FORM 2
THE PATENTS ACT, 1970 (39 of 1970) THE PATENTS RULES, 2003
COMPLETE SPECIFICATION
(See section 10; rule 13)
TITLE OF THE INVENTION
SYSTEM AND METHOD FOR MONITORING CLEAR CODE TRENDS
APPLICANT
JIO PLATFORMS LIMITED
of Office-101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad -
380006, Gujarat, India; Nationality : India
The following specification particularly describes
the invention and the manner in which
it is to be performed

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,
5 trademark, Integrated Circuit (IC) layout design, and/or trade dress protection, belong-
ing 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
10 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 mon-
15 itoring clear code trends.
BACKGROUND OF DISCLOSURE
[0003] The following description of related art is intended to provide background in-formation pertaining to the field of the disclosure. This section may include certain
20 aspects of the art that may be related to various features of the present disclosure. How-
ever, it should be appreciated that this section be used only to enhance the understand¬ing 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
25 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
2

call termination and taking preventative or alleviative measures to resolve any abnor-malities 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
5 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
10 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.
15 SUMMARY
[0008] In an exemplary embodiment, a method for monitoring clear code trends is de-scribed.
[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
20 request for generating a trend report on one or more clear codes associated with a net-
work 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
25 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 mon¬itoring unit when the pre-computed trend report is not available in the first database.
The method further includes forecasting, by an artificial intelligence (AI) engine, a
3

trend for a period of time based on the trend report, and communicating, by the proces¬sor, 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
5 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, visu-
10 alization 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 AI engine uses historical clear code data for per-forming the forecasting.
[0014] In some embodiments, the monitoring unit communicates, by the monitoring
15 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 net-
20 work 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
25 a trend report on one or more clear codes associated with the at least one network func¬
tion. 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-
4

municate the pre-computed trend report associated with the at least one network func¬
tion upon determining that the pre-computed trend report is available in the first data¬
base. 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
5 pre-computed trend report is not available in the first database. The system also in-
cludes an artificial intelligence (AI) engine configured to forecast a clear code trend for
a period of time based on the trend report. The processor is further configured to com¬
municate 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
10 trend report is displayed.
[0015] In some embodiments, the generated trend reports are stored in the first data-base such that subsequent requests with substantially similar set of parameters is re-trieved from the first database instead of being recomputed.
[0016] In some embodiments, one or more pre-computed clear code trend reports are
15 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 pro-
20 cessor. The programming includes instructions to receive a first set of signals associ¬
ated with a network wherein the first set of signals is indicative of a request for gener¬
ating 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
25 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
5

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 com¬
puter program product comprising a non-transitory computer-readable medium is de¬
scribed. The non-transitory computer-readable medium comprises instructions that,
5 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 pro-
10 cessor, 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
15 based on the set of parameters using a computation engine. The method further includes
generating and forecasting, by an artificial intelligence (AI) 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 fol-
20 lowing 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
25 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.
6

[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
5 allows for network entity-wise trend analysis of clear codes and network entity proce-
dure failures.
[0023] An object of the present disclosure is to provide a system and a method that uses an Artificial Intelligence (AI) model for predicting and forecasting trends in clear codes generated by network entities.
10 [0024] An object of the present disclosure is to provide a system and a method that
continually retrains the AI 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
15 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.
20 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 differ¬
ent drawings. Components in the drawings are not necessarily to scale, emphasis in-
25 stead being placed upon clearly illustrating the principles of the present disclosure.
Some drawings may indicate the components using block diagrams and may not rep¬
resent the internal circuitry of each component. It will be appreciated by those skilled
7

in the art that disclosure of such drawings includes the disclosure of electrical compo-nents, electronic components or circuitry commonly used to implement such compo-nents.
[0028] FIG. 1 illustrates an exemplary network architecture for monitoring clear code
5 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.
10 [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
15 description of the disclosure.
LIST OF REFERENCE NUMERALS
100 – Network architecture
102-1, 102-2 – Users
20 104-1, 104-2 – User equipment
106 - Network
108-System
110-1, 110-2 – Network entities
112-1, 112-2– one or more base stations
25 114– Monitoring Unit
202– Processor
204– Memory
206– Interface
208– Processing Engine
8

210– Database
210-1– First database
210-2– Second database
212– Request Processing Engine
5 214– Computation Engine
216– AI Engine
218- Other Units
300- Implementation of the system
400-Method
10 402-Step
404-Step
406-Step
408-Step
410-Step
15 412-Step
500- Computer system
510- External storage device
520- Bus
530- Main memory
20 540- Read only memory
550- Mass Storage Device
560- Communication Port
570- Computer System Processor
25 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
9

