FORM 2
PATENTS ACT, 1970 (39 of 1970) PATENTS RULES, 2003
COMPLETE SPECIFICATION
TITLE OF THE INVENTION
SYSTEM AND V
METHOD FOR MAPPING AND ANALYZING DATA VISUALIZATION AND EXTRACTION OPERATIONS
APPLICANT
380006, Gujarat, India; Nationality: India
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, trademark, In¬
tegrated Circuit (IC) layout design, and/or trade dress protection, belonging to Jio Platforms
5 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
10 [0002] The embodiments of the present disclosure generally relate to communication networks.
In particular, the present disclosure relates to a system and method for mapping and analyzing data for data visualization and extraction operations.
DEFINITION
[0003] As used in the present disclosure, the following terms are generally intended to have the
15 meaning as set forth below, except to the extent that the context in which they are used to
indicate otherwise.
[0004] The expression ‘Geography’ may refer to the spatial distribution of network elements like cell towers and data centers. It affects network coverage, performance, and planning.
[0005] The expression ‘Filtering Options’ may refer to tools or criteria used to sort and manage
20 data, allowing users to focus on specific subsets based on parameters such as time, location, or
error type.
[0006] The expression ‘CRR (Call Release Reason)’ may refer to codes that explain why a call ended, used to monitor and improve network performance by identifying normal and abnormal call terminations.
2

[0007] The expression ‘Raw Error Code Data’ refers to numerical codes from network compo-nents indicating specific errors or issues, used for diagnosing and troubleshooting network problems.
[0008] The expression ‘Data Formatting’ may refer to a process of organizing and structuring
5 data to make it readable and usable, often involving standardization to ensure consistency across
systems.
[0009] The expression ‘Dashboard and Report Integration’ may refer to combining data visu-alization tools with reporting capabilities to provide comprehensive insights and analyses in a single interface, aiding in decision-making and performance monitoring.
10 BACKGROUND OF DISCLOSURE
[0010] 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
15 present disclosure, and not as admissions of prior art.
[0011] Typically, data visualization and extraction for geography is based on different network
geographies such as, but not limited to, circle, centre, and point, and are limited to only support
filtering and analysis based on a specific option, for example, circle. In other words, current
dashboards are limited in their data visualization and extraction capabilities, only supporting
20 the circle option for geographical analysis. This constraint hampers the ability to explore and
interpret data effectively, especially in complex networks where various geographic shapes and structures play a crucial role. By relying solely on circles, users miss out on valuable insights that could be gleaned from other geographical frameworks like Supercore, R4G State, Centre, and Point.
3

[0012] Each of these geographic models offers unique perspectives and advantages. The Super-
core model, for example, can reveal dense clusters of activity, highlighting areas of high sig¬
nificance or intensity. On the other hand, the R4G State framework might provide insights into
regional variations and trends, allowing users to understand differences across larger areas. The
5 Centre and Point options can help in pinpointing specific locations and analyzing their impact
or role within a broader network.
[0013] These limitations highlight the need for a more versatile dashboard that can accommo¬
date diverse network geographies. Each geographic model offers unique perspectives and ad¬
vantages. For instance, the Supercore model might reveal dense clusters of activity, while the
10 R4G State framework could provide insights into regional variations. Without these options,
analysis remains one-dimensional and less informative, affecting decision-making processes that rely on comprehensive data interpretation.
[0014] There is, therefore, a need in the art to provide an enhanced visual representation func-tionality that includes support for mapping and analysis of data using network geographies.
15 SUMMARY
[0015] In an exemplary embodiment, a method for performing geography-based analytics is described. The method includes receiving, by a workflow engine, a request through a user in-terface (UI) of a user device, the request comprising at least one of a user selection of one or more geography and one or more filtering options, wherein the one or more filtering options
20 comprising: a normal call release reason or an abnormal call release reason (CRR), one or more
geographies, and computation of data for data analysis, processing, by the workflow engine, the request, to map information associated with the one or more selected geographies with net¬work data and communicate the processed request, to a distributed computing engine, aggre¬gating and computing, by the distributed computing engine, data associated with the mapped
25 information for the selected one or more geographies based on the request, communicating, by
the distributed computing engine, the computed data to the workflow engine, the computed data
4

