DESC:RESERVATION OF RIGHTS
[0001] A portion of the disclosure of this patent document contains material, which is subject to intellectual property rights such as but are not limited to, copyright, design, trademark, integrated circuit (IC) layout design, and/or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (hereinafter referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully reserved by the owner.

TECHNICAL FIELD
[0002] The embodiments of the present disclosure generally relate to systems and methods for network management in telecommunication systems. More particularly, the present disclosure relates to a system and a method for categorizing alarms and generating an effective ticket resolution for network performance issues, thereby enhancing customer experience.

BACKGROUND
[0003] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admission of the prior art.
[0004] Computer networks with wired or wireless fidelity (Wi-Fi) forms may be used for transmitting, exchanging, and/or sharing data. Further, computer networks use hardware (routers, switches, access points, and cables) and software (operating systems or business applications) and can be dependent on a specific geographical location. Computer networks utilize protocols to communicate and enable communication means for every business, entertainment, and research organization. Furthermore, computer networks enable online search, e-mail, audio-video sharing, online commerce, live-streaming, and social networks to provide a wide spectrum of multi-media information to its customers.
[0005] However, computer networks are prone to faults, and customers may experience connectivity issues, poor network performance, and total network outages at certain periods of time. Complaint tickets may be raised by customers/users, whereas ticket generation can also be a result of network faults and customer experiences due to poor cellular services. Based on incident management tools, the ticket may be logged where the ticket can go through several categorizations and eventually reach the concerned resolution team for generation of resolution actions through the appropriate field team which includes field engineers. The field teams are required to be updated about network faults on a real-time basis so that an appropriate resolution may be achieved. The raised ticket reflects the issue faced by customers in their specific geographical area. There can be different outages or network faults possible which may affect a single customer or multiple customers. Hence, there may be multiple tickets which may reflect the same issue. Also, the same issue may be raised multiple times over a period of time. Hence, root cause analysis of the actual core issue becomes essential while resolving issues. Moreover, the possible updates or upgradation required for resolving issues must also be identified. Further, raising huge number of appropriate alarms over various issues/tickets may be challenging.
[0006] There is, therefore, a need in the art to provide a system and a method that can mitigate the problems associated with the prior arts.

OBJECTS OF THE PRESENT DISCLOSURE
[0007] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are listed herein below.
[0008] It is an object of the present disclosure to provide a system and a method that segregates various network faults, alarms, and outages into different categories at different levels.
[0009] It is an object of the present disclosure to provide a system and a method that utilizes network availability data with information about various network faults, alarms, and outages, and categorizes them into cloud-managed territories and generates tickets accordingly.
[0010] It is an object of the present disclosure to provide a system and a method that utilizes a comprehensive categorization technique and differentiates alarms based on network domains, translates service impacting catastrophic alarms into specific down sites, distributes all alarm attributes into multiple tabs, and suggests corrective actions for each alarm.
[0011] It is an object of the present disclosure to provide a system and a method that categorizes alarm events into Radio Frequency (RF), Back Haul (BH), and utility tickets.
[0012] It is an object of the present disclosure to provide a system and a method that generates network analytics data related to network downtime for identifying outage and repeat outage sites while generating complete information of tickets including work order, assignee name, and contacts.
[0013] It is an object of the present disclosure to provide a system and a method that enhances customer experience and in-turn, customer loyalty by proactively identifying the issues/drops behind poor services, and further generates specific categorized alarms for respective issues and respective simplified resolutions.
[0014] It is an object of the present disclosure to provide a system and a method that reduces the number of port outs and complaints.
[0015] It is an object of the present disclosure to provide a system and a method for correlating a site identity of alarm events, a timestamp of the alarm events, and raw alarm data of the alarm events to categorize tickets.

