EP3494566A2

EP3494566A2 - Life performance management system and method thereof

Info

Publication number: EP3494566A2
Application number: EP17838867.4A
Authority: EP
Inventors: Krishnakuma THOGAMALAI
Original assignee: Individual
Current assignee: Individual
Priority date: 2016-08-06
Filing date: 2017-08-05
Publication date: 2019-06-12
Also published as: WO2018029533A3; EP3494566A4; WO2018029533A2

Abstract

The present invention relates to a system and corresponding computer-implemented methods for management of user's life performance by implementing intelligence mechanism; the method includes receiving one or more input parameters corresponding to one or more requirements. Further, the method understands the needs of the user based on the received input or derived input. In an embodiment, the derived input corresponds to the preferences of the user that is determined through various ways such as behavioral analysis of the user based on one or more factors such as (but not limited to) past activities of the user. The method does perform various functionalities corresponding to life performance management of the user. Such functionalities include, but not limited to, determining weightage for the input parameters, clustering request and respond input, ranking the result and determining suggestions that are relevant based on the user's request and preferences.

Description

LIFE PERFORMANCE MANAGEMENT SYSTEM AND METHOD THEREOF

CROSS REFERENCE

This Application claims benefit of US Provisional Application No 62371728 Filed on 06-AUG- 2016 which is incorporated by reference.

TECHNICAL FIELD

The present invention relates in general to a life management system. The present invention particularly relates to a system and methods for life performance management with life guidance, intelligence and enlightenment.

BACKGROUND

[001] Every person requires suitable guidance at some point of time to make right decisions in order to perform well in one's own life and also help others like family members, friends etc. The guidance may be required corresponding to various needs that may arise during anytime in the life of a person. Additionally, in this fast paced world, most often people work in multitasking environment wherein, a person may busily work for an external organization or a person may run a multi-functionality business or multiple businesses of varied domains. In such professional scenario, there remains a need for management of various aspects of life.

[002] Most known and prevalent systems so far provide solutions in a few specific areas pertaining to management of certain aspects of life be it health, finance, social separately; or only a few aspects combined together. Situation arises wherein one or more systems need to be leveraged for managing more aspects of life and the challenges like limited functionalities, multiple platforms, multiple access controls, limitation in integration etc. are quite apparent. Thus, there is a need for a system that can provide holistic life management solution and guidance with advanced intelligence, capable of delivering overall management of life's performance of a person, user, and entity that involves many aspects of life such as; business, family, health, wealth, wellness, and friends all together under one roof.

[003] Reference is be made to US6164974A which discloses an evaluation based learning system (EBLS), which is used by authors, teachers, students and education administrators for the development of courses, the teaching of courses, the studying of courses and the administration of information and data relevant to the courses. The EBLS provides an efficient authoring, teaching and learning environment wherein a database of questions and answers are linked to a textbook to facilitate the learning and evaluation process of students studying a textbook.

[004] Reference is made to US20070111180A1 which discloses delivery methods for remote learning system courses. In one embodiment, a method includes transmitting, to a remote learning management system, a request for a course associated with a course type. The remote learning management system is operable to provide a plurality of courses based on the request. Information associated with the course is transmitted to or received from the remote learning management system. The information included a delivery method. The course catalog is automatically updated based, at least in part, on the delivery method of the course.

[005] Reference is made to US5722418A which discloses a method for mediating social and behavioral influence processes through an interactive telecommunications guidance system for use in medicine and business (10) that utilizes an expert (200) such as a physician, counselor, manager, supervisor, trainer, or peer in association with a computer (16) that produces and sends a series of motivational messages and/or questions to a client, patient or employee (50) for changing or reinforcing a specific behavioral problem and goal management. The system (10) consists of a client database (12) and a client program (14) that includes for each client unique motivational messages and/or questions based on a model such as the trans theoretical model of change comprising the six stages of behavioral change (100) and the 14 processes of change (114), as intertwining, interacting variables in the modification of health, mental health, and work site be- haviors of the client or employee (50). The client program (14) in association with the expert (200) utilizes the associated 14 processes of change (114) to move the client (50) through one of the six stages of behavioral change (100) when appropriate by using a plurality of transmission and receiving means. The database and program are operated by a computer (16) that at preselected time periods sends the messages and/or questions to the client (50) through use of a variety of transmission means and furthermore selects a platform of behavioral issues that is to be addressed based on a given behavioral stage or goal (100) at a given time of day.

[006] Reference is be made to US9239989B2 a computer-implemented system includes an edge module and at least one input device coupled to the edge module. The at least one input device is configured to generate data input signals. The system also includes a cognitive module coupled to the edge module. The cognitive module includes a perception sub-module coupled to the edge module. The perception sub-module is configured to receive the data input signals. The cognitive module also includes a learning sub-module coupled to the perception sub-module. The learning sub-module is configured to adaptively learn at least in part utilizing the data input signals.