comprising geography-based network information to the UI, and rendering, by the workflow
engine, the computed data comprising geography-based network information on the UI.
[0016] In some embodiments, the method includes performing, by the workflow engine, at least
one of: a geographical mapping, a dashboard and report integration, a call release reason (CRR)
5 management, and a data formatting, performing at least one of: generating or processing, by the
workflow engine, a forward request based on the geography selected, and generating the com-putation data based on the forward request.
[0017] In some embodiments, the method includes enhancing user interface to support network
geographies-based analytics, and providing the user with an insight based on for decision-mak-
10 ing and analysis.
[0018] In an exemplary embodiment, a system for performing geography-based analytics is
disclosed. The system includes a user interface (UI) comprising at least one of one or more
geographies selection options and one or more filtering options, wherein the one or more filter¬
ing options comprising at least one of: a normal call release reason or an abnormal call release
15 reason (CRR), one or more geographies, and computation of data for data analysis. The system
includes a workflow engine configured to receive a request through the user interface, the re¬
quest comprising at least one of a user selection of at least one of the one or more geographies
and the one or more filtering options and process the request to map data associated with the
one or more selected geographies with network data and communicate the processed request,
20 to a distributed computing engine, to a distributed computing engine. The distributed compu-
ting engine of the system is configured to: aggregate and compute the mapped data for the
selected one or more geographies based on the request, and communicate the computed data to
the workflow engine, the computed data comprising geography-based network information to
the UI (206). The workflow engine (212) is further configured to render the computed data
25 comprising geography-based network information on the UI (206).
[0019] In some embodiments, the workflow engine performs at least one of: generating or pro-cessing a forward request based on the geography selected.
5

[0020] In some embodiments, the system includes a dashboard and a report integration mech-anism, for integrating one or more geographies support into a plurality of xProbe dashboards and reports.
[0021] In an exemplary embodiment, a computer program product comprising a non-transitory
5 computer-readable medium comprising instructions that, when executed by one or more pro-
cessors, cause the one or more processors to perform the steps of: receiving, by a workflow
engine, a request through a user interface (UI) of a user device, the request comprising at least
one of a user selection of one or more geography and one or more filtering options, wherein the
one or more filtering options comprising: a normal call release reason or an abnormal call re-
10 lease reason (CRR), one or more geographies, and computation of data for data analysis, pro¬
cessing, by the workflow engine, the request to map data associated with the one or more se¬
lected geographies with network data and communicate the processed request, to a distributed
computing engine, aggregating and computing, by the distributed computing engine, the
mapped data for the selected one or more geographies based on the request, communicating, by
15 the distributed computing engine, the computed data to the workflow engine, the computed data
comprising geography-based network information to the UI, and rendering, by the workflow
engine, the computed data comprising geography-based network information on the UI.
[0022] In an exemplary embodiment, a user equipment (UE) configured for mapping and ana¬
lyzing data for performing data visualization and extraction operations using pre-defined net-
20 work geographies, the user equipment comprising a processor, and a computer readable storage
medium storing programming for execution by the processor, the programming including in¬
structions to receive, by a workflow engine, a request through a user interface of the UE, the
request comprising at least one of a user selection of one or more geography and one or more
filtering options, wherein the one or more filtering options comprising: a normal call release
25 reason or an abnormal call release reason (CRR), one or more geographies, and computation of
data for data analysis, and responsive to the request, and receive and render, on the UI, the
computed data comprising geography-based clear code based on processing the request using
the method for performing geography-based analytics as claimed in the method claim.
6

[0023] 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
5 [0024] Some of the objects of the present disclosure, which at least one embodiment herein
satisfies are as listed herein below.
[0025] An object of the present disclosure is to provide system and a method for performing mapping and analysis of data using predefined network geographies.
[0026] An object of the present disclosure is to develop a mapping mechanism to link network-
10 enriched data with network geographies from raw network data for analysis and visualization.
[0027] An object of the present disclosure is to provide an enhanced User Interface (UI) for selection and filtering of options related to additional geographies (such as normal Call Release Reason (CRR)/abnormal CRR, geographies, etc.) and computation of huge data for data analy¬sis.
15 [0028] An object of the present disclosure is to implement visual representations like bar chart,
line chart, and region-specific charts to display data based on the selected geographies.
BRIEF DESCRIPTION OF DRAWINGS
[0029] 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
20 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 illus-trating 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
7

of electrical components, electronic components or circuitry commonly used to implement such components.
[0030] FIG. 1 illustrates an example network architecture for implementing a system for
mapping and analyzing data for performing data visualization and extraction operations using
5 pre-defined network geographies, in accordance with an embodiment of the present disclosure.
[0031] FIG. 2A illustrates an example block diagram a system for mapping and analyzing data for performing data visualization and extraction operations using pre-defined network geographies, in accordance with an embodiment of the present disclosure.
[0032] FIG. 2B illustrates a flowchart showing the mapping and analysis of data using
10 predefined network geographies, in accordance with an embodiment of the present disclosure.
[0033] FIG. 3 illustrates a process flow showing mapping and analysis of data using the predefined network geographies, in accordance with an embodiment of the present disclosure.
[0034] FIG. 4 illustrates a flowchart of a method for mapping and analyzing data for performing
data visualization and extraction operations using pre-defined network geographies, in
15 accordance with an embodiment of the present disclosure.
[0035] FIG. 5 illustrates an exemplary block diagram of a computer system in which or with which embodiments of the present invention may be implemented.
[0036] The foregoing shall be more apparent from the following more detailed description of the disclosure.
20
LIST OF REFERENCE NUMERALS
100 – Network architecture
8