SUMMARY
[0016] This section is provided to introduce certain objects and aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
[0017] In an aspect, the present disclosure relates to a system for alarm categorization. The system includes one or more processors, and a memory operatively coupled to the one or more processors, where the memory includes processor-executable instructions, which on execution, cause the one or more processors to receive one or more alarm events occurred at one or more locations from one or more sources, and determine one or more parameters of each alarm event. Further, the one or more processors are to generate one or more tickets corresponding to each alarm event based on the one or more parameters, and categorize the one or more tickets with respect to the one or more parameters in real-time based on the generation.
[0018] In an embodiment, the one or more parameters may include at least one of: a priority level, a type of fault, information of alarm, service disruptions, cloud-management territories, information of network domain, information of Radio Frequency (RF), information of Back Haul (BH), utility information, cell information, information of Radio Access Network (RAN), information of Internet Protocol-Multi-Protocol Label Switching (IP-MPLS), information of Wireless Fidelity (Wi-Fi), and location information.
[0019] In an embodiment, the one or more processors may determine whether a critical level of each alarm event exceeds a predetermined range, and assign the priority level to each alarm event based on the critical level.
[0020] In an embodiment, the one or more processors may determine that the one or more tickets are not categorized based on categorization results, and extract information of one or more other alarm events from each of the one or more tickets that are not categorized. Further, the one or more processors may receive raw alarm data of each of the one or more other alarm events corresponding to the extracted information, and correlate the information and the raw alarm data to determine the one or more parameters of each of the one or more other alarm events based on the correlation.
[0021] In an embodiment, the information may include at least one of: site identity, and timestamp of each of the one or more other alarm events.
[0022] In an embodiment, the one or more processors may convert the raw alarm data into refined alarm data prior to the correlation of the information and the raw alarm data.
[0023] In an embodiment, the one or more processors may determine one or more issues corresponding to each ticket, and determine a root cause of each issue to generate one or more resolutions corresponding to the root cause of each issue.
[0024] In an embodiment, the one or more processors may generate one or more work orders corresponding to each resolution, and determine one or more work groups to assign each work order to the one or more work groups.
[0025] In another aspect, the present disclosure relates to a method for alarm categorization. The method includes receiving, by one or more processors associated with a system, one or more alarm events occurred at one or more locations from one or more sources, and determining, by the one or more processors, one or more parameters of each alarm event. Further, the method includes generating, by the one or more processors, one or more tickets corresponding to each alarm event based on the one or more parameters, and categorizing, by the one or more processors, the one or more tickets with respect to the one or more parameters in real-time based on the generation.
[0026] In an embodiment, the method may include determining, by the one or more processors, whether a critical level of each alarm event exceeds a predetermined range, and assigning, by the one or more processors, the priority level to each alarm event based on the critical level.
[0027] In an embodiment, for categorizing, by the one or more processors, the one or more tickets, the method may include determining, by the one or more processors, that the one or more tickets are not categorized based on categorization results, and extracting, by the one or more processors, information of one or more other alarm events from each of the one or more tickets that are not categorized. Further, the method may include receiving, by the one or more processors, raw alarm data of each of the one or more other alarm events corresponding to the extracted information, and correlating, by the one or more processors, the information and the raw alarm data. Further, the method may include determining, by the one or more processors, the one or more parameters of each of the one or more other alarm events based on the correlation.
[0028] In an embodiment, the method may include converting, by the one or more processors, the raw alarm data into refined alarm data prior to correlating the information and the raw alarm data.
[0029] In an embodiment, the method may include determining, by the one or more processors, one or more issues corresponding to each ticket and determining, by the one or more processors, a root cause of each issue for generating, by the one or more processors, one or more resolutions corresponding to the root cause of said each issue.

BRIEF DESCRIPTION OF DRAWINGS
[0030] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such drawings includes the disclosure of electrical components, electronic components, or circuitry commonly used to implement such components.
[0031] FIG. 1 illustrates an exemplary network architecture (100) of a system (108), in accordance with embodiments of the present disclosure.
[0032] FIG. 2 illustrates an example block diagram (200) of the system (108), in accordance with embodiments of the present disclosure.
[0033] FIG. 3 illustrates a schematic representation (300) of a high-level flow of an alarm categorization, in accordance with embodiments of the present disclosure.
