WO2025022443A1

WO2025022443A1 - System and method for monitoring clear code trends

Info

Publication number: WO2025022443A1
Application number: PCT/IN2024/051348
Authority: WO
Inventors: Aayush Bhatnagar; Ankit Murarka; Gaurav Saxena; Meenakshi Shobharam; Mohit Bhanwria; Vinay Gayki; Durgesh KUMAR; Shashank Bhushan; Aniket Anil Khade; Jugal Kishore Kolariya; Rahul Verma; Gaurav Kumar; Sunil Meena; Kishan Sahu
Original assignee: Jio Platforms Ltd
Current assignee: Jio Platforms Ltd
Priority date: 2023-07-24
Filing date: 2024-07-23
Publication date: 2025-01-30
Anticipated expiration: 2026-01-24

Abstract

The present disclosure provides a system(108) and a method(400) for moni- toring clear code trends. The method(400) includes receiving(402), by a processor(202), a first set of signals from a monitoring unit(114) associated with a network(106). The method(400) further includes checking(404), by the processor(202), if a pre-computed trend report of a network entity(110) is stored in a first database(210-1). The method includes communicating(406) the pre-computed trend report associated with the network function upon the pre-computed trend report related to the re- quest being available in the first database(210-1). The method further includes generating(406), by the processor(202), the trend report based on clear code data associated with the network function, and transmitting the trend report to the monitoring unit(114) when the pre-computed trend report related to the request is not available in the first database(210-1).

Description

SYSTEM AND METHOD FOR MONITORING CLEAR CODE TRENDS

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.

FIELD OF DISCLOSURE

[0002] The embodiments of the present disclosure generally relate to communication networks. In particular, the present disclosure relates to a system and method for monitoring clear code trends.

BACKGROUND OF DISCLOSURE

[0003] The following description of 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 be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.

[0004] Network entities generate clear codes as they provide services to one or more user equipment. Clear codes provide error codes or status codes that indicate the reason for call failures in a network. In examples, clear code may refer to errors that are coded to indicate, for example, a reason for terminating a call or connection. The clear codes help diagnose issues by specifying why a call failed, service failed or was dropped. Analyzing the clear codes is important for understanding the predominant causes of call termination and taking preventative or alleviative measures to resolve any abnormalities in the network.

[0005] Monitoring clear code data may be difficult due to the volume and velocity at which they are generated. Most existing solutions do not maintain historical data of clear codes for performing a meaningful analysis. For instance, it is difficult to analyze trends in clear code data without sufficiently large historical data.

[0006] In conventional systems, the operators of networks do not have the flexibility to check previous clear codes or procedures associated with network entities. Further, existing solutions do not provide for a unified dashboard where subscriber experience can be captured and displayed for monitoring and analysis, thereby severely limiting the operator’s ability to study clear code data.

[0007] There is, therefore, a need in the art to provide a method and a system that can overcome the shortcomings of the existing prior arts.

SUMMARY

[0008] In an exemplary embodiment, a method for monitoring clear code trends is described.

[0009] The method includes receiving, by a processor, a first set of signals from a monitoring unit associated with a network. The first set of signals is indicative of a request for generating a trend report on one or more clear codes associated with a network function, wherein the trend report is indicative of clear code trends. The method also includes checking, by the processor, whether a pre-computed trend report for the network function is available in a first database. The method includes communicating, by the processor, the pre-computed trend report associated with the network function upon the pre-computed trend report being available in the first database. In addition, the method includes generating, by the processor, the trend report based on clear code data associated with the network function, and transmitting the trend report to the monitoring unit when the pre-computed trend report is not available in the first database. The method further includes forecasting, by an artificial intelligence (Al) engine, a trend for a period of time based on the trend report, and communicating, by the processor, at least one of the trend report and trends to the monitoring unit.

[0010] In some embodiments, the method includes analyzing, by the processor (202), the clear code data to determine at least one pattern, and processing the at least one pattern to generate an insight for predictive maintenance of the NF.

[0011] The method of claim 1, further comprising generating, by the processor (202), visualization for the trend, based on at least one of the trend report to show real-time changes.

[0012] In some embodiments, the method includes generating, by the processor, visualization for the trend based on at least one of the trend reports and the trend to provide real-time changes.

[0013] In some embodiments, the Al engine uses historical clear code data for performing the forecasting.

[0014] In some embodiments, the monitoring unit communicates, by the monitoring unit, a second request for one or more trend reports of clear codes selected by a user for a predefined interval. In another exemplary embodiment, a system for monitoring clear code trends is described. The system includes a memory configured to store one or more computer-readable instructions or routines in a non-transitory computer-read- able storage medium, fetched and executed to create or share data packets over a network service. The system further includes a processor configured to fetch and execute computer-readable instructions stored in the memory. The system further includes an interface configured to provide a communication pathway for one or more components of the system. The processor is configured to receive a first set of signals associated with a network wherein the first set of signals is indicative of a request for generating a trend report on one or more clear codes associated with the at least one network function. The trend report comprises at least one clear code trend. The processor is further configured to check whether a pre-computed trend report for the at least one network function is available in the first database. The processor is further configured to com- municate the pre-computed trend report associated with the at least one network function upon determining that the pre-computed trend report is available in the first database. The processor is further configured to generate and transmit the trend report based on the clear code data associated with the at least one network function when the pre-computed trend report is not available in the first database. The system also includes an artificial intelligence (Al) engine configured to forecast a clear code trend for a period of time based on the trend report. The processor is further configured to communicate at least one of the trend reports and the trend to a monitoring unit. In some embodiments, the system transmits the trend reports to the monitoring unit, and the trend report is displayed.

