FIELD OF INVENTION
The embodiments of the present disclosure generally relate to data
processing systems. More particularly, the present disclosure relates to systems and methods for social protection using data model.
BACKGROUND OF THE INVENTION
[0002] The following description of related art is intended to provide
background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0003] Generally, one or more data models for social protection may be
quite complex in nature considering the dynamism, complicated bureaucratic
arrangements within government and related organisation, and such other reasons.
The data model may be the foundation to design any technology system for social
protection that may be configurable, flexible, and scalable. A robust, well tested
model reduces the efforts of developers, government officers in meeting the
dynamic requirements due to the ever-changing policy environments.
[0004] There is therefore a need in the art to provide systems and methods
for social protection using data model, that can overcome the shortcomings of the existing prior art.
OBJECTS OF THE PRESENT DISCLOSURE
[0005] Some of the objects of the present disclosure, which at least one
embodiment herein satisfies are as listed herein below.
[0006] An object of the present disclosure is to provide systems and
methods for social protection using data model.
[0007] Another object of the present disclosure is to provide systems and
methods for robust data model which reduces the efforts of developers, government

officers in meeting the dynamic requirements due to the ever-changing policy
environments.
[0008] An object of the present disclosure is to provide systems and
methods for selecting attributes and categorising the attributes.
[0009] An object of the present disclosure is to enable to configure any
number/type of social protection program/scheme using the same data model.
[0010] Another object of the present disclosure is to provide systems and
methods for identification of more than e.g., 300 attributes after analyzing and
deconstructing e.g., 1500+ social welfare programs.
[0011] Another object of the present disclosure is to provide systems and
methods for mapping interdependency and relationship among close to e.g., 200
data points.
[0012] Another object of the present disclosure is to provide systems and
methods for organizing the attributes in e.g., 6 different categories - Social,
economic, occupation, education, housing, and health.
[0013] Yet another object of the present disclosure is to enable mapping of
individual profile data with the rules derived from multiple schemes, and for
thousands of such scenarios in run time within a fraction of a second, while the user
is responding to a question.
SUMMARY
[0014] This section is provided to introduce certain objects and aspects of
the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.
[0015] In an aspect, the present disclosure provides for a system for
facilitating a social protection application for a plurality of users. The system may include one or more processors operatively coupled to a plurality of first computing devices. The one or more processors may be coupled with a memory that may store instructions which when executed by the one or more processors may cause the system to receive a first set of data packets from a plurality of first computing

devices (104), the first set of data packets pertaining to an information service corresponding to a plurality of policy documents associated with one or more social welfare programs to be availed by the plurality of users operating the plurality of first computing devices. The system may be configured to create a descriptive document for the one or more social welfare programs based on the first set of data packets. The descriptive document may include a set of eligibility and predefined rules provided in the plurality of policy documents. Further, the system may extract a first set of attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents. Based on the extracted first set of attributes, the system may identify, by using an artificial intelligence (AI) engine, a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents. The second set of attributes may pertain to existing rules and conditions of the social welfare program associated with any or a combination of the current societal norms, geography and profile level of each user. The system may then generate, through the AI engine, a trained model configured to process the decision tree, and predict, from the processed decision tree, the information service associated with the one or more social welfare programs, and facilitate response corresponding to said information service to the plurality of users based on the trained model. Furthermore, the system may auto-generate, using the AI engine, the social protection application for the plurality of users.
[0016] In an embodiment, the system may be further configured to check,
by the AI engine, if the second set of attributes in the social protection application.
[0017] In an embodiment, the system may be further configured to generate
anew second set of attributes if the second set of attributes are absent the descriptive document.
[0018] In an embodiment, the system may be further configured to receive
the first set of data packets from a plurality of first computing devices (104) based on a user query associated with the one or more social welfare program.

[0019] In an embodiment, a user query associated with the information
service may be received at a client side of the social protection application through
a user interface in the form of a second set of data packets from the user computing
device, and the response that may be mapped with the information service may be
transmitted in real-time in the form of a third set of data packets to said user
computing device from server side of the social protection application.
[0020] In an embodiment, the system may be further configured to obtain a
registration data based on a request from an unregistered user through respective
user computing device, wherein login credentials may be generated based on
acknowledgement of the request and verification of the registration data, wherein
the user may enter the generated login credentials to access the system to obtain the
information service associated with the user.
[0021] In an embodiment, the system may be further configured to display,
through a user interface, a text and a hierarchical structure with geography and
profile levels associated with the first and the second set of attributes.
[0022] In an embodiment, the system may be further configured to iterate
steps for the decision tree for updating the new second set of attributes that takes
into account relevant information associated with the society at the predefined point
of time.
[0023] In an embodiment, the relevant information associated with the
society at the predefined point of time may be data that has been built over a period
of time after thorough analysis of a plurality of policies.
[0024] In an embodiment, the system may be further configured to analyse
the plurality of policies to come up with a plurality of first set of attributes.
[0025] In an embodiment, the system may be further configured to the
plurality of policies into a plurality of categories associated with eligibility, benefit,
reporting rules and payment rules.
[0026] In an embodiment, the system may be further configured to build the
decision tree in a hierarchical tree structure, wherein a top node in the decision tree
comprises the most generic level data, and wherein each node comprises