[0034] FIG. 4 illustrates a schematic representation (400) of a high-level architecture of the system (108), in accordance with embodiments of the present disclosure.
[0035] FIG. 5 illustrates a schematic representation (500) of a customer closed loop logic of the system (108), in accordance with embodiments of the present disclosure.
[0036] FIGs. 6A-6B illustrate schematic representations (600A, 600B) of a system of interaction, in accordance with embodiments of the present disclosure.
[0037] FIG. 7 illustrate an exemplary flow chart of a method (700) for alarm categorization, in accordance with embodiments of the present disclosure.
[0038] FIG. 8 illustrates an exemplary computer system (800) in which or with which the system (108) may be implemented, in accordance with an embodiment of the present disclosure.
[0039] The foregoing shall be more apparent from the following more detailed description of the disclosure.

BRIEF DESCRIPTION OF THE PRESENT DISCLOSURE
[0040] In the following description, for explanation, various specific details are outlined in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0041] The ensuing description provides exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.
[0042] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.
[0043] Also, it is noted that individual embodiments may be described as a process that is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0044] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive like the term “comprising” as an open transition word without precluding any additional or other elements.
[0045] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0046] The terminology used herein is to describe particular embodiments only and is not intended to be limiting the disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any combinations of one or more of the associated listed items.
[0047] The various embodiments throughout the disclosure will be explained in more detail with reference to FIGs. 1-8.
[0048] FIG. 1 illustrates an exemplary network architecture (100) of a system (108), in accordance with embodiments of the present disclosure. As illustrated in FIG. 1, one or more computing devices (104-1, 104-2…104-N) may be connected to the system (108) through a network (106). A person of ordinary skill in the art will understand that the one or more computing devices (104-1, 104-2…104-N) may be collectively referred as the computing devices (104) and individually referred as the computing device (104). It should be understood that the computing device (104) may also be known as a user equipment (UE) that may include, but not be limited to, a mobile, a laptop, etc. Further, the computing devices (104) may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as a camera, audio aid, microphone, or keyboard. Further, the computing devices (104) may include a smartphone, Virtual Reality (VR) devices, Augmented Reality (AR) devices, a general-purpose computer, a desktop, a personal digital assistant, a tablet computer, and a mainframe computer. Additionally, input devices for receiving input from a user (102) such as a touchpad, touch-enabled screen, electronic pen, and the like may be used.
[0049] Th network (106) may include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. The network (106) may also include, by way of example but not limitation, one or more of a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof.
[0050] Referring to FIG. 1, one or more users (102-1, 102-2…102-N) may be associated with the computing devices (104). A person of ordinary skill in the art will understand that the one or more users (102-1, 102-2…102-N) may be collectively referred as the users (102) and individually referred as the user (102). In an exemplary embodiment, the users (102) may be customers providing complaints and queries to the system (108) through the computing devices (104).
[0051] In an embodiment, the system (108) may receive one or more alarm events occurred at one or more locations from one or more sources and determine one or more parameters of each alarm event. Further, the system (108) may generate one or more tickets corresponding to each alarm event based on the one or more parameters, and categorize the one or more tickets with respect to the one or more parameters in real-time based on the generation.
[0052] FIG. 2 illustrates an example block diagram (200) of a system (108), in accordance with embodiments of the present disclosure. A person of ordinary skill in the art will understand that the system (108) of FIG. 2 may be similar to the system (108) of FIG. 1 in functionality.
[0053] Referring to FIG. 2, the system (108) may include one or more processor(s) (202). The one or more processor(s) (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the one or more processor(s) (202) may be configured to fetch and execute computer-readable instructions stored in a memory (204) of the system (108). The memory (204) may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (204) may comprise any non-transitory storage device including, for example, volatile memory such as Random-Access Memory (RAM), or non-volatile memory such as Erasable Programmable Read Only Memory (EPROM), flash memory, and the like.
