device that executes a software application associated with the functionality of the fault support system 102), a specially configured network access point (e.g., a router or modem that is specially configured, via software and / or firmware, to provide data associated with network-connected devices and / or that embody a dynamic home communication network), or a dedicated network-connected device (e.g., a computing device that is specially configured to monitor data associated with the network-connected devices that are connected to and / or that embody a dynamic home communication network to which the computing device is connected). In this regard, in some embodiments, the fault support system 102 communicates via the second communication network 502 with one or more computing devices associated with each of the dynamic home communication networks 504 to receive specific data associated with the network-connected devices of the dynamic home communication networks 504, such as device activity data, device identification data, etc.

[0102] In some embodiments, the fault support system 102 receives one or more data sets from each of the dynamic home communication networks for use in training one or more data models. For example, the fault support system 102 in some embodiments receives one or more device activity data sets associated with each of the dynamic home communication networks 504, data indicative of faults encountered by network-connected devices of each of the dynamic home communication networks 504, device identification data sets indicative of network-connected devices and / or device types of network-connected devices on the dynamic home communication networks, etc. The fault support system 102 in some embodiments stores and / or otherwise maintains data sets including data specific to each dynamic home communication network and network-connected devices of the dynamic home communication networks. In this regard, in some such embodiments, the fault support system 102 is configured to store and / or maintain historical activity data including the data portion received for each of the dynamic home communication networks. The resulting historical activity data may include historical device activity data, fault device history data for network-connected devices of each of the dynamic home communication networks, historical device identification data, etc. for each of the one or more dynamic home communication networks.

[0103] In some embodiments, the fault support system 102 utilizes stored data associated with the dynamic home communication network 504 to train a fault classification data model. In some such embodiments, the fault classification data model is specifically trained for a particular task associated with selecting and / or providing predicted operational support data objects. For example, in some embodiments, the fault support system 102 trains the fault classification data model to select predicted operational support data objects from a device operational support management repository that includes any number of operational support data objects available for selection. To select predicted operational support data objects, in some embodiments, the fault classification data model is trained to identify device identification data corresponding to network-connected devices that are likely to encounter or are currently encountering a particular fault based on associated device activity data. The fault classification data model in some embodiments is further trained to identify operational support data objects that are likely to be associated with or otherwise assist in resolving a particular fault. In this regard, the fault support system 102 may train a fault classification data model to identify particular fault classification identifiers that represent particular faults affecting the communications network and / or particular network-connected devices of the communications network, and to identify operational support data objects that are determined to be most likely to assist in resolving the faults represented by the fault classification identifiers.

[0104] In some embodiments, the fault support system 102 learns from aggregated data from several external systems, e.g., external dynamic home communication networks, to increase the amount of data available for use during training and / or improve the overall accuracy of the determination based on different data patterns identified from the aggregation of each of the individual data sets. For example, in some embodiments, the fault classification data model learns data patterns, trends, etc., indicative of a particular fault affecting a particular network-connected device from external aggregated device activity data embodying an aggregation of each of the individual device activity data sets for each of the dynamic home communication networks 504 and / or an aggregation of other similar data sets associated with each of the dynamic home communication networks 504. Once the model is trained, in some embodiments, the fault support system 102 stores the trained model for use, e.g., to actively select and output predicted operational support data objects associated with faults affecting one or more network-connected devices and / or communication networks.

[0105] In some embodiments, the fault support system 102 utilizes and / or communicates with a separate system that performs training of one or more models, such as a fault classification data model, based on data received from one or more of the dynamic home communication networks 504. For example, in some embodiments, the fault support system 102 pushes data to one or more external systems that are configured to utilize the pushed data to train one or more models and return the trained models to the fault support system 102. Such an embodiment allows the fault support system 102 to reduce the amount of computing resources required to perform such training and to increase the amount of computing resources available to service other tasks, such as determining faults that will affect or are likely to affect one or more communication networks and / or selecting predicted operational support data objects associated with resolving such faults.

[0106] Exemplary Data Environment of the Present Disclosure Having described the exemplary systems, devices, data representations, and training methodologies of the present disclosure, an exemplary data environment including visualizations of data elements and interactions between such data elements will now be described. It will be understood that the particular visualizations of data elements are exemplary, and that in some embodiments, data elements are actually embodied using any of numerous data configurations, data types, and values. In this regard, the particular visualizations of data elements and interactions between such data elements are for non-limiting purposes of understanding, and are not intended to limit the scope and spirit of the disclosure herein and the appended claims.

[0107] 6 illustrates an example data representation of operational support data object storage in a system operations support management repository, according to at least some embodiments of the present disclosure. Specifically, FIG. 6 illustrates an operations support management repository 602 configured to store any number of operational support data objects, such as each of operational support data objects 604A, 604B, 604C, 604D, and 604E (collectively, "operations support data objects 604"). In some embodiments, the system operations support management repository 602 is embodied by, included in, and / or otherwise maintained by the fault support apparatus 200. Additionally or alternatively, in some embodiments, the system operations support management repository 602 is embodied by, included in, and / or otherwise maintained by a separate device, system, and / or apparatus, and the fault support apparatus 200 is configured to access the system operations support management repository 602. For example, in some such embodiments, the system operations support management repository 602 may be maintained separately to enable periodic and / or ongoing updates of the system operations support management repository 602 (e.g., adding new operational support data objects stored in the repository, purging old, unused, and / or otherwise marked operational support data objects previously stored in the repository, updating operational support data objects stored in the repository, etc.) without affecting the operation of the fault support apparatus 200.

[0108] Systems operations support management repository 602, in some embodiments, includes one or more computing devices embodied in hardware, software, firmware, and / or combinations thereof. For example, in some embodiments systems operations support management repository 602 includes one or more virtual databases, physical database servers, software-based storage solutions, etc. that store operations support data objects. Systems operations support management repository 602 may store any number of operations support data objects, each representing, for example, computer-executable instructions, software applications, web resources, and / or other content that assists in resolving one or more faults.

[0109] In some embodiments, the system operations support management repository 602 stores third party fault support data objects. Each third party operations support data object in some contexts embodies a data link (e.g., URL, IP address, etc.) or other data-driven mechanism for accessing data objects stored by devices, systems, and / or other computing devices external to the system operations support management repository 602 and / or the fault support apparatus 200. In this regard, the third party operations support data object in some embodiments enables access to other data objects stored by external data systems. Each third party operations support data object in some contexts is maintained by a different external system and / or is associated with a different provider entity that controls the data system that stores the data object retrieved via the third party operations support data object. For example, in some embodiments, two different third party operations support data objects are associated with the same provider entity but are accessible via different external systems associated with the same provider entity. Alternatively or additionally, in some embodiments, two different third party operations support data objects are associated with different provider entities and are accessible via different external systems. Further, additionally or alternatively, in some embodiments, system operations support management repository 602 stores operational support data objects that do not require access via external data systems (e.g., files, internal links, and / or other resources embodying content stored in system operations support management repository 602). In this regard, system operations support management repository 602 advantageously provides a centralized mechanism for enabling access to operational support data objects, regardless of whether data corresponding to such operational support data objects is stored locally or maintained externally.

[0110] As illustrated, each of the operational support data objects 604 embodies data links to data objects associated with resolving one or more faults. The various operational support data objects 604 are associated with various provider identifiers, specifically provider identifiers representing providers 1, 2, 3, and 4. In some embodiments, each of the providers maintains any number of systems for storing and / or otherwise making accessible data associated with one or more operational support data objects. In some embodiments, one or more of the provider identifiers correspond to an entity that controls the system operational support management repository 602 and / or the fault support apparatus 200. Alternatively or additionally, in some embodiments, each of the provider identifiers corresponds to a third party entity that controls one or more data systems external to the system operational support management repository 602 and / or the fault support apparatus 200. As shown, operational support data object 604A and operational support data object 604B are each associated with provider 1, operational support data object 604C is associated with provider 2, operational support data object 604D is associated with provider 3, and operational support data object 604E is associated with provider 4. In some embodiments, third party resources may be identified via a recommendation engine. In some embodiments, third party resources may be identified by generating structured data from a previous technical support use case that indicates links in a database that a particular resource may solve the identified technical support use case.