continuously evolving fields associated with the one or more social welfare programs.
[0027] In an embodiment, the system may be further configured to eliminate
a user, if ineligible at a very early step based on the hierarchical tree structure.
[0028] In an embodiment, the system may be further configured to construct
a descriptive document for every scheme to of the one or more social welfare programs.
[0029] In an aspect, the present disclosure provides for a user equipment
(UE) for facilitating a social protection application for a plurality of users. The UE may include a processor operatively coupled to a plurality of first computing devices , the processor coupled with a memory that may store instructions which when executed by the processor may cause the UE to receive a first set of data packets from a plurality of first computing devices (104), the first set of data packets pertaining to an information service corresponding to a plurality of policy documents associated with one or more social welfare programs to be availed by the plurality of users operating the plurality of first computing devices. The UE may be configured to create a descriptive document for the one or more social welfare programs based on the first set of data packets. The descriptive document may include a set of eligibility and predefined rules provided in the plurality of policy documents. Further, the UE may extract a first set of attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents. Based on the extracted first set of attributes, the UE may identify, by using an artificial intelligence (AI) engine, a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents. The second set of attributes may pertain to existing rules and conditions of the social welfare program associated with any or a combination of the current societal norms, geography and profile level of each user. The UE may then generate, through the AI engine, a trained model configured to process the decision tree, and predict, from the processed decision tree, the information service associated with the one or more social welfare programs, and facilitate response corresponding to said information

service to the plurality of users based on the trained model. Furthermore, the UE may auto-generate, using the AI engine, the social protection application for the plurality of users.
[0030] In an aspect, the present disclosure provides a method for facilitating
a social protection application for a plurality of users. The method may include the step of receiving, by one or more processors, a first set of data packets from a plurality of first computing devices, the first set of data packets pertaining to an information service corresponding to a plurality of policy documents associated with one or more social welfare programs to be availed by the plurality of users operating the plurality of first computing devices. In an embodiment, the one or more processors may be operatively coupled to a plurality of first computing devices, the one or more processors may be coupled with a memory that may store instructions which are executed by the one or more processors. The method may also include the step of creating, by the one or more processors, a descriptive document for the one or more social welfare programs based on the first set of data packets. The descriptive document may include a set of eligibility and predefined rules provided in the plurality of policy documents. The method may further include the step of extracting, by the one or more processors, a first set of attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents. Based on the extracted first set of attributes, the method may include the step of identifying, by using an artificial intelligence (AI) engine, a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents. The second set of attributes may pertain to existing rules and conditions of the social welfare program associated with any or a combination of the current societal norms, geography and profile level of each user. Furthermore, the method may include the step of generating, through the AI engine, a trained model configured to process the decision tree, and predict, from the processed decision tree, the information service associated with the one or more social welfare programs, and facilitate response corresponding to said information service to the plurality of users based on the trained model; and then the method

may include the step of auto-generating, using the AI engine, the social protection application for the plurality of users.
BRIEF DESCRIPTION OF DRAWINGS
[0031] The accompanying drawings, which are incorporated herein, and
constitute a part of this invention, illustrate exemplary embodiments of the
disclosed methods and systems in which like reference numerals refer to the same
parts throughout the different drawings. Components in the drawings are not
necessarily to scale, emphasis instead being placed upon clearly illustrating the
principles of the present invention. 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 invention of such
drawings includes the invention of electrical components, electronic components or
circuitry commonly used to implement such components.
[0032] FIG. 1 illustrates an exemplary network architecture in which or with
which proposed system of the present disclosure can be implemented, in accordance
with an embodiment of the present disclosure.
[0033] FIG. 2A illustrates an exemplary block diagram representation of
proposed system/Artificial Intelligence (AI) engine for social protection using data
model, in accordance with an embodiment of the present disclosure.
[0034] FIG. 2B illustrates an exemplary block diagram representation of a
user equipment (UE) for social protection using data model, in accordance with an
embodiment of the present disclosure.
[0035] FIG. 2C illustrates exemplary method flow diagram, in accordance
with an embodiment of the present disclosure.
[0036] FIG. 3 illustrates exemplary flow diagram representation of data
model flow, in accordance with an embodiment of the present disclosure.
[0037] FIG. 4 illustrates an exemplary hierarchical tree structure
representation of data attributes, in accordance with an embodiment of the present
disclosure.