[0054] In an embodiment, the system (108) may include an interface(s) (206). The interface(s) (206) may comprise a variety of interfaces, for example, interfaces for data input and output devices (I/O), storage devices, and the like. The interface(s) (206) may facilitate communication through the system (108). The interface(s) (206) may also provide a communication pathway for one or more components of the system (108). Examples of such components include, but are not limited to, processing engine(s) (208) and a database (210).
[0055] In an exemplary embodiment, the processing engine (208) may receive inputs from a Service Manager (SM) module. The inputs may include complaints, alarms, and alerts registered by one or more users (102) through the computing device (104) and store the information in the database (210). In an embodiment, the processing engine(s) (208) may categorize the alarms based on, but not limited to, network domains, translate service impacting catastrophic alarms into current sites down, and distribute all alarm attributes into multiple tabs, and suggest corrective actions for each alarm.
[0056] The processing engine(s) (208) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) (208). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) (208) may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) (208) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (208). In such examples, the system may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system and the processing resource. In other examples, the processing engine(s) (208) may be implemented by electronic circuitry. Further, the processing engine (208) may include an alarm events determination module (212), a ticket generation module (214), a ticket categorization module (216), a resolution determination module (218), and other module(s) (220).
[0057] In an embodiment, the system (108) may receive alarm events occurred at different locations from various sources such as, but not limited to, SM module, alarm event detection module, and other network modules which maintain data related to complaints and alarms registered by sites/customer actions. Once the system (108) receives the alarm events, the alarm events determination module (212) may determine parameters of the alarm events and generate tickets corresponding to the alarm events based on the parameters. In some embodiments, the parameters may include, but not limited to, a priority level, a type of fault, information of alarm, service disruptions, cloud-management territories, information of network domain, information of Radio Frequency (RF), information of Back haul (BH), utility information, cell information, information of Radio Access Network (RAN), information of Internet Protocol-Multi-Protocol Label Switching (IP-MPLS), information of Wireless Fidelity (Wi-Fi), and location information. In some embodiments, the priority level may be determined based on determining whether a critical level of each alarm event exceeds a predetermined range or is lesser than the predetermined range. If the critical level of the alarm event exceeds the predetermined threshold or is lesser than the predetermined range, the alarm events determination module (212) may assign the priority level to the alarm event based on the critical level.
[0058] In an embodiment, once the parameters are determined, the ticket generation module (214) may generate tickets corresponding to the alarm events based on the parameters. Once the tickets are generated, the ticket categorization module (216) may categorize the tickets with respect to the parameters. Further, in some embodiments, the ticket categorization module (216) may determine whether all tickets are categorized or not. If some tickets are not categorized, the ticket categorization module (216) may extract information of alarm events from the tickets that are not categorized. Simultaneously, the system (108) may search raw alarm data of the alarm events to determine the location information of the alarm events corresponding to the extracted information. In some exemplary embodiments, the information may include, but not limited to, site identity of the alarm events, timestamp of the alarm events, and the like. In an embodiment, the ticket categorization module (216) may convert the raw alarm data into refined alarm data to correlate the information and the refined alarm data. Based on the correlation, the ticket categorization module (216) may determine the parameters of the alarm events corresponding to the tickets that are not categorized and categorize the tickets based on the parameters corresponding to the tickets that are not categorized.
[0059] In some embodiments, once all tickets are categorized, the resolution determination module (218) may determine issues corresponding to the tickets and determine a root cause of the issues to generate resolutions corresponding to the root cause. Once the resolutions are generated, the resolution determination module (218) may generate work orders corresponding to the resolutions and determine work groups with respect to the work orders. Once the work groups are determined, the resolution determination module (218) may assign the work order to the work groups.
[0060] FIG. 3 illustrates a schematic representation (300) of a high-level flow of an alarm categorization, in accordance with embodiments of the present disclosure.
[0061] In an embodiment, a system (e.g., 108) may include a customer closed looping (CCL) mechanism. The CCL mechanism may capture the overall health of pillars of network, towers, and mobility. Further, the system (108) may be implemented on a Data Platform (DP). The system (108) may receive data majorly from a SM module (304A) module along with data of alarm events (304B), where all complaints and alarms registered by sites/customer actions may be compiled together. Data from the SM (304A) may be extracted for utility, including RAN-related and IP-MPLS related data. Data may be updated in real-time and any improvements made in the system (108) are reflected through an application.