[0111] Operations support data object 604A embodies a first third party operations support data object associated with web content hosted by Provider 1. For example, the third party operations support data object embodies a web page 606A hosted by an external system controlled by Provider 1. The web page includes a variety of content, including textual content associated with connecting a printer to a home network. In this regard, in some contexts, the third party operations support data object stored in system operations support management repository 602 embodies a URL utilized to retrieve the web page from the external system that hosts the web page.

[0112] The operational support data object 604E embodies a second third-party operational support data object associated with the web content hosted by Provider 4. For example, the third-party operational support data object embodies a web page 606B hosted by an external system controlled by Provider 4. The web page includes various content, including textual content associated with determining why a computing device's battery may consistently appear to be depleted. In this regard, it should be appreciated that in some embodiments, the third-party operational support data object stored in the operational support management repository 602 embodies a URL utilized to retrieve the web page from the external system hosting the web page. In a situation where the identified fault classification identifier represents a fault in the printer system, the operational support data object 604A may be output and utilized to access the corresponding data (e.g., web page 606A). Similarly, in some embodiments, in a situation where the identified fault classification identifier represents a fault in the battery life system, the operational support data object 604E is output and utilized to access the corresponding data (e.g., web page 606B). For example, in some embodiments, a fault classification data model is trained to identify fault classification identifiers indicated by data associated with a particular set of devices, communication networks, and / or user profiles (e.g., device activity data, support activity data, fault text description data, etc.).

[0113] In some embodiments, operational support data objects are linked or otherwise associated and stored with particular device identification data. For example, operational support data objects in some embodiments are linked to device identification data to indicate that the operational support data object assists in resolving faults associated with that particular network-connected device, type of network-connected device, etc. In some embodiments, such links between operational support data objects and particular device identification data are generated manually (e.g., in response to user input upon determining that the operational support data object is associated with such particular device identification data) and / or automatically (e.g., in response to text, voice, and / or other algorithmic processing of the operational support data object that determines the particular device identification data to which the operational support data object should be linked). It will be appreciated that operational support data objects may be linked with any number of pieces of device identification data. In some embodiments, the models described herein learn to predict which network-connected devices are likely to experience one or more malfunctions and / or provide predicted operational support data objects determined to be most likely to be useful in resolving such malfunctions based on, for example, the device identification data of the network-connected devices and / or other data associated with the device identification data, such as device activity data and / or support activity data.

[0114] FIG. 7 illustrates an example data representation of an operational support data object associated with a fault classification identifier, according to at least some embodiments of the present disclosure. In some embodiments, the association between the fault classification identifier and the operational support data object is maintained by the fault support device 200. For example, in some embodiments, the association between the fault classification identifier and the operational support data object is stored in a system operational support management repository. For example, in some contexts, each operational support data object is embodied by one or more data records stored in the system operational support management repository that include the fault classification identifier with which the operational support data object is associated. Alternatively or additionally, in some embodiments, the association between the operational support data object and the fault classification identifier is maintained by the fault support device 200 and / or stored in one or more other repositories accessible to the fault support device 200.

[0115] 7 illustrates an association between operational support data objects 604 and various fault classification identifiers 702A, 702B, 702C, and 702D. Fault classification identifier 702A represents a classification of a system event that embodies a fault in connecting a new device to a communications network (e.g., a home network). Fault classification identifier 702B represents a classification of a system event that embodies a fault in the operation of a printer having a make of printer brand A. Fault classification identifier 702C represents a classification of a system event that embodies a fault in the printer generally.

[0116] The fault classification identifier 702D represents a classification system event that embodies a fault that results in a reduction in device battery life. It should be understood that in some embodiments, the first fault classification identifier represents a more detailed and / or refined classification of the fault represented by the second fault classification identifier. For example, a "printer problem" may encompass all the various faults for various types, makes, and / or models of printers, a "Brand A Printer Problem" may encompass a subset of such faults that are specific to printers having a brand of printer brand A, and similarly, a fault classification identifier for a "Brand A Model 1 Printer Problem" may encompass a subset of faults of the fault classification identifier "Brand A Printer Problem", specifically, faults associated with model 1 of the Brand A printer. Thus, the exemplary contextual fault classification identifiers are generated to represent any level of specificity and / or detail with respect to device characteristics, data characteristics, and the like. The fault classification identifier 702D represents a classification system event that embodies a fault that results in a reduction in device battery life.

[0117] In some embodiments, each association between an operational support data object and a fault classification identifier indicates that the operational support data object assists in resolving one or more faults represented by the fault classification identifier. For example, as shown, operational support data object 604A is associated with fault classification identifiers 702A, 702B, and 702C. In this regard, the association with fault classification identifier 702A indicates that operational support data object 604A may be useful or otherwise assist in resolving faults involving the connection of a new network-connected device, the association with fault classification identifier 702B indicates that operational support data object 604A may be useful or otherwise assist in resolving faults involving printers having a brand of brand A, and the association with fault classification 702C indicates that operational support data object 604A may assist in resolving faults involving printers in general. Alternatively, operational support data object 604B is associated with fault classification identifier 702B and fault classification identifier 702C, indicating that operational support data object 604B may be useful or assist in resolving faults involving printers having a brand A make and / or involving printers in general but not involving the connection of a new network-connected device (e.g., no association is established with fault classification identifier 702A).

[0118] Furthermore, operational support data objects 604C and 604D are each associated only with fault classification identifier 702C. In some contexts, such an association indicates that each of operational support data objects 604C and 604D may assist in resolving faults involving printers in general, but not specific to printers having a brand name of Brand A, and / or in resolving faults involving the attachment of a new device. For example, operational support data object 604C may be associated with or otherwise include text data, software applications, video content data, image content data, etc., that assist in resolving faults associated with a printer cartridge for an inkjet printer. Similarly, operational support data object 604D may be associated with or otherwise include text data, software applications, video content data, image content data, etc., that assist in resolving faults associated with the operation of a printhead for a thermal printer.

[0119] Finally, the operational support data object 604E is associated only with the fault classification identifier 702D. Such an association indicates that the operational support data object 604E may assist in resolving faults involving reduced battery life of a network-connected device. In this regard, the operational support data object 604E may not assist in resolving any faults represented by one or more of the other fault classification identifiers 702A, 702B, and / or 702C. For example, the operational support data object 604E may be associated with or otherwise include text data, software applications, video content data, image content data, etc. that assist in resolving faults associated with degraded and / or otherwise reduced battery life (e.g., diagnosing hardware thermal fatigue issues, software applications that drain significant battery life, etc.).

[0120] Some embodiments of the present disclosure generate such associations between operational support data objects and one or more defect classification identifiers, manually and / or automatically, based at least in part on processing of the operational support data objects and / or defect classification identifiers. For example, in some embodiments, a database administrator of a repository in which such associations are stored (e.g., a database administrator of a systems operational support management repository) generates and / or stores such associations based on the content of the operational support data objects. Alternatively or additionally, in some embodiments, the defect support apparatus 200 processes content, metadata, and / or any other data associated with the operational support data objects to generate associations between the operational support data objects and one or more defect classification identifiers. For example, in some embodiments, the defect support apparatus 200 utilizes natural language processing to determine which defects are discussed in the content data of a particular operational support data object. In some such embodiments, the defect support apparatus 200 associates the operational support data objects with defect classification identifiers that represent defects identified in such content data.

[0121] It will be appreciated that in some embodiments, an operational support data object is linked with various data identifiers that indicate different aspects of the operational support data object. For example, in some embodiments, an operational support data object is linked with a particular fault identifier that represents a fault that the operational support data object may assist in resolving, device identification data that indicates a particular network-connected device, a type of network-connected device, a category of network-connected devices, and / or other group of network-connected devices that may encounter or are likely to encounter a fault that the operational support data object may assist in resolving, and the like. In some such embodiments, an operational support data object is stored in conjunction with a composite identifier that includes one or more subparts that indicate a particular individual identifier and / or a set of identifiers with which the operational support data object is associated. For example, in some embodiments, operational support data object 604B is associated with one or more identifiers and / or composite identifiers that include an identifier of device identification data that uniquely identifies a printer brand A printer and a fault identifier that indicates a printer problem (or a particular type of printer problem).

[0122] 8 illustrates an example visualization of predicted operational resource selection utilizing a fault classification data model, according to at least some embodiments of the present disclosure. Specifically, FIG. 8 illustrates an example operational support process data model 808 that selects and / or outputs at least predicted operational support data objects 810 based on one or more input portions of input data. In this regard, the fault support apparatus 200 in some embodiments maintains the operational support process data model 808 to select the predicted operational support data objects 810. The fault classification data model 808 may be pre-trained based on the particular type of input data utilized to select the operational support data objects.