[0038] FIG. 5 illustrates an exemplary computer system in which or with
which embodiments of the present invention can be utilized, in accordance with embodiments of the present disclosure.
[0039] The foregoing shall be more apparent from the following more
detailed description of the invention.
DETAILED DESCRIPTION OF INVENTION
[0040] In the following description, for the purposes of explanation, various
specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0041] The ensuing description provides exemplary embodiments only, and
is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth.
[0042] Embodiments of the present disclosure provides systems and
methods for social protection using data model. The present disclosure provides systems and methods for robust data model which reduces the efforts of developers, government officers in meeting the dynamic requirements due to the ever-changing policy environments. The present disclosure provides systems and methods for selecting attributes and categorising the attributes. The present disclosure enables to configure any number/type of social protection program/scheme using the same data model. The present disclosure provides systems and methods for identification

of more than e.g., 300 attributes after analyzing and deconstructing e.g., 1500+
social welfare programs. The present disclosure provides systems and methods for
mapping interdependency and relationship among close to e.g., 200 data points. The
present disclosure provides systems and methods for organizing the attributes in
e.g., 6 different categories - Social, economic, occupation, education, housing, and
health. The present disclosure enables mapping of individual profile data with the
rules derived from multiple schemes, and for thousands of such scenarios in run
time within a fraction of a second, while the user is responding to a question.
[0043] Referring to FIG. 1 that illustrates an exemplary network
architecture for social protection system (100) (also referred to as network
architecture (100)) in which or with which a system (110)/Artificial Intelligence
(AI) engine (216) or simply referred to as the system (110)/AI engine (216) of the
present disclosure can be implemented, in accordance with an embodiment of the
present disclosure. As illustrated, the exemplary architecture (100) may be
equipped with the system (110)/AI engine (216) for social protection based on
data/answers/input received from users (102-1, 102-2, 102-3, ...102-N)
(individually referred to as the user (102) and collectively referred to as the users
(102)) associated with one or more first computing devices (104-1, 104-2... 104-N)
(individually referred to as the first computing device (104) and collectively
referred to as the first computing devices (104)). The system (110) may be further
operatively coupled to a second computing device (108) (also referred to as the user
computing device or user equipment (UE) hereinafter) associated with an entity
(114). The entity (114) may include a company, a hospital, an organisation, a
university, a lab facility, a business enterprise, or any other secured facility
associated with welfare and social policy benefits. In some implementations, the
system (110) may also be associated with the UE (108). The UE (108) can include
a handheld device, a smart phone, a laptop, a palm top and the like. Further, the
system (110) may also be communicatively coupled to the one or more first
computing devices (104) via a communication network (106).
[0044] The system (110) may be coupled to a centralized server (112). The
centralized server (112) may also be operatively coupled to the one or more first

computing devices (104) and the second computing devices (108) through the communication network (106). In some implementations, the system (110) may also be associated with the centralized server (112).
[0045] In an embodiment, the system (110) may be configured to receive a
first set of data packets from a plurality of first computing devices (104) pertaining to an information service associated with a plurality of policy documents further associated with one or more social welfare programs to be availed by the plurality of users (102) operating the plurality of first computing devices (104). The system (110) may then create, a descriptive document for the one or more social welfare programs based on the first set of data packets. The descriptive document may include a set of eligibility and predefined rules provided in the plurality of policy documents. For example, the system (110) may analyse a policy document of the social welfare program, and a descriptive document may be created for the same social welfare program to segregate the eligibility and other rules (data) from the policy.
[0046] In an embodiment, the system may further extract a first set of
attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents. Based on the extracted first set of attributes, the system may identify, by using an artificial intelligence (AI) engine (216), a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents. The second set of attributes pertain to existing rules and conditions of the social welfare program associated with any or a combination of the current societal norms, geography and profile level of each user. For example, the system (110) may check which already present in the plurality of policies (also referred to as the master data) one or more first set of attributes required for building the decision tree of the program, based on the descriptive document. If the required first attribute is already present in the master data, the same is used, if not, a new second attribute is to be created.
[0047] In an embodiment, generate, through the AI engine, a trained model
configured to process the decision tree, and predict, from the processed decision