[007] Based on the aforementioned, none of the cited prior art documents disclose a holistic computer based intelligent life management system for overall management of life's performance of a person/user. Further, none of the prior art documents disclose the system that is able to proactively or reactively understand the needs of the user, and provides the right choices to the fingertips of the user. The present invention provides a life management system to enable the holistic performance of users' life with adaptive intelligence. Furthermore, the system provides guidance to the user in various pursuits of life. Moreover, the system disclosed in this application intelligently understands the repercussion of any action that is be adopted by the user and accordingly guide the user in various ways for the overall benefit/safeguard of the user without compromising on any factor. Additionally, the system disclosed in this application alleviates the challenges and drawbacks of existing practices/sy stems. SUMMARY OF THE INVENTION

[008] In one aspect of the present invention a system is provided with corresponding computer- implemented methods for management of life's performance of a user. The method includes receiving one or more input parameters corresponding to one or more requirements. Herein, the requirements correspond to any requirement of a user. Further, the method understands the needs of the user based on the received input or derived input. In an embodiment, the derived input corresponds to the preferences of the user that are determined through various ways such as habits and practice analysis of the user based on one or more factors such as (but not limited to) past actions, preferences and performance of the user. The system utilizes a cognitive module (hereinafter interchangeably be referred to as 'cognitive engine') to perform various operations corresponding to life performance management of the user. The cognitive module includes one or more modules including instructions, intelligence, data, logic, algorithms corresponding to various aspects for providing guidance and intelligent options to the user. Further, the cognitive engine utilizes (but not limited to) self-intelligence mechanism, collective intelligence mechanism, social and market intelligence mechanisms.

[009] In another aspect of the present invention, the cognitive module includes executable instructions to perform one or more functionalities including, but not limited to, understanding user's needs, providing weight to input parameters corresponding to the needs of the user, Scoring, Receptor-Responder Clustering, Inferring, Receptor-Responder Matching and ranking, User Response Guidance to determine guidance for the user. Furthermore, the cognitive engine includes intelligence, instructions and stimuli & reflex to react to the request and respond appropriately. The System further repackages the responses (determined guidance) and delivers the guidance to the users. Further, based on the one or more functionalities, the system provides one or more choices, options, assistance, recommendations and guidance to the user considering past, present and future aspects related to the need(s) of the user. Moreover, the system includes intelligent learning module (i.e., adaptive intelligence) that enables continuous evolution of the cognitive engine. [010] In another aspect of the present invention, the system provides Human to Machine, Machine to Human and Machine to Machine learning capabilities using cognitive engine, using the adaptive intelligence and intelligent guiding and information delivery mechanisms.

[Oi l] In still another aspect of the present invention, the system has built-in emotional intelligence based on philosophical grounds and emotional quotient to understand human emotions better and provides human-like interactive support. The system is capable of receiving, understanding and interpreting human emotions through gestures, emotional expressions etc., captured using various methods utilizing Cognitive Intelligence (Intelligence derived using Cognitive abilities) to respond to users' expressions more appropriately by expressing Sentiments, Empathy, and Encouragement based on scenarios & situations corresponding to users. This helps users to get better traction in life, handle challenges and life dynamics and attain equilibrium quite well. The emotional response is configured to work according to users' choices.

[012] In yet another aspect of the present invention, the system is not only one user focused, it helps to manage dependent users within the family and supports user inheritance (e.g., supports all the stages of human life from cradle to grave and beyond). The system supports the transition of status of a user from being a dependent to independent. It also helps the dependent users to become independent based on the progression of life.

BRIEF DESCRIPTION OF DRAWINGS

[013] Having thus described the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein

[014] FIG. 1 illustrates an exemplary environment where various embodiments of the present disclosure are implemented;

[015] FIG. 2 illustrates another exemplary environment where various embodiments of the present disclosure are implemented; [016] FIGS. 3 and 4 illustrate block diagrams of a system for managing performance of life for multiple, in accordance with an embodiment of the disclosure;

[017] FIG. 5 illustrates an exemplary database for storing information corresponding to various parameters, in accordance with an embodiment of the present disclosure; and

[018] FIG. 6 illustrates a flow diagram of a method for managing performance of life, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION

[019] In one embodiment the present invention provides a holistic, self-aware life management system and a method for managing performance of users' lives. Herein, the users include, but are not limited to, registered users of the system those need guidance and suggestions for fulfillment of their necessities and requirements in relation to various aspects of life. Further, the system functions to guide a user with or without receiving multiple user input for users' requirements. Particularly, the system intelligently tracks the users' actions and monitor and evaluate moods of the users. Furthermore, the system guides the user by the system itself based on the users' habits, interest, practices, situation, state, ambience, surrounding and self-awareness and preferences etc.

[020] In another embodiment of the present invention, the system tracks past record/activities of the user; determine current scenario of the user's life in various domains of the user's interests; analyze various types of intelligent information corresponding to various domains (such as wellness, market, expertise, profession, wealth, social, wisdom, spirituality market, social, profession etc.); and accordingly determine probability of future prospects to guide the user beforehand. In this way, the system makes the user aware of various possible challenges that arise anytime during the lifespan of the user. Further, the system guides the user to avoid/overcome such possible challenging situations. [021] Illustrative embodiments of the invention now will be described in detailed manner hereinafter with reference to the accompanying drawings.

[022] Further the present invention is elucidated by way of accompanying drawings and embodiments and should not be construed to limit the scope of the invention in any manner.

[023] Referring to FIG. 1 that illustrates an exemplary environment 100 where various embodiments of the present disclosure are implemented. As depicted, a plurality of users, such as user 1

102a, user 2 102b, ,and so on up to user n 102n, are connected to a system 106 via a network, such as a network 1 108. Hereinafter, the user 1 102a, user 2 102b, , and so on up to user n

102n are collectively to be referred to as 'users 102' . Each user of the users 102 can access the system 106 through a User Access Medium (UAM) 104. Examples of the User Access Medium (corresponding to each user) includes, but is not restricted to, devices, machines, peripherals such as laptop, tablet computer, smart phone, personal digital assistant, cell phone, personal computer, robots, gaming gadgets, and so on. The system 106 is utilized for managing life performance of the users 102. Further, the system 106 is connected to one or more servers such as a server 1 110a, a server 2 110b, and so on a server n 110η through a network2 112. The networkl 108 and the network2 112 includes, but are not restricted to, a communication network such as the Internet, a Metropolitan Area Network (MAN), a Local Area Network (LAN), a Wide Area Network (WAN), or a Public Switched Telephone Network (PSTN).