[0123] The fault classification data model 808 in some contexts is embodied in any of a number of manners. For example, in some embodiments, the fault classification data model 808 is embodied by one or more specially configured and / or trained algorithmic models, statistical models, and / or machine learning models, or combinations thereof. The fault classification data model 808 is configurable and / or trainable using supervised and / or unsupervised learning. For example, in some embodiments, the fault classification data model 808 is embodied by one or more regression models, random forest models, KNN models, etc. In some embodiments, the fault classification data model 808 is embodied by one or more k-means models, clustering models, etc. In some embodiments, the fault classification data model 808 embodies artificial intelligence specially configured to select predicted operational support data objects 810 based at least in part on input data.

[0124] In some embodiments, as illustrated, the fault classification data model 808 takes as input at least a device identification dataset 802. The device identification dataset 802 in some embodiments includes device identification data of one or more network-connected devices that are connected to a particular communication network, that have been previously connected to a particular communication network, and / or that embody at least a portion of a particular communication network, such as a dynamic home communication network. In this regard, in some contexts, the device identification dataset 802 represents any number of network-connected devices that may experience one or more faults at a given time. Additionally or alternatively, in some contexts, the device identification dataset 802 represents any number of network-connected devices that contribute, singly or in combination, to one or more faults. The device identification data for each network-connected device in some embodiments is identified through direct communication with the network-connected device, retrieved from a data repository that stores device identification data associated with the particular communication network, and / or retrieved from another network-connected device of the communication network that maintains device identification data associated with some or all of the network-connected devices on the communication network.

[0125] In some embodiments, as illustrated, the fault classification data model 808 takes as input at least the device identification dataset 804. In some embodiments, the device activity data 804 includes various data received, requested, and / or otherwise detected for one or more network-connected devices, communication networks, and / or requesting client devices that are processed to provide predicted operational data objects associated with the identified faults. For example, in some embodiments, the device activity data 804 includes various portions of device activity data each associated with a network-connected device (or combination of network-connected devices) identified in the device identification dataset 802.

[0126] In some embodiments, device activity data 804 includes, without limitation, current values ​​of one or more configuration characteristics of a network-connected device. Alternatively or additionally, in some embodiments, device activity data 804 includes past data values ​​of configuration characteristics of such network-connected devices. Further, alternatively or additionally, in some embodiments, device activity data 804 includes indications of changes from past data values ​​of particular configuration characteristics of such network-connected devices. Alternatively or additionally, in some embodiments, device activity data 804 includes indications of connections between a particular network-connected device and one or more other network-connected devices, communication networks, etc. In this regard, device activity data 804 may include any data related to identifying a particular computing device, data characteristics of such computing devices, connectivity of such computing devices, etc.

[0127] In some embodiments, the device activity data 804 is received from the fault support apparatus 200 for processing. In some embodiments, the device activity data 804 is received from a requesting client device that collects a portion of the device activity data from each network-connected device capable of communicating with the requesting client device over one or more communication networks at any number of time intervals. Alternatively or additionally, in some embodiments, the fault support apparatus 200 requests the device activity data directly from the requesting client device and / or one or more network-connected devices. The fault support apparatus 200 in some embodiments requests the device activity data 804 upon initiation of a fault support session, at regular time intervals, upon receipt of other input data (e.g., fault text description data), etc. Furthermore, alternatively or additionally, in some embodiments, the fault support apparatus 200 detects the device activity data, for example, by interrogating network-connected devices on the communication network and / or by processing communications transmitted over the communication network. For example, in some embodiments, the fault support device 200 processes transmission messages, networking packets, and / or other data communicated over a particular communications network to determine the device activity data 804 from the metadata and / or data therein.

[0128] Optionally, in some embodiments, the fault classification data model 808 additionally or alternatively takes as input at least support activity data. In some embodiments, the support activity data includes various data associated with actions performed by a user to attempt to diagnose and / or resolve one or more faults. Such support activity data may include, but is not limited to, support search data performed via one or more network-connected devices, fault text description data, previously accessed operational support data objects, and / or external query data. In this regard, in some exemplary contexts, the support activity data includes various data related to specific support-related actions performed by a user to attempt to diagnose and / or resolve one or more faults.

[0129] In some embodiments, the support activity data is received by the defect support apparatus 200 for processing. For example, in some embodiments, the support activity data is received from a requesting client device in response to a request by the defect support apparatus 200. In some embodiments, the defect support apparatus 200 requests the support activity data at specific time intervals and / or when a specific event is determined to have occurred. For example, in some embodiments, the defect support apparatus 200 requests the support activity data from the requesting client device and / or associated network-connected device in response to receiving data requesting and / or triggering the initiation of a defect support session. Alternatively or additionally, in some embodiments, the defect support apparatus 200 receives and stores some or all of the support activity data as the requesting client device interacts with the defect support apparatus 200. For example, in some such embodiments, the defect support apparatus 200 receives and stores the support activity data, including defect text description data entered via the requesting client device and / or associated network-connected device during a main support process, such as a defect support session. Alternatively or additionally, in some embodiments, for example, the problem support apparatus 200 receives and stores support search data by a requesting client device indicative of a user request to initiate a problem support session.

[0130] Additionally or alternatively, optionally, in some embodiments, the fault classification data model 808 takes as input at least the operational support data object set 806. In some embodiments, the operational support data object set 806 embodies or is included in a device operational support management repository. The operational support data object set 806 in some contexts embodies a set including any number of operational support data objects available for selection by the fault classification data model 808. In some embodiments, the fault support apparatus 200 retrieves the operational support data object set 806 from a system operational support management repository. The operational support data object set 806 in some embodiments includes all available operational support data objects, and in some embodiments includes a particular subset of the available operational support data objects. For example, in some embodiments, a fault classification identifier is identified for processing by the operational support processing data model 808, and the operational support data object set 806 includes a subset of the available operational support data objects associated with the identified fault classification identifier.

[0131] In some embodiments, the fault classification data model 808 outputs predicted operational support data objects 810 based at least in part on the input data. The predicted operational support data objects 810 in some contexts embody operational support data objects that are determined to be sufficiently likely to assist in resolving the fault associated with the identified fault classification identifier. In this regard, the predicted operational support data objects 810 in some embodiments are each output to enable access to the operational support data object and / or content in the operational support data object for use in attempting to resolve the fault (e.g., automatically or via a user-initiated action based at least in part on one or more of the predicted operational support data objects 810).

[0132] In some embodiments, the fault classification data model 808 generates a confidence score for one or more operational support data objects (e.g., each operational support data object in the operational support data object set 806). The confidence score for each operational support data object in some embodiments represents a likelihood that the operational support data object is associated with attempting to resolve a particular identified fault classification identifier. For example, in some embodiments, the fault classification data model 808 processes some or all of the input data (e.g., the device activity data set 802 and / or the support activity data 804) to identify fault classification identifiers that represent one or more faults affecting network-connected devices that can communicate with and / or are otherwise associated with a particular requesting client device. Alternatively or additionally, in some embodiments, the fault classification data model 808 receives the identified fault classification identifiers as input. Thus, the generated confidence score for each operational support data object embodies a likelihood and / or a confidence that the fault support apparatus 200 has that the operational support data object will assist in resolving the fault associated with the identified fault classification identifier.

[0133] In some embodiments, the fault classification data model 808 selects predicted operational support data objects 810 based on a confidence score for each operational support data object. For example, in some embodiments, the fault classification data model 808 is configured to select and output a determinable number of predicted operational support data objects 810 associated with the highest confidence scores. For example, in some embodiments, other determinable numbers of operational support data objects having the top 1, top 3, top 10%, and / or highest confidence scores are selected and / or output. Alternatively or additionally, in some embodiments, the fault classification data model 808 selects and / or outputs predicted operational support data objects 810 that embody all operational support data objects that meet a certain minimum score threshold. In some such embodiments, any number of predicted operational support data objects are identifiable based on the scores (e.g., confidence scores) generated by the fault classification data model 808.