tree, the information service associated with the one or more social welfare programs, and facilitate response corresponding to the information service to the plurality of users based on the trained model. The system may be further configured to auto-generate, using the AI engine (216), the social protection application for the plurality of users.
[0048] In an embodiment, the system (110) may critically analyse the first
and second set of attributes and a User Interface (UI) question for the same may be framed upon, to create a new second set of attributes. The attribute may also be given the desired display text and a hierarchical structure with geography and profile levels is defined for the attribute.
[0049] In an embodiment, the system (110) may iterate above steps for all
new attributes, for gathering the required attributes (both the first and the second set of attributes) to construct an eligibility engine for the social welfare program. Attributes of the decision tree are the subset values taken from the master data, and the same are then further used to construct the decision tree for the social welfare program.
[0050] In an embodiment, the system (110) may create the master data. The
master data sheet may include sufficiently required attributes and possible values
of those attributes in the social welfare context. This data has been built over a
period of time after thorough analysis of the government policies. The government
policies were broken down to discrete data points under groups such as, but are not
limited to, eligibility, benefit, reporting rules and payment rules, and the like.
[0051] In an embodiment, the system (110) may organize the data attributes
in a manner to build hierarchical tree structure. Top node may be the most generic
level data. It is further broken in multiple layers until the last leaf is arrived. This
helps in eliminating the user, if ineligible at a very early step.
[0052] For example, by reading and analysing 1500+ social welfare
schemes to come up with approximately 300 attributes. A hierarchical structure may be defined and continuously evolving fields are populated onto it. For example, design of data modelling considers four pointers of, but are not limited to, who, what, for, specific, and the like. A descriptive document may be constructed for

every scheme to segregate data from the Policy document. The data model may define the schemes objectively, covering necessary points. It follows a hierarchical structure with geography and profile levels.
[0053] In an embodiment, the system (110) may be a System on Chip (SoC)
system but not limited to the like. In another embodiment, an onsite data capture, storage, matching, processing, decision-making and actuation logic may be coded using Micro-Services Architecture (MSA) but not limited to it. A plurality of microservices may be containerized and may be event based in order to support portability.
[0054] In an embodiment, the network architecture (100) may be modular
and flexible to accommodate any kind of changes in the system (110). The system (110) configuration details can be modified on the fly.
[0055] In an embodiment, the system (110) may be remotely monitored and
the data, application and physical security of the system (110) may be fully ensured. In an embodiment, the data may get collected meticulously and deposited in a cloud-based data lake to be processed to extract actionable insights. Therefore, the aspect of predictive maintenance can be accomplished.
[0056] In an exemplary embodiment, the communication network (106)
may include, by way of example but not limitation, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. A network may include, by way of example but not limitation, one or more of: a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, some combination thereof.
[0057] In another exemplary embodiment, the centralized server (112) may
include or comprise, by way of example but not limitation, one or more of: a stand¬alone server, a server blade, a server rack, a bank of servers, a server farm, hardware

supporting a part of a cloud service or system, a home server, hardware running a
virtualized server, one or more processors executing code to function as a server,
one or more machines performing server-side functionality as described herein, at
least a portion of any of the above, some combination thereof.
[0058] In an embodiment, the one or more first computing devices (104),
the one or more second computing devices (108) may communicate with the system (110) via set of executable instructions residing on any operating system. In an embodiment, to one or more first computing devices (104), and the one or more second computing devices (108) may include, but not limited to, any electrical, electronic, electro-mechanical or an equipment or a combination of one or more of the above devices such as mobile phone, smartphone, Virtual Reality (VR) devices, Augmented Reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, wherein the computing device may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as camera, audio aid, a microphone, a keyboard, input devices for receiving input from a user such as touch pad, touch enabled screen, electronic pen, receiving devices for receiving any audio or visual signal in any range of frequencies and transmitting devices that can transmit any audio or visual signal in any range of frequencies. It may be appreciated that the to one or more first computing devices (104), and the one or more second computing devices (108) may not be restricted to the mentioned devices and various other devices may be used. A smart computing device may be one of the appropriate systems for storing data and other private/sensitive information.
[0059] FIG. 2A illustrates an exemplary block diagram representation of
proposed system (110) for facilitating a social protection application for a plurality of users, in accordance with an embodiment of the present disclosure. In an aspect, the system (110) may include one or more processor(s) (202). The one or more processor(s) (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, edge or fog microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that

process data based on operational instructions. Among other capabilities, the one or more processor(s) (202) may be configured to fetch and execute computer-readable instructions stored in a memory (204) of the system (110). The memory (204) may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (204) may comprise any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0060] In an embodiment, the system (110) may include an interface(s) 206.
The interface(s) (206) may comprise a variety of interfaces, for example, interfaces
for data input and output devices, referred to as I/O devices, storage devices, and
the like. The interface(s) (206) may facilitate communication of the system (110).
The interface(s) (206) may also provide a communication pathway for one or more
components of the system (110). Examples of such components include, but are not
limited to, processing unit/engine(s) (208) and a database (210).
[0061] The processing unit/engine(s) (208) may be implemented as a
combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) (208). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) (208) may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) (208) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (208). In such examples, the system (110) may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but