[024] The server 1 110a, a server 2 110b, and so on a server n 110η are collectively to be referred as the servers 110. The servers 110 can be accessed by the system 106 for various purposes such as for gathering knowledge, for accessing information corresponding to market intelligence, social intelligence and so on. Such information is additionally stored in the database 114. Furthermore, the servers 110 include third party servers for catering directly to the needs of the user. Furthermore, the system 106 is connected to a database 114. The database 114 is an external database 114 (as shown outside the system 106). Further, the database 114 can inbuilt a system (such as shown in FIG. 2). [025] Herein, each user of the users 102 is registered with the system 106 and is authenticated and allowed with confidential credential to access the system 106. The system 106 stores the users' information in the database 114. Further, the system 106 stores customizable taxonomies in the database 114. The system 106 does implement for the registered users to provide guidance and suggestions to the users for their explicit and implicit needs. Herein, the explicit needs include the needs that is provided by the user to the system 106 to receive guidance and for managing the performance of the life. Further, the implicit needs include needs of the user that is understood by the system 106 without any explicit provision thereof by the user. Thus, the system 106 implements in an intelligent manner to understand the situation and needs of the user and accordingly provides solution to cater to the needs of the user.

[026] The user provides one or more input parameters, corresponding to individuals requirements, to the system 106 through the network 1 108. The input parameters include, but are not limited to, at least one or more essentials corresponding to the one or more requirements of the user, usage, purpose, delivery, and budget for said requirement. Further, the input parameters further include emotional expressions, mental and physical gestures of said user that is depicted or captured by the system 106 based on upon the respective situation of the user.

[027] The system 106 analyzes the user's input (such as explicit and implicit needs, expressions, emotions and gestures) to understand the user's requirements and accordingly to translate the user's input into more refined form so as to confirm from the user regarding individual's needs. Further, the SMEs (Subject Matter Experts) are a part of the system 106. In an alternative embodiment, the SMEs (Subject Matter Experts) are external to the system 106 that serves the system 106 with the knowledge regarding an intermittent system query that is generated to determine the user's emotional expressions (emotions). For example, the SMEs (Subject Matter Experts) provide such service to the system 106 through one of the one or more servers 110. For example, the SMEs (Subject Matter Experts) feed the system 106 with the relevant information (i.e., related to the need of the user) such as definitions, market data, principles, set of rules, tree- maps and so on for enabling the system 106 to determine the meaning and intent of the user's needs. Further, for example, the system 106 matches the user's input with the relevant infor- mation to determine the meaning and intent of the user's needs. Once the user's needs are confirmed, the system 106 performs intelligent analysis thereof to determine one or more suitable options depicting suggestions and guidance points.

[028] Such analysis involves implementation of the system 106 to provide optimized intelligence suitable for the user's life. The system 106 utilizes one or more intelligent sources to improve performance of the user's life. Such intelligent sources include, but are not limited to, self- intelligence, collective intelligence, market intelligence and social intelligence. Further, the servers 110 are utilized to gather such required intelligence based on the user's needs. The system 106 builds such intelligent sources and stores the corresponding relevant intelligence information in the database 114. Due to this, the system 106 utilizes such intelligences anytime (even in offline mode, i.e., without requiring an access to any of the servers 110) on need basis. These sources are updated on regular basis to keep the intelligence up to date in order to serve the users in most effective way. These types of intelligence are explained further in conjunction with FIG. 4.

[029] In further, the system 106 performs intelligent search to determine suitable respondents (options) those are relevant to cater to the needs of the user. For this, the system 106 analyzes input parameters that include defined and derived needs of the user. The derived needs are derived or determined based on the behavioral analysis (as aforementioned) of the user to determine preferences of the user. Such input parameters (including defined and derived needs) are analyzed to determine one or more options (i.e., suitable respondents) relevant for providing solution corresponding to the needs of the user. Further, the system 106 is implemented to process the determined options to identify the relevancy thereof. Further, in an embodiment, the system 106 provides relevancy rank to each of available option based on the processing thereof. Furthermore, the system 106 generates one or more intelligent suggestions based on at least one of the relevancy rank of each available option and one or more elements. These one or more elements correspond to at least one of the input parameters and the user. For example, the one or more elements include, but are not limited to, past activities of the user, dependents list of the user, current situation of the user (such as budget, mood, current location and environment etc.). [030] It shall be appreciated by a person skilled in the art that the system 106 analyzes the past actions and current situation of the user to determine probability of particular future prospects and challenges for the user's life. Such past actions and current scenario of the user's life is determined through the online actions and activities of the user, user's dependents, friends and family. Thus, the System 106 utilizes information corresponding to the past and present events and actions; and probable future events and future requirements of the user to provide guidance to the user. In this way, the user is enabled to plan for the present or for the better future for self and one's family. Further, based on the determination of probability of some happenings in future, the system 106 generates emergency alerts for the user. Such alerts include both online and offline alerts (such as system messages, SMS (Short Message Service), mails, etc.) to the user.