[0134] The predicted operational support data objects in some embodiments are utilized in any of a number of manners. In some embodiments, the fault support apparatus 200 outputs the predicted operational support data objects 810 to a requesting client device. The requesting client device in some such embodiments renders the predicted operational support data objects 810 via a support user interface. In some such embodiments, a user of the requesting client device may analyze the predicted operational support data objects 810 rendered by the requesting client device and determine whether to interact with any of the predicted operational support data objects. In the event of interacting with one or more of the predicted operational support data objects 810, the main support process (e.g., the fault support session) is interrupted and / or terminated. Alternatively or additionally, in some embodiments, a user input is received indicating one or more accessed data objects of the predicted operational support data objects 810 that assist in resolving one or more faults, and the fault support apparatus 200 terminates the main support process in response to receiving such an indication.

[0135] In some embodiments, the fault classification data model 808 outputs a fault classification identifier 812. The fault classification identifier 812 represents one or more faults associated with the requesting client device, the network-connected devices capable of communicating with the requesting client device, and / or the communication network. In some embodiments, the fault classification data model 808 is configured to select a fault classification identifier from one or more portions of the input data. For example, in some embodiments, the fault classification data model 808 is configured to select a fault classification identifier 812 based at least in part on the device identification data set 802 and / or the device activity data 804. In one such exemplary context, the fault support apparatus 200 determines a fault indicated as affecting one or more network-connected devices based on the device activity data 804 (e.g., from fault text description data embodied in the device activity data 804) and identifies a network-connected device corresponding to such fault based at least in part on the device activity data 804. In this regard, in some embodiments, the fault classification data model 808 scores each possible fault classification identifier and selects and outputs the fault classification identifier 812 associated with the highest score. The fault classification identifier 812 in some contexts is referred to as being associated with one or more network-connected devices, a portion of device identification data, or the like.

[0136] In some embodiments, the fault classification data model identifies any number of fault classification identifiers that, for example, meet a particular threshold or programmatically generate a score that indicates a predetermined likelihood that a device is affected by a particular problem. In some embodiments, the fault classification data model 808 utilizes device activity data to determine a first set of fault classification identifiers and identifies a particular fault classification identifier (e.g., fault classification identifier 812) or a subset of the first set of fault classification identifiers that correspond to the most likely faults based at least in part on the support activity data (e.g., the highest scoring faults or a hierarchical list of faults based on scoring a list of potential problems). In this regard, the support activity data in some embodiments is utilized to narrow down the particular set of fault classification identifiers to a subset of fault classification identifiers determined to be most likely to affect one or more devices, systems, networks, etc.

[0137] It should be appreciated that in other embodiments, the fault classification data model 808 includes one or more sub-models. For example, in some embodiments, the fault classification data model 808 includes a first sub-model that is specifically configured and / or trained to select predicted operational support data objects 810 and a second sub-model that is specifically configured and / or trained to select fault classification identifiers 812. Alternatively or additionally, in some embodiments, a second model, separate from the fault classification data model 808, is specifically configured and / or trained to select fault classification identifiers 812. In this regard, it should be appreciated that in some embodiments, the fault classification data model 808 includes multiple specifically trained sub-models or modules, each trained for a specific task.

[0138] In some embodiments, the fault classification identifier 812 (and / or a set of fault classification identifiers having any number of fault classification identifiers) is utilized to select one or more operational support data objects as described herein. Alternatively or additionally, in some embodiments, the fault classification identifier 812 (and / or a set of fault classification identifiers) is output to a client device associated with a user. For example, in some embodiments, the fault classification identifier is utilized to render one or more user interface elements that enable a user to select a particular fault associated with one or more of his / her devices from a limited list of such faults, as determined by the selected fault classification identifier. Alternatively or additionally, in some embodiments, the fault classification identifier is utilized to render one or more user interface elements on a technician device (e.g., associated with a support technician to assist the user) that enables a support technician to select a particular fault that the support technician believes to be affecting the user's device(s) based on one or more portions of the received data associated with such fault. For example, in some embodiments, the support technician may have access to select a particular fault classification identifier determined to be likely to affect one or more devices from a curated subset of possible faults determined by the model based on device activity data and / or device support data.

[0139] Exemplary Processes of the Present Disclosure Having described the exemplary systems, apparatus, computing environments, interfaces, and data visualizations of the present disclosure, an exemplary process according to the present disclosure will now be described. It will be understood that each of the flowcharts illustrates an exemplary computer-implemented process that may be executed by one or more of the apparatus, systems, devices, and / or computer program products described herein, e.g., utilizing one or more of its specifically configured components.

[0140] The illustrated blocks indicate the operations of each process. Such operations may be performed in any of numerous ways, including, but not limited to, in the order and manner as shown and described herein. In some embodiments, one or more blocks of any of the processes described herein are performed between one or more blocks of another process, before one or more blocks of another process, in parallel with one or more blocks of another process, and / or as a sub-process of a second process. Additionally or alternatively, any of the processes in various embodiments include some or all of the operational steps described and / or shown, including one or more optional blocks in some embodiments. With respect to the flowcharts illustrated herein, one or more of the illustrated blocks are optional in some or all embodiments of the present disclosure. Optional blocks are indicated with dashed lines (or "dotted lines"). Similarly, it should be understood that one or more of the operations of each flowchart may be combined, interchanged, and / or otherwise modified as described herein.

[0141] FIG. 9 illustrates a flow chart showing an example operation of an example process for selecting and outputting predicted operational support data objects according to at least some example embodiments of the present disclosure. Specifically, FIG. 9 illustrates the operation of an example process 900. In some embodiments, the process 900 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 900 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in the fault support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, and / or otherwise accessible to the fault support apparatus 200, to perform the operations as shown and described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatuses, systems, devices, etc. to perform one or more of the operations as shown and described. For example, the fault support apparatus 200 communicates with client devices and / or external data systems. For purposes of simplicity of explanation, the process 900 is described as being performed by and from the perspective of the fault support apparatus 200.

[0142] The process 900 begins at operation 902. The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for identifying in real time a device identification dataset associated with a network connected device capable of communicating with a communication network, e.g., a dynamic home communication network. In some embodiments, the device identification dataset is retrieved from a data repository that stores device identification data associated with network connected devices of a particular communication network over a past period of time. Additionally or alternatively, in some embodiments, the fault support apparatus 200 interrogates the dynamic home communication network and / or one or more individual network connected devices of the dynamic home communication network to identify a device identification dataset including device identification data of each network connected device of the communication network. In some embodiments, a single network connected device (e.g., a network access point) of the dynamic home communication network maintains a device identification dataset including device identification data of each network connected device on the communication network, and the fault support apparatus 200 requests or otherwise interrogates the single network connected device to identify the device identification dataset. In yet some other embodiments, the fault support device 200 is embodied as part of a dynamic home communications network, such that the fault support device 200 can identify a device identification dataset in real time, by direct communication with each network-connected device of the dynamic home communications network and / or by collecting and storing device identification data of network-connected devices that connect to the communications network over a period of time.

[0143] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for retrieving a device activity data set associated with the set of network-connected devices at operation 904. In some embodiments, the device activity data set is retrieved from one or more network-connected devices associated with the communication network being processed, such as a dynamic home communication network. For example, in some embodiments, the fault support apparatus 200 retrieves device activity data associated with each network-connected device of the set of network-connected devices from each individual network-connected device to which the device activity data corresponds. Alternatively or additionally, in some embodiments, the fault support apparatus 200 retrieves the device activity data set from a particular network-connected device that detects, aggregates, and / or otherwise maintains device activity data corresponding to each of a plurality of network-connected devices. For example, in some embodiments, a client device associated with the dynamic home communication network executes a specially configured software application that causes the collection and / or storage of device activity data for any number of network-connected devices on the particular communication network. The fault support apparatus 200 in some embodiments then retrieves the device activity data set via communication with the client device that maintains such information. In some embodiments, the fault support apparatus 200 stores the received device activity data associated with one or more network-connected devices in one or more repositories, such as a device operations support management repository maintained by or otherwise accessible to the fault support apparatus 200. Alternatively or additionally, in some embodiments, the fault support apparatus 200 retrieves device activity data sets from a device operations support management repository for mode training and / or use.