102-1, 102-2…102-N - Users
104-1, 104-2… 104-N - User equipment
106 - Network
108 - System 5 202- Processor
204- Memory
206- User Interface
208- Load Balancer Unit
210- Database 10 212- Workflow engine
214- Distributed computing engine
216- Dashboard
218- Method
220- 228 Steps 15 230-Distributed File System
232-Distributed Data Lake
300-Implementation of the system
301-UI Server
9

302- User
304- 326 Steps
400-Method
402-412 Steps
5 500- Computer system
510- External storage device 520- Bus
530- Main memory
540- Read only memory
10 550- Mass Storage Device
560- Communication Port 570- Computer System Processor
DETAILED DESCRIPTION OF THE DISCLOSURE
15 [0037] In the following description, for the purposes of explanation, various specific details are
set forth 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
20 all the problems discussed above or might address only some of the problems discussed above.
10

Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0038] 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
5 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.
[0039] Specific details are given in the following description to provide a thorough understand-
10 ing 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, sys¬
tems, networks, processes, and other components may be shown as components in block dia¬
gram 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
15 unnecessary detail in order to avoid obscuring the embodiments.
[0040] 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 opera-
20 tions 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 func¬
tion, 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.
25 [0041] 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
11

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 advanta¬
geous 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
5 terms “includes,” “has,” “contains,” and other similar words are used in either the detailed de-
scription 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.
[0042] Reference throughout this specification to “one embodiment” or “an embodiment” or
“an instance” or “one instance” means that a particular feature, structure, or characteristic de-
10 scribed 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 em¬
bodiment. Furthermore, the particular features, structures, or characteristics may be combined
in any suitable manner in one or more embodiments.
15 [0043] 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 indi¬
cates 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, opera-
20 tions, 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 all combinations of one or more of the associated listed
items.
[0044] The aspects of the present disclosure are directed to a method and system for mapping
25 and analyzing data for performing data visualization and extraction operations using pre-de-
fined network geographies. In examples, the geographies as discussed may refer to the physical locations and spatial distribution of network infrastructure, such as cell towers, cables, and data
12

centers. In current context, the geographies involve understanding how these telecommunica¬
tion elements are arranged across different regions to optimize network coverage, capacity, and
performance. In examples, the network infrastructure elements such as, for example, cells may
be mapped on the physical geography, and the cells may be tagged with the physical geography.
5 The disclosed system and method support mapping and analysis of the data, in addition to per-
forming data visualization and extraction operations, based on different predefined network
geographies. This capability may be implemented and made available across all visual repre¬
sentations and reports in xProbe. The disclosed system and method provide a mapping mecha¬
nism to link network-enriched data with network geographies from raw network data for anal-
10 ysis and visualization. The disclosed system and method extend data extraction capabilities to
extract specific data subsets based on chosen geographies. The disclosed system and method
implement an enhanced user interface with more geographies selection and filtering options
(e.g., normal/abnormal CRR, geographies, etc), and computation of huge data for data analysis.
Implementation of visualizations like bar chart, line chart, and region-specific charts may be
15 used to display the data based on the selected geographies. In an embodiment, the disclosed
system and method uses a mapping mechanism to associate predefined network geographies
with data points and create a configuration module for administrators to manage and upload
geographies mapping. In another embodiment, the disclosed system and method provides a data
extraction and reporting enhancement to modify data extraction and reporting functionalities
20 based on the network geographies. In addition, filters and options may be incorporated for ex¬
tracting data specific to the defined geographies. In another embodiment, the disclosed system
and method provides a data visualization enhancement. Enhanced data visualization capabilities
may support the different network geographies and may facilitate to develop interactive charts
and region-specific graphs for geographies-based data representation. In yet another embodi-
25 ment, the disclosed system and method provides a dashboard and a report integration mecha¬
nism, for seamlessly integrating geographies support into all xProbe dashboards and reports.
This facilitates modification of existing modules to include selection and analysis of data based
on the predefined geographies. The current xProbe dashboards lack the ability to perform data
visualization and extraction based on different network geographies such as Supercore, Circle,
13