[0062] In an exemplary embodiment, tickets/work orders may be assigned on the basis of assignment group which may be configured in the system (108). Further, as the alarm pertaining to a particular group is received, the corresponding ticket may be quickly routed to a group which may be field engineers, an Integrated Access Network Lad (IANL), and state leaders. The group may access this information through the application installed on their mobile devices in real time. Alarm types may be reconfigured for better representation. Alarm categories available in the application may include RAN, BH, utility, small cell, and Wi-Fi. After breaking alarm categories, sub-categories may be formed by using alarm name and alarm text that may help in generating a proper resolution method. Severity and impact may also be specified for the particular alarm and represented through a particular filed by the SM with regular updates.
[0063] In an embodiment, the system (108) may categorize keywords (306) into an alarm category (308) and an alarm subcategory (310) to generate resolutions (312) based on the inputs provided by the SM (304A). Further, the system (108) may provide these inputs to an alarm DP (314) that may include work order information (316) with specific details related to status and time taken. The system (108) may generate outputs after processing and provide the information to a system of intelligence and system of integration (318).
[0064] In an exemplary embodiment, the SM may hold data for all events, complaints, and alarms. Further, data (304A) is received by the SM from multiple data streams for complaints, alarms, and alerts and refreshed in real time. Additionally, alarm data (304B) may be streamed from the SM to the alarm DP (314) intermittently after a predetermined time interval, for example, but not limited to, every 15 minutes. The predetermined time interval may depend on the time taken by the DP (314) to perform actions and send information to the application. Further, manual intervention may also be provided within this time interval. The SM may hold raw data for all attributes, so that cleaning and processing may be provided by the SM and sent to the DP (314).
[0065] In an exemplary embodiment, the SM may include attributes and several repetitive garbage rows which may not be pushed straight away to the application. Data may require removal of null rows and/or repetitive data. Solution specific alarms may be provided by the standard data prepared in the alarm DP (314).
[0066] In an exemplary embodiment, data may be cleaned and well equipped with information to be seen by end users. Further, data may be provided to the application. The application may show alarms in categories sent by the alarm DP (314) and the corresponding resolution calculated by the alarm DP (314). After an alarm is resolved, for example, by a field engineer, the information may be sent to the SM and the cycle may be repeated and may be verified by the field engineer. Based on the implementation used by the field engineer and its results, alarms may be tagged as open or resolved in the SM and the alarm DP (314), and henceforth in the application.
[0067] In some exemplary embodiments, the system (108) may categorize/subcategorize trouble tickets using a master sheet technique. Further, the system (108) may identify any tickets that have not been categorized, and extract the site identity and timestamp of alarm events from these uncategorized tickets. Further, the system (108) may search raw feed of source data to locate alarm events corresponding to the site and timestamp. Once the alarm is identified, the system (108) may provide necessary actions for the respective trouble ticket and consolidate all modified tickets to transmit the data for visualization to the system of interaction, ensuring a streamlined and an efficient process for handling and resolving network-related issues.
[0068] FIG. 4 illustrates a schematic representation (400) of a high-level architecture of a system (108), in accordance with embodiments of the present disclosure.
[0069] As illustrated in FIG. 4, the high-level architecture (400) may include multiple modules for processing complaints provided by users. The system (108) may be configured with a system of records module (402). The system of records module (402) may include network data, customer experience data, and customer complaint data, but not limited to the like. Further, a system of instrumentation module (404) may be configured in the system (108). The system of instrumentation module (404) may include SM. The SM may handle Internet Protocol (IP) router, and multiple tools (Tool 1, Tool 2) as shown in FIG. 4. Further, the SM may include Service Request(s) (SR) from users. The system (108) may be configured with a system of data engineering module (406) that may include a DP (previously alarm DP (314) in FIG. 3) and a query manager (QM). In an embodiment, the DP may refer to Big Data Lake. The DP and the QM may process the information received from the system of records module (402) and the system of instrumentation module (404), and direct the information to a system of intelligence module (408) configured in the system (108).