[0144] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for applying the fault classification data model to the device activity data set to select a predicted operational support management repository at operation 906. In some such embodiments, the fault classification data model is trained based on training data from the dynamic home communication network. In some embodiments, the training data includes previously collected device activity data specifically associated with the dynamic home communication network. In this regard, such data in some embodiments exhibits data patterns specific to the particular dynamic home communication network. Additionally or alternatively, in some embodiments, the fault classification data model is trained at least in part based on external aggregated device activity data from one or more external dynamic home communication networks. The external aggregated device activity data in some embodiments includes device activity data of any number of network-connected devices of other external dynamic home communication networks. Additionally or alternatively, in some embodiments, the fault classification data model is trained at least in part based on faulty device history data from the device operational support management repository. The faulty device history data in some embodiments indicates a particular fault classification identifier for a fault affecting a network-connected device of such a dynamic home communications network. In some embodiments, one or more of such data sets include timestamp data and / or other identifiers that, in some contexts, can be used to link corresponding data in each of the data sets.

[0145] In some embodiments, the fault classification data model is configured or includes one or more sub-models configured to perform one or more sub-decisions as part of selecting a predicted operational support data object. For example, in some embodiments, the fault classification data model (or a sub-model of the fault classification data model) is configured to identify fault classification identifiers of faults that are likely to have and / or are likely to affect the network-connected device represented in the received device identification data set. Additionally or alternatively, in some embodiments, the fault classification data model (or a sub-model on the fault classification data model) is configured to identify which operational support data object of a set of possible operational support data objects is most likely to assist in resolving a particular fault that has been and / or is likely to be encountered. The fault classification data model and / or various sub-models of the fault classification data model are trained in some embodiments to perform various sub-decisions associated therewith based on data patterns represented in such portions of the training data, at least in part based on the training data described, external aggregated device activity data, and / or faulty device history data.

[0146] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for outputting the predicted operational support data object to the requesting client device in real time at operation 908. In some embodiments, the fault support apparatus 200 transmits the predicted operational support data object to one or more requesting client devices upon request of the predicted operational data object received from the requesting client device via one or more data transmissions. Alternatively or additionally, in some embodiments, the predicted operational support data object is output to a client device associated with the processed dynamic home communication network. The fault support apparatus 200 in some embodiments transmits the predicted operational support data object to cause the requesting client device to render in real time a support user interface including at least an interface element associated with the predicted operational support data object. In this regard, in some embodiments, the predicted operational support data object is rendered sufficiently fast via the client device to allow the predicted operational support data object to be accessed during the initiation of a particular software application associated with the functionality of the fault support apparatus 200. Alternatively or additionally, in some embodiments, the fault support apparatus 200 transmits one or more messages to a client device for processing and / or display by a third party application, such as an email communication, a push notification, etc.

[0147] FIG. 10 illustrates a flow chart showing an example operation of an example process for determining fault classification data based at least in part on specific device identification data, according to at least some example embodiments of the present disclosure. Specifically, FIG. 10 illustrates the operation of an example process 1000. In some embodiments, the process 1000 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 1000 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in and / or otherwise accessible to the fault support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, to perform the operations as shown and described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatus, systems, devices, etc. to perform one or more of the operations as shown and described. For purposes of simplicity of explanation, the process 1000 is described as being performed by and from the perspective of the fault support apparatus 200.

[0148] Process 1000 begins at operation 1002. In some embodiments, process 1000 begins after one or more operations shown and / or described with respect to any of the other processes described herein. For example, in some embodiments as described, process 1000 begins after execution of operation 904. In this regard, some or all of process 1000 may replace or complement one or more blocks shown and / or described with respect to any of the other processes described herein. Upon completion of process 1000, the flow of operations may end. Additionally or alternatively, as shown, upon completion of process 1000, the flow may return to one or more operations of another process, such as operation 906. It should be understood that in some embodiments, process 1000 embodies a sub-process of one or more other processes, such as process 900.

[0149] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for identifying a first device identification data from a device identification set at operation 1002. In some embodiments, the first device identification data is associated with a first device of the set of network-connected devices. In some embodiments, for example, the fault support apparatus 200 iterates through each device identification data of the device identification data set and processes each portion of the device identification data individually and / or in combination with one or more other portions of the device identification data to determine a fault classification identifier associated with the corresponding network-connected device.

[0150] The defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for determining defect classification data representing any number of defect classification identifiers corresponding to the first device identification data and the device activity data set in operation 1004. In some embodiments, the defect support apparatus 200 utilizes a specially trained data model to determine the defect identifier associated with the particular first device identification data and / or the device activity data set. For example, in some embodiments, the defect support apparatus 200 utilizes a specially trained defect classification data model and / or a sub-model of the defect classification data model to determine the defect classification identifier. In some embodiments, the one or more defect classification identifiers can be determined based at least in part on the device activity data of the device activity data set corresponding to the particular first device identification data. In this regard, in some such contexts, such portion of the device activity dataset corresponding to the first device identification data is specifically processed to determine that data values ​​in this portion are indicative of the likelihood of an existing or future fault affecting or caused by the network-connected device identified by the first device identification data. In one exemplary context, for example, the fault support apparatus 200 determines a fault classification identifier indicating that the network-connected device identified by the first device identification data is not configured to operate based on one or more data values ​​corresponding to a particular configuration characteristic indicated in the device activity dataset.

[0151] FIG. 11 illustrates a flow chart showing an example operation of an example process for determining fault classification data based at least in part on a plurality of device identification data, according to at least some example embodiments of the present disclosure. Specifically, FIG. 11 illustrates the operation of an example process 1100. In some embodiments, the process 1100 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 1100 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in and / or otherwise accessible to the fault support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, to perform the operations as shown and described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatus, systems, devices, etc. to perform one or more of the operations as shown and described. For purposes of simplicity of explanation, the process 1100 is described as being performed by and from the perspective of the fault support apparatus 200.

[0152] Process 1100 begins at operation 1102. In some embodiments, process 1100 begins after one or more operations shown and / or described with respect to any of the other processes described herein. For example, in some embodiments as described, process 1100 begins after execution of operation 904. In this regard, some or all of process 1100 may replace or complement one or more blocks shown and / or described with respect to any of the other processes described herein. Upon completion of process 1100, the flow of operations may end. Additionally or alternatively, as shown, upon completion of process 1100, the flow may return to one or more operations of another process, such as operation 906 as illustrated. It should be understood that in some embodiments, process 1100 embodies a sub-process of one or more other processes, such as process 900.

[0153] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for identifying a plurality of device identification data from a device identification dataset at operation 1102. The plurality of device identification data in some embodiments is associated with a plurality of network-connected devices of the set of network-connected devices. In this regard, in some embodiments, the plurality of identification data embodies a subset of device identification data corresponding to a particular subset of network-connected devices in the set of network-connected devices. In some embodiments, the plurality of device identification data is associated with a plurality of distinct network-connected devices. For example, in some embodiments, the fault support apparatus 200 identifies a particular configuration and / or presence of a plurality of device identification data representing a particular group of network-connected devices. In this regard, the fault support apparatus 200 processes the device identification dataset to determine whether such a particular combination of network-connected devices is represented in the device identification dataset. Alternatively or additionally, in some embodiments, the fault support apparatus 200 utilizes one or more trained models, such as a fault classification data model, to identify a particular plurality of device identification data corresponding to a particular combination of network-connected devices (e.g., a combination of network-connected devices determined to contribute to and / or otherwise cause a fault represented by a particular fault classification identifier).

[0154] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for determining a fault classification identifier corresponding to the plurality of device identification data and the device activity data set at operation 1104. In some embodiments, the fault support apparatus 200 utilizes a specially trained data model to determine the fault identifier associated with the plurality of device identification data and the device activity data set. For example, in some embodiments, the fault support apparatus 200 utilizes a specially trained fault classification data model and / or a sub-model of the fault classification data model to determine the fault classification identifier. One or more fault classification identifiers in some contexts can be determined based at least in part on device activity data of the device activity data set corresponding to a particular network-connected device identified by the plurality of device identification data. In this regard, such a portion of the device activity data set corresponding to the plurality of device identification data in some embodiments is specifically processed to determine that data values ​​in this portion are indicative of a likelihood of an existing or future fault affecting the network-connected device or caused by the network-connected device identified by the first device identification data. In one exemplary context, for example, the fault support apparatus 200 determines a fault classification identifier indicative of a plurality of network-connected devices identified by a plurality of device identification data, and contributes to a reduction in communications network operation (e.g., a reduction in bandwidth allocation to one or more network-connected devices, and / or to network-connected devices connected to the dynamic home communications network generally) based at least in part on one or more data values ​​corresponding to particular configuration characteristics indicated in a device activity dataset corresponding to the plurality of device identification data.