R4G State, Centre, and Point. The existing dashboard only supports filtering and analysis based
on the circle option. To address this limitation, the requirement is to enhance the dashboard
functionality to include support for mapping and analyzing data using these predefined network
geographies. This capability should be made available across all dashboards and reports in
5 xProbe by developing mapping mechanism to link network-enriched data with network geog-
raphies from raw network data for analysis and visualization. The present technology extends
data extraction capabilities to extract specific data subsets based on chosen geographies. The
present system performs implementation of enhance user interface with more geographies se¬
lection and filtering options (normal/abnormal CRR, geographies, etc) and computation of huge
10 data for data analysis. The present technology implements visualizations like bar chart, line
chart and region-specific charts to display data based on selected geographies. The inventive step is being performed at the application server level.
[0045] According to an embodiment, the geographies mapping mechanism comprises design¬
ing and developing a mapping mechanism to associate predefined network geographies with
15 data points and create a configuration module for administrators to manage and upload geogra-
phies mapping. The method also includes modifying data extraction and reporting functionality
to enable extraction based on network geographies and incorporating filters and options for
extracting data specific to defined geographies. The method also includes seamlessly integrat¬
ing geographies support into all xProbe dashboards and reports. The method also includes mod-
20 ifying existing modules to include selection and analysis of data based on predefined geogra¬
phies. The present disclosure enhances xProbe dashboards to support network geographies-
based analytics, providing users with valuable insights for better decision-making and analysis.
[0046] The various embodiments throughout the disclosure will be explained in more detail with reference to FIGs. 1-5.
25 [0047] Referring to FIG. 1, a network architecture (100) may include one or more computing
devices or user equipment (104-1, 104-2…104-N) (used interchangeably with the term “user device”) associated with one or more users (102-1, 102-2…102-N) in an environment. A person
14

of ordinary skill in the art will understand that one or more users (102-1, 102-2…102-N) may
be individually referred to as the user (102) and collectively referred to as the users (102). Sim¬
ilarly, a person of ordinary skill in the art will understand that one or more user equipment (104-
1, 104-2…104-N) may be individually referred to as the user equipment (104) and collectively
5 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 through-out 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.
10 [0048] 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
15 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 equip-ment, 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
20 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
25 that the user equipment (104) may not be restricted to the mentioned devices and various other
devices may be used.
15

[0049] In an embodiment, the user equipment (104) may include smart devices operating 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
5 peripheral devices, networked lighting system, communication devices, networked vehicle ac-
cessories, networked vehicular devices, smart accessories, tablets, smart television (TV), com¬
puters, 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,
10 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 net-work-connected.
[0050] 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 at least one of a
15 Fifth Generation (5G) network, 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
20 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
25 equipment identity (IMEI) number, international mobile subscriber identity (IMSI), subscriber
permanent identifier (SUPI) and the like.
16

[0051] In an embodiment, the system (108) may receive and analyse call record data from each
cell site. The call record data may include, but not limited to, call records, call duration, fre¬
quency, user location, minutes of usage, etc. The system (108) may normalize and pre-process
the call record data. The system (108) may extract one or more relevant features, such as net-
5 work load, time of day, and user behavior, from the pre-processed call record data to capture
call patterns and user characteristics. The system (108) may feed the call record data and the
extracted features to an artificial intelligence (AI)/machine learning (ML) model, and the
AI/ML model may be trained based on the call record data and the extracted features. These
call-related details may be included with network network-related information that may be
10 mapped to geographies. Further, the system (108) may process the network related information
to perform analytics. When the user requests for geography-based analytics, the system (108)
may generate the data as per geography and provide insights gleaned from other frameworks
like Supercore, R4G State (readiness state for network transition from 4G to 5G), Centre, and
Point.
15 [0052] Although FIG. 1 shows exemplary components of the network architecture (100), in
other embodiments, the network architecture (100) may include fewer components, different
components, differently arranged components, or additional functional components than de¬
picted in FIG. 1. Additionally, or alternatively, one or more components of the network archi¬
tecture (100) may perform functions described as being performed by one or more other com-
20 ponents of the network architecture (100).
[0053] FIG. 2A illustrates a block diagram of the system (108) for mapping and analyzing data
for performing data visualization and extraction operations using pre-defined network geogra¬
phies, in accordance with embodiments of the present disclosure. In an aspect, the system (108)
may include one or more processor(s) (202) and a memory (204). The one or more processor(s)
25 (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers,
edge or fog microcontrollers, digital signal processors, central processing units, logic circuit-
17

ries, and/or any devices that process data based on operational instructions. Among other capa¬
bilities, the one or more processor(s) (202) may be configured to fetch and execute computer-
readable instructions stored in a memory (204) of the system (108). The memory (204) may be
configured to store one or more computer-readable instructions or routines in a non-transitory
5 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 de-vice 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.
10 [0054] The memory (204) may include, for example, a hard disk drive and/or a removable stor-
age drive, representing a floppy disk drive, a magnetic tape drive, a compact disk drive, a pro-gram cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as EPROM or PROM), and the like, which is read by and written to by removable storage unit. As will be appreciated, the removable storage unit includes a computer
15 usable storage medium having stored therein computer software and/or data. The removable
storage drive reads from and/or writes to a removable storage unit in a well-known manner. The removable storage unit, also called a program storage device or a computer program prod-uct, represents a floppy disk, magnetic tape, compact disk, etc. The computer programs (also called computer control logic) are stored in main memory (204). Such computer programs,
20 when executed, enable the system (108) to perform the functions of the present disclosure as
discussed herein. In particular, the computer programs, when executed, enable the one or more processor (102) to perform the functions of the present disclosure. Accordingly, such computer programs represent controllers of the system (108).
[0055] Referring to FIG. 2A, the system (108) may also include an interface(s) (206). The in-
25 terface(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 interface(s) (206) may also provide
18