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 prob¬
lems discussed above might not be fully addressed by any of the features described
5 herein.
[0035] The ensuing description provides exemplary embodiments only, and is not in-tended 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
10 understood that various changes may be made in the function and arrangement of ele-
ments 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.
15 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.
20 [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 dia¬gram, or a block diagram. Although a flowchart may describe the operations as a se¬quential 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
25 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 corre¬spond to a return of the function to the calling function or the main function.
10

[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 de¬
scribed herein as “exemplary” and/or “demonstrative” is not necessarily to be con-
5 strued 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
10 open transition word without precluding any additional or other elements.
[0039] Reference throughout this specification to “one embodiment” or “an embodi¬
ment” 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
15 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 embod-
20 iments 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,
25 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.
11

[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
5 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 (AI) engine to forecast
10 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 fail¬
ures, etc., such as network congestion, busy lines, or other issues. In an example, gen¬
erally the call failures may be maximum during morning rush hours due to network
15 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-
20 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 mainte¬
nance, network optimization, capacity planning, quality improvement, cost efficiency
25 of the NF. The system may transmit the trend reports to the monitoring unit for moni¬
toring, 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
12

performs computation on data present in a distributed file system and shows the re¬
quested 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
5 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
10 data is pre-computed or not by searching in the database. If the data is already pre-
computed, it sends the response to the user interface (UI). If the data is not pre-com-
puted, 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
15 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 com-
20 puting 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 individ-
25 ually 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
13

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 pha-
5 blet device, and so on), a wearable computer device (e.g., a head-mounted display com¬
puter 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 sys¬
tem, and/or any other type of computer device with wireless communication capabili-
10 ties, 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 combi¬
nation of one or more of the above devices such as virtual reality (VR) devices, aug¬
mented reality (AR) devices, laptop, a general-purpose computer, desktop, personal
digital assistant, tablet computer, mainframe computer, or any other computing device,
15 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
20 be restricted to the mentioned devices and various other devices may be used. The net¬
work 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 trans¬
mitted by a system (108). In an embodiment, the monitoring unit (114) may be imple¬
mented on the UE (104) and may be used by operators of the system (108).
25 [0047] In an embodiment, the user equipment (104) may include smart devices oper¬
ating in a smart environment, for example, an Internet of Things (IoT) 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,
14

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
5 will appreciate that the user equipment (104) may include, but is not limited to, intelli-
gent, 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 sys-
10 tem (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 net¬
work (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 commu-
15 nication. 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 at-
20 tribute associated therewith. In an embodiment, the unique identifier attribute may be
indicative of mobile station international subscriber directory number (MSISDN), in¬
ternational 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
25 (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
15

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
5 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
10 (SMF) unit, network exposure function (NEF) units, or any custom built functions ex-
ecuting 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
15 providing services to the UEs (104). In an embodiment, the clear codes may also indi-
cate 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.
20 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 analys-
25 ing data. In an embodiment, the monitoring unit (114) may provide an interface, in¬
cluding, but not limited to, a graphical user interface (GUI), an application program¬
ming interface (API) or a command line interface (CLI). In an embodiment, the moni¬
toring unit (114) may be configured to provide real-time visualizations and trend re-
16

ports of clear code data provided by the system (108). In an embodiment, the monitor¬
ing 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).
5 [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.
10 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
15 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
20 (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 data¬
base (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 gener-
25 ated trend reports in the first database (210-1) such that subsequent requests with sub¬
stantially 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 dis-tribution of the clear code data. In an embodiment, the trend reports may include one
17

or more visualizations of the clear code data, the one or more visualizations being gen¬
erated 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,
5 the trend report may also identify issues or bottlenecks causing degradations in perfor-
mance. 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 AI engine, such as an AI engine (216) of FIG. 2, for generating
the forecasts. In an embodiment, the system (108) may also generate one or more rec-
10 ommendations 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 sys¬
tem (108) may transmit the trend reports to the monitoring unit (114), wherein the trend
report may be displayed.
15 [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 em-
20 bodiments 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 microcontrol¬
lers, digital signal processors, central processing units, logic circuitries, and/or any de-
25 vices 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
18

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 ran¬
dom-access memory (RAM), or non-volatile memory such as erasable programmable
read-only memory (EPROM), flash memory, and the like.
5 [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 I/O 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 compo-
10 nents 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 instruc¬
tions) to implement one or more functionalities of the processing engine(s) (208). In
15 examples described herein, such combinations of hardware and programming may be
implemented in several different ways. For example, the programming for the pro¬
cessing 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 ex-
20 ecute 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 ma¬
chine-readable storage medium storing the instructions and the processing resource to
execute the instructions, or the machine-readable storage medium may be separate but
25 accessible to the system (108) and the processing resource. In other examples, the pro¬
cessing 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
19

