DESC:FORM 2

THE PATENTS ACT, 1970
(39 OF 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(Section 10 and Rule 13)

1. Title of the Invention
METHOD AND SYSTEM TO FACILITATE APPLIED LEARNING AND INCULCATING PROBLEM SOLVING
2. Applicant(s)
GROK LEARNING PRIVATE LIMITED, INDIAN, 30 IST VAIBHAV IND ESTATE SION TROMBAY ROAD DEONAR BOMBAY MUMBAI, MAHARASHTRA-400088, INDIA
3. Preamble to the description

The following complete specification describes the invention.

METHOD AND SYSTEM TO FACILITATE APPLIED LEARNING AND INCULCATING PROBLEM SOLVING

CROSS-REFERENCE TO RELATED APPLICATION AND PRIORITY
[0001] The present application claims priority from Indian provisional patent application number 202221053293, filed on September 18, 2022. The entire content of the abovementioned application is incorporated herein by reference.
TECHNICAL FIELD
[0002] The disclosure herein generally relates to a field for facilitating applied learning, integrating approaches for solving a real-life industry problem, and more particularly, to a method and a system for facilitating applied learning to solve the real-life industry problems depending on the nature and complexity of the real-life industry problems and inculcating the approach of problem-solving in a learning environment.
BACKGROUND
[0003] Merriam Webster dictionary defines learning as acquisition of knowledge or skill by instructions of study. The sole purpose of learning is to substitute an empty mind with an open and inquisitive mind and like the sides of a coin, it has theoretical on one side and practical on the other side. Theoretical learning means learning anything without adopting a practical approach. While theoretical leaning is what learning and knowledge acquisition is about, the practical learning is implementing the knowledge so acquired, for solving problems and building viable solutions.
[0004] Educators across the world, time and again, emphasize the importance of learning by doing and it becomes imperative for students, learning professionals and users in professional programs to put up to practice what they have learnt in the classroom or educational programs. There have been research literatures which support the assertion that learning takes place within a cycle that includes action, reflection and application of mind. In a classroom learning set-up (irrespective of its online or offline nature), theoretical clarity would be provided on a particular topic or subject, wherein the participant may get adequate understanding about aspects related to constitution of things, their principles of working but may not learn or understand how to build new products or things using the acquired knowledge. For example, if a person studies about an engine and parts thereto, the person will know of the working of the engine, construction of the parts, material from which the engine is made, but would not be able to reinvent the engine or improve the performance of the engine. Current teaching mechanisms face the challenge of providing participants with knowledge often without incorporating meaningful real-world applications and programming the human mind with problem-solving acumen.
[0005] With the integration of technology into learning and teaching domains, the index of learning has improved with seamless integration of visual, auditory and tactile senses with refinement of conceptual and practical learning. However, said integration comes with its own disadvantages and issues. The conventional software applications aiding students in learning, provide accessibility to various courses, materials and tools to improve student engagement with the course content. However, said applications are limited to the course content and do not give any support to the student towards solving the real-life technical problems faced by the student. For example, a conventional software providing learning courses and applications for Internet of things (IoT) may include theoretical content on IoT including origins of IoT, building blocks of IoT, communication among IoT components, IoT designs, IoT frameworks, security considerations and a generic problem for the student to solve, which is very different from the issues and challenges faced by the student in real-world while dealing with IoT enterprise. Also, the current learning software provide no or limited intellectual ability to the learner engaging with it, thereby inculcating the learner’s approach instead of thinker and/or problem solver approach.
[0006] Another issue identified in the domain of learning and problem solving is the issue of attention span and retention of concentration for users/participants. The fast-paced nature of digital world has led to a decrease in average attention span and a growing satisfaction with superficial understanding. The average span of human beings over two decades has decreased by 25% and there is a foundational need to ensure that learning goes beyond superficial understanding and to develop systems for helping participants better manage their own attention and concentration and not get distracted while engaged in a learning environment.
[0007] The efforts made in the prior arts are far from solving the problem detailed above, as most of the prior arts focus on deepening the engagement and concentration of the users with the current technology platforms, instead of inculcating the innovator and problem-solving approach and attempting to increase the attention span of the users. Considering the foregoing, there exists a need for a technical and reliable solution to facilitate applied learning with emphasis on problem solving approach and retaining the attention span of the user.
OBJECTIVES OF THE INVENTION
[0008] Some of the objectives of the present disclosure, which at least one embodiment herein satisfies, are as follows:
[0009] It is an objective of the present disclosure to overcome one or more problems of the prior art or at least provide a useful alternative.
[00010] An objective of the present disclosure is to provide a system and method to aid the user to solve real-life industry problems by using the applied knowledge provided by the system.
[00011] Another objective of the present disclosure is to provide a system and method that help in maximizing user cognitive development and scholastic performance towards solving technical problems faced in real-life.
[00012] Yet another objective of the present disclosure is to provide a system and method that’s helps in facilitating learning and problem solving for a user with ease and irrespective of pre-requisite knowledge level requirements.
[00013] Yet another objective of the invention is to provide a system and/or a platform which is compatible to any academic or learning infrastructure.
[00014] Yet another objective of the invention is to allow the system to understand user learning and approach pattern towards solving a real-life technical problem.
[00015] Yet another objective of the invention is to manage and monitor the attention span of the user engaged in solving a real-life industry problem.