a communication pathway for one or more components of the system (108). Examples of such components include, but are not limited to, a database (210).
[0056] In an embodiment, the system (108) may be implemented as a combination of hardware
and programming (for example, programmable instructions) to implement one or more func-
5 tionalities. In examples described herein, such combinations of hardware and programming
may be implemented in several different ways.
[0057] In an embodiment, the system (108) may include one or more databases such as data¬
bases (210). In an embodiment, the database (210) includes data that may be either stored or
generated because of functionalities implemented by any of the components of the processor
10 (202). 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.
[0058] In an embodiment, the system (108) includes a user interface (206), a load balancer unit
15 (208), a workflow engine (212), a distributed computing engine (214), and a dashboard (216).
The user interface (206) comprises one or more geographies selection options and one or more
filtering options comprising at least one of a normal call release reason or an abnormal call
release reason (CRR), one or more geographies, and the computation of data for data analysis.
The one or more filtering options may refer to user interface element that provide options on
20 the user interface for the user to make choices. In examples, the one or more filtering options
may be in a form of a dropdown element, choice radio buttons, or as list of options provided on
the user interface.
[0059] In embodiments, the load balancer unit (208) is configured to monitor network traffic
and automatically redirecting traffic to available workflow engines based on load of each work-
25 flow engines. The load balancer unit (208) also routes traffic through a group of network fire¬
walls for security. In current context, the load balancer unit (208) is configured for forwarding
19

a user request to a workflow engine (212) and for forwarding the computed data comprising
geography-based clear code to the UI (206). The workflow engine (212) is configured for send¬
ing computation data comprising at least one of one or more filters, a geography, and one or
more error codes, to a distributed computing engine (214), based on the user request. According
5 to one embodiment of the present technology, the workflow engine (212) performs at least one
of generating or processing a forward request based on the geography selected. The distributed
computing engine (214) is configured for computing data based on at least one of the geogra¬
phies and one or more error codes from the computation data by using at least one of raw error
code data or pre-aggregated error code data, from a distributed file system (232) associated with
10 a database (210). The dashboard (216) and a report integration mechanism are configured for
integrating one or more geographies support into a plurality of xProbe dashboards and reports.
[0060] FIG. 2B illustrates a flowchart (218) showing the mapping and analysis of data using predefined network geographies, according to an embodiment of the present disclosure.
[0061] As illustrated, at step (220), the process begins.
15 [0062] At step (222), a UI (206) is provided to a user. The UI (206) may provide options for
the user to select one or more network, one or more geographies and/or use predefined filters.
[0063] At step (224), a load balancer may identify one or more workflow engine (212) based onload of the workflows.
[0064] At step (226), the workflow engine (212) based on the geography/time may be selected.
20 In examples, in step (228) the workflow engine (212) may process the request, and results of
the processing may be stored in a distributed data lake (234). If the workflow engine (212) does not have geographical data, then the request is forwarded to the distributed computing engine.
[0065] In step (230), the distributed computing engine computes data for selected network
25 geography. For computing the data for the selected network geography, raw or pre-aggregated
20

network data may be fetched and used from a distributed file system (232). The results from both the processed request and the computing engine are collected at a distributed data lake (234).
[0066] FIG. 3 illustrates a process flow (300) showing mapping and analysis of data using
5 predefined network geographies, according to an embodiment of the present disclosure.
[0067] As illustrated, a user request with more geography selection options is passed to a load balancer unit (208).
[0068] At step (304), a user (302) sends a request with one or more geography selection options to a user interface server (301).
10 [0069] At step (306), the request is forwarded to load balancer unit (208). The load balancer
unit (208) is configured to communicate the request to an appropriate available workflow engine (212).
[0070] At step (308), the load balancer unit (208) forwards the request to the xProbe manager unit that is the workflow engine (212).
15 [0071] At step (314), the workflow engine (212) sends filters, geography, and error codes to a
distributed computing engine (328).
[0072] At step (310), at the workflow engine (212), geographical mapping, dashboard, report
integration, CRR management, and data formatting are performed. For example, the workflow
engine (212) may obtain the user-selected one or more geographies and identifies regions or
20 areas relevant to the network (e.g., cities, regions, countries). In aspects, the workflow engine
(212) may gather data related to network performance, coverage, or infrastructure associated with the one or more geographies. The workflow engine (212) may ensure data points have geographic attributes (e.g., GPS coordinates). The workflow engine (212) may map data points to the geographies to generate geographical mapping. The geographical mapping may be
21