[0015] In some embodiments, the generated trend reports are stored in the first database such that subsequent requests with substantially similar set of parameters is retrieved from the first database instead of being recomputed.

[0016] In some embodiments, one or more pre-computed clear code trend reports are stored such that trend reports for requests comprising a similar set of parameters is retrieved from the first database instead of being recomputed.

[0017] In yet another exemplary embodiment, a user equipment (UE) configured for monitoring clear code trends is described. The user equipment includes a processor and a computer readable storage medium storing programming for execution by the processor. The programming includes instructions to receive a first set of signals associated with a network wherein the first set of signals is indicative of a request for generating a trend report on one or more clear codes associated with at least one network function, wherein the trend report comprises at least one clear code trend, check whether a pre-computed trend report for the at least one network function is available in a first database, communicate the pre-computed trend report associated with the at least one network function upon determining that the pre-computed trend report is available in the first database, and generate and transmit the trend report based on clear code data associated with the at least one network function when the pre-computed trend report is not available in the first database, forecast a clear code trend for a period of time based on the trend report, and communicate at least one of the trend report and the clear code trend to a monitoring unit. In yet another exemplary embodiment, a computer program product comprising a non-transitory computer-readable medium is described. The non-transitory computer-readable medium comprises instructions that, when executed by one or more processors, cause the one or more processors to perform a method. The method includes receiving, by a processor, a first set of signals from a monitoring unit associated with a network. The first set of signals is indicative of a request for generating a trend report on one or more clear codes created by a network entity associated with the network. The method further includes checking, by the processor, if a pre-computed trend report of a selected network entity for a similar set of parameters is stored in the first database. The method further includes generating, by the processor, the trend report and transmitting the trend report to the monitoring unit upon the pre-computed trend report being available in the first database. The method further includes retrieving, by the processor, the clear code data from a second database based on the set of parameters using a computation engine. The method further includes generating and forecasting, by an artificial intelligence (Al) engine, clear code trends based on the retrieved clear code data. The method further includes transmitting, by the processor, the trend reports to the monitoring unit.

[0018] The foregoing general description of the illustrative embodiments and the following detailed description thereof are merely exemplary aspects of the teachings of this disclosure and are not restrictive.

OBJECTS OF THE PRESENT DISCLOSURE

[0019] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.

[0020] An object of the present disclosure is to provide a system and a method for monitoring clear code trends. [0021] An object of the present disclosure is to provide a system and a method for analyzing trends in a plurality of time intervals such as hourly, daily, monthly, half- yearly, yearly, and the like.

[0022] An object of the present disclosure is to provide a system and a method that allows for network entity-wise trend analysis of clear codes and network entity procedure failures.

[0023] An object of the present disclosure is to provide a system and a method that uses an Artificial Intelligence (Al) model for predicting and forecasting trends in clear codes generated by network entities.

[0024] An object of the present disclosure is to provide a system and a method that continually retrains the Al model with the clear code data generated as the network provides services to user equipment in real-time.

[0025] An object of the present disclosure is to provide a system and a method that allows operators to take proactive steps to resolve network issues based on forecasted clear code trends.

[0026] An object of the present disclosure is to provide a system and a method that stores pre-computed data in databases such that similar queries can be retrieved from the database rather than being recomputed, thereby reducing computational burdens.

BRIEF DESCRIPTION OF DRAWINGS

[0027] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in 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.

[0028] FIG. 1 illustrates an exemplary network architecture for monitoring clear code trends, in accordance with embodiments of the present disclosure.

[0029] FIG. 2 illustrates an exemplary block diagram of a system, in accordance with embodiments of the present disclosure.

[0030] FIG. 3 illustrates an exemplary implementation of the system, in accordance with embodiments of the present disclosure.

[0031] FIG. 4 illustrates an exemplary flow diagram of a method for monitoring clear code trends, in accordance with embodiments of the present disclosure.

[0032] FIG. 5 illustrates an exemplary computer system in which or with which embodiments of the present disclosure may be implemented.

[0033] The foregoing shall be more apparent from the following more detailed description of the disclosure.