[00016] Other objectives and advantages of the present invention will become apparent from the following descriptions, taken in connection with the accompanying drawings, wherein, by way of illustration and example, an embodiment of the present invention is disclosed.
SUMMARY OF THE INVENTION
[00017] This summary is provided to introduce aspects to method and system for facilitating applied learning and inculcating problem solving, and the aspects are further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
[00018] In view of the foregoing (para [00017]), an embodiment herein provides a system for facilitating applied learning and inculcating problem solving. In one aspect, a system for facilitating applied learning, to solve a real-life industry problem, depending on a nature and complexity of the real-life industry problem, is provided. The system comprises an input/output interface to receive an input query from a user to solve a real-life industry problem, wherein the query is in the form of a textual input, an audio input, a video input, and an image input. Further, the system comprises at least one memory storing a plurality of instructions, and one or more hardware processors communicatively coupled with the at least one memory, wherein the one or more hardware processors are configured to execute one or more modules.
[00019] A collection module of the system is configured to collect a subscription status of the user, a history information, one or more preferences, and one or more responses of the system to one or more queries raised by the user to facilitate an interaction of the user with the system. A query analyzing module of the system is configured to analyze the received input query using natural language processing to identify a set of keywords of the received input query, received in audio or textual format. Furthermore, a matching module of the system is configured to assist the user through one or more approaches, a list of hardware components and related software need to solve the real-life industry problem contained in the input query. Further, an assistance module of the system is configured to monitor and provide the user with cues to select one or more hardware components and related software and a pattern of implementation and assembly. Finally, a pre-trained AI engine of the system to ensure active compliance of a set of pre-defined rules governing the pattern of implementation and assembly of one or more hardware components and related software and analyze the selected pattern of implementation and assembly, wherein the pre-trained AI engine is trained based on number of times such pattern is successfully implemented for solving a similar real-life problem.
[00020] In another embodiment, an application management module of the system is configured to capture one or more information related to the user to create a user account and an authentication module of the system is configured to authenticate an identification of the user upon receipt of an authentication request from the user, by matching a predefined unique identification detail to enable the user to get access secured data stored within a system repository.
[00021] In yet another embodiment, an appliance repository of the system is configured to include data related to one or more hardware components, wherein the one or more hardware components include one or more known appliances and one or more developed appliances.
[00022] In another embodiment, a processor implemented method of an applied learning to solve a real-life industry problem depending on a nature and complexity of the real-life industry problem is provided. The processor implemented method includes receiving, via an input/output interface, an input query from a user to solve a real-life industry problem. The received input query is received in textual, audio, video or image format wherein the input query in the textual or audio format is analyzed using a natural language processing to identify a set of keywords of the received input query. Further, the processor-implemented method includes collecting a subscription status of the user, history information, one or more preferences, and one or more responses of the system to one or more queries raised by the user to facilitate an interaction of the user with the system. Further, the processor-implemented method includes assisting the user with one or more approaches, a list of hardware components and software respectively needed to solve the real-life industry problem contained in the received input query. Further, the processor-implemented method includes monitoring the user and providing one or more cues to select one or more hardware components, related software and a pattern of implementation and assembly. In furtherance, the processor-implemented method includes ensuring active compliance of a set of pre-defined rules governing the pattern of implementation and assembly of one the one or more hardware components and related software and analyzing the selected pattern of implementation and assembly against a frequency of implementation of the pattern and the assembly for solving a similar real-life industry problem.
[00023] It should be appreciated by those skilled in the art that any block diagram herein represents conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo codes, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computing device or processor, whether or nor such computing device or processor is explicitly shown.
BRIEF DESCRIPTION OF DRAWINGS
[00024] The following detailed description of preferred embodiments are better understood when read in conjunction with the appended drawings. For the purpose of illustrating the invention, there is shown in the drawings exemplary constructions of the invention; however, the invention is not limited to the specific methods and system disclosed. In the drawings:
[00025] Figure 1 illustrates a network implementation of a system for facilitating applied learning and inculcating problem-solving in accordance with an embodiment of the present disclosure;
[00026] Figure 2 illustrates a high-level architecture of a part of the system of Figure 1 that facilitates applied learning and inculcating problem-solving, in accordance with an embodiment of the present disclosure;
[00027] Figure 3 illustrates a flow diagram depicting the process of a user accessing the system of Figure 1 for learning educative content in accordance with an embodiment of the present disclosure;
[00028] Figure 4 illustrates a flow diagram for a processor-implemented method for depicting the process of the user solving a real-life industry problem by accessing the system of Figure 1 in accordance with an embodiment of the present disclosure;
[00029] Figure 5 depicts an exemplary embodiment of an exemplary user accessing and using the system of Figure 1 for solving an exemplary real-life industry problem in accordance with an exemplary embodiment of the present disclosure;
[00030] Figure 6a, 6b, 6c, 6d, 6e, 6f and 6g depict an exemplary illustration of solving the exemplary real-life industry problem of Figure 5 by processor implemented method in accordance with an exemplary embodiment of the present disclosure.