processed for the dashboard and report integration. For example, the workflow engine (212) may also gather call release reasons and abnormal call release reasons as a part of gathering data related to network performance.
[0073] At step (312), based on the geography selected, the workflow engine (212) may decide
5 to perform compute information for the geographical mapping or generate forward request. In
examples, for some select geographies, the workflow engine (212) may forward the request to the distributed computing engine (214) at a computation layer (328).
[0074] At step (316), at the computation layer (328), based on the geography selected, data
collection and computation may be done for the selected geography and the error code, while
10 receiving raw error code data (318) from a distributed file system (232). The raw error code
data consists of numerical codes generated by network elements to indicate specific errors or issues. The raw error codes may help indicate in the dashboard or the computed data, the error and related analytics. For example, the raw error codes captured in the network are generally stored in the distributed file system, although they can be stored in another database as well.
15 [0075] At step (320), computed data is sent from the distributed computing engine (328) via a
distributed data lake (234) to the workflow engine (212) in one embodiment. The computation layer (328) may include the distributed computing engine (214). In some embodiments, the computed data may be communicated directly to the workflow engine (212), directly.
[0076] At step (322), geography-based clear code data along with notification is sent to the load
20 balancer unit (208) and is forwarded to the UI (206) (at step (324)) and to the user (302) at step
(326). At the UI (206), the user may be enabled to view and perform geography related analytics using filters, one or more geography options, etc. For example, the user may be able to obtain insights and information at various network levels and frameworks such as Supercore, R4G State, Centre, Point, etc.
25 [0077] FIG. 4 illustrates a flowchart (400) of a method for mapping and analyzing data for
performing data visualization and extraction operations using pre-defined network geographies,
22

according to an embodiment of the present invention.
[0078] At step (402), a request through a user interface (UI) of a user device may be received
by a workflow engine (212), the request comprising at least one of a user selection of one or
more geography and one or more filtering options. The one or more filtering options
5 comprising: a normal call release reason or an abnormal call release reason (CRR), one or more
geographies, and computation of data for data analysis.
[0079] At step (404), the request may be processed to map data associated with the one or more selected geographies with network data and communicate the processed request to a distributed computing engine (214), may be performed by the workflow engine (212).
10 [0080] At step (406), the mapped data for the selected one or more geographies based on the
request may be aggregated and computed, by the distributed computing engine (214) distributed computing engine.
[0081] At step (408), the computed data may be communicated by the distributed computing engine (214) to the workflow engine (212) distributed computing engine.
15 [0082] At step (410), the computed data comprising geography-based network information on
the UI (206) may be rendered by the workflow engine (212) distributed computing engine.
[0083] According to one embodiment of the present technology, sending the computation data
from the workflow engine comprises performing, by the workflow engine, at least one of: a
geographical mapping, a dashboard and report integration, a call release reason (CRR)
20 management, and a data formatting, performing one of: generating or processing, by the
workflow engine, a forward request based on the geography selected and generating the computation data based on the forward request.
[0084] According to one embodiment of the present technology, the method further comprises enhancing xProbe user interface to support network geographies-based analytics and providing
23

the user with valuable insight for decision-making and analysis. The UI (206) may be configured to include various frameworks such as Supercore, R4G State, Centre, and Point. The user may be able to use any of the frameworks, change geographies, and use different filters to anaylze the network information associated with the geographies.
5 [0085] In an exemplary embodiment, the present disclosure discloses the user equipment (UE)
(104) configured for tracking a network performance summary and subscriber activity within a network. The user equipment (104) includes the processor (202) and a computer-readable storage medium storing programming for execution by the processor (202). The programming includes instructions to the UE configured for receiving a request to map network data,
10 including call release reasons, abnormal call release reasons and error codes, to specific
geographies. This step involves linking network performance data to geographic regions, providing essential context for further analysis. The workflow engine (212) ensures that data points (e.g., network information, etc.), such as CRR and error codes, are accurately associated with their respective geographies, enabling a comprehensive understanding of network
15 behavior across different areas. Once geographies are mapped, the workflow engine (212)
communicates this information, including raw error code data and CRR, to a distributed computing engine. The workflow engine (212) is equipped to handle large-scale data processing tasks by leveraging multiple nodes for efficient computation. By distributing the workload, the distributed computing engine (214) aggregates raw network data and pre-aggregated error
20 codes, processing them to derive insights into network performance and stability across various
regions.
[0086] The distributed computing engine (214) aggregates data related to mapped geographies,
performing computations on CRR, raw error codes, and other network metrics. This involves
identifying patterns in call releases and error occurrences and analyzing them to pinpoint issues
25 affecting network reliability and user experience. The distributed computing engine (214)
capability to process large volumes of data ensures timely and accurate insights, highlighting areas needing improvement and optimizing network operations. Following computation, the
24

distributed computing engine (214) sends the processed data back to the workflow engine (212).
This data, enriched with geography-based insights and analysis of CRR and error codes, is
communicated to the UI (206). The workflow engine (212) renders this information on the UI,
transforming complex datasets into intuitive visualizations and reports that facilitate user
5 understanding and decision-making.
[0087] The UI (206) serves as a critical platform for exploring and visualizing geography-based
network information. Through interactive dashboards, users can analyze CRR patterns, error
code distributions, and raw network data, gaining insights into how different regions perform.
This visual representation enables stakeholders to identify problem areas, optimize network
10 resources, and enhance service quality by leveraging geographic and performance data
effectively. The integration of CRR and error data into the analysis provides a detailed view of network challenges, guiding strategies for improvement, and ensuring robust network management.
[0088] FIG. 5 illustrates an exemplary computer system (500) in which or with which embod-
15 iments of the present disclosure may be implemented. 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 in-
20 clude various modules associated with embodiments of the present disclosure.
[0089] 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 fibre, a serial port, a parallel port, or other existing or future ports. The com¬
munication port (560) may be chosen depending on the network (106), such a Local Area Net-
25 work (LAN), Wide Area Network (WAN), or any network to which the computer system (500)
connects.
25