[031] Referring to FIG. 2 that illustrates a user 1 202a, a user 2 202b... and so on up to user n 202n (hereinafter collectively be referred to as 'user 202') are linked to a server 204 through the network 1 206. Each user can access the system 106 by utilizing an electronic device (hereinafter interchangeably be referred to as 'user device'). The user device includes, but is not limited to, a laptop, a tablet computer, a smart phone, a personal digital assistant, a cell phone, a personal computer, mechanical robots, gadgets and/or the like. The server 204 includes a system 106 and a database 212. The database 212 includes, but is not limited to, information corresponding to all the registered users of the system, intelligence parameters (such as self-intelligence, collective intelligence, market and social intelligence) and so on. The database (such as the database 212) that can be utilized by the system 106 is explained further in conjunction with FIG. 5. Herein, the users 202 are similar to the users 102 (as described in conjunction with FIG. 1). Such users 202 are registered users of the system 106 and can utilize the system 106 for enhancing and managing performance of their lives. The system 106 manages each and every user independently. If two or more users of the system 106 are related (for example, belonging to a common family) then the system 106 analyzes the activities of each user collaboratively and intelligently with/without sharing the personal information of one user to another user. Such collaborative and intelligent analysis of the related users are performed to determine information regarding current scenario about each user's life; and such information is utilized for better management of each user's life performance.

[032] Further, as depicted, the server 204 is connected to social networks 208 through the network 2 210. In this embodiment, the system 106 can track each user's activities through the social networks to determine more information (such as the user's interest, preferences, current life scenario etc.) about the user's life and to serve the user in accordance with the user's interest and preferences. It is apparent to a person skilled in the art that the system 106 obtains the user's prior permission to track such activities of the user through social networks. Further, the networkl 206 and the network2 210 includes, but is not limited to, Internet, a Metropolitan Area Network (MAN), a Local Area Network (LAN), a Wide Area Network (WAN), or a Public Switched Telephone Network (PSTN).

[033] The users 202 utilize the system 106 for better management of life's performance of the user (as explained previously in conjunction with FIG. 1 and further in conjunction with FIGS. 3-6).

[034] Referring now to FIGS. 3 and 4 that illustrate the block diagram of a system 106 for managing performance of the users' life, in accordance with an embodiment of the disclosure. Further, as shown, the system 106 includes a memory 302 communicably coupled with a processor 304. Further, as shown in FIG. 3, the memory 302 includes instructions set 306 and a central Data such as the database 308. The instructions set include a plurality of executable instructions for performing one or more tasks when executed by the processor. Such one or more tasks are performed by various components/modules of the system when the processor 304 executes the corresponding instructions.

[035] Further, as depicted in FIG. 4, the instructions sets described in the FIG. 3 are implemented through various modules when executed by the processor 304. [036] Specifically, as depicted in FIG. 4, the memory 302 of the system 106 includes, but is not limited to, need identification module 402, a cognitive module 404, an output module 406, and the database 308. The system 106 utilizes the processor 304 for implementing the modules stored in the memory 302.

[037] Further, the need identification module 402 includes, but is not limited to, a receiving module 408, a quizzing module 410 and an emotional module 412. Further, the cognitive module 404 includes an analysis module 414 that includes a monitoring module 416. The cognitive module 404 further includes (but not limited to) a processing module 418, a suggestion module 420, an evolution module 422, a managing module 424 and the database 308. Furthermore, the processing module 418 includes, but not limited to, a determination module 426, a clustering module 428 and a ranking module 430. The evolution module 422 includes, but is not limited to, a learning module 432, an updating module 434 and a response module 436.

[038] The need identification module 402 identifies the need of the user. The user provides input to the system 106 of a particular type that includes, but is not limited to, a query type, textual input, emotional input (by utilizing emotional expressions feature that is provided by the system 106) and gesture input. The need identification module 402 determines the type of request from the user and accordingly performs one or more functionalities based on the type of the input.

[039] In yet another embodiment, the receiving module 408 receives input/request from the user that includes direct information/query corresponding to the needs. Further, the input/request received by the receiving module 408 includes emotions or just the gestures. The input query (received) includes, but is not limited to, data, statistics, intent, emotions etc. The quizzing module 410 of the need identification module 402 transforms the user's request into the system understandable form. Such transformation is performed by utilizing (but not limited to) question based model, language referencing, taxonomies, tree maps, semantics etc. Further, the quizzing module 410 further has instructions that are executed by the processor 304 to interact with the user to confirm the needs of the user. For example, the quizzing module 410 can better understand the user's query based on the analysis of the user's information. Further, the quizzing module 410 forms a query in refined form that is understandable by the user. Such refined query is verified by the user to confirm needs of the user. Furthermore, the quizzing module 410 triggers one or more subsequent questions for the user (if required) based on analysis of the initial input received from the user. Such subsequent questions enables the need identification module 402 to gather, completely, the required information from the user and accordingly to transform the received input information into the system understandable format.

[040] In further embodiment, the emotional module 412 reacts to emotions expressed by the users corresponding to situations and circumstances by applying the empathy and the emotional patterns as required. Understand and analyze the emotional expressions (provided by the user) based on the user's information and other gathered information. The SMEs (Subject Matter Experts) is an external entity that serve the system 106 explicitly by providing relevant information such as (but not limited to) definitions, tree-maps, principles, rules, and other stored information corresponding to the user's input. Such relevant information (provided by the SMEs (Subject Matter Experts)) can be analyzed by the system 106 for determining the meaning and intent of the user's input (such as, but not limited to, emotional expressions). The emotional module 412 themselves include SMEs (Subject Matter Experts) that can analyze the emotional expressions with reference to one or more definitions thereof. Such definitions corresponding to the emotional expressions are stored in a database (such as, but not limited to, the database 308. Further, the emotional module 412 determines the user's current state of mind by analyzing the user's other activities within the system or external to the system (such as on social networks etc.). Based on the current state of mind of the user and definition of the emotional expressions (as provided by the user), the emotional module 412 determines the intent or the problem/challenge in the user's life. The need identification module (with the help of built-in emotional intelligence mechanism) identifies captures the user emotions. The system 106 utilizes its own intelligence to calculate scores separately for different emotions (e.g., happy, sad, angry, stressed, etc.) that help the user to check their emotion levels under each emotion category separately. This feature highly helps users to maintain and control their emotions that in turn help them to maintain good health. In addition, emotional response is tailored to individual's emotional quotient, patterns, preferences, and surroundings. The system 106 enables changing of its emotional response mode from its default mode to environmentally sensitive mode based on preference of the owner or the privileged user.