DETAILED DESCRIPTION

[00031] Exemplary embodiments are described herein with reference to accompanying drawings. While examples and features of disclosed principles are described herein, modifications, adaptations and other implementations are possible without departing from the spirit and scope of the disclosed embodiments. It is intended that the following detailed description be considered as exemplary only.
[00032] The terms “comprising”, “containing”, including”, “having” and other forms thereof, are intended to be equivalent in meaning and open ended in that item(s) following any of these terms is not meant to be exhaustive listing of such item or items or meant to be limited to only the listed item or items.
[00033] The following description and drawings are illustrative in nature and not to be construed as limiting. Numerous specific details are provided to provide a thorough understanding. However, in certain instances, well-known or conventional details are not described in order to avoid obscuring the description.
[00034] It must also be noted that the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present invention, the preferred, systems and methods are now described. In the following description for the purpose of explanation and understanding, reference has been made to numerous embodiments for which the intent is not to limit the scope of the invention. The elements illustrated in the Figures interoperate as explained in more detail below. Before setting forth the detailed explanation, however, it is noted that all the discussion below, regardless of the particular implementation being described, is exemplary in nature, rather than limiting.
[00035] Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skills in the art will readily recognize that the present disclosure is not intended to be limited to the embodiments illustrated but is to be accorded the widest scope consistent with the principles and features described herein.
[00036] The invention disclosed herein, through contemplated embodiments, resolve the biggest challenge of the conventional learning software and applications through the creation of a system, which provides a platform for learning new and innovative concepts with the additional provision for inculcating solving the real-life industry problems using the learning acquired by the user from the system. The design intent of the invention is to provide its users with quality of educative content for learning while ensuring that the user applies the principles and concepts learnt by accessing the educative content, to solve technical challenges with maximum resource utilization. Some additional intents include providing access to repository of the educative content and possible solutions for technical problems (irrespective of the nature, industry and complexity), learning and access to the educative content in relation to known devices or appliances or hardware components, related software components and programming logics and rules and methods governing the assembly of said known devices to build new and improved devices, learning to build solutions (existing and new) for industry problems or already identified industry problems to instill the thinker approach within the user and to monitor and manage the attention span of the user engaged in learning concepts and solving real-life industry problems.
[00037] It is to be noted that the terms “real-life industry problems”, “technical problems”, “industry problems”, “real-life technical problems” may be interchangeably used based on the context, however, they refer to the technical problems or challenges faced by the user in real-life, be it academia, be it in a professional set-up or at domestic front.
[00038] Turning now to Figure 1, illustrated therein is a network implementation (100) of a system (102) for facilitating applied learning and inculcating problem-solving, according to an embodiment disclosed herein. One or more users (112), (114) may communicate with the system (102) to participate in, learn and acquire knowledge related to any educational discipline, course, sub-course, topic, sub-topic, multi-disciplinary courses, and the like and apply the newly acquired knowledge to solve the real-life industry problems. It is to be understood that a course is not limited to formal courses offered by educational institutions and academia. The courses may include any form of learning instructions offered by an entity of any type which may be proprietary in nature or provided under licensing arrangements. The courses may include learning instructions to cover the range of procedural, cognitive, behavioral and attitudinal constructs for learning and problem solving. For the purpose of clarity, the knowledge or learning material available within the system (102) in the form of course, sub-course, topic and the like, shall be hereinafter referred to as educative content. The educative content within the system (102) can be assembled into specific lesson plans, experimental activities, course units, courses, courses equivalents, problem solving curricula of different disciplines, multi-disciplinary course modules, modalities, certifications and programs. In an embodiment, the educative content within the system (102) may be arranged in the form of a relational database with each data point representing a course module. In another embodiment, the educative content within the system (102) may be arranged in the form of AWS S3 storage or NoSQL database.
[00039] In another embodiments, one or more user groups can be defined as one or more users. For example, as shown in Figure 1, the users (112), (114) may be grouped together to form a user group (116) participating and learning common educative content, such as within a school or college environment. In another embodiment, sub-user groups may be formed in relation to a particular project or assignment or basis the real-life industry problem to be solved or any other criteria defined by the users (112) (114) or user groups (116). In yet another embodiment, due to nature of the learning involved, the users (112-1), (112-2), (112-3) in a subgroup of users (112) may not meet physically but may collaborate with one another using various tools provided by the system (102).
[00040] As depicted in Figure 1, the system (102) for facilitating applied learning and inculcating problem-solving, is connected to at least one user device (106), through a communication network (104). The user device (106) can be any type of portable personal device capable of independently communicating with the communication network (104) (hereinafter referred to as “network”) and includes without limitation a handheld mobile phone (e.g., iPhoneTM or AndroidTM Smart phones), a handheld mobile device (e.g., iPod TouchTM), a tablet (e.g., iPadTM), a PDA, a notebook computer, a personal data assistant (PDA) or the like.
[00041] The network (104) provides voice and messaging capabilities and may provide access to other communication networks such as, for example, other mobile communication networks and internet. The network (104) includes any type of wireless communication network such as CDMA, GSM and other satellite-based networks. In one embodiment, the network (104) may be at least one of a wireless network and a wired network. The network (104) can be implemented as one or more of the different types of networks, such as intranet, local area network (LAN), wide area network (WAN), the Internet, etc. The network (104) may either be a dedicated network or a shared network. The shared network may represent an association of the different types of networks that use a variety of protocols (e.g., Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc.) to communicate with one another. Further, the network (104) may include a variety of network devices, including, for example, routers, bridges, servers, computing devices, storage devices, etc.
[00042] In an implementation, the system (102) may be connected to an appliance system (108) over the network (104) through one or more communication links. The communication link between the system (102) and the appliance system (108) may be enabled through a desired form of communication for example via dial-up modem connections, cable links, digital subscriber lines (DSL), wireless or satellite links, or any other suitable form of communication. The appliance system (108) comprises of one or more hardware components which can be inter-connected to each other. In an embodiment, the appliance system (108) comprises of known appliances (109) and developed appliances (110), capable of communicating with the system (102).
[00043] The known appliances (109) can be of any types of portable hardware components capable of communicating with the system (102), directly through communication network (104) or indirectly through appliance system (108) and includes without limitation sensors, motors, valves, relays, micro-controllers, actuators, transducers, solenoids, thermistors, thyristors, triacs, transistors, batteries, power supplies, potentiometers, electronic chips, connectors, and the like. For the purpose of clarity, the known appliances (109) may be interchangeably used with known device(s) in the prior art which can be assembled with other known devices as a whole or with their parts to assemble, create and/or make developed appliances (110). In another embodiment, the known appliances (109) may be used with other developed appliances (110) to improve upon the existing developed appliances (110) or to create/re-make/re-engineer the developed appliances (110).
[00044] The developed appliances (110) can be any type of hardware component(s), capable of being built by combining at least one of known appliances (109) with hardware components or machinery known in the prior art. The developed appliances (110) are capable of communicating independently with the system (102) through the communication network (104) and includes without limitation robots, robotic kits, instrument kits, a micro assembled device, assembled device kits, assembled hardware kits, assembled equipment and the like, capable of understanding and implementing instructions given locally or remotely.