LIST OF REFERENCE NUMERALS

100 - Network architecture

102-1, 102-2 - Users

104-1, 104-2 - User equipment

106 - Network

108-System

110-1, 110-2 - Network entities

112-1, 112-2- one or more base stations

114- Monitoring Unit

202- Processor

204- Memory

206- Interface

208- Processing Engine 210- Database

210-1- First database

210-2- Second database

212- Request Processing Engine

214- Computation Engine

216- Al Engine

218- Other Units

300- Implementation of the system

400-Method

402-Step

404-Step

406-Step

408-Step

410-Step

412-Step

500- Computer system

510- External storage device

520- Bus

530- Main memory

540- Read only memory

550- Mass Storage Device

560- Communication Port

570- Computer System Processor

DETAILED DESCRIPTION OF DISCLOSURE

[0034] In the following description, for the purposes of explanation, various specific details are set forth 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.

[0035] 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.

[0036] 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 in order to avoid obscuring the embodiments.

[0037] Also, it is noted that individual embodiments may be described as a process which 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. [0038] 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 in a manner similar to the term “comprising” as an open transition word without precluding any additional or other elements.

[0039] 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.

[0040] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly 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 and all combinations of one or more of the associated listed items. [0041] The aspects of the present disclosure are directed to a system and a method for monitoring clear code trends. The system receives, from a monitoring unit, a first set of signals indicative of a request for generating one or more trend reports on clear codes created by a network entity of a network. The first set of signals may include a set of parameters having, among others, a time interval parameter. The system generates the trend report based on whether a pre-computed trend report is stored in a first database. To generate the trend report, the system dips into a second database for retrieving clear code data and generating the trend reports for the given set of parameters therewith. In some embodiments, the system uses an artificial intelligence (Al) engine to forecast clear code trends. In examples, a clear code trend may refer to the analysis of patterns in clear codes associated with call termination, service failure, etc., over time. The clear code trends may help identify common reasons for dropped or failed calls, service failures, etc., such as network congestion, busy lines, or other issues. In an example, generally the call failures may be maximum during morning rush hours due to network congestion. The call failures may be minimal during afternoon hours as people would not be using call services. This may be a pattern during a work week. However, there may be days, such as holidays or events such as bad weather, that can change the usage pattern and cause network congestion during unexpected hours. The clear code trend captures one or more patterns that include errors/issues during routine days and er- rors/issues caused due to events, etc, over a period of time. The period of time may be a day, a week, a month, 3 months, 6 months, a year, etc. The trend report may include one or more such identified clear code trends over a period of time. The trend report containing the pattern may be processed to generate an insight for predictive maintenance, network optimization, capacity planning, quality improvement, cost efficiency of the NF. The system may transmit the trend reports to the monitoring unit for monitoring, analysis, and performing preventative maintenance.

[0042] According to an embodiment, the system of the present disclosure takes inputs including request for a trend report or a trend or from a user interface. The system performs computation on data present in a distributed file system and shows the requested trend report or a trend to the end-user on the user interface. From the user interface (UI), the end users have the option to forecast future trends as well since the solution keeps on updating its data set and keeps on training itself with the incoming data by using artificial intelligence/machine learning (AI/ML) algorithms.

[0043] According to an embodiment, the process of the present disclosure is performed at the application level (microservice level). In some embodiments, the user requests trends data for a particular network function (NF) (for example, trends for the previous three months). The request flows to the workflow, and it checks whether the requested data is pre-computed or not by searching in the database. If the data is already precomputed, it sends the response to the user interface (UI). If the data is not pre-computed, it sends the request to a computation engine. The computation engine performs a computation activity by reading data from the distributed file system. Once computed data is available, it forwards the data to workflow. Workflow stores the calculated data in its database and sends the response to the user interface. The data as discussed herein refers to clear code data

[0044] The various embodiments throughout the disclosure will be explained in more detail with reference to FIGs. 1-5.

[0045] Referring to FIG. 1, a network architecture (100) may include one or more computing devices or user equipment (104-1, 104-2) associated with one or more users (102-1, 102-2) in an environment. A person of ordinary skill in the art will understand that one or more users (102-1, 102-2) may be individually referred to as the user (102) and collectively referred to as the users (102). Similarly, a person of ordinary skill in the art will understand that one or more user equipment (104-1, 104-2) may be individually referred to as the user equipment (104) and collectively referred to as the user equipment (104). A person of ordinary skill in the art will appreciate that the terms “computing device(s)” and “user equipment” may be used interchangeably throughout the disclosure. Although two user equipment (104) are depicted in FIG. 1, however any number of the user equipment (104) may be included without departing from the scope of the ongoing description.

[0046] In an embodiment, the user equipment (104) may include, but is not limited to, a handheld wireless communication device (e.g., a mobile phone, a smart phone, a phablet device, and so on), a wearable computer device (e.g., a head-mounted display computer device, a head-mounted camera device, a wristwatch computer device, and so on), a global positioning system (GPS) device, a laptop computer, a tablet computer, or another type of portable computer, a media playing device, a portable gaming system, and/or any other type of computer device with wireless communication capabilities, and the like. In an embodiment, the user equipment (104) may include, but is not limited to, any electrical, electronic, electro-mechanical, or an equipment, or a combination of one or more of the above devices such as virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, where the user equipment (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, an audio aid, a microphone, a keyboard, and input devices for receiving input from the user (102) or the entity such as touch pad, touch enabled screen, electronic pen, and the like. A person of ordinary skill in the art will appreciate that the user equipment (104) may not be restricted to the mentioned devices and various other devices may be used. The network architecture (100) may include a monitoring unit (114) having a user interface that provides audio-visual indications to the user (102) based on a set of signals transmitted by a system (108). In an embodiment, the monitoring unit (114) may be implemented on the UE (104) and may be used by operators of the system (108).