[041] In further embodiment, the need identification module 402 derives the user's needs based on the user's habits and practices. For this, the list of users, groups or other entities, which display similar habits, practices, mannerisms, intents etc., can be grouped/clustered. It uses a combination of factor deviation and event occurrence frequency and sequence to deliver descriptive statistics, statistical models, percentile ranking models etc. for identifying and maintaining these groups. Once the user group is formed, the descriptive statistics, statistical models are used to define a particular user group. It uses a combination of percentile rank, deviation parameters to find out the characteristics, habits, mannerisms that define this particular group. The output of the need identification module 402 is provided to the cognitive module 404 that take into account such particular characteristic to fine tune the search for a person belonging to this user habits and practices group.

[042] Once the input/request is understood and confirmed from the user and after identifying the common characteristics (depicting habits and practices) of the user among one or more groups, the cognitive module 404 can be intelligence derived, combines the power of intelligence and activated to analyze the request of the user. The analysis module 414 analyzes the user's request based on one or more intelligence parameters. The intelligence parameters includes, but are not limited to, self-intelligence (Si), collective intelligence (Ci), market intelligence (Mi) and social intelligence (SOi). Such intelligence parameters are monitored by the monitoring module 416 through (but not limited to) one or more servers, online databases, and other knowledge base.

[043] In further embodiment, the self-intelligence is obtained by continuously monitoring the user's activities and performances within the system (and external to the system 106) and collects all the input and activity data of that particular user. The Si acts as a repository to store all user input/activity related information's category wise. Such category wise information of the user is utilized by the cognitive module 404 to know more about the users interests and performances to choose the proximate choices and options based on the requirements/needs of the user.

[044] In further embodiment the collective intelligence can be obtained by collecting all the input, activity or performance based data of all worldwide registered users of the system 106. It is to be noted that data/information is collected based on the permission of the users. The Ci (Collective intelligence) includes worldwide registered users' activities / input. Such information corresponding to the collective intelligence is stored in the database in accordance with the categories distribution (i.e., category -wise) in the database. Such stored Ci (Collective intelligence) information is utilized by the cognitive module 404 to provide guidance/intelligent options for different users.

[045] The market intelligence is obtained by collecting all the market trend, knowledge based, significant, general information that is stored in the database according to the defined categories in the database. Further, such Mi (Market Intelligence) information is utilized by the cognitive module 404 for further analysis of the user's request and/or for ranking the output according to the Mi (Market Intelligence) information. Further, the Social intelligence (SOi) deals with complex social relationships and environment information's.

[046] The Social intelligence (SOi) works based on information extracted from sources such as and not limited to; CD (Club Data), PMD (Public Media Data) and SME(s) (Subject Matter Experts) that are collectively gathered, transformed to valuable intelligent informational assets that are stored in the knowledge repositories (such as the database 500, as described further in conjunction with FIG. 5).

[047] Herein, the Club Data renders a system where users can utilize this platform to collaborate and post valuable information, intelligence, offers, share and also perform group activities, promote services and also collectively manage efforts and resources. The data is gathered from the above sources and stored in the database 500 and utilized by the system for its functions. [048] In further embodiment, the Public Media Data refers to the system wherein users utilize this platform to post articles, artifacts, blogs, important information's on various subjects, topics etc., This platform has the ability to store the above mentioned knowledge materials, information, visuals etc., for the system 106 to utilize for the benefit of the users and public. All information is validated and published by the SME(s) (Subject Matter Experts).

[049] In further embodiment, RTDH (Real Time Data Hub) helps the interface to receive inbound data from external sources and also provide outbound data extracted from the system 106. Further, this component includes functions to integrate other source systems with the system 106.

[050] In further embodiment, the system 106 use Adaptive Intelligence, corresponding to the learning module 432, to understand and learn, in what manner the user is most receptive to the system's guidance. The System understands the user's receptive ability through different input mediums, but not limited to, visual, textual, audio, statistical, inference based etc., by the use of quizzing module 410, past user habits and practices, user intent, content etc. The System 106 use the learning of user's receptive abilities or effective ways of learning and use it to deliver the guidance after the response repackaging through the right medium.

[051] In yet another embodiment the database 308 that is utilized by the system 106 has customizable taxonomy. A set of taxonomy tables is maintained that includes a large collection of categories, sub categories and contexts. The taxonomy table is customizable and the users include their own categories and sub categories and use the table in this way. By this way, the table keeps on growing. The taxonomy table is linked with each and every aspect/functionality of the system 106. The cognitive module 404 refers the taxonomy table for various functionalities thereof. Further, the input/request, data, response etc. is categorized based on the categories in the taxonomy tables.

[052] The system 106 transforms the input data/monitored data such as a particular date to number of days from the current date that serves as input data to the need identification module of the system 106. Further, the system 106 performs calculations on raw data in various ways to derive statistics, statistical or predictive models and transform it to input data in the required format that is further analyzed by the analysis module 414.