accessible to the system (110) and the processing resource. In other examples, the
processing engine(s) (208) may be implemented by electronic circuitry.
[0062] The processing engine (208) may include one or more engines
selected from any of a data acquisition engine (212), a social protection engine (214), an artificial intelligence engine (216) and other engines/units (218). The processing engine (208) may further edge based micro service event processing but not limited to the like.
[0063] The data acquisition engine (212) may receive a first set of data
packets from a plurality of first computing devices (104) pertaining to an
information service associated with a plurality of policy documents further
associated with one or more social welfare programs to be availed by the plurality
of users (102) operating the plurality of first computing devices (104).
[0064] The social protection engine (214) may create, a descriptive
document for the one or more social welfare programs based on the first set of data packets. The descriptive document may include a set of eligibility and predefined rules provided in the plurality of policy documents. For example, the system (110) may analyse a policy document of the social welfare program, and a descriptive document may be created for the same social welfare program to segregate the eligibility and other rules (data) from the policy. The social protection engine (214) may further extract a first set of attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents.
[0065] Based on the extracted first set of attributes, the AI engine (216) may
identify, a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents. The second set of attributes pertain to existing rules and conditions of the social welfare program associated with any or a combination of the current societal norms, geography and profile level of each user. For example, the AI engine (216) may check which already present in the plurality of policies (also referred to as the master data) one or more first set of attributes required for building the decision tree of the program, based on the descriptive document. If the required first attribute is

already present in the master data, the same is used, if not, a new second attribute is to be created.
[0066] The AI engine, may further generate, a trained model configured to
process the decision tree, and predict, from the processed decision tree, the information service associated with the one or more social welfare programs, and facilitate response corresponding to the information service to the plurality of users based on the trained model. The AI engine (216) may further auto-generate the social protection application for the plurality of users.
[0067] FIG. 2B illustrates an exemplary representation (220) of the user
equipment (UE) (108), in accordance with an embodiment of the present disclosure. In an aspect, the UE (108) may comprise a processor (222). The processor (222) may be implemented as an edge processor, one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the processor(s) (222) may be configured to fetch and execute computer-readable instructions stored in a memory (224) of the UE (108). The memory (224) may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (224) may comprise any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0068] In an embodiment, the UE (108) may include an interface(s) (226).
The interface(s) (226) may comprise 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) (226) may facilitate communication of the UE (108). Examples of such components include, but are not limited to, processing engine(s) (228) and a database (230).
[0069] The processing engine(s) (228) may be implemented as a
combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s)

(228). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) (228) may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) (228) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (228). In such examples, the UE (108) may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the UE (108) and the processing resource. In other examples, the processing engine(s) (228) may be implemented by electronic circuitry.
[0070] FIG. 2C illustrates exemplary method flow diagram (250) for
facilitating a social protection application for a plurality of users, in accordance
with an embodiment of the present disclosure. At 252, the method may include
receiving, by one or more processors (202), a first set of data packets from a
plurality of first computing devices (104), the first set of data packets pertaining to
an information service corresponding to a plurality of policy documents associated
with one or more social welfare programs to be availed by the plurality of users
(102) operating the plurality of first computing devices (104).
[0071] The method may also include at 254, the step of creating, by the one
or more processors (202), a descriptive document for the one or more social welfare programs based on the first set of data packets. The descriptive document may include a set of eligibility and predefined rules provided in the plurality of policy documents.
[0072] The method may include at 256, the step of extracting, by the one or
more processors (202), a first set of attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents.

[0073] The method may include at 258, the step of identifying, by using an
artificial intelligence (AI) engine (216), a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents based on the extracted first set of attributes. The second set of attributes may pertain to existing rules and conditions of the social welfare program associated with any or a combination of the current societal norms, geography and profile level of each user.
[0074] Furthermore, the method may include at 260, the step of generating,
through the AI engine (216), a trained model configured to process the decision
tree, and predict, from the processed decision tree, the information service
associated with the social welfare program, and facilitate response corresponding
to said information service to the plurality of users based on the trained model.
[0075] The method may further include at 262, the step of auto-generating,
using the AI engine (216), the social protection application for the plurality of users.
[0076] FIG. 3 illustrates exemplary flow diagram representation of data
model flow, in accordance with an embodiment of the present disclosure.
[0077] At step (302), master data sheet may include a universe of required
attributes and possible answers to the questions in the social welfare context. The master data sheet may include of a universe of required questions and possible answers to the questions in the social welfare context. The parameters in the master datasheet cover almost all the attributes that could be required to design the eligibility engine for a scheme or service. The master data-sheet may be continuously updated to add any new attributes encountered. The questions and values of the decision tree are the subset values taken from the master sheet of the data model.
[0078] At step (304), the master sheet may be continuously evolving and
fields are populated onto it. At step (306), read and analyse the policy document of the social welfare program. At step (308), a descriptive document may be created for the same social welfare program to segregate the eligibility and other rules (data) from the policy. At step (310), as per the descriptive documents, the attributes required for building the decision tree of the program are checked to be already