[0047] In an embodiment, the user equipment (104) may include smart devices operating in a smart environment, for example, an Internet of Things (loT) system. In such an embodiment, the user equipment (104) may include, but is not limited to, smart phones, smart watches, smart sensors (e.g., mechanical, thermal, electrical, magnetic, etc.), networked appliances, networked peripheral devices, networked lighting system, communication devices, networked vehicle accessories, networked vehicular devices, smart accessories, tablets, smart television (TV), computers, smart security system, smart home system, other devices for monitoring or interacting with or for the users (102) and/or entities, or any combination thereof. A person of ordinary skill in the art will appreciate that the user equipment (104) may include, but is not limited to, intelligent, multi-sensing, network-connected devices, that can integrate seamlessly with each other and/or with a central server or a cloud-computing system or any other device that is network-connected.

[0048] Referring to FIG. 1, the user equipment (104) may communicate with the system (108) through a network (106). In an embodiment, the network (106) may include a fifth generation (5G) network, a sixth generation (6G) network, or the like. The network (106) may enable the user equipment (104) to communicate with other devices in the network architecture (100) and/or with the system (108). The network (106) may include a wireless card or some other transceiver connection to facilitate this communication. In another embodiment, the network (106) may be implemented as, or include any of a variety of different communication technologies such as a wide area network (WAN), a local area network (LAN), a wireless network, a mobile network, a virtual private network (VPN), the Internet, the public switched telephone network (PSTN), or the like. In an embodiment, each of the UE (104) may have a unique identifier attribute associated therewith. In an embodiment, the unique identifier attribute may be indicative of mobile station international subscriber directory number (MSISDN), international mobile equipment identity (IMEI) number, international mobile subscriber identity (IMSI), subscriber permanent identifier (SUPI) and the like.

[0049] In an embodiment, the network (106) may include one or more base stations (112), which the UEs (104) may connect to and request services from. The base station (112) may be a network infrastructure that provides wireless access to one or more terminals associated therewith. The base station (112) may have coverage defined to be a predetermined geographic area based on the distance over which a signal may be transmitted. The base station (112) may include, but not be limited to, wireless access point, evolved NodeB (eNodeB), 5G node or next generation NodeB (gNB), wireless point, transmission/reception point (TRP), and the like. In an embodiment, the base station (112) may include one or more operational units that enable telecommunication between two or more UEs (104). In an embodiment, the one or more operational units may include, but not be limited to, transceivers, baseband unit (BBU), remote radio unit (RRU), antennae, mobile switching centres, radio network control units, one or more processors associated thereto, and a plurality of network entities (110-1, 110-2) (also interchangeably referred to as network function (NF) in the disclosure) such as access and mobility management function (AMF) unit, session management function (SMF) unit, network exposure function (NEF) units, or any custom built functions executing one or more processor-executable instructions, but not limited thereto.

[0050] In an embodiment, clear code data may be generated as the operational units or network entities (110) interact with each other and the UE (104) to provide services. In an embodiment, the clear codes may provide indications of success or failures in providing services to the UEs (104). In an embodiment, the clear codes may also indicate causes of failures. In an example, the network entities (110) may create a ‘failed’ clear code, along with a message indicating the reason for failure, such as ‘network function time-out.’ In such examples, the clear code may indicate that the failure in providing services was caused by a failure in execution of network entity procedures. In an embodiment, the clear codes may also include one or more attributes including, but not limited to, subscriber detail records, UE attributes, location attributes, network entity identity attributes, session detail attributes, and the like.

[0051] In an embodiment, the system (108) may be coupled to a monitoring unit (114) that may provide an audio-visual interface to the user (102) for monitoring and analysing data. In an embodiment, the monitoring unit (114) may provide an interface, including, but not limited to, a graphical user interface (GUI), an application programming interface (API) or a command line interface (CLI). In an embodiment, the monitoring unit (114) may be configured to provide real-time visualizations and trend re- ports of clear code data provided by the system (108). In an embodiment, the monitoring unit (114) may provide a dashboard for visualizing and monitoring trends in clear codes data and its changes in real time. In an embodiment, the monitoring unit (114) may be used by users (102) or operators of the system (108).