[053] Based on the monitoring of the information by the monitoring module 416 and further, based on input request and other information corresponding to the users need, the analysis module is selected from one or more servers, online and other knowledge base 414 determines one or more available options corresponding to the request of the user. The analysis module 414 perceives a set of input data, emotions, statistics etc. based on the information (Time, Location, Language, Ethnicity, Lifestyle, Emotions, Situations etc.) about the situation and applicability gathered from the users and surroundings (including monitored Intelligence). The Perception based intuition is derived using inputs from a set of past and future actions along with surroundings and context/relevance data. For example, the analysis module 414 understands and analyzes the emotional signs such as emotional expressions, gestures, visual signs, etc. (provided by the user) based on the user's information and other gathered/monitored information. In an embodiment, the analysis module 414 determines, analyze, queue, prioritize and infer the meaning and intent of the emotional signs provided by the user.

[054] In further embodiment, the output from the analysis module 414 is provided to the processing module 418. The processing module 418 process the available options to determine relevancy of the available options based on the analyzed information. Further, the processing module 418 includes orchestration of the execution of processes, functions, methods involved in providing the right guidance, intelligence and options to the user's needs. The determination module 426 determines the weightage dynamically of each factor for every need, request, statistic, emotion etc. the determining module 426 takes input through feedback mechanisms, which correlates the guidance given and the guidance followed in each category.

[055] In Further embodiment, the clustering module 428 clusters the user's inputs and the corresponding responder input into different clusters. Herein, the responder corresponds to any response that address the requirements of the user based on the user's input/determined user's re- quirement. Responder includes any entity that responds to the requirements and in the form of (but not limited to) a system's user, Vendor, and an Online Database entity. The clustering module 428 ensures that even if an exact match for the search parameter is not available, the closest match is given a matching score.

[056] In further embodiment, the clustering module 428 treats every data type differently but the parameter (input) is the same. Each input parameter is put into clusters of different levels. With each higher level, the cluster may become wider and the matching score becomes lower. At one particular level, the receptor inputs in a particular level might match with the responder' s input at the same level, which indicates a match. As the cluster level keeps increasing, the matching score keeps decreasing.

[057] In further embodiment, the ranking module 430 takes into account all the receptor's inputs and match one or more of the corresponding responder' s inputs. The responder output (matching score) is a function of how close the receptor input is to the responder input. Herein, the matching score not only considers the proximity but also take into account, if the input is better for the user if it is closer to the lower bound or the upper bound of the response. For example, the system has a set of emotional responses which include scores for agitation and happiness as parameters; the response with lower agitation score has a higher matching score than a response with the higher agitation score even if both the responses fall into the same cluster (by the clustering module 428). On the contrary, the response with higher happiness score will have higher matching score than the response with the lower one.

[058] In another embodiment, the System 106 receives the emotional states of several users, surrounding data etc. as input and delivers the guidance based on that particular context. In an informal situation, it delivers guidance in a different manner, as compared to a formal situation. Further, in an embodiment, the system 106 delivers the intelligence/guidance as obtained from the Cognitive module 404 to the users. Further, in an embodiment, the users preferences, abilities, patterns, interests, environments (but not limited to) can be determined and accordingly the system 106 delivers the required intelligence appropriately. Further, the output module 406 can further be utilized by the devices, gadgets etc., to deliver intelligence, content and conversations in the form of voice, text, visual, gestures, actions etc., and repackage the output parameters of the responses after the match and translates it into answers to the question based model (understandable form by the user) using language referencing.

[059] Furthermore, the managing module 424 manage the user's and system's actions, functions, preferences, processes, data, communications, rules, triggers, mechanisms etc. Further, the system 106 manage family activities and enable them to customize various features (provided by the system 106) according to their needs. Such managing includes complete monitoring and providing guidance and options at each stage proactively with the help of its own intelligence. For example, business aspects as an individual can also own the private business where business aspects like performance, financial accounting is applicable for both personal and business and wherever financial transactions takes place, there arises the need for recording and summarizing these transactions when they occur and the necessity of finding out the net result of the same at the month/year end. Besides this there is also a need to communicate that information to appropriate persons like accountant or auditors, stakeholders, etc. the system 106 enable the users to set goals and budgets, maintain and track their financial information's, build accounting reports and get prepared for tax filing through simple steps on their own.

[060] Further, it is to be appreciated by a person skilled in the art that the system 106 is not restricted to aforementioned modules and instructions set. For example, in an embodiment, the memory 302 includes instructions (executable by the processor 304) for assessing the significance and urgency of each action in a set of actions or may assess the significance of each input parameter for performing a single action. Hereinafter, the assessed significance and urgency shall collectively be referred to as 'Factor Significance' . The 'Factor Significance' is a function of rate and time to decay of resources available, importance for the set of activities defined inputs or derived inputs and the elasticity of the inputs in that particular situation. The system checks frequency of each event to determine its timeline and based on the proximity to timeline, time value of priority score is derived. [061] Further, in an embodiment, the system 106 converts one or more resources to a function of time and check the elasticity of the events in that particular situation.

[062] In further embodiment, the system 106 correlates causes using users, surrounding, context inputs for each or a set of users actions, emotions, content, context etc. with the use of advanced intelligence to proactively assess users intentions, need of the same or similar users in similar situations in future.

[063] It is to be appreciated by a person skilled in the art, that the system 106 utilizes information corresponding to the past events and activities; present events and activities; and future events, intentions and future requirements of one or several users. In this way, the user's life is enhanced presently, helping to avoid critical situations or enlightened using the system's guidance using human determination for a better life.