[0070] In an embodiment, the system of intelligence module (408) may include alarms corresponding to RF, BH, and utility complaints. The system of intelligence module (408) may further generate Root Cause Analytics (RCA) and incident details based on the information received from the system of data engineering module (406). The system of intelligence module (408) may also include different action groups based on problem domain and geography.
[0071] In some embodiments, resolver groups may be action groups based on problem domain and geography. Furthermore, the RCA and incident details may be directed towards a system of interaction module (410) once they are processed by the resolver groups. The system of interaction module (410) may include a C-level dashboard, a performance dashboard, and an application stack. Information generated by the system of interaction module (410) may be accessed by a lead engineer through a system of operation module (412). The lead engineer may further provide feedback to the system of records module (402) related to experience improvement verification.
[0072] FIG. 5 illustrates of a schematic representation (500) of a customer closed loop logic of a system (108), in accordance with embodiments of the present disclosure.
[0073] In an embodiment, the system (108) (previously described in FIGs. 1 and 2) may include customer closed loop logic as illustrated in FIG. 5. A health card platform (502) may be configured as part of the customer closed loop logic (500) to include health card aggregates from various users/customers. Health card aggregates may include customer events from a predefined time period, for example, but not limited to, past 30 days, where the customer events may include coverage, High-Speed Synchronous Interface (HSI), Channel Quality Indicator (CQI), consumption, voice, location, availability. In an embodiment, outputs from the health card platform (502) may be provided to a root-cause fix (RCF) logic module (504). The RCF logic module (504) may perform RCF analysis using an RCF engine on the inputs provided by the health card platform (502) on every cell impacting customer experience to identify digital and physical actions. The RCF logic module (504) may include outage serving sites/neighbour cells, backhaul problems, quality issues, and capacity/coverage issues related to health card aggregates from various users/customers. The RCF logic module (504) may further generate actions including, but not limited to, availability improvement on the outage serving sites/neighbour cells the based on the RCF analysis. Further, the RCF logic module (504) may generate actions including availability/augmentation on the backhaul problems based on the RCF analysis. The RCF logic module (504) may provide optimization on the quality issues through the RCF analysis. Further, the RCF logic module (504) may generate planned actions for new network rollout based on the capacity/coverage issues through the RCF analysis.
[0074] In an embodiment, a work order platform (506) may be configured as part of the customer closed loop logic (500) for scrubbing all actions against customer complaints and porting out request data for priority actions. The work order platform (506) may include digital and physical actions across all customers. Further, the work order platform (506) may scrub against customer complaints and port outs for priority actions. Further, the work order platform (506) may include planning actions based on the planned actions of the RCF logic module (504).
[0075] In an embodiment, a presentation module (508)/application layer may be configured as part of the customer closed loop logic (500) for all actions executed through the work order platform (506). Further, the presentation module (508)/application layer may track closure/circle level through action sheets. The presentation module (508)/application layer may include field and centralized Network Operations Centre (NOC) led assignment/tracking/Service Level Agreements (SLAs) based on the digital/physical actions across all customers generated by the work order platform (506). In an embodiment, the presentation module (508)/application layer may provide a feedback to the health card platform (502) with suggestions related to track experience improvement.
[0076] FIGs. 6A-6B illustrate schematic representations (600A, 600B) of a system of interaction, in accordance with embodiments of the present disclosure.
[0077] Referring to FIGs. 6A-6B, a system (108) may include a user interface (e.g., the system of interaction) such as, but not limited to a display and the like. In some exemplary embodiments, information related to each categorized ticket or consolidated ticket may be provided on the user interface for visual representation as illustrated in FIGs. 6A-6B. In an embodiment, the system (108) may process for specific network issues by offering an optimal and efficient resolution plan, significantly reducing the time required to pinpoint the problem’s cause and determine the path to resolution. Moreover, the system (108) may facilitate real-time resolution checks, allowing users to seamlessly access automatic updates in ticket generation through an interactive system (e.g., user interface).