[0052] In an embodiment, a user (102) or operator of the system (108) may use the monitoring unit (114) to transmit a request to generate trend reports of the clear code data for a set of parameters. The first set of signals may include a set of parameters having, among others, a time interval parameter. In an embodiment, the system (108) may allow operators to analyze clear code trends between any custom time intervals. In an embodiment, the operator may select one or more network entities (110) for which the trend reports may be required. In an embodiment, the system (108) may allow for network entity-wise trend report generation, whereby the operators may be able to uniquely identify the network entity (110) having clear codes values greater than a predetermined performance threshold. The system (108) may receive the request and determine whether a pre-computed trend report for a network entity (110) selected by a user for similar set of parameters is stored in a first database 210-1, as shown in FIG. 3. If the pre-computed trend report is available in the first database 210-1, the system (108) retrieves and transmits said trend report to the monitoring unit (114). The pre-computed trend report may refer to reports that are already generated by the system (108), periodically or on demand and stored in a database (210).

[0053] In an embodiment, if the pre-computed trend report is unavailable in the first database 210-1, the system (108) may retrieve the clear code data from a second database (210-2), as shown in FIG. 3, based on the set of parameters, and generate the trends reports for the clear code data therewith. The system (108) may store the generated trend reports in the first database (210-1) such that subsequent requests with substantially similar set of parameters may be retrieved from said first database (210-1) instead of being recomputed.

[0054] In an embodiment, the trend reports may include the network entity-wise distribution of the clear code data. In an embodiment, the trend reports may include one or more visualizations of the clear code data, the one or more visualizations being generated based on a predetermined set of visualization suite. In an embodiment, the trend report may also include key performance indicators (KPIs) derived from the clear code data that indicate the health and performance of the network (106). In an embodiment, the trend report may also identify issues or bottlenecks causing degradations in performance. In an embodiment, the system (108) may include the trend forecasts of the clear code data for each network entity (110) in the trend reports. In an embodiment, the system (108) may use an Al engine, such as an Al engine (216) of FIG. 2, for generating the forecasts. In an embodiment, the system (108) may also generate one or more recommendations for preventative maintenance or pre-emptive expansion of the network (106). In an embodiment, the trend reports may be used to resolve network issues and appropriately upgrade specifications or configurations of the network (106). The system (108) may transmit the trend reports to the monitoring unit (114), wherein the trend report may be displayed.

[0055] In accordance with embodiments of the present disclosure, the system (108) may be designed and configured for monitoring clear code trends. In an embodiment, the system (108) may also be configured to provide reports on clear code trends on user defined intervals.

[0056] FIG. 2 illustrates a block diagram of the system (108), in accordance with embodiments of the present disclosure.

[0057] In an aspect, the system (108) may include one or more processor(s) (202) and a memory (204). The one or more processor(s) (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, edge or fog 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-read- able 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 include 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.

[0058] Referring to FIG. 2, the system (108) may also include an interface(s) (206). The interface(s) (206) may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as RO devices, storage devices, and the like. The interface(s) (206) may facilitate communication to/from the system (108). The in- terface(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 unit/engine(s) (208) and a database (210).

[0059] In an embodiment, the processing unit/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-tran- sitory machine -readable storage medium and the hardware for the processing engine(s) (208) may include 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 (108) may include 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 (108) and the processing resource. In other examples, the processing engine(s) (208) may be implemented by electronic circuitry.

[0060] In an embodiment, the system (108) may include one or more databases such as a first database (210-1) and a second database (210-2) (collectively referred to as database or databases (210)). In an embodiment, the database (210) includes data that may be either stored or generated as a result of functionalities implemented by any of the components of the processor (202) or the processing engines (208). In an embodiment, the database (210) may be separate from the system (108). In an embodiment, the database (210) may be indicative of including, but not limited to, a relational database, a distributed database, distributed file sharing system, a cloud-based database, or the like.

[0061] In an embodiment, the first database (210-1) may be configured to store precomputed clear code trend reports. In an embodiment, the clear code trend reports may be associated with requests received from the monitoring unit (114). In an embodiment, the pre-computed clear code trend reports may be stored such that trend reports for requests having similar set of parameters can be retrieved from the first database (210- 1 ) instead of being recomputed. In an embodiment, the clear code data may be stored in the second database (210-2). The clear code data may be retrieved by the system (108) for processing the requests from a monitoring unit (114). In an embodiment, the monitoring unit (114) is configured to transmit a second request for one or more trend reports of clear codes generated by a network entity (110) selected by a user for a predefined interval.

[0062] In an exemplary embodiment, the processing engine (208) may include one or more engines selected from any of a request processing engine (212), a computation engine (214), an Al engine (216), and other engines (218) having functions that may include, but are not limited to, testing, storage, and peripheral functions, such as wireless communication unit for remote operation, audio unit for alerts and the like, as described in FIG. 3. The computation engine (214) is configured to compute the trend reports by retrieving clear code data from the second database (210-2) based on the set of parameters if the pre-computed trend report is unavailable in the first database (210- 1). The Al engine (216) is configured to forecast the clear code trends based on a retrieved clear code data.