[00045] The system (102) may be implemented in any of a variety conventional computing system, including, for example, servers, a desktop PC, a notebook or portable computer, a workstation, a mobile computing device, an entertainment device, and an internet appliance. It is also appreciated that the system (102) may be accessed by multiple users through one or more user devices (106-1), (106-2) ... (106-N) or applications residing on the user device (106) respectively. The system (102) enables the user to practice the skills, techniques and tools they have learned and then to assess the new approaches or solutions mostly adapted by users for its precision and incorporates the new approach or solution into its repository.
[00046] Figure 2 illustrates a high-level architecture of a part of the system (102) of Figure 1 that facilitates applied learning and inculcates problem-solving, in accordance with an embodiment of the present disclosure. The system (102) includes one or more hardware processors (202), an input/output (I/O) interface (204), and at least one memory (206) coupled to one or more hardware processors (202). The one or more hardware processors (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the one or more hardware processors (202) are configured to fetch and execute computer- readable instructions stored in the at least one memory (206).
[00047] The input/output (I/O) interface (204) may include a variety of software and hardware interfaces, for example, a web interface or a graphical user interface (GUI), allowing the system (102) to interact with the user devices (106). Further, the input/output (I/O) interface (204) may enable the system (102) to communicate with other computing devices, such as web servers and external data servers (not shown in figure). The input/output (I/O) interface (204) may facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular, or satellite. The input/output (I/O) interface (204) may include one or more ports for connecting a number of devices to each other or to another server.
[00048] The at least one memory (206) can include any computer-readable medium known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and/or non- volatile memory, such as read-only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes. In one embodiment, the at least one memory (206) includes module(s) (208) and data (210). The module(s) (208), amongst other things, includes instructions, routines, programs, objects, components, data structure, etc., that perform tasks or implement particular abstract data types.
[00049] In one implementation, the module(s) (208) may include an application management module (212), an authentication module (214), a collection module (216), a query analyzing module (218), a matching module (220), an assistance module (222), a pre-trained AI engine (224) and other modules (not shown in the figure). The other modules may include programs or coded instructions that supplement applications and functions of the system (102). It will be appreciated that such modules may be represented as a single module or a combination of different modules. Additionally, the data (210) serves, amongst other things, as a repository for storing data fetched, processed, received and generated by one or more of the modules (208). In one implementation, the data (210) may include, for example, user data (234) and other data (236). In one embodiment, the data (210) may be stored in the memory (206) in the form of data structures. Additionally, the aforementioned data can be organized using data models, such as relational or hierarchical data models.
[00050] In an implementation, the system (102) is coupled to a system repository (226). In an implementation, the system repository (226) may include a knowledge repository (228), an appliance repository (230) and a solution repository (232). It would be appreciated that although the system repository (226) is shown external to the system (102), the system repository (226) may also be provided internal to the system (102). In one implementation, the system repository (226) may be provided as relational database and may store data in various formats such as relational tables, appliance oriented relational tables and the like. Further, it would be understood that that the system repository (226) may be provided as one or more operational databases.
[00051] In another implementation, the knowledge repository (228) may include data that may define different types of educative content related to wide variety of disciplines, subjects, courses, topics, curriculum requirements, certification requirements and the like and may enable management and presentation of the educative content by the system (102) to the user device (106) and a relationship between the user and the educative content accessed. Accordingly, the knowledge repository (228) may provide consistent and reliable means of accessing educative content. Further, the educative content may be presented in the form of training material, documents, video files and audio files, interactive multi-media workbook, interactive glossary and simulation trainings, simulating environment and the like.
[00052] In yet another implementation, the appliance repository (230) may include data about various appliances (hardware components and related connections and inter-connections) connected and supported on the system (102). The appliance repository (230) may contain data related to the known appliances (109) including the data related to construction, principles and working of the known appliances (109). The appliance repository (230) may contain data related to the known appliances (109) including data related to hardware assembly of various known appliances (109) in various permutations and combinations to create or re-engineer the developed appliances (110). The appliance repository (230) may additionally contain data related to developed appliances (110) i.e., devices or appliances developed by the user for solving a real-life industry problem with the combination of one or more known appliances (109) and the machinery, equipment and parts thereof, by applying the learning and knowledge gained through accessing the system (102). The appliance repository (230) may contain data related to developed appliances (110) including data related to hardware assembly of developed appliances (110) from known appliances (109) or through a combination of the known appliances (109) and the developed appliances (110).
[00053] In another implementation, the solution repository (232) may contain the programming logics, applications, codes and data related to the appliance system (108). The solution repository (232) provides the user with requisite programming logic while deploying the known appliances (109) and the developed appliances (110) as an aid to solve the real-life industry problem(s). In an implementation, the solution repository (232) may receive data from the appliance system (108). The solution repository (232) is configured to store relations between various applications, inter-connections and assembly between known appliances (109) and developed appliances (110), their associated data and associated users. The solution repository (232) may include data that may be learnt by the system (102) in real-time, basis user application of acquired knowledge to solve the real-life industry problems through approaches not covered under system rules and logic.
[00054] In an implementation, the application management module (212) is configured to enable a downloaded mobile application (not shown in figures) to be registered with unique user identification data for creation of a user account on the system (102). The unique user identification data includes one or more parameters used in relation to registration of the user through user device (106) and creation of the user account on the system (102). The unique user identification data includes unique identification details such as login credentials, bio-metric data, session key (code, PIN, a one- time passcode (OTP), a digital signature, a key, a secret, a datum, a signal, a machine identifier or other dynamic value). It is to be noted that the unique user identification data would be used for authenticating user(s) and associated user device(s) (106) by the system (102) for future access. The user may be an adult and/or a child accessing the mobile application (not shown). The user device (106) maintains a connection with the network (104) through procedures executed within the user device (106). The mobile application can be executed on the user device (106) wherein the mobile application is hosted and operated by the system (102) (either independently or through a third-party) for use by its user through the network (104). In an embodiment, the mobile application is accessible through an API accessible over the Web (or another network).
[00055] Subsequent to creation of the user account and registration of associated user device (106) with the system (102), the application management module (212) is configured to capture information related to the user to create a user profile in the system (102). In an embodiment, the application management module (212) is configured to capture user information including name, age, gender, educational qualification, areas of interests, and any other information as voluntarily provided by the user for creation of user profile in the system (102). In an implementation, the application management module (212) is configured to enable the receipt of requests sent by the user through user device (106). In an embodiment, the requests sent by user through user device (106) may include an authentication request.
[00056] Upon receipt of the authentication request from the user device (106), the authentication module (214) is configured to match the unique user identification data with one or more user credentials contained in the authentication request. In another implementation, the one or more user credentials contained in authentication request include login id and password, bio-metric data and a, session key. In another embodiment, the session key may be a code, PIN, a one-time passcode (OTP), a digital signature, a key, a secret, a datum, a signal, a machine identifier or other dynamic value. In the event of a successful match between the one or more user credentials in the authentication request with the unique user identification data stored in the system (102), the authentication module (214) validates access of the user device (106). Upon successful authentication, the authentication module (214) is configured to enable access of user through user device (106) to secured data or the educative content within the system (102).