present in the master data. At steps (312) and (314), if the required attribute is already present in the master data, the same is used, if not, a new attribute is to be created, respectively. At step (316), to create a new attribute, the attribute is critically analysed and a UI question for the same is framed upon, the attribute is also given the desired display text and a hierarchical structure with geography and profile levels is defined for the attribute. At step (318), (320), (322) and (324), repeating above steps for all new attributes, all the required attributes are gathered to construct an eligibility engine for the social welfare program. At (326) and (328), attributes of the decision tree are the subset values taken from the master data, and the same are then further used to construct the decision tree for the social welfare program.
[0079] FIG. 4 illustrates an exemplary hierarchical tree structure
representation of data attributes, in accordance with an embodiment of the present disclosure.
[0080] In an embodiment, master data sheet may include a universe of
required attributes and possible values of those attributes in the social welfare
context. This data may be been built over a period of time after thorough analysis
of the government policies. The government policies may be broken down to
discrete data points under following rule groups such as, but are not limited to,
eligibility, benefit and reporting rules and payment rules. To use master data
efficiently for the decision trees, it is required to have the number of values under
10 for a particular attribute. Hence, the data attributes may be organised in a manner
to build hierarchical tree structure. Top node may be the most generic level data.
The top node may be further broken in multiple layers until the last leaf is arrived.
This helps in eliminating the user, if ineligible at a very early step.
[0081] For example, the first attribute asked to the user (102) may be about
his/her occupation, if the user (102) selects the value unorganised sector as shown in FIG. 4, then more specific attributes related to the user (102) answer may be displayed such as construction worker, agricultural labour, domestic worker, sanitation worker, artisan, (as shown in FIG. 4 in the similar way depending on the value selected from the above, the next attribute is displayed. In this way very

specific information may be gathered for the user depending upon the requirement of his profile/scheme applied. Similarly, if values for each node is presented to the user (102), the final representation may be of a hierarchical structure similar to a tree.
[0082] A decision tree may be a type of supervised machine learning where
the data may be continuously split according to a certain parameter. The tree can be explained by two entities, namely decision nodes and leaves. The leaves may be the decisions or the final outcomes. The system (110) may provide welfare schemes and services offered by the government. Hence, the final outcome (leaf node) may be exact benefit along with required documents for schemes. For services, the final outcome may be discovery of sub service which is determined by a unique fee and set of documents. Further, the decision nodes are where the data may be split. Here, decision nodes may be various attributes of the social welfare domain as defined in the master data. These decision nodes may be specific to scheme/service as per the eligibility and the benefit rules. The master data may be a repository of all the attributes with their respective values and the text to be displayed to the user on the front end. The decision may be made on the basis of values of the attributes. Thus, the decision tree may be the logical flow of the attributes and their value determining the next attribute in the tree. It has a hierarchical structure. Following decisions may be handled with the help of the decision tree such as, but are not limited to, which question to be displayed for a value selected by the user for the preceding question? which value to be displayed for a value selected by the user for a preceding question?, which document to be mapped to a value selected by the user? document is mapped with a certain value of the attribute to validate the response, what fees to be mapped to a value selected by the user?, what benefit should be displayed to the user based on the values selected by him during the execution of the decision tree?, and the like.
[0083] FIG. 5 illustrates an exemplary computer system (500) in which or
with which embodiments of the present invention can be utilized, in accordance with embodiments of the present disclosure.

[0084] As shown in FIG. 5, computer system (500) can include an external
storage device (510), a bus (520), a main memory (530), a read only memory (540), a mass storage device (550), communication port (560), and a processor (570). Processor (570) may include various modules associated with embodiments of the present invention. Communication port (560) can 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. Communication port (560) may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects. Memory (530) can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read-only memory (540) can be any static storage device(s). Mass storage (550) may be any current or future mass storage solution, which can be used to store information and/or instructions.
[0085] Bus (520) communicatively couples' processor(s) (570) with the
other memory, storage and communication blocks. Bus (520) can be, e.g., a
Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small
Computer System Interface (SCSI), 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 processor (570) to software system.
[0086] Optionally, operator and administrative interfaces, e.g., a display,
keyboard, and a cursor control device, may also be coupled to bus (520) to support direct operator interaction with a computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port (560). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[0087] 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 invention. These and other changes in the preferred

embodiments of the invention 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 invention and not as limitation.
[0088] 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, IC layout design, and/or trade dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (herein after 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.
ADVANTAGES OF THE PRESENT DISCLOSURE
[0089] The present disclosure provides systems and methods for social
protection using data model.
[0090] The present disclosure provides systems and methods for robust data
model which reduces the efforts of developers, government officers in meeting the
dynamic requirements due to the ever-changing policy environments.
[0091] The present disclosure provides systems and methods for selecting
attributes and categorising the attributes.
[0092] The present disclosure enables to configure any number/type of
social protection program/scheme using the same data model.
[0093] The present disclosure provides systems and methods for
identification of more than e.g., 300 attributes after analyzing and deconstructing
e.g., 1500+ social welfare programs.
[0094] The present disclosure provides systems and methods for mapping
interdependency and relationship among close to e.g., 200 data points.
[0095] The present disclosure provides systems and methods for organizing
the attributes in e.g., 6 different categories - Social, economic, occupation,
education, housing, and health.