[0155] FIG. 12 illustrates a flow chart showing an example operation of an example process for determining fault classification data based on a set of device types, according to at least some example embodiments of the present disclosure. Specifically, FIG. 12 illustrates the operation of an example process 1200. In some embodiments, the process 1200 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 1200 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in the fault support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, and / or otherwise accessible to the fault support apparatus 200, to perform the operations as shown and described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatus, systems, devices, etc. to perform one or more of the operations as shown and described. For purposes of simplicity of explanation, the process 1100 is described as being performed by and from the perspective of the fault support apparatus 200.

[0156] Process 1200 begins at operation 1202. In some embodiments, process 1200 begins after one or more operations shown and / or described with respect to any of the other processes described herein. For example, in some embodiments as described, process 1200 begins after execution of operation 904. In this regard, some or all of process 1200 may replace or complement one or more blocks shown and / or described with respect to any of the other processes described herein. Upon completion of process 1200, the flow of operations may end. Additionally or alternatively, as shown, upon completion of process 1200, the flow may return to one or more operations of another process, such as operation 906 as illustrated. It should be understood that in some embodiments, process 1200 embodies a sub-process of one or more other processes, such as process 900.

[0157] The defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for identifying a first defect classification identifier associated with a set of device types at operation 1202. The set of device types in some embodiments contributes to or otherwise causes the defect represented by the first defect classification identifier. In some embodiments, the defect support apparatus 200 identifies that a particular defect is associated with the set of device types based on a particular set of rules indicating the device types that contribute to or cause each defect associated with the defect classification identifier. Alternatively or additionally, in some embodiments, the defect support apparatus 200 identifies that a particular defect is associated with the set of device types utilizing a particular trained data model. For example, in some embodiments, the defect support apparatus 200 identifies that a first defect classification identifier is associated with the set of device types utilizing a defect classification data model trained to identify such correlations based on data patterns, trends, and / or other correlations extracted and / or learned from particular input training data, as described herein.

[0158] The defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for storing a first defect classification identifier representing a first defect classification associated with a set of device types at operation 1204. In some embodiments, the defect support apparatus 200 maintains a device operational support management repository that stores certain data (e.g., defective device history data) indicative of an association between the first defect classification identifier and the set of device types. In this regard, in some embodiments, the defect support apparatus 200 then determines a likelihood that a defect corresponding to the first defect classification identifier exists based at least in part on the existence of the set of device types and / or a particular configuration of the set.

[0159] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for identifying a device type of each of the one or more network-connected devices of the set of network-connected devices based at least in part on the device identification set at operation 1206. For example, in some embodiments, the device type of each network-connected device is received as part of device activity data and / or device identification data associated with the network-connected device. Alternatively or additionally, in some embodiments, the fault support apparatus 200 identifies the device type based on the device identification data of a particular network-connected device. For example, in some embodiments, the fault support apparatus 200 maintains and / or otherwise accesses a data repository linking device identifiers included in the device identification data with particular device types.

[0160] The fault support apparatus 200 includes means, such as the support providing circuit 210, the communication circuit 208, the input / output circuit 206, the processor 202, etc., or a combination thereof, for determining, at operation 1208, that the device type of each of one or more network-connected devices of the set of network-connected devices representing a communication network, such as a dynamic home communication network, is represented in a set of device types associated with a first fault classification identifier. In this regard, the fault support apparatus 200 in some embodiments compares the device types of the network-connected devices of the set of network-connected devices with the set of device types associated with each first fault classification identifier. In a situation where the fault support apparatus 200 determines that the device type of a particular communication network is represented in the set of device types associated with a particular fault classification identifier, the fault support apparatus 200 in some embodiments determines that the fault represented by the fault classification identifier is likely to affect or has affected the communication network accordingly.

[0161] FIG. 13 illustrates a flow chart showing an example operation of an example process for storing fault classification data associated with one or more faults according to at least some example embodiments of the present disclosure. Specifically, FIG. 13 illustrates the operation of an example process 1300. In some embodiments, the process 1300 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 1300 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in the fault support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, and / or otherwise accessible to the fault support apparatus 200, to perform the operations as shown and described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatus, systems, devices, etc. to perform one or more of the operations as shown and described. For purposes of simplicity of explanation, the process 1100 is described as being performed by and from the perspective of the fault support apparatus 200.

[0162] Process 1300 begins at operation 1302. In some embodiments, process 1300 begins after one or more operations shown and / or described with respect to any of the other processes described herein. In this regard, in some embodiments, some or all of process 1300 replaces or complements one or more blocks shown and / or described with respect to any of the other processes described herein. Upon completion of process 1300, the flow of operations may end. Additionally or alternatively, upon completion of process 1300, as shown, the flow may return to one or more operations of another process, such as operation 902 as illustrated. It should be understood that in some embodiments, process 1300 embodies a sub-process of one or more other processes, such as process 900.

[0163] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for identifying historical device activity data at operation 1302. In some embodiments, the historical device activity data is retrieved from one or more data repositories, such as a device operational support management repository maintained by the fault support apparatus 200. The historical device activity data in some embodiments is received and / or stored over a period of time and is received by the fault support apparatus 200, for example, at predefined time intervals, upon submission by a user (e.g., in response to a particular user input), upon occurrence of a particular trigger (e.g., initiation of an authenticated session between the fault support apparatus 200 and a client device), etc. Alternatively or additionally, in some embodiments, the fault support apparatus 200 identifies the historical device activity data from one or more third-party data repositories.

[0164] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for determining that the historical device activity data indicates a first fault at operation 1304. The historical device activity data may be processed to determine a particular portion of the historical device activity data (e.g., a particular data value of a particular configuration characteristic) that contributes to or otherwise causes a fault in one or more network-connected devices and / or in a network of devices. In some embodiments, the fault support apparatus 200 identifies that a particular fault is associated with a particular portion of the historical device activity data based on a particular rule set that indicates an associated portion of the historical device activity data that causes or otherwise contributes to a fault classification identifier. Alternatively or additionally, in some embodiments, the fault support apparatus 200 utilizes a data model, such as a trained fault classification data model, to determine that a first fault classification identifier is associated with a particular portion of the historical device activity data and identifies such correlations based on data patterns, trends, and / or other correlations extracted from the historical device activity data and / or particular input training data, as described herein. In one exemplary context, the fault support apparatus 200 indicates a fault based on changes in performance, operation, and / or functionality of one or more network-connected devices based on data indicative of operational performance of such network-connected devices (e.g., represented in or associated with the historical device activity data).

[0165] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for storing a first fault classification identifier associated with the historical device activity data in operation 1306. The fault classification identifier in some embodiments is generated to represent the newly determined fault. In this regard, in some embodiments, the fault support apparatus 200 associates the historical device activity data together with the fault classification identifier to indicate that the historical device activity data contributes to or otherwise causes the first fault. In some embodiments, the stored association is represented by a hyperparameter of the trained data model. Alternatively or additionally, in some embodiments, the first fault classification identifier is stored in association with the historical device activity data as faulty device history data in the device operational support management repository. In this regard, in some embodiments, such data is retrieved for use in subsequent training of one or more data models, such as a fault classification data model trained to select predicted operational support data objects associated with a particular fault classification identifier.

[0166] conclusion Although an exemplary processing system has been described above, implementations of the subject matter and functional operations described herein may be implemented in other types of digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed herein and their structural equivalents, or in combinations of one or more of these.

[0167] In some embodiments, some of the above operations may be modified or further extended. Furthermore, in some embodiments, additional optional operations may be included. Modifications, extensions, or additions to the above operations may be performed in any order and in any combination.

[0168] Many modifications and other embodiments of the disclosure described herein will come to mind to one skilled in the art to which the disclosure pertains having the benefit of the teachings presented in the foregoing description and the associated drawings. Accordingly, it should be understood that the embodiments are not to be limited to the specific embodiments disclosed, and that modifications and other embodiments are intended to be included within the scope of the appended claims. Moreover, while the foregoing description and the associated drawings describe exemplary embodiments in the context of certain example combinations of elements and / or features, it should be understood that different combinations of elements and / or features may be provided by alternative embodiments without departing from the scope of the appended claims. In this regard, for example, it is contemplated that combinations of elements and / or features other than those expressly described above may be recited in the appended claims. Unless otherwise defined herein, terms are used in a generic and descriptive sense only and not for limiting purposes.