[064] Further, the evolution module 422 is implemented to enhance the performance of the system 106. In an embodiment, the cognitive module 404 learns (through learning module 432) from the system's activities, users' activities and result of the system's activities to determine efficiency of the system 106 For example, the learning module 432 evaluates performance of the system 106 every time an action is performed. The response module 436 receives learning from the learning module 432 to form a probable answer set that is utilized for future processing of users' requests. For example, the response module determine (during each processing) regarding each user's selection of particular option and that is utilized to build a probable answers set for providing options to other users (in cloud environment) having the similar needs and situations. Further, the response module is upgraded every time based on the users' reaction corresponding to the system's actions (i.e., output to users).

[065] Further, the updating module 434 update the database (including corrections of the past failed attempts and suggestions provide to any of the registered users) based on the past requests, suggestions provided, suggestions adopted by the user and the effect/consequence of the adopting the suggestion by the user. By updating the database based on the learning, the system 106 is self-improving intelligently. Further, the updating module 434 updates the system 106 based on the learning module. In an embodiment, the updating module 434 updates the system to maintain equilibrium within the system's functionalities. For example, the updating module 434 decides the best suitable sequence of the functionalities that is performed by the system and accordingly updates the system 106 to enable functioning thereof in the decided manner for attaining maximum possible efficiency therefrom.

[066] The learning module 432 involves (but not limited to) Human-to Machine, Machine-to Human and Machine-to Machine learning. In an embodiment, the system itself learns to adapt (as part of learning module (adaptive mechanism)), this shall be referred to as 'Human-to- machine' learning wherein the machine (i.e., system 106) learns from humans. For example, training is to be provided by the user; e.g. the user trains the machine to understand the user's style, preferences, language etc. and behave accordingly. Further, the cognitive module (engine) 404 learns the method of delivery for each user based on what they subscribe to, what they accept (Receptivity) and determine the most effective way of learning skills. Further, it delivers appropriate guidance. Based on this, the Cognitive Module 404 evolves as per specific user's guidance as what user trains and behaves accordingly to the same specific user. Likewise, the system adapts to each user independently.

[067] Further, in another embodiment, the Machine-to-human learning includes, but not limited to, training of users by the system. For example, the system 106 captures and determines the user performance as part of the training and provide appropriate guidance to improve the learning abilities. For example, the system trains users for various skills such as Dance, Yoga and Emergency Procedure etc. Furthermore, the machine-to-machine learning includes, but not limited to, providing intelligence to other systems (machines). For example, the system 106 trains other systems/devices, such Internet Of things (IOT), Robots etc., for managing performance of life.

[068] It is to be appreciated by a person skilled in the art that the system is not restricted to the above-mentioned description. Further many more embodiments and examples are implemented in light of the present disclosure. Furthermore, the system 106 is not restricted to the modules, as described in this disclosure; further, various additional modules are utilized by the system 106 for carrying out functionalities associated with the present disclosure. For example (but not limited to): the system 106 has further modules/instructions to play a vital role in automating specific functions of the system 106 based on triggers, events, stimuli, actions, reactions, requirements to proactively process the information for the benefit of the users. Moreover, it is to be appreciated by a person skilled in the art that the system 106 is not restricted to a particular sequence to execute instructions related to various modules of the system.

[069] Referring now to FIG. 5 that illustrates an exemplary database 500 for storing information corresponding to various parameters, in accordance with an embodiment of the present disclosure. These parameters correspond to user, user's needs, surroundings, market data and the corresponding aspects. The database 500 includes information corresponding to each registered user of the system, such as the system 106. Further, as depicted, the database stores information corresponding to Master Data, Users Data, System Data, Transactional Data, Analytical Data, Streaming Data, Universal Taxonomy, System Taxonomy, Hierarchies & Tree-Maps, Rules, Language Reference, Transactional Models, Statistical Models, Object Models and File Management.

[070] In an embodiment, the database 500 stores information corresponding to the users' activities and further corresponding to the system's activities. For example, the database 500 stores a high level of information as master data and users' information as user data. The user data includes every information related to each user. Such user data includes the users' personal information, professional information, social and economic information corresponding to each user. For example, the personal information of each user includes, but is not limited to, information corresponding to oneself such as name, habit, preferences, achievements and so on. Further, the professional information includes, but not restricted to, the information corresponding to profession of the user, earning (or range thereof) of the user etc. the social information includes, but is not limited to, friends, family, culture, situation, society etc. Further, the economic information may correspond to (but not limited to) budget etc. [071] The user information is further secured and utilized by the system 106 to understand each user's needs, preferences and behavior pattern. Furthermore, based on one user's information, the system 106 determines information and performs planning corresponding to other related users.

[072] Further, the database 500 stores system information based on system's activities, transactional data, analytical data, streaming data and so on. Such system information can further be utilized to evolve the system in better way based on the past transactions/functionalities by the system. For example, if the system's actions such as guidance to a user helped the user in achieving individual's goal, the system adds such guidance in a priority list for utilization thereof (in future) for other related users (with similar preferences, and background).

[073] Information corresponding to taxonomy includes one or more taxonomy tables that are maintained and customizable by each user of the system. The taxonomy table includes a large collection of categories and sub categories. The taxonomy table is customizable and the users include their own categories and sub categories and use the table in this way. By this way, the table keeps on growing. The taxonomy table is linked with each and every aspect/functionality of the system 106. Further, the input/request, data, response etc. is categorized based on the categories and context in the taxonomy table.

[074] In an embodiment, a set of many taxonomy tables is maintained that includes a large collection of multi-level of classification of data (categories, sub categories, micro categories, context etc.). The taxonomy tables evolves based on users' own data classification that is customizable and also based on universal Subject Matter Expertise, industry specific terminologies and nomenclatures maintained centrally.