[00057] In an implementation, the collection module (216) of the system (102) is configured to gather plurality of information including user preference, a subscription status, user information, time spent by the user on the system (102), time spent by the user accessing the educative content and parts thereof, history information, response of the user to survey questions and/or response of user to queries generated (at random or periodic) by the system (102) basis the user activity to facilitate user interaction with the system (102) and to help the user engage more effectively and to retain the attention span of the user.
[00058] The history information refers to the information reflecting activity of the user through user device (106) on the system (102) and include data representations of search queries issued by user, search results provided to the user in response to search queries, selection indicators that reflect that the user has selected a particular result or content, dwell time (indicating the amount of time a user spends on a particular content or result) and any other type of activity that can be monitored and recorded by tracking the user’s input. The user information is generally collected from the user profile created at the time of user registration and includes registered user details such as name and age of the user, educational qualification of the user, areas of interest of the users, an educative content accessed by the user (completed and/or under process) and any other as voluntarily provided by the user. In an embodiment, the collection module (216) may collect the user information and/or update the existing user information from the mobile application hosted on the user device (106). The collection module (216) may derive the user preference from the user behavior or other implicit characteristics, or explicit characteristics of the user. The collection module (216) also collects the time spent by the user accessing the system (102) including the time spent on different courses, time spent on solving real-life industry problems, time-breaks taken while accessing educative contents and problem-solving to monitor the attention span of the user.
[00059] In an implementation, the query analyzing module (218) of the system (102) is configured to receive one or more input query from the user device (106). The input query received from the user device (106) is received in one of the formats including textual input, an audio input, a video input, and an image input. The query analyzing module (218) is configured to process the input query in textual or audio format through natural language processing to identify a set of keywords. The input query with image or video inputs may be processed by the query analyzing module (218) through technology architecture involving convolutional neural networks for extracting relevant information (features) and visual data from the images.
[00060] In an implementation, the matching module (220) of the system (102) is configured to analyze the input query received from the user device (106) and categorize the input query into one of learning query or problem-solving query, depending on the information extracted from the input query by the query analyzing module (218). The matching module (220) is configured to categorize the input query basis the set of keywords extracted by the query analyzing module (218). The matching module (220) upon categorization of the input query as the learning query, is configured to identify the educative content relevant to the user by performing various multi-way searches of the knowledge repository (228). In another implementation, the matching module (220) is configured to intelligently match the educative content basis the information collected by the collection module (216). The matching module (220) assists the user to access the educative content basis the user information and the history information collected by the collection module (216). In an embodiment, the input query received from the user device (106) may be in the form of multi-way search query wherein the first node is a wish-list search (where the input query is keywords) or a reference search. In a second node of multi-way search, the results from first node may be used to identify the courses that match the requirements of the user. In another implementation, the matching module (220) upon categorization of the input query as the problem-solving query, is configured to identify one or more approaches for solving the real-life industry problem contained in the input query, from the system repository (226). The one or more approaches for solving real-life industry problem are accompanied by a list of hardware components and software or programming logic related to the hardware components respectively, needed to solve the real-life industry problem contained in the input query. In an embodiment, the one or more approaches are accompanied by a list of known appliances (109), developed appliances (110) or a combination thereof, with related programming logic for connections and inter-connections and assembly of the foregoing.
[00061] In an implementation, the assistance module (222) of the system (102) is configured to assist the user through one or more approaches for solving the real-life industry problem, identified by the matching module (220) against the input query categorized as the problem-solving query, received from the user device (106). For the problem-solving query, the query analyzing module (218) is further configured to aid the user to clearly and succinctly define key facts around the real-life industry problem including the nature of industry the problem relates to, nomenclature of proposed solution or the approach used to derive the solution and description of the proposed solution.
[00062] In an implementation, the assistance module (222) of the system (102) is configured to monitor and provide the user through user device (106), one or more cues to select one or more hardware components out of the known appliances (109), the developed appliances (110) and combination thereof and a pattern of implementation and assembly (pattern of assembly). The assistance module (222) provides the user device (106) with the one or more cues towards selection of the one or more hardware component out of the known appliances (109), the developed appliances (110) and combination thereof and the pattern of implementation and assembly. Further, the assistance module (222) is configured to provide the user with one or more cues towards selection of one or more programming logic or software for solving the real-life industry problem.
[00063] In an implementation, the pre-trained Artificial Intelligence (AI) engine (224) of the system (102) is configured to monitor the selection and the assembly of one or more hardware components and related software/programming logic along with their assembly by the user through the user device (106) to solve the real-life industry problem while ensuring active compliance of a set of pre-defined rules governing an arrangement and assembly of the one or more hardware components. The pre-trained AI engine (224) is configured to evaluate the arrangement and assembly of known appliances (109), developed appliances (110) or a combination thereof and related software components by the user and ensuring compliance with the set of pre-defined rules governing the assembly and arrangement of known appliances (109), developed appliances (110) or a combination thereof and related software components. The set of pre-defined rules governing the assembly and arrangement of known appliances (109), developed appliances (110) or a combination thereof and related software components are stored in the appliance repository (230) and solution repository (232). The pre-trained AI engine (224) may be configured to manage and monitor the compliance of the set of pre-defined rules associated with the layout, configuration, arrangement and connection of known appliances (109), developed appliances (110) and a combination thereof. The pre-trained AI engine (224) may be configured to monitor the compliances of the set of pre-defined rules by evaluating in real-time the arrangement and assembly of hardware and related software deployed by the user to solve the real-life industry problem.
[00064] The pre-trained AI engine (224) is further configured to evaluate the final assembly and arrangement of the hardware components (known appliances (109) and developed appliances (110) and the software or programming logic proposed by the user as end-solution to the real-life industry problem. The pre-trained AI engine (224) compares the solution proposed to the solutions existing in solution repository (232) to evaluate whether a new solution has been proposed by the user. In the event of a new pattern of implementation and assembly (new solution), the pre-trained AI engine (224) may be configured to keeps a check in the system (102) for the number of times, such pattern is implemented or used by the users for solving similar real-life problem for validation and real-time learning.
User Device Authentication
[00065] In one implementation as illustrated in Figure 3, a flow diagram depicting the process of a user accessing the system (102) in Figure 1 for learning the educative content, in accordance with an embodiment of the present disclosure. Initially at step 301, to gain access to the system (102), a new user creates a user account on the mobile application (not shown) on the user device (106). The creation and registration of the user account is enabled by the application management module (212) by addition of unique user identification data through user device (106). In addition to capturing unique user identification data, the application management module (212) captures additional user information including fingerprint scan, face scan etc., name and age of user, education qualification of user, area of interests and the like for the creation of user account on the system (102).
[00066] At the next step 302, to gain access to the system (102), the user raises an authentication request through the mobile application on the user device (106). The authentication request received from the user device (106) is transmitted through application management module (212).