[0090] 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 Input/Output System (BIOS)
5 instructions for the processor (570).
[0091] 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 (inter-
10 nal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), one or more
optical discs, Redundant Array of Independent Disks (RAID) storage, e.g., an array of disks
(e.g., SATA arrays).
[0092] 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
15 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 pro-cessor (570) to the computer system (500).
[0093] Optionally, operator and administrative interfaces, e.g., a display, keyboard, joystick,
20 and cursor control device, may also be coupled to the bus (520) to support direct operator in-
teraction 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
25 disclosure.
TECHNICAL ADVANCEMENT OF THE PRESENT DISCLOSURE
26

[0094] The present disclosure provides technical advancement compared to existing art by ex¬
tending data extraction capabilities to extract specific data subsets based on chosen geographies.
The present disclosure performs implementation of enhancing the user interface with more ge¬
ography’s selection and filtering options (normal/abnormal CRR, geographies, etc) and com-
5 putation of huge data for data analysis. The present disclosure implements visualizations like
bar chart, line chart and region-specific charts to display data based on selected geographies.
[0095] Following the process flow steps effectively enhances xProbe user interface(s) to
support network geographies-based analytics, providing the users with valuable insights for
better decision-making and analysis. The disclosed system and method provide an enhanced
10 data analysis by enabling the inclusion of different network geographies for data visualization
and extraction. This analysis provides a more comprehensive and granular analysis of network data that helps the users to analyze the performance, trends, and patterns specific to geography, enabling better decision-making and troubleshooting.
[0096] In addition, by having access to network geographies-based analytics, the users may
15 have the capability to make more informed decisions regarding network optimization, resource
allocation, and infrastructure planning. They may identify specific areas or regions where the network performance is lacking or exceeding expectations, allowing for targeted interventions and improvements.
[0097] Also, an ability to extract data based on different network geographies may allow for
20 customized reporting tailored to specific areas of interest. Stakeholders may generate reports
specific to the geography, providing localized insights and facilitating better communication and collaboration among teams.
[0098] Further, with the inclusion of network geographies-based analytics, it may become
easier to monitor the performance of different regions or specific network segments. This may
25 enable proactive identification of the network issues, such as congestion or service outages, and
facilitate timely resolution to minimize customer impact. Furthermore, the availability of
27

network geographies-based analytics may assist in optimizing resource allocation. By analyzing
the performance metrics and user behavior within specific geographies, network operators may
efficiently allocate resources and capacity, ensuring a better user experience and reduction in
operational costs. It may be appreciated that the proposed enhancement may allow for the
5 inclusion of additional network geographies as per requirements. This flexibility may ensure
the analytics solution to be scaled and adapted to changing network configurations, expansion into new regions, or introduction of new service areas. Overall, the disclosed system and method provide a comprehensive, localized, and targeted analysis of the network data, leading to improved decision-making, better resource utilization, and enhanced customer experience.
10 [0099] 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
15 foregoing descriptive matter to be implemented merely as illustrative of the disclosure and not
as limitation.
ADVANTAGES OF THE PRESENT DISCLOSURE
[00100] The present disclosure provides a system and a method for mapping and analyz-
ing data for performing data visualization and extraction operations using pre-defined network
20 geographies.
[00101] The present disclosure develops a mapping mechanism to link network enriched
data with network geographies from raw network data for analysis and visualization.
[00102] The present disclosure extends data extraction capabilities to extract specific
data subsets based on chosen geographies.
28