[0169] It will be appreciated that various exemplary embodiments are described herein that provide technical advantages and solve technical problems specific to the complex nature of dynamic home communication networks. In other embodiments and contexts, similar advantages may be provided to other types of communication networks (e.g., enterprise networks, etc.) without departing from the innovative architectures and operations described throughout. Thus, it will be appreciated that in some embodiments, communication networks other than dynamic home communication networks may similarly be monitored (e.g., by a fault support system) and / or otherwise interacted with to provide similar advantages with respect to such non-dynamic home communication networks, albeit with reduced complexity.

[0170] Embodiments of the subject matter and operations described herein may be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed herein and their structural equivalents, or a combination of one or more of them. Embodiments of the subject matter described herein may be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a computer storage medium for execution by or to control the operation of an information / data processing apparatus. Alternatively, or in addition, the program instructions may be encoded in an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information / data for transmission to a suitable receiver apparatus for execution by the information / data processing apparatus. The computer storage medium may be, or may be included in, a computer readable storage device, a computer readable storage substrate, a random or serial access memory array or device, or a combination of one or more of them. Furthermore, the computer storage medium is not a propagating signal, but the computer storage medium may be a source or destination of computer program instructions encoded in an artificially generated propagated signal. A computer storage medium may also be, or be contained in, one or more separate physical components or media (eg, multiple CDs, disks, or other storage devices).

[0171] The operations described herein may be implemented as operations performed by an information / data processing apparatus on information / data stored in one or more computer-readable storage devices or received from other sources.

[0172] The term "data processing apparatus" encompasses any kind of apparatus, device, and machine for processing data, including, by way of example, a programmable processor, a computer, a system on a chip, or a plurality or combination of the foregoing. The apparatus may include special purpose logic circuitry, such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC). In addition to hardware, the apparatus may also include code that creates an execution environment for the computer program in question, such as code that constructs a processor firmware, a protocol stack, a repository management system, an operating system, a cross-platform runtime environment, a virtual machine, or one or more combinations of these. The apparatus and execution environment may implement a variety of different computing model infrastructures, such as web services, distributed computing, and grid computing infrastructures.

[0173] A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted, declarative or procedural, and can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or information / data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in several coordinated files (e.g., a file that stores one or more modules, subprograms, or portions of code). A computer program can be deployed to be executed on one computer, or on several computers that are located at one site or distributed across several sites and interconnected by a communication network.

[0174] The processes and logic flows described herein may be executed by one or more programmable processors executing one or more computer programs to perform actions by operating on input information / data and generating output. Processors suitable for executing computer programs include, by way of example, both general-purpose and special-purpose microprocessors, and one or more processors of any type of digital computer. Generally, a processor receives instructions and information / data from a read-only memory or a random access memory, or both. The essential elements of a computer are a processor for performing actions according to the instructions, and one or more memory devices for storing instructions and data. Generally, a computer also includes one or more mass storage devices, such as magnetic disks, magneto-optical disks, or optical disks, for storing data, or is operatively coupled to receive information / data from them, or to transfer information / data to them, or both. However, a computer need not have such devices. Suitable devices for storing computer program instructions and information / data include all forms of non-volatile memory, media, and memory devices, including, by way of example, semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices, magnetic disks, e.g., internal hard disks or removable disks, magneto-optical disks, e.g., CD-ROM and DVD-ROM disks. The processor and memory may be supplemented by, or incorporated in, special purpose logic circuitry.

[0175] To provide for user interaction, embodiments of the subject matter described herein may be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information / data to the user, and a pointing device, e.g., a mouse or trackball, by which the user can provide input to the computer. Other types of devices may also be used to provide for user interaction, e.g., feedback provided to the user may be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback, and input from the user may be received in any form, including acoustic, speech, or tactile input. Additionally, the computer may interact with the user by sending and receiving documents to and from a device used by the user, e.g., by sending a web page to a web browser on the user's client device in response to a request received from the web browser.

[0176] An embodiment of the subject matter described herein may be implemented in a computing system that includes a back-end component, e.g., as an information / data server, or includes a middleware component, e.g., an application server, or includes a front-end component, e.g., a client computer having a graphical user interface or web browser through which a user may interact with an implementation of the subject matter described herein, or includes any combination of one or more such back-ends, middleware, or fronts. The components of the system may be interconnected by any form or medium of digital information / data communication, e.g., a communications network. Examples of communications networks include local area networks ("LANs") and wide area networks ("WANs"), networks-to-networks (e.g., the Internet), and peer-to-peer networks (e.g., ad-hoc peer-to-peer networks).

[0177] A computing system may include clients and servers. Clients and servers are generally remote from each other and typically interact through a communications network. The relationship of clients and servers arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In some embodiments, a server transmits information / data (e.g., HTML pages) to a client device (e.g., for the purpose of displaying the information / data to a user interacting with the client device and receiving user input). Information / data generated at the client device (e.g., results of user interaction) may be received from the client device at the server.

[0178] Although the present specification contains many specific implementation details, these should not be construed as limiting the scope of any disclosure or what may be claimed, but as describing features specific to certain embodiments of a particular disclosure. Certain features described in the present specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Furthermore, even if features are described above as acting in a particular combination and initially claimed as such, one or more features from the claimed combination may in some cases be carved out of the combination, and the claimed combination may be subject to subcombinations or variations of the subcombination.

[0179] Similarly, although operations are depicted in the figures in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown, or in the sequential order, or that all of the illustrated operations be performed, to achieve desirable results. In certain situations, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the program components and systems described may generally be integrated together in a single software product or packaged into multiple software products.

[0180] Thus, certain embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In certain implementations, multitasking and parallel processing may be advantageous.

[0181] Non-limiting exemplary embodiments of the present disclosure Having described various aspects of the present invention, it will be understood that various embodiments are described herein. The subject matter described in the specification includes, but is not limited to, the following specific embodiments. These embodiments are merely examples and should not be construed as limiting the scope of the disclosure. It will be understood that the embodiments in some aspects can be freely combined. In other aspects of the disclosure, each embodiment is independent of the other embodiments described.

[0182] Embodiment 1. A computer-implemented method comprising: Identifying, in real time, a device identification data set associated with a set of network connected devices capable of communicating with the dynamic home communications network; Retrieving a device activity data set associated with a set of network-connected devices; applying a fault classification data model to the device activity dataset to select predicted operational support data objects from the device operational support management repository, the fault classification data model being trained based on training data from the dynamic home communication network, external aggregated device activity data from one or more external dynamic home communication networks, and faulty device history data from the device operational support management repository; and outputting the predicted operational support data object to a client device in communication with the dynamic home communications network.

[0183] Embodiment 2: A computer-implemented method according to any one of embodiments 1, wherein the predicted operational support data object includes a data link to a solution page associated with correcting the fault classification data associated with the set of network-connected devices.

[0184]

[0023] Embodiment 3: Fault classification data associated with a set of network-connected devices is collected by at least Identifying a first device identification data from the set of device identification data, the first device identification data being associated with a first device of the set of network-connected devices; 3. The computer-implemented method of embodiment 1 or 2, further comprising determining fault classification data corresponding to the first identification data and the device activity data set.

[0185]

[0023] Embodiment 4: Fault classification data associated with a set of network-connected devices is collected by at least identifying a plurality of device identification data from a device identification dataset, the plurality of device identification data being associated with a plurality of network-connected devices of a set of network-connected devices; 4. The computer-implemented method of any one of the first to third embodiments, further comprising: determining fault classification data corresponding to the plurality of device identification data and device activity data sets.

[0186]

[0023] Embodiment 5: Fault classification data associated with a set of network-connected devices is collected by at least The computer-implemented method of any one of embodiments 1 to 4, further comprising determining by determining that the device activity data set indicates a first fault classification represented by the fault classification data.

[0187] Embodiment 6: A computer-implemented method described in any one of embodiments 1 to 5, wherein the device operations management repository includes at least a predicted operations support data object associated with the set of device types and at least one fault classification identifier in fault classification data associated with the set of network-connected devices, and the device identification dataset indicates that the set of network-connected devices includes one or more network-connected devices of the set of device types.