[00067] At the next step 303, upon receipt of the authentication request from the user device (106), the authentication module (214) matches at least one of the plurality of parameters entered within the authentication request, into the mobile application on the user device (106) with the unique user identification data. The parameter compared by the authentication module (214) includes at least one of unique user identification data including bio-metric data, session key (code, PIN, a one-time passcode (OTP), a digital signature, a key, a secret, a datum, a signal, a machine identifier or other dynamic value). Upon failure to match the plurality of parameters with the unique user identification data, the authentication of the user device (106) fails and the authentication module (214) transmits a prompt to the user device (106) to go back to step 302.
[00068] At the next step 304, upon successful grant of access to the system (102), the collection module (216) is configured to monitor and collect details related to the user activity, a subscription status of the user, one or more user preference, history information of the user, one or more user response to survey questions, one of more system responses to one or more queries raised by the user to facilitate interaction of the user with the system (102) and the time spent by the user accessing the system (102).
Accessing educative content
[00069] Upon gaining access to the system (102), the user may opt to access the educative content from the system repository (226) or solve the real-life industry problem by transmitting one or more query containing real-life industry problem to the system (102) through the user device (106). At step 304, the collection module (216) monitors user activity and collects information related to user preferences, subscription status and history information.
[00070] At the next step 305, the query analyzing module (218) receives an input query from the user device (106). The input query received by the system (102) is processed by the query analyzing module (218) for extracting keywords through natural language processing or technology architecture including convolutional neural networks for extracting query features.
[00071] At the next step 306, the matching module (220) categorizes the input query into one of learning query or problem-solving query, basis the keywords extracted at step 305. The categorization of the input query into one of the learning query or problem-solving query is done by the matching module (220) on the basis of user requirement specified in the input query. More specifically, whether the requirement is restricted to learning course modules (irrespective of multi-disciplinary nature) or is directed towards problem solving.
[00072] At the next step 307, the matching module (220) matches the requirements contained in the learning query and identifies educative content relevant to the user by performing multi-way searches of the educative content contained in knowledge repository (228). With the identification of user preferences and user activity by the collection module (216), the matching module (220) recommends one or more learning modules to the user basis the requirements stated in the input query and user behavior. The matching module (220) aids the user in selecting knowledge or learning blocks to fulfill the user requirements. In another implementation, the matching module (220), in the absence of an input query, matches the user preference and history information against the knowledge repository (228) and recommends course modules from the educative content to the user on the user device (106).
Solving a real-life industry problem
[00073] In one implementation as illustrated in Figure 4, a flow diagram for a processor-implemented method for depicting the process of user solving a real-life industry problem by accessing the system (102) in accordance with an embodiment of the present disclosure. Initially, at step 401, the system (102) receives input query from the user through the mobile application on the user device (106). The input query transmitted from the user device (106) through the mobile application contains details of the real-life industry problem faced by the user. In an embodiment, the input query including the real-life industry problem may be in the form of textual input, audio input, video/image input and the like. In an embodiment, the textual input may be in the form of a keyword, key phrase, sentence or the like.
[00074] At the next step 402, upon receipt of the input query, the query analyzing module (218) of the system (102) analyzes the received input query comprising of textual input or audio input or a combination thereof, using natural language processing (NLP) to identify a set of keywords from the received input query. For the input query comprising of video or image inputs, the query analyzing module (218) deploys technology architecture including convolutional neural networks for extracting query features.
[00075] To capture clear and succinct description of the real-life industry problem within the input query, the query analyzing module (218) aids the user to clearly and succinctly define the key facts about the real-life industry problem. For example, the query analyzing module (218) prompts a user with various data as needed to define the real-life industry problem. The query analyzing module (218) aids the user to define the real-life industry problem by providing access to a drop-down menu, recommend search strings etc. The query analyzing module (218) apart from the input query aids the user to submit information related to the nature of industry the problem relates to, nomenclature of the proposed solution or the approach used to derive the solution and the description of the proposed solution
[00076] At the next step 403, the collection module (216) of the system (102) evaluates the subscription status of the user, the history information, pre-collected user preferences, one or more user response to survey questions and one or more responses of the system to historical/past input queries of the user to facilitate the interaction of the user with the system (102).
[00077] At the step 404, the matching module (220) of the system (102) matches the real-life industry problem detailed in the input query against the system repository (226) to recommend one or more approaches to solve the real-life industry problem. The one or more approaches comprise a list of hardware components and related software/programming logic needed to solve the real-life industry problem contained in the input query. The matching module (220) analyses the contents of the user search input towards solving real-life industry problem and provides the user with possible approaches for solving the problem. The assistance module (222) assists the user through one or more recommended approaches including the list of known appliances (109) and developed appliances (110) and related software components to solve the real-life industry problem.
[00078] The assistance module (222) analyses the extracted information from the input query to evaluate the completeness of the input query with regards to description of the real-life industry problem.
[00079] At the next step 405, the assistance module (222) of the system (102) monitors user activity upon receipt of one or more approaches to solve real-life industry problem contained in the input query and provides the user on the user device (106) with one or more cues to select one or more hardware components and a pattern of implementation and assembly.
[00080] At the next step 406, the pre-trained AI engine (224) monitors the selection of one or more hardware components and related software/programming logic by the user through the user device (106) to create a solution to solve the real-life industry problem. The pre-trained AI engine (224) retrieves the set of pre-defined rules or logic governing the pattern of implementation and assembly of hardware (known appliances (109) and developed appliances (110)) and related software or programming logics from the knowledge repository (228) and appliance repository (230). The pre-trained AI engine (224) ensures compliance with the set of pre-defined rules governing the assembly of known-appliances (109), developed appliance (110) or a combination thereof, with related programming logic or software towards the assembly and pattern implementation.
[00081] At the step 406, the pre-trained AI engine (224) evaluates the arrangement of hardware components and related software component by the user against the pre-stored solutions in the solution repository (232). The pre-trained AI engine (224) analyses whether the pattern of implementation of the arrangement of hardware and software components in the proposed solution by the user during the assembly process and thereafter, is as per the set of pre-defined rules. In the event of a new pattern, the assistance module (222) keeps a check in the system (102) for the number of times, such pattern is implemented or used by the users for solving identical or similar real-life problem for validation.
Improving attention span of the user
[00082] The system (102) facilitates applied learning and inculcating the tendency to apply the learned knowledge to solve real-life industry problems. In the learning domain, the greatest challenge has been maintaining the attention span and concentration of the user within the learning program. The system (102) monitors in real-time the attention span of the user while accessing the system (102) which includes monitoring dwell time without interruption for a pre-determined duration of time. The dwell time is monitored by the system (102) by monitoring user activity the execution of learning query and problem-solving query within the system (102).
[00083] The academic literature is replete with articles and books supporting the conclusion that classroom-based learning (lectures) should adhere to 10-15 minutes span and the student’s attention span tends to wane after 10-15 minutes. With the integration of the present system (102) which includes aspects of applied learning with simulated environment for problem solving, the average attention span of the user has improved considerably.
Exemplary embodiment illustrating solving real-life industry problem.