[0096] The present disclosure enables mapping of individual profile data
with the rules derived from multiple schemes, and for thousands of such scenarios in run time within a fraction of a second, while the user is responding to a question.

We Claim:

1. A system (110) for facilitating a social protection application for a plurality of users (102), said system (110) comprising;
one or more processors (202) operatively coupled to a plurality of first computing devices (104), the one or more processors (202) coupled with a memory (204), wherein said memory (204) stores instructions which when executed by the one or more processors (202) causes said system (110) to:
receive a first set of data packets from a plurality of first computing devices (104), the first set of data packets pertaining to an information service corresponding to a plurality of policy documents associated with one or more social welfare programs to be availed by the plurality of users (102) operating the plurality of first computing devices (104);
create, a descriptive document for the one or more social welfare programs based on the first set of data packets, wherein the descriptive document comprises a set of eligibility and predefined rules provided in the plurality of policy documents;
extract a first set of attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents;
based on the extracted first set of attributes, identify, by using an artificial intelligence (AI) engine (216), a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents, wherein the second set of attributes pertain to existing rules and conditions of the social welfare program associated with any or a combination of the current societal norms, geography and profile level of each user;

generate, through the AI engine, a trained model configured to process the decision tree, and predict, from the processed decision tree, the information service associated with the one or more social welfare programs, and facilitate response corresponding to said information service to the plurality of users based on the trained model; and
auto-generate, using the AI engine, the social protection application for the plurality of users.
2. The system as claimed in claim 1, wherein the system is further configured to check, by the AI engine, if the second set of attributes in the social protection application.
3. The system as claimed in claim 1, wherein the system is further configured to generate a new second set of attributes if the second set of attributes are absent the descriptive document.
4. The system as claimed in claim 1, wherein the system is further configured to receive the first set of data packets from a plurality of first computing devices (104) based on a user query associated with the one or more social welfare program.
5. The system as claimed in claim 1, wherein a user query associated with the information services is received at a client side of the social protection application through a user interface in the form of a second set of data packets from said user computing device, and wherein said response that is mapped with the information service is transmitted in real-time in the form of a third set of data packets to said user computing device from server side of the social protection application.

6. The system as claimed in claim 1, wherein the system is configured to obtain a registration data based on a request from an unregistered user through respective user computing device, wherein login credentials are generated based on acknowledgement of the request and verification of the registration data, wherein the user enters the generated login credentials to access the system to obtain the information service associated with the user.
7. The system as claimed in claim 1, wherein the system is configured to display, through a user interface, a text and a hierarchical structure with geography and profile levels associated with the first and the second set of attributes.
8. The system as claimed in claim 1, wherein the system is configured to iterate steps for the decision tree for updating the new second set of attributes that takes into account relevant information associated with the society at the predefined point of time.
9. The system as claimed in claim 8, wherein the relevant information associated with the society at the predefined point of time is data that has been built over a period of time after thorough analysis of a plurality of policies.
10. The system as claimed in claim 8, wherein the system is further configured to analyse the plurality of policies to come up with a plurality of first set of attributes.
11. The system as claimed in claim 8, wherein the system is further configured
to categorise the plurality of policies into a plurality of categories associated
with eligibility, benefit, reporting rules and payment rules.

12. The system as claimed in claim 8, wherein the system is further configured
to build the decision tree in a hierarchical tree structure, wherein a top node
in the decision tree comprises the most generic level data, and wherein each
node comprises continuously evolving fields associated with the one or
more social welfare programs.
13. The system as claimed in claim 8, wherein the system is further configured to eliminate a user, if ineligible at a very early step based on the hierarchical tree structure.
14. The system as claimed in claim 8, wherein the system is further configured to construct a descriptive document for every scheme to of the one or more social welfare programs.
15. A user equipment (UE) (108) for facilitating a social protection application for a plurality of users (102), said UE comprising;
a processor (222) operatively coupled to a plurality of first computing devices (104), the processor (222) coupled with a memory (224), wherein said memory (224) stores instructions which when executed by the processor (222) causes said UE (108) to:
receive a first set of data packets from a plurality of first computing devices (104), the first set of data packets pertaining to an information service corresponding to a plurality of policy documents associated with one or more social welfare programs to be availed by the plurality of users (102) operating the plurality of first computing devices (104);
create, a descriptive document for the one or more social welfare programs based on the first set of data packets, wherein the descriptive document comprises a set of eligibility and predefined rules provided in the plurality of policy documents;