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 embodi¬
ment, 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 data-
5 base, 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 pre-computed 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,
10 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
15 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 pre-defined 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
20 engine (214), an AI engine (216), and other engines (218) having functions that may
include, but are not limited to, testing, storage, and peripheral functions, such as wire-less communication unit for remote operation, audio unit for alerts and the like, as de-scribed 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
25 of parameters if the pre-computed trend report is unavailable in the first database (210-
1). The AI engine (216) is configured to forecast the clear code trends based on a re-trieved clear code data. [0063] For forecasting, the AI engine (216) may collect historical clear code data on
clear codes associated with network functions, procedures/processes associated with
20

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,
5 etc. Further, the AI engine (216) may identify features from the clear code data. The
AI engine (216) may normalize the features. Further, the AI engine (216) may identify
relevant features that might influence clear code occurrences, such as time of day, net¬
work load, or geographical location. Based on the features, the AI engine (216) may
select appropriate machine learning models such as time series models (e.g., auto-
10 regressive 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 opti¬
mize 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
15 and validation. Post the training, the AI engine (216) may evaluate the chosen model's
accuracy using metrics such as precision, recall, or mean absolute error. In some ex¬
amples, the chosen models may be tested with the testing dataset. In aspects when
there is sufficient confidence, the AI engine (216) may deploy the evaluated model. In
examples, a confidence level threshold may be between 85% to 95% to gain sufficient
20 confidence. The AI 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 pos¬
sibilities of trend variation, the AI engine (216) may update the model frequently with
new clear code data to continuously retrain to maintain accuracy over time. In aspects,
the AI engine (216) stores the trend reports in its database and trains the models with
25 the updated clear code for future requests. The deployed model may be used by the AI
engine (216) to predict or forecast the one or more trends.
[0064] According to one embodiment of the present disclosure, the system (108) trans¬mits 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
21

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. Accord¬
ing 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
5 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 cou¬
pled to implement the system (108) and method of the present disclosure.
[0065] FIG. 3 illustrates an exemplary implementation 300 of the system (108), in ac¬
cordance with embodiments of the present disclosure. In an embodiment, a user (102)
10 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 gen¬
erated 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 deter-
15 mine 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 pre-
computed trend report is available in the first database (210-1), the system (108) re¬
trieves 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
20 (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 com¬
pute 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
25 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 compu-tation 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
22

therewith. In an embodiment, the computation engine (214) may return the generated trend reports to the system (108).
[0067] In an embodiment, the AI 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
5 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
10 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 indic-
15 ative 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).
20 [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 re-
25 port 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 (AI) engine (216), a clear code trend for a period of time based on the trend report.
23

[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 monitor¬
ing clear code trends. The user equipment includes the processor (202) and a computer
5 readable storage medium storing programming for execution by the processor (202).
The programming includes instructions for monitoring clear code trends include re-ceiving, the first set of signals from the monitoring unit (114) associated with the net-work (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
10 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
15 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
20 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 embod-iments 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
25 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.
24

[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
5 (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
10 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. Exem¬
plary mass storage solutions include, but are not limited to, Parallel Advanced Tech-
15 nology 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 Firewire interfaces), one or more optical discs, Redundant Array of In¬
dependent 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)
20 (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 con¬
necting 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).
25 [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 admin¬
istrative interfaces may be provided through network connections connected through
25

the communication port (560). The components described above are meant only to ex-emplify various possibilities. In no way should the aforementioned exemplary com-puter system (500) limit the scope of the present disclosure.
[0082] The present disclosure provides technical advancement related to managing
5 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 implement¬
ing 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,
10 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 embodi¬
ments, 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 princi-
15 ples 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.
20 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
25 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 (AI) model for predicting and forecasting trends in clear codes generated
by network entities.
26

[0087] The present disclosure provides a system and a method that continually retrains the AI 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
5 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-com-puted 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
10 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
15 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 pre-computed 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,
20 the present technology reduces computation for every query as well.
27

WE CLAIM:
5 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
10 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
15 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 mon¬
itoring unit (114) when the pre-computed trend report related to the request is not avail¬
able in the first database (210-1);
20 forecasting (410), by an artificial intelligence (AI) 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:
25 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 mainte-nance of the NF.
28

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 AI engine (216) uses historical clear code
5 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:
10 a memory (204) configured to store one or more computer-readable instructions
or routines in a non-transitory computer-readable storage medium, fetched and exe-cuted to create or share data packets over a network service;
a processor (202) configured to fetch and execute computer-readable instruc¬
tions stored in the memory (204);
15 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 plu-
20 rality 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
25 network function, and wherein the trend report comprises at least one
clear code trend over a period of time;
29

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
5 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 (AI) engine (216 configured to forecast a clear code
10 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) con¬
figured to transmit a second request for one or more trend reports of clear codes gen-
15 erated 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
20 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 re¬
ports are stored in the first database (210-1) to enable retrieval of the one or more pre-
computed 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
25 user equipment (104) comprising:
a processor (202); and
30

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
5 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
10 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 associ¬
ated with the network function when the pre-computed trend report is not avail¬
able in the first database (210-1);
15 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).