[00084] In an exemplary implementation as illustrated in Figure 5 and Figures 6a to 6g, a flow diagram and pictorial representations are presented to disclose the steps involved in solving the real-life industry problem. Illustrated in Figure 6a, at step 501 in Figure 5, the user through the mobile application on user device (106) provides the real-life problem faced by it into the system (102) as an input query in the textual format and runs a search against the system repository (226). Herein, the real-life industrial problem shared by the user as an input query to the system (102) is directed “To build smart vertical parking arrangement for space optimization”. The phrase “To build smart vertical parking arrangement” constitutes the input query in textual format as per the exemplary embodiment of this invention. Apart from the input query, the query analyzing module (218) at step 502 in Figure 5, collects from the user, through the user device (106), additional information related to the input query. As illustrated in Figure 6b, the additional information includes details of industry connected to the real-life industry problem, user’s approach towards building the solution, nomenclature for the proposed solution and description of the solution. Upon receipt of the additional details, the matching module (220) identifies and provides recommendations including hardware components recommendations, software module recommendations (program modules), assembly recommendations (assembly of hardware and related software components). Additionally, the matching module (220) also provides template recommendations of solutions available in the system repository for similar real-life industry problems.
[00085] As illustrated in Figure 6b, the recommendation entries for the problem “How to build vertical parking arrangement for parking space optimization include:
Hardware components:
IR Sensors, Ultrasonic Sensors, Servo Motors & Buzzer
Software Components:
IR & servo program, Ultrasonic trigger buzzer & IR sensor control
Assembly:
IR & servo motor, Ultrasonic sensor & buzzer, IR, ultrasonic & buzzer, ultrasonic, buzzer and servo motor
Templates:
Smart car parking system, parking availability detection and parking management system.
[00086] As illustrated in Figure 6c and at step 503 in Figure 5, the matching module (220) provides to the user through the user device (106) access to deploy hardware components (known appliances (109) to solve the real-life industry problem. The assistance module (222) of the system (102) continues to monitor user activity in the selection of the hardware components (known appliances (109)) while recommending hardware components needed to solve the real-life industry problem. For the problem statement given in foregoing paras, the system (102) provides access to the complete repository of the known appliances (109) and the developed appliances (110). In the present exemplary embodiment, the known-appliances (109) depicted in Figure 6c are accessible to the user. It is to be noted that the known-appliances (109) depicted in Figure 6c are not the exhaustive appliance/devices mapped in the system (102). In the present exemplary embodiment illustrated in Figure 6c, the assistance module (222) recommends the IR sensor and ultrasonic sensor as recommended known appliances (109) needed for solving the foregoing real-life industry problem.
[00087] As illustrated in Figure 6d, the system (102) provides to the user through the user device (106) access to deploy hardware components (developed appliances (110) to solve the real-life industry problem. At step 504 of the Figure 5, the assistance module (222) of the system (102) continues to monitor user activity in the selection of the hardware components (developed appliances (110)) while recommending hardware components needed to solve the real-life industry problem. For the problem statement given in foregoing paras, the system (102) provides access to the complete repository of the known appliances (109) and developed appliances (110). In the present exemplary embodiment, the developed-appliances (110) depicted in Figure 6d are accessible to the user. It is to be noted that the developed-appliances (110) depicted in Figure 6d are not the exhaustive appliance/devices mapped in the system (102). In the present exemplary embodiment illustrated in Figure 6d, the assistance module (222) recommends the servo motor, buzzer and LED module as recommended developed appliances (110) needed for solving the foregoing real-life industry problem.
[00088] Figure 6e illustrates the interface for solving real-life technical problem accessible to the user on the user device (106). The user activity on this interface is monitored by the assistance module (222) in real-time and basis the user activity, the assistance module (222) aids the user to solve the real-life industry problem. The interface shown in Figure 6e provides user access to known appliances (109), developed appliances (110), programming logic or related software (illustrated in Figure 6f) for connection and inter-connections with assembly recommendations. It is to be noted that the assistance module (222) continues to aid the user with approaches for solving foregoing real-life industry problem with recommendations as illustrated in Figure 6e and Figure 5f in the form of cues.
[00089] As illustrated in Figure 6g and at step 504 of Figure 5, the pre-trained AI engine (224) monitors the selection of hardware components (known appliances (109) and developed appliances (110)) and related software code or programing logic by the user through its user device (106) while attempting to solve the real-life industrial problem on the interface. The pre-trained AI engine (224) evaluates attempts by the user to solve the real-life industry problem including the circuit connections between the known appliances (109) and developed appliances (110) and a combination thereof. The pre-trained AI engine (224) analyses the connections between the hardware components (known appliances (109) and the developed appliances (110)) and related programming logics with the set of pre-defined rules stored within the system repository (226) and in case of non-adherence with the set of pre-defined rules, transmits system response to the user device (106) towards violation of the set of pre-defined rules and sends cues for correct connections and patterns of implementation through the assistance module (222). One such exemplary embodiment is illustrated in Figure 6g.
[00090] The pre-trained AI engine (224) monitors the final proposed solution against the real-life industry problem and evaluates the proposed solution against the stored solutions in the system repository (226). In the event of a new solution or pattern of implementation, the pre-trained AI engine (224) keeps a check in the system (102) for the number of times, such pattern is implemented or used by the users for solving identical or similar real-life problem for validation.
[00091] At step 505 of the Figure 5, the pre-trained AI engine (224) analyses whether the pattern of selection of components is known to the system (102) or new. In the event of a new pattern, the pre-trained AI engine (224) keeps a check in the system (102) for the number of instances, said pattern is implemented or used by the users through user device (106-1), (106-2), (106-N) for solving identical or similar real-life problem.
[00092] Various figures of the present application include block diagrams, flowchart and control flow illustrations of methods, systems and program products according to the invention, it will be understood that each block or step of the block diagram, flowchart and control flow illustration, and combinations of blocks in the block diagram, flowchart and control flow illustration, can be implemented by computer program instructions. These computer program instructions may be loaded onto a computer or other programmable apparatus to produce a machine, such that the instructions which execute on the computer or other programmable apparatus create means for implementing the functions specified in the block diagram, flowchart or control flow block(s) or step(s). These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable apparatus to function in a particular manner, such that the instructions stored in the computer- readable memory produce an article of manufacture including instruction means which implement the function specified in the block diagram, flowchart or control flow block(s) or step(s). The computer program instructions may also be loaded onto a computer or other programmable apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the block diagram, flowchart or control flow block(s) or step(s).
[00093] The preceding description has been presented with reference to various embodiments. Persons having ordinary skill in the art and technology to which this application pertains will appreciate that alterations and changes in the described structures and methods of operation can be practiced without meaningfully departing from the principle, spirit and scope.
,CLAIMS:WE CLAIM:
1. A system (102) comprising:
an input/output (I/O) interface (204) to receive an input query from a user to solve a real-life industry problem, wherein the input query is in a form of a textual input, an audio input, a video input, and an image input;
at least one memory (206) storing a plurality of instructions;
one or more hardware processors (202) communicatively coupled with the at least one memory (206), wherein the one or more hardware processors (202) are configured to execute one or more modules;
a collection module (216), stored in the at least one memory (206), configured to collect a subscription status of the user, a history information, one or more user preferences, and one or more responses of the system to one or more queries raised by the user to facilitate an interaction of the user with the system;
a query analyzing module (218), stored in the at least one memory (206), configured to analyze the received input query in the form of the textual input or audio input using a natural language processing to identify a set of keywords from the input query;
a matching module (220), stored in the at least one memory (206), configured to identify one or more approaches to solve the real-life industry problem contained in the input query, wherein one or more approaches are accompanied by one or more hardware components, related software and a pattern of implementation and assembly;
an assistance module (222), stored in the at least one memory (206), configured to assist the user with the one or more approaches to solve the real-life industry problem contained in the input query and monitor and provide the user with cues to select the one or more hardware components, related software and the pattern of implementation and assembly; and
a pre-trained AI engine (224) to ensure active compliance of a set of predefined rules governing the pattern of implementation and assembly of the one or more hardware components and related software and analyze the selected pattern of implementation and assembly, wherein the pre-trained AI engine (224) is trained based on number of times such pattern is successfully implemented for solving a similar real-life problem.