extract a first set of attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents;
based on the extracted first set of attributes, identify, by using an artificial intelligence (AI) engine (236), a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents, wherein the second set of attributes pertain to existing rules and conditions of the one or more social welfare programs associated with any or a combination of the current societal norms, geography and profile level of each user;
generate, through the AI engine (236), a trained model configured to process the decision tree, and predict, from the processed decision tree, the information service associated with the one or more social welfare programs, and facilitate response corresponding to said information service to the plurality of users based on the trained model; and
auto-generate, using the AI engine (236), the social protection application for the plurality of users.
16. A method (250) for facilitating a social protection application for a plurality of users (102), said method (110) comprising;
receiving, by one or more processors (202), a first set of data packets from a plurality of first computing devices (104), the first set of data packets pertaining to an information service corresponding to a plurality of policy documents associated with one or more social welfare programs to be availed by the plurality of users (102) operating the plurality of first computing devices (104), wherein the one or more processors (202) operatively coupled to a plurality of first computing devices (104), the one or more processors (202)

coupled with a memory (204), wherein said memory (204) stores instructions which are executed by the one or more processors (202);
creating, by the one or more processors (202), a descriptive document for the one or more social welfare programs based on the first set of data packets, wherein the descriptive document comprises a set of eligibility and predefined rules provided in the plurality of policy documents;
extracting, by the one or more processors (202), a first set of attributes from the descriptive document, the first set of attributes pertaining to the set of eligibility and predefined rules provided in the plurality of policy documents;
based on the extracted first set of attributes, identifying, by using an artificial intelligence (AI) engine (216), a decision tree to segregate and identify a second set of attributes from the set of eligibility and predefined rules provided in the plurality of policy documents, wherein the second set of attributes pertain to existing rules and conditions of the one or more social welfare programs associated with any or a combination of the current societal norms, geography and profile level of each user;
generating, through the AI engine (216), a trained model configured to process the decision tree, and predict, from the processed decision tree, the information service associated with the social welfare program, and facilitate response corresponding to said information service to the plurality of users based on the trained model; and
auto-generating, using the AI engine (216), the social protection application for the plurality of users.
17. The method as claimed in claim 16, wherein the method further comprises the step of checking, by the AI engine, if the second set of attributes in the social protection application.

18. The method as claimed in claim 16, wherein the method further comprises the step of generating a new second set of attributes if the second set of attributes are absent the descriptive document.
19. The method as claimed in claim 16, wherein the method further comprises the step of receiving the first set of data packets from a plurality of first computing devices (104) based on a user query associated with the one or more social welfare program.
20. The method as claimed in claim 16, wherein a user query associated with the information service is received at a client side of the social protection application through a user interface in the form of a second set of data packets from said user computing device, and wherein said response that is mapped with the information service is transmitted in real-time in the form of a third set of data packets to said user computing device from server side of the social protection application.
21. The method as claimed in claim 16, wherein the method is configured to obtain a registration data based on a request from an unregistered user through respective user computing device, wherein login credentials are generated based on acknowledgement of the request and verification of the registration data, wherein the user enters the generated login credentials to access the method to obtain the information service associated with the user.
22. The method as claimed in claim 16, wherein the method further comprises the step of displaying, through a user interface, a text and a hierarchical structure with geography and profile levels associated with the first and the second set of attributes.

23. The method as claimed in claim 16, wherein the method further comprises
the step of iterating steps for the decision tree for updating the new second
set of attributes that takes into account relevant information associated with
the society at the predefined point of time.
24. The method as claimed in claim 23, wherein the relevant information
associated with the society at the predefined point of time is data that has
been built over a period of time after thorough analysis of a plurality of
policies.
25. The method as claimed in claim 23, wherein the method further comprises
the step of analysing the plurality of policies to come up with a plurality of
first set of attributes.
26. The method as claimed in claim 23, wherein the method further comprises the step of categorising the plurality of policies into a plurality of categories associated with eligibility, benefit, reporting rules and payment rules.
27. The method as claimed in claim 23, wherein the method further comprises the step of building the decision tree in a hierarchical tree structure, wherein a top node in the decision tree comprises the most generic level data, and wherein each node comprises continuously evolving fields associated with the one or more social welfare programs.
28. The method as claimed in claim 27, wherein the method further comprises
the step of eliminating a user, if ineligible at a very early step based on the
hierarchical tree structure.

29. The method as claimed in claim 16, wherein the method further comprises the step of constructing a descriptive document for every scheme to of the one or more social welfare programs.