[0078] FIG. 7 illustrate an exemplary flow chart of a method (700) for alarm categorization, in accordance with embodiments of the present disclosure.
[0079] Referring to FIG. 7, at block (702), the method (700) may include receiving one or more alarm events occurred in one or more locations from one or more sources.
[0080] At block (704), the method (700) may include determining one or more parameters of each alarm event. In some embodiments, the parameters mat include a priority level, a type of fault, information of alarm, service disruptions, cloud-management territories, information of network domain, information of RF, information of BH, utility information, cell information, information of RAN, information of IP-MPLS, information of Wi-Fi, and location information.
[0081] At block (706), the method (700) may include generating one or more tickets corresponding to said each alarm event based on the one or more parameters.
[0082] At block (708), the method (700) may include categorizing the one or more tickets with respect to the one or more parameters in real-time based on the generation. Further, the method (700) may include determine that one or more tickets are not categorized based on categorization results and extract information of one or more another alarm events from said each ticket that are not categorized. Further, the method (700) may include receiving raw alarm data of each another alarm event corresponding to the extracted information and correlating the information and the raw alarm data for determining the one or more parameters of said each another alarm event based on the correlation.
[0083] FIG. 8 illustrates an exemplary computer system (800) in which or with which a system (108) may be implemented, in accordance with an embodiment of the present disclosure.
[0084] As shown in FIG. 8, the computer system (800) may include an external storage device (810), a bus (820), a main memory (830), a read-only memory (840), a mass storage device (850), a communication port(s) (860), and a processor (870). A person skilled in the art will appreciate that the computer system (800) may include more than one processor and communication ports. The processor (870) may include various modules associated with embodiments of the present disclosure. The communication port(s) (860) may be any of an RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fibre, a serial port, a parallel port, or other existing or future ports. The communication port(s) (860) may be chosen depending on a network, such as a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system (800) connects. The main memory (830) may be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. The read-only memory (840) may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chip for storing static information e.g., start-up or basic input/output system (BIOS) instructions for the processor (870). The mass storage device (850) may be any current or future mass storage solution, which can be used to store information and/or instructions.
[0085] The bus (820) may communicatively couple the processor (870) with the other memory, storage, and communication blocks. Optionally, operator and administrative interfaces, e.g., a display, keyboard, and cursor control device may also be coupled to the bus (820) to support direct operator interaction with the computer system (800). Other operator and administrative interfaces can be provided through network connections connected through the communication port(s) (860). In no way should the aforementioned exemplary computer system (800) limit the scope of the present disclosure.
[0086] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be implemented merely as illustrative of the disclosure and not as a limitation.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0087] The present disclosure reduces human error based on an efficient and automatic alarm categorization engine.
[0088] The present disclosure describes the best and fastest resolution plan for a single problem.
[0089] The present disclosure reduces the time taken to identify the cause of the alarm due to the accuracy of the data.
[0090] The present disclosure helps in real-time resolution check as the corrections may be automatically updated in service manager (SM) where the user can access this information on the application through a mobile device.
[0091] The present disclosure reduces learning and training duration cost of employees as the application predicts the solution.
[0092] The present disclosure provides a system and a method that is more user-friendly than conventional solutions that require logging back and forth to SM to the check issue list.
[0093] The present disclosure provides a process that is automated and can be easily tweaked with configurable parameters.
[0094] The present disclosure provides a system that is highly modular such that it may accommodate new modules whenever they are developed and the framework built is highly scalable.
[0095] The present disclosure provides a real-time root cause identification and real-time resolution corresponding to the root cause and reduces manual effort.