2. The system as claimed in claim 1, further comprising:
an application management module (212), stored in the at least one memory (206), configured to capture one or more information related to the user to create a user profile; and
an authentication module (214), stored in the at least one memory (206), configured to authenticate an identification of the user upon receipt of an authentication request from the user, by matching a predefined unique user identification data with the user credentials contained in the authentication request to enable the user to get access to secured data stored within a system repository (226).

3. The system as claimed in claim 1, further comprising an appliance repository (230) including data related to one or more hardware components, wherein the one or more hardware components include one or more known appliances (109) and one or more developed appliances (110).

4. The system as claimed in claim 3, wherein the one or more developed appliances (110) is developed by the user while solving the real-life industry problem with combination of the one or more known appliances (109).

5. The system as claimed in claim 1, wherein the matching module (220) is configured to recommend a list of educative content basis the information collected by the collection module (216).

6. The system as claimed in claim 2, wherein the one or more information related to the user include name of the user, age of the user, education qualification, and an area of interest of the user.

7. The system as claimed in claim 1, wherein the history information includes one or more past activities of the user, and one or more search queries and responses thereof.

8. The system as claimed in claim 1, wherein the matching module (220) categorizes the input query into one of a learning query or problem-solving query.

9. The system as claimed in claim 1, wherein the query analyzing module (218) assists the user to clearly and succinctly define one or more key facts of the input query containing the real-life industry problem.

10. The system as claimed in claim 1, wherein the pre-trained AI engine (224) evaluates the selection and assembly of the one or more hardware and software components by the user against one or more solutions stored in a solution repository (232) of the system.

11. A processor-implemented method, comprising:
receiving, via an input/output interface, an input query from a user to solve a real-life industry problem, wherein the input query is in a form of a textual input, an audio input, a video input, and an image input;
collecting, via the one or more hardware processors, a subscription status of the user, a history information, one or more preferences, and one or more responses of the system to one or more queries raised by the user to facilitate an interaction of the user with the system;
analyzing, via one or more hardware processors, the input query using a natural language processing to identify a set of keywords of the input query;
identifying, via one or more hardware processors, one or more approaches to solve the real-life industry problem contained in the input query, wherein one or more approaches are accompanied by one or more hardware components, related software and a pattern of implementation and assembly;
assisting, via the one or more hardware processors, the user with the one or more approaches to solve the real-life industry problem contained in the input;
monitoring and providing, via the one or more hardware processors, the user with one or more cues to select one or more hardware components, related software and a pattern of implementation and assembly; and
ensuring active compliance of a set of pre-defined rules governing the pattern of implementation and assembly of the one or more hardware components and related software and analyzing the selected pattern of implementation and assembly against a frequency of implementation of the pattern and the assembly for solving a similar real-life industry problem.

12. The processor-implemented method as claimed in claim 11, further comprising:
capturing, via one or more hardware processors, one or more information related to the user to create a user profile; and
authenticating, via the one or more hardware processors, an identification of the user upon receipt of an authentication request from the user, by matching a predefined unique user identification data with the user credentials contained in the authentication request to enable the user to get access to secured data stored within a system repository (226).

13. The processor-implemented method as claimed in claim 11, further comprising an appliance repository (230) including data related to one or more hardware components, wherein the one or more hardware components include one or more known appliances (109) and one or more developed appliances (110).

14. The processor-implemented method as claimed in claim 13, wherein the one or more developed appliances (110) is developed by the user while solving the real-life industry problem with combination of the one or more known appliances (109).

15. The processor-implemented method as claimed in claim 11, further comprising recommending a list of educative content basis the information collected.

16. The processor-implemented method as claimed in claim 12, wherein the one or more information related to the user includes name of the user, age of the user, education qualification, and an area of interest of the user.

17. The processor-implemented method as claimed in claim 11, wherein the history information includes one or more past activities of the user, and one or more search queries and responses thereof.

18. The processor-implemented method as claimed in claim 11, further comprising categorizing the input query into one of a learning query or problem-solving query.

19. The processor-implemented method as claimed in claim 11, further comprising assisting the user to clearly and succinctly define one or more key facts of the input query containing the real-life industry problem.

20. The processor-implemented method as claimed in claim 11, further comprising evaluating the selection and assembly of the one or more hardware and software components by the user against one or more solutions stored in a solution repository (232).