[00103] The present disclosure provides an enhanced User Interface (UI) for selection
and filtering of options related to additional geographies (such as normal Call Release Reason (CRR)/abnormal CRR, geographies, etc.,), and computation of huge data for data analysis.
[00104] The present disclosure implements visual representations like bar chart, line
5 chart, and region-specific charts to display data based on the selected geographies.
[00105] The present disclosure provides a comprehensive, localized, and targeted analy-
sis of the network data, leading to improved decision-making, better resource utilization, and
enhanced customer experience. The inclusion of different network geographies for data visual¬
ization and extraction in xProbe dashboards provides a more comprehensive and granular anal-
10 ysis of network data.
[00106] The present disclosure enables the users to analyse the performance, trends, and
patterns specific to Supercore, Circle, R4G State, Centre, and Point, enabling better decision-
making and troubleshooting. By having access to network geographies-based analytics, users
can make more informed decisions regarding network optimization, resource allocation, and
15 infrastructure planning. They can identify specific areas or regions where network performance
is lacking or exceeding expectations, allowing for targeted interventions and improvements.
[00107] The present disclosure extracts data based on different network geographies al-
lows for customized reporting tailored to specific areas of interest. With the inclusion of net¬
work geographies-based analytics, it becomes easier to monitor the performance of different
20 regions or specific network segments.
[00108] The present disclosure enables proactive identification of network issues, such
as congestion or service outages, and facilitates timely resolution to minimize customer impact.
The availability of network geographies-based analytics assists in optimizing resource alloca¬
tion. By analyzing the performance metrics and user behaviour within specific geographies,
25 network operators can allocate resources and capacity more efficiently, ensuring a better user
experience and reducing operational costs.
29

[00109] The present disclosure provides an enhancement to xProbe dashboards which
allows for the inclusion of additional network geographies as per requirements. This flexibility ensures that the analytics solution can scale and adapt to changing network configurations, ex-pansion into new regions, or the introduction of new service areas.
5 [00110] The present disclosure has the ability to provide a comprehensive, localized, and
targeted analysis of network data, leading to improved decision-making, better resource utili-zation, and enhanced customer experience.
30

WE CLAIM:
5
1. A method (400) for performing geography-based analytics, the method comprising:
receiving (402), by a workflow engine (212), a request through a user interface (UI) of
a user device, the request comprising at least one of a user selection of one or more geography
10 and one or more filtering options, wherein the one or more filtering options comprising: a nor-
mal call release reason or an abnormal call release reason (CRR), one or more geographies, and computation of data for data analysis;
processing (404), by the workflow engine (212), the request, to map information asso¬
ciated with the one or more selected geographies with network data and communicate the pro-
15 cessed request, to a distributed computing engine (214);
aggregating and computing (406), by the distributed computing engine (214), data as-sociated with the mapped information for the selected one or more geographies based on the request;
communicating (408), by the distributed computing engine (214), the computed data to
20 the workflow engine (212), the computed data comprising geography-based network infor-
mation to the UI (206); and
rendering (410), by the workflow engine (212), the computed data comprising geogra-phy-based network information on the UI (206).
25 2. The method of claim 1, wherein the computed data comprises enriched network data
comprising user-select geographies mapped with data points.
3. The method (400) of claim 1, further comprising:
31

performing, by the workflow engine (212), at least one of: a geographical mapping, a dashboard (110) and report integration, a call release reason (CRR) management, and a data formatting;
performing one of: generating or processing, by the workflow engine (212), a forward
5 request based on the geography selected; and
generating the computation data based on the forward request.
4. The method (400) of claim 1, further comprising enhancing user interface to support
network geographies-based analytics, and providing the user with an insight based on for deci-
10 sion-making and analysis.
5. A system (108) for performing geography-based analytics, the system (108) comprising:
a user interface (UI) (206) comprising at least one of one or more geographies selection
options and one or more filtering options, wherein the one or more filtering options comprising
15 at least one of: a normal call release reason or an abnormal call release reason (CRR), one or
more geographies, and computation of data for data analysis;
a workflow engine (212) configured to:
receive a request through the user interface, the request comprising at least one
of a user selection of at least one of the one or more geographies and the one or more
20 filtering options; and
process the request, to map information associated with the one or more selected
geographies with network data and communicate the processed request, to a distributed
computing engine (214);
the distributed computing engine (214) configured to:
25 aggregate and compute associated with the mapped information for the selected
one or more geographies based on the request; and
communicate the computed data to the workflow engine (212), the computed
data comprising geography-based network information to the UI (206); and
the workflow engine (212) is further configured to:
32

render the computed data comprising geography-based network information on the UI (206).
6. The system (108) of claim 4, wherein the workflow engine (212) performs at least one
5 of: generating or processing a forward request based on the geography selected.
7. The system (108) of claim 4, further comprising a dashboard (216) and a report integra¬
tion mechanism, for integrating one or more geographies support into a plurality of xProbe
dashboards and reports.
10
8. A user equipment (UE) (104) configured for mapping and analyzing data for performing
data visualization and extraction operations using pre-defined network geographies, the user
equipment (104) comprising:
a processor (202); and
15 a computer readable storage medium storing programming for execution by the processor
(202), the programming including instructions to:
receiving (402), by a workflow engine (212), a request through a user interface of the
UE, the request comprising at least one of a user selection of one or more geography and one
or more filtering options, wherein the one or more filtering options comprising: a normal call
20 release reason or an abnormal call release reason (CRR), one or more geographies, and compu-
tation of data for data analysis;
responsive to the request, receiving and rendering (412), on the UI, the computed data
comprising geography-based network information on the UI (206) based on processing the re¬
quest using the method (400) for performing geography-based analytics as claimed in the claim