,CLAIMS:1. A system (108) for alarm categorization, comprising:
one or more processors (202); and
a memory (204) operatively coupled to the one or more processors (202), wherein the memory (204) comprises processor-executable instructions, which on execution, cause the one or more processors (202) to:
receive one or more alarm events from one or more sources occurred at one or more locations;
determine one or more parameters corresponding to each of the one or more alarm events;
generate one or more tickets corresponding to each of the one or more alarm events based on the one or more parameters; and
categorize, in real-time, the one or more tickets with respect to the one or more parameters based on the generation.
2. The system (108) as claimed in claim 1, wherein the one or more parameters comprise at least one of: a priority level, a type of fault, information of alarm, service disruptions, cloud-management territories, information of network domain, information of Radio Frequency (RF), information of Back Haul (BH), utility information, cell information, information of Radio Access Network (RAN), information of Internet Protocol-Multi-Protocol Label Switching (IP-MPLS), information of Wireless Fidelity (Wi-Fi), and location information.
3. The system (108) as claimed in claim 2, wherein the one or more processors (202) are to:
determine whether a critical level of each of the one or more alarm events exceeds a predetermined range; and
assign the priority level to each of the one or more alarm events based on the critical level.
4. The system (108) as claimed in claim 1, wherein the one or more processors (202) are to:
determine that the one or more tickets are not categorized based on categorization results;
extract information of one or more other alarm events from the one or more tickets that are not categorized;
receive raw alarm data of each of the one or more other alarm events corresponding to the extracted information;
correlate the information and the raw alarm data; and
determine the one or more parameters of each of the one or more other alarm events based on the correlation.
5. The system (108) as claimed in claim 4, wherein the information comprises at least one of: site identity, and timestamp of each of the one or more other alarm events.
6. The system (108) as claimed in claim 4, wherein the one or more processors (202) are to:
convert the raw alarm data into refined alarm data prior to the correlation of the information and the raw alarm data.
7. The system (108) as claimed in claim 4, wherein the one or more processors (202) are to:
determine one or more issues corresponding to each of the one or more tickets;
determine a root cause of each of the one or more issues; and
generate one or more resolutions corresponding to the root cause of each of the one or more issues.
8. The system (108) as claimed in claim 7, wherein the one or more processors (202) are to:
generate one or more work orders corresponding to each of the one or more resolutions;
determine one or more work groups; and
assign each of the one or more work orders to the one or more work groups.
9. A method (700) for alarm categorization, comprising:
receiving (702), by one or more processors (202) associated with a system (108), one or more alarm events from one or more sources occurred at one or more locations;
determining (704), by the one or more processors (202), one or more parameters of each of the one or more alarm events;
generating (706), by the one or more processors (202), one or more tickets corresponding to each of the one or more alarm events based on the one or more parameters; and
categorizing (708), by the one or more processors (202), in real-time, the one or more tickets with respect to the one or more parameters based on the generation.
10. The method (700) as claimed in claim 9, comprising:
determining, by the one or more processors (202), whether a critical level of each of the one or more alarm events exceeds a predetermined range; and
assigning, by the one or more processors (202), a priority level to each of the one or more alarm events based on the critical level.
11. The method (700) as claimed in claim 9, wherein categorizing, by the one or more processors (202), the one or more tickets comprises:
determining, by the one or more processors (202), that the one or more tickets are not categorized based on categorization results;
extracting, by the one or more processors (202), information of one or more other alarm events from the one or more tickets that are not categorized;
receiving, by the one or more processors (202), raw alarm data of each of the one or more other alarm events corresponding to the extracted information;
correlating, by the one or more processors (202), the information and the raw alarm data; and
determining, by the one or more processors (202), the one or more parameters of each of the one or more other alarm events based on the correlation.
12. The method (700) as claimed in claim 11, comprising:
converting, by the one or more processors (202), the raw alarm data into refined alarm data prior to correlating the information and the raw alarm data.
13. The method (700) as claimed in claim 9, comprising:
determining, by the one or more processors (202), one or more issues corresponding to each of the one or more tickets;
determining, by the one or more processors (202), a root cause of each of the one or more issues; and
generating, by the one or more processors (202), one or more resolutions corresponding to the root cause of each of the one or more issues.