[0063] For forecasting, the Al engine (216) may collect historical clear code data on clear codes associated with network functions, procedures/processes associated with network functions, including timestamps, frequency, and associated metadata. The historical clear code data may be in the range of 1 day to few years. The collected data may be normalized and pre-processed. In examples, normalizing and preprocessing includes analyzing the data, identifying anomalies, outliers, handling missing values, etc. Further, the Al engine (216) may identify features from the clear code data. The Al engine (216) may normalize the features. Further, the Al engine (216) may identify relevant features that might influence clear code occurrences, such as time of day, network load, or geographical location. Based on the features, the Al engine (216) may select appropriate machine learning models such as time series models (e.g., autoregressive integrated moving average (ARIMA), and long-term short memory (LSTM)) or classification models (e.g., random forests, neural networks). The selected model may be trained on historical data, using techniques like cross-validation to optimize performance. In some examples, the training data may be about 80% of the clear code dataset, and the remaining 20% of the clear code dataset may be used for testing and validation. Post the training, the Al engine (216) may evaluate the chosen model's accuracy using metrics such as precision, recall, or mean absolute error. In some examples, the chosen models may be tested with the testing dataset. In aspects when there is sufficient confidence, the Al engine (216) may deploy the evaluated model. In examples, a confidence level threshold may be between 85% to 95% to gain sufficient confidence. The Al engine (216) may deploy the model in a real-time system to predict future clear code trends and enable proactive network management. As there are possibilities of trend variation, the Al engine (216) may update the model frequently with new clear code data to continuously retrain to maintain accuracy over time. In aspects, the Al engine (216) stores the trend reports in its database and trains the models with the updated clear code for future requests. The deployed model may be used by the Al engine (216) to predict or forecast the one or more trends.

[0064] According to one embodiment of the present disclosure, the system (108) transmits the trend reports to the monitoring unit (114), and the trend report is displayed. According to one embodiment of the present disclosure, the generated trend reports are stored in the first database (210-1) such that subsequent requests with similar set of parameters are retrieved from the first database instead of being recomputed. According to one embodiment of the present technology, one or more pre-computed clear code trend reports are stored such that trend reports for requests comprising a similar set of parameters are retrieved from the first database (210-1) instead of being recomputed. In an embodiment, each of the processing engines (208) may be communicatively coupled to implement the system (108) and method of the present disclosure.

[0065] FIG. 3 illustrates an exemplary implementation 300 of the system (108), in accordance with embodiments of the present disclosure. In an embodiment, a user (102) or operator of the system (108) may use the monitoring unit (114) to transmit a request to generate trend reports of the clear code data for a set of parameters. In an example, the monitoring unit (114) may transmit a request for trend reports of clear codes generated by a network entity (110) selected by the user (102) or operator, for a predefined interval, for example, 3 months. The system (108) may receive the request and determine whether a pre-computed trend report for the selected network entity (110) for substantially similar set of parameters is stored in the first database (210-1). If the precomputed trend report is available in the first database (210-1), the system (108) retrieves and transmits said trend report to the monitoring unit (114). In an embodiment, the request may be processed as described herein by the request processing engine (212) of the system (108).

[0066] In an embodiment, if the pre-computed trend report is unavailable in the first database (210-1), the system (108) may request the computation engine (214) to compute the trend reports. While FIG. 3 describes an embodiment where the computation engine (214) is external to the system (108), it may be appreciated by those skilled in the art that the computation engine (214) may be implemented within the processing engines (208) of the system (108), as shown in FIG. 2. In an embodiment, the computation engine (214) may retrieve the clear code data from the second database (210-2) based on the set of parameters and generate the trend reports for the clear code data therewith. In an embodiment, the computation engine (214) may return the generated trend reports to the system (108).

[0067] In an embodiment, the Al engine (216), as shown in FIG. 2, may be configured to forecast the clear code trends based on the retrieved clear code data. Forecasting the clear code trends may allow operators of the system (108) to perform preventative maintenance on the network (106). The system (108) may store the generated trend reports in the first database (210-1) such that subsequent requests with substantially similar set of parameters may be retrieved from the first database (210-1) instead of being recomputed. The system (108) may transmit the trend reports to the monitoring unit (114), wherein the trend report may be displayed.

[0068] FIG. 4 illustrates an exemplary flow diagram of a method (400) for monitoring clear code trends, in accordance with embodiments of the present disclosure.

[0069] Step (402) includes receiving, by a processor (202), a first set of signals from a monitoring unit (114) associated with a network (106). The first set of signals is indicative of a request for generating a trend report on one or more clear codes associated with a network function. The trend report includes at least one clear code trend over a period of time.

[0070] Step (404) includes checking, by the processor (202), whether a pre-computed trend report for the network function is available in a first database (210-1).

[0071] Step (406) includes communicating, by the processor (202), the pre-computed trend report associated with the network function upon the pre-computed trend report being available in the first database (210-1).

[0072] Step (408) includes generating, by the processor (202), the trend report based on clear code data associated with the network function and transmitting the trend report to the monitoring unit (114) when the pre-computed trend report is not available in the first database (210-1).