[0188] Embodiment 7: Identifying a first fault classification associated with a set of device types; storing first fault classification data representing a first fault classification associated with the set of device types; 2. A method for manufacturing a network-connected device comprising: identifying a device type for each of the one or more network-connected devices of the set of network-connected devices based at least in part on the set of device identifications; and The computer-implemented method of any one of embodiments 1 to 6, further comprising determining that the set of device types associated with the first fault classification data includes a device type of each of the one or more network-connected devices of the network-connected device set.

[0189] Embodiment 8: Identifying historical activity data; determining that the historical activity data indicates a first malfunction; The computer-implemented method according to any one of the first to seventh embodiments, further comprising: storing a first fault classification identifier representing the first fault associated with the historical activity data.

[0190] Embodiment 9: A computer-implemented method according to any combination of embodiments 1 to 8. Embodiment 10: An apparatus comprising at least one processor and at least one non-transitory memory having computer program code stored therein, the computer program code, when executed on the at least one processor, causing the apparatus to perform any one of the computer-implemented methods of embodiments 1 to 9.

[0191] Embodiment 11: A computer program product comprising at least one non-transitory computer-readable storage medium having computer program code stored thereon, the computer program code configuring the computer program product, when executed on at least one processor, to perform any one of the computer-implemented methods of embodiments 1 to 9.

Claims

1. 1. An apparatus for selecting predicted operational support data objects from a device operational support management repository using diverse device activity data from a dynamic home communications network, the apparatus comprising: at least one processor; and at least one memory having stored thereon computer-coded instructions, the computer-coded instructions, when executed on the at least one processor, causing the apparatus to: identifying, in real time, a device identification data set associated with a set of network connected devices capable of communicating with the dynamic home communications network; Retrieving a device activity data set associated with a set of network-connected devices; applying a fault classification data model to the device activity data set to select the predicted operational support data object from the device operational support management repository, the fault classification data model being trained based on training data from the dynamic home communication network, external aggregated device activity data from one or more external dynamic home communication networks, and faulty device history data from the device operational support management repository; outputting the predicted operational support data object to a client device in communication with the dynamic home communications network.

2. The apparatus of claim 1 , wherein the predicted operational support data object includes a data link to a solution page associated with correcting fault classification data associated with the set of network-connected devices.

3. further causing the apparatus to determine fault classification data associated with the set of network-connected devices, wherein to determine the fault classification data, the apparatus: identifying first device identification data from a set of device identification data, the first device identification data being associated with a first device of the set of network-connected devices; and determining the fault classification data corresponding to the first identification data and the device activity data set.

4. further causing the apparatus to determine fault classification data associated with the set of network-connected devices, wherein to determine the fault classification data, the apparatus: identifying a plurality of device identification data from the device identification data set, the plurality of device identification data being associated with a plurality of network-connected devices of the set of network-connected devices; and determining the fault classification data corresponding to the plurality of device identification data and the device activity data set.

5. further causing the apparatus to determine fault classification data associated with the set of network-connected devices, wherein to determine the fault classification data, the apparatus: The apparatus of claim 1 , further comprising: determining that the device activity data set is indicative of a first fault classification represented by the fault classification data.

6. 2. The apparatus of claim 1, wherein the device operations management repository includes at least the predicted operations support data objects associated with a set of device types and at least one fault classification identifier in fault classification data associated with the set of network-connected devices, and the device identification data set indicates that the set of network-connected devices includes one or more network-connected devices of the set of device types.

7. The apparatus further comprises: Identifying a first fault classification associated with a set of device types; and storing first fault classification data representative of the first fault classification associated with the set of device types; determining fault classification data associated with the set of network-connected devices; and causing the apparatus to: identifying a device type for each of the one or more network-connected devices of the set of network-connected devices based at least in part on a set of device identifications; and 2. The apparatus of claim 1, further comprising: determining that the set of device types associated with the first fault classification data includes the device type of each of the one or more network-connected devices in the set of network-connected devices.

8. The apparatus further comprises: Identifying historical activity data; determining that the historical activity data is indicative of a first malfunction; The apparatus of claim 1 , further comprising: storing a first fault classification identifier representing the first fault associated with the historical activity data.

9. 1. A computer-implemented method for selecting predicted operational support data objects from a device operational support management repository using diverse device activity data from a dynamic home communications network, the computer-implemented method comprising: identifying, in real time, a device identification data set associated with a set of network connected devices capable of communicating with the dynamic home communications network; Retrieving a device activity data set associated with a set of network-connected devices; applying a fault classification data model to the device activity data set to select the predicted operational support data object from the device operational support management repository, the fault classification data model being trained based on training data from the dynamic home communication network, external aggregated device activity data from one or more external dynamic home communication networks, and faulty device history data from the device operational support management repository; and outputting the predicted operational support data object to a client device in communication with the dynamic home communications network.

10. 10. The computer-implemented method of claim 9, wherein the predicted operational support data object includes a data link to a solution page associated with correcting fault classification data associated with the set of network-connected devices.

11. The computer-implemented method further comprises: generating fault classification data associated with the set of network-connected devices, the fault classification data comprising at least: identifying first device identification data from a set of device identification data, the first device identification data being associated with a first device of the set of network-connected devices; 10. The computer-implemented method of claim 9, further comprising: determining the fault classification data corresponding to the first identification data and the device activity data set.

12. The computer-implemented method further comprises: generating fault classification data associated with the set of network-connected devices, the fault classification data comprising at least: identifying a plurality of device identification data from the device identification data set, the plurality of device identification data being associated with a plurality of network-connected devices of the set of network-connected devices; 10. The computer-implemented method of claim 9, further comprising: determining the fault classification data corresponding to the plurality of device identification data and the device activity data set.

13. The computer-implemented method further comprises: generating fault classification data associated with the set of network-connected devices, the fault classification data comprising at least: The computer-implemented method of claim 9 , further comprising determining by determining that the device activity data set indicates a first fault classification represented by the fault classification data.

14. 10. The computer-implemented method of claim 9, wherein a device operations management repository includes at least the predicted operations support data objects associated with a set of device types and at least one defect classification identifier in defect classification data associated with the set of network-connected devices, and the device identification data set indicates that the set of network-connected devices includes one or more network-connected devices of the set of device types.

15. The computer-implemented method further comprises: Identifying a first fault classification associated with a set of device types; storing first fault classification data representative of the first fault classification associated with the set of device types; a fault classification data associated with the set of network-connected devices, the fault classification data associated with the set of network-connected devices being at least identifying a device type for each of the one or more network-connected devices of the set of network-connected devices based at least in part on a set of device identifications; and 10. The computer-implemented method of claim 9, further comprising: determining by determining that the set of device types associated with the first fault classification data includes the device type of each of the one or more network-connected devices of the set of network-connected devices.

16. The computer-implemented method further comprises: Identifying historical activity data; determining that the historical activity data is indicative of a first malfunction; The computer-implemented method of claim 9 , further comprising: storing a first fault classification identifier representing the first fault associated with the historical activity data.

17. 1. A computer program product for selecting predicted operational support data objects from a device operational support management repository using diverse device activity data from a dynamic home communications network, the computer program product comprising at least one non-transitory computer readable storage medium having computer program code stored thereon, the computer program code, when executed on at least one processor, causing the computer program product to: identifying, in real time, a device identification data set associated with a set of network connected devices capable of communicating with the dynamic home communications network; Retrieving a device activity data set associated with a set of network-connected devices; applying a fault classification data model to the device activity data set to select the predicted operational support data object from the device operational support management repository, the fault classification data model being trained based on training data from the dynamic home communication network, external aggregated device activity data from one or more external dynamic home communication networks, and faulty device history data from the device operational support management repository; and outputting the predicted operational support data object to a client device in communication with the dynamic home communications network.

18. 20. The computer program product of claim 17, wherein the predicted operational support data object comprises a data link to a solution page associated with correcting fault classification data associated with the set of network-connected devices.

19. 20. The computer program product, Identifying a first fault classification associated with a set of device types; storing first fault classification data representative of the first fault classification associated with the set of device types; Fault classification data associated with the set of network-connected devices, at least identifying a device type for each of the one or more network-connected devices of the set of network-connected devices based at least in part on a set of device identifications; and 20. The computer program product of claim 17, further configured to: determine by determining that the set of device types associated with the first fault classification data includes the device type of each of the one or more network-connected devices of the set of network-connected devices.

20. 20. The computer program product, Identifying historical activity data; determining that the historical activity data is indicative of a first malfunction; 20. The computer program product of claim 17, further configured to: store a first fault classification identifier representing the first fault associated with the historical activity data.

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