[0073] Step (410) includes forecasting, by an artificial intelligence (Al) engine (216), a clear code trend for a period of time based on the trend report. [0074] Step (412) includes communicating, by the processor (202), at least one of the trend reports and the trend to the monitoring unit (114). In an exemplary embodiment, the present disclosure discloses the user equipment (UE) (104) configured for monitoring clear code trends. The user equipment includes the processor (202) and a computer readable storage medium storing programming for execution by the processor (202). The programming includes instructions for monitoring clear code trends include receiving, the first set of signals from the monitoring unit (114) associated with the network (106), where the first set of signals is indicative of the request for generating the trend report on one or more clear codes created by the network entity (110) associated with the network (106), checking, if a pre-computed trend report of a selected network entity for a similar set of parameters is stored in the first database (210-1), generating, the trend report and transmitting the trend report to the monitoring unit (114) upon the pre-computed trend report being available in the first database (210-1), retrieving, the clear code data from the second database (210-2) based on the set of parameters using the computation engine (214), generating and forecasting clear code trends based on the retrieved clear code data and transmitting, the trend reports to the monitoring unit (114).

[0075] FIG. 5 illustrates an exemplary computer system (500) in which or with which embodiments of the present disclosure may be implemented. Elements of the disclosure including the system (108), the monitoring unit (114), the user equipments (104-1-N), etc., may be implemented using the computer system (500) to perform various embodiments disclosed by the disclosure.

[0076] As shown in FIG. 5, the computer system (500) may include an external storage device (510), a bus (520), a main memory (530), a read-only memory (540), a mass storage device (550), a communication port (560), and a processor (570). A person skilled in the art will appreciate that the computer system (500) may include more than one processor (570) and communication ports (560). The processor (570) may include various modules associated with embodiments of the present disclosure. [0077] In an embodiment, the communication port (560) 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 fiber, a serial port, a parallel port, or other existing or future ports. The communication port (560) may be chosen depending on the network (106), such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system (500) connects.

[0078] In an embodiment, the memory (530) may be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read-only memory (540) may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or Basic In- put/Output System (BIOS) instructions for the processor (570).

[0079] In an embodiment, the mass storage (550) may be any current or future mass storage solution, which may be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Lirewire interfaces), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g., an array of disks (e.g., SATA arrays).

[0080] In an embodiment, the bus (520) communicatively couples the processor(s) (570) with the other memory, storage, and communication blocks. The bus (520) may be, e.g., a Peripheral Component Interconnect (PCI)/PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), Universal Serial Bus (USB) or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects the processor (570) to the computer system (500). [0081] Optionally, operator and administrative interfaces, e.g., a display, keyboard, joystick, and cursor control device, may also be coupled to the bus (520) to support direct operator interaction with the computer system (500). Other operator and administrative interfaces may be provided through network connections connected through the communication port (560). The components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system (500) limit the scope of the present disclosure.

[0082] The present disclosure provides technical advancement related to managing clear code trends associated with the NF and the NF procedures in telecommunications systems. This advancement addresses the limitations of existing solutions that include managing large volumes of clear codes that are generated at rapid pace. By implementing the disclosure, the clear code data is not only organized and managed but mined for trend reports and forecasting. This approach helps keep track of issues in the network, identify risk factors, and mitigate them in advance, thereby improving overall network efficiency and user experience.

[0083] 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 to be implemented merely as illustrative of the disclosure and not as limitation.

ADVANTAGES OF THE PRESENT DISCLOSURE

[0084] The present disclosure provides a system and a method for monitoring clear code trends that analyses trends in a plurality of time intervals such as hourly, daily, monthly, half-yearly, yearly, and the like.

[0085] The present disclosure provides a system and a method that allows for network entity-wise trend analysis of clear codes and network entity procedure failures.

[0086] The present disclosure provides a system and a method that uses an artificial intelligence (Al) model for predicting and forecasting trends in clear codes generated by network entities. [0087] The present disclosure provides a system and a method that continually retrains the Al model with the clear code data generated as the network provides services to user equipment in real time.

[0088] The present disclosure provides a system and a method that allows operators to take proactive steps to resolve network issues based on forecasted clear code trends.

[0089] The present disclosure provides a system and a method that stores pre-computed data in databases such that similar queries can be retrieved from database rather than recomputed, thereby reducing computational burdens. In traditional systems, user did not have the flexibility to check the past trends of the clear codes, procedures of a particular network function (NF) and for particular NF. The end user had to keep the track about past behaviours. The present technology enables end users to view all these reports in a single dashboard. With the clear code wise, NF procedure wise and NF wise trending report, solution helps user in observing, monitoring the trend of these attributes at various levels like hour wise trend, day wise trend, month wise trend, last 6 months trend and year wise trend. The disclosed solution helps user to track the trends and based on its AI/ML model it can predict/forecast the trend as well, which helps end user in taking appropriate actions beforehand. Since it is storing the output of the precomputed data in database, if same query comes to fetch the data for same time period, the present system just returns the present calculated data from database. Accordingly, the present technology reduces computation for every query as well.

Claims

We Claim:

1. A method (400) for monitoring clear code trends, the method (400) comprising: receiving (402), by a processor (202), a first set of signals from a monitoring unit (114) associated with a network (106), wherein the first set of signals is indicative of a request for generating a trend report on clear codes associated with a network function, wherein the trend report comprises at least one clear code trend over a period of time; checking (404), by the processor (202), whether a pre-computed trend report for the network function, related to the request, is available in a first database (210-1); communicating (406), by the processor (202), the pre-computed trend report associated with the network function upon the pre-computed trend report related to the request being available in the first database (210-1); generating (406), by the processor (202), the trend report based on clear code data associated with the network function, and transmitting the trend report to the monitoring unit (114) when the pre-computed trend report related to the request is not available in the first database (210-1); forecasting (410), by an artificial intelligence (Al) engine (216), a clear code trend for a period of time, based on the trend report; and communicating (412), by the processor (202), at least one of the trend reports and the clear code trend to the monitoring unit (114).

2. The method of claim 1, further comprising: analyzing, by the processor (202), the clear code data to determine at least one pattern; and processing the at least one pattern to generate an insight for predictive maintenance of the NF.

3. The method of claim 1, further comprising generating, by the processor (202), visualization for the trend, based on at least one of the trend report to show real-time changes.

4. The method of claim 1, wherein the Al engine (216) uses historical clear code data for performing the forecasting.

5. The method of claim 1, further comprising communicating, by the monitoring unit (114), a second request for one or more trend reports of clear codes selected by a user for a predefined interval.

6. A system (108) for monitoring clear code trends, the system (108) comprising: a memory (204) configured to store one or more computer-readable instructions or routines in a non-transitory computer-readable storage medium, fetched and executed to create or share data packets over a network service; a processor (202) configured to fetch and execute computer-readable instructions stored in the memory (204); an interface (206) configured to provide a communication pathway for one or more components of the system (108); a first database (210-1) for storing one or more pre-computed trend reports for at least one network function (110) of a plurality of network functions; a second database (210-2) for storing clear code data associated with the plurality of network functions; the processor (202) configured to: receive a first set of signals associated with a network (106), wherein the first set of signals is indicative of a request for generating a trend report on one or more clear codes associated with the at least one network function, and wherein the trend report comprises at least one clear code trend over a period of time; check whether a pre-computed trend report for the at least one network function is available in the first database (210-1); communicate the pre-computed trend report associated with the at least one network function upon determining that the pre-computed trend report is available in the first database (210-1); and generate and transmit the trend report based on the clear code data associated with the network function when the pre-computed trend report is not available in the first database (210-1); an artificial intelligence (Al) engine (216 configured to forecast a clear code trend for a period of time based on the trend report; and the processor (202) configured to communicate at least one of the trend reports and the clear code trend to the monitoring unit (114).

7. The system (108) of claim 6, further comprising a monitoring unit (114) configured to transmit a second request for one or more trend reports of clear codes generated by a network entity (110) for a predefined interval.

8. The system (108) of claim 6, wherein the monitoring unit (114) transmits the trend reports to a user equipment (104).

9. The system (108) of claim 6, wherein the generated trend reports are stored in the first database (210-1) such that subsequent requests with similar set of parameters are retrieved from the first database (210-1) instead of being recomputed.

10. The system (108) of claim 6, wherein the one or more pre-computed trend reports are stored in the first database (210-1) to enable retrieval of the one or more precomputed trend reports from the first database (210-1) instead of being recomputed.

11. A user equipment (UE) (104) configured for monitoring clear code trends, the user equipment (104) comprising: a processor (202); and a computer readable storage medium storing programming for execution by the processor (202), the programming including instructions to: receive a first set of signals associated with a network (106), wherein the first set of signals is indicative of a request for generating a trend report on one or more clear codes associated with at least one network function, wherein the trend report comprises at least one clear code trend over a period of time; check whether a pre-computed trend report for the at least one network function is available in the first database (210-1); communicate the pre-computed trend report associated with the at least one network function upon determining that the pre-computed trend report is available in the first database (210-1); and generate and transmit the trend report based on clear code data associated with the network function when the pre-computed trend report is not available in the first database (210-1); forecast a clear code trend for a period of time based on the trend report; and communicate at least one of the trend reports and the clear code trend to the monitoring unit (114).

12. A computer program product comprising a non -transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform a method for monitoring clear code trends, the method (400) comprising: receiving (402), by a processor (202), a first set of signals from a monitoring unit (114) associated with a network (106), wherein the first set of signals is indicative of a request for generating a trend report on clear codes associated with a network function, wherein the trend report comprises at least one clear code trend over a period of time; checking (404), by the processor (202), whether a pre-computed trend report for the network function, related to the request, is available in a first database (210-1); communicating (406), by the processor (202), the pre-computed trend report associated with the network function upon the pre-computed trend report related to the request being available in the first database (210-1); generating (406), by the processor (202), the trend report based on clear code data associated with the network function, and transmitting the trend report to the monitoring unit (114) when the pre-computed trend report related to the request is not available in the first database (210-1); forecasting (410), by an artificial intelligence (Al) engine (216), a clear code trend for a period of time, based on the trend report; and communicating (412), by the processor (202), at least one of the trend reports and the trend to the monitoring unit (114).