[075] Language reference is utilized to understand the users' languages. For example, if the user provides request verbally, the language references is utilized for voice recognition of the user. The system 106 performs natural language processing and provides voice based personal assistance. Language references include semantic definition corresponding to the users' languages. Based on such information corresponding to the language, the system 106 supports both Monologue & Dialogues based communications through voice. Further, the past record of the users' include, but not limited to, past activities of the user, action taken, guidance adopted and rejected and so on.

[076] Furthermore, the rules may be stored for intelligent functioning of the system 106. The subject matter knowledge includes facts corresponding to subject knowledge. These facts may be analyzed by implementing rules that enable the system 106 to take intelligent decisions for fulfilling the users' requirements. Further, the database 500 stores the users' information that includes personal, professional, environmental, social and family information. Such information corresponding to the user forms a part of the self-intelligence. Additionally, the information corresponding to suggestions also is stored. This includes, the suggestions provided by the system and the suggestions adopted under a particular circumstances of the user's life.

[077] Moreover, the database stores the cognitive information that includes intelligence parameters such as self-intelligence, collective intelligence, market and social intelligence (as explained previously in conjunction with FIG. 4). Also, the database stores the feedback information that is utilized for self-learning/improvement and self improvement of the system. The feedback information depicts information regarding challenging and successful guidance provided by the system 106 to the user. This helps in continuous evolution of the system 106.

[078] It is to be appreciated by a person skilled in the art that the database 500 is not limited to aforementioned description. Further, additional various types of information are stored based on the activities, requests, and situations corresponding to the user. The information stored in the database is utilized by the system 106 to manage the overall performance of each user's life.

[079] FIG. 6 illustrates a flow diagram 600 of a method for managing performance of life, in accordance with an embodiment of the present disclosure. The management of life performance of a user is facilitated by a system (such as the system 106). Further, in an embodiment, the user is registered with the system for managing life's performance. The method can be understood more clearly when read in conjunction with FIGS. 1-5. The order in which the method is performed is not intended to be construed as limitation, and further any number of the method steps may be combined in order to implement the method or an alternative method without departing from the scope of the invention.

[080] At step 602, the method receives input from a user. The input includes, but is not limited to, a query type; emotional input (by utilizing emotional expressions' feature that is provided by a system, such as the system 106) and gesture based input type. Further, the method enables each user for interaction to provide input through various mediums of communications such as, but not limited to, voice, text, visual, sensors, videos, signals etc.

[081] Further, at step 604, the method understands the type of request from the user (requestor) and determines the functionality that needs to be executed to fulfill the need of the user. At this step, the method verifies whether all the required inputs are received from the user. Further, in an embodiment, the method gathers user related data and perception inputs such as surroundings, context, relevance etc. corresponding to the user.

[082] Further, at step 606, the method transforms the user's request into the understandable form (such as in digital form). In an embodiment, such transformation is performed by utilizing (but not limited to) question based model, language referencing, taxonomies, tree maps, semantics etc. More specifically, the SME(s) (Subject Matter Experts) provides information corresponding to answer sets, principles, definitions, determination rules and tree-maps to enable the method to understand the meaning, context and intent of the input (such as emotional expressions) provided by the user. For example, based on the information provided by the SME(s) (Subject Matter Experts), the method match the user's emotional expressions with a defined set of rules to determine the meaning and intent of the user's input query. Further, in an embodiment, the method decides sequence for a plurality of functionalities that need to be performed based on the received inputs (and gathered inputs) corresponding to the user. [083] At step 608, the method determines habit and practices of the user to derive data corresponding to the user's request. For this, the list of users, groups or other entities, which display similar habits, practices, mannerisms, intents etc., may be grouped, clustered. The method utilizes a combination of factor deviation and event occurrence frequency and sequence to deliver descriptive statistics, statistical models, percentile ranking models etc. for identifying and maintaining these groups. Once the user group is formed, the descriptive statistics, statistical models are used to define a particular user group. It uses a combination of percentile rank, deviation parameters to find out the characteristics, habits, mannerisms that define this particular group.

[084] Further, in an embodiment, the method captures each and every action of the users and figures out the characteristics of every single user individually and collectively based on clustering. Further, it compares the data and groups of similar users based on their characteristics less than one cluster. In most cases, users with similar characteristics are at different stages (Milestones) of their lives; the past performance of the cluster indicates the intelligence as to what life choices made by those users to achieve their milestones better. These indicators are critical for several individuals to take critical decisions to pass through certain stages of life well. The method analyzes the data, derive insights and disseminate the intelligence and the appropriate users based on the requirements or situations.

[085] Further, the method implements various intelligent mechanisms to determine intelligence data from various sources. Such intelligence data is relevant for the user's input that is analyzed to provide an effective solution, accordingly, to the user. The intelligence data that is derived and analyzed by the method include, but is not limited to, Self-intelligence (Si), Collective intelligence (Ci), Market intelligence (Mi) and Social intelligence (SOi). The intelligent data gathering and analysis is explained previously in this disclosure and thus not repeated herein for the sake of brevity. Further, in an embodiment, the method collects validated data from SMEs (Subject Matter Experts) and system data from the data source to derive intelligence data (i.e., Si, Ci, Mi and SOi). [086] The output of the method step 608 can be further processed to take into account such particular characteristic to fine tune the search for a person belonging to this user habits and practices group.

[087] Further, at step 610, the method processes the available options to determine relevancy of the available options based on the analyzed information. Further, in an embodiment, the method determines the weightage dynamically of each factor for every need, request, statistic, emotion etc. for this, in an embodiment, the method takes input through feedback mechanisms, which correlates the guidance given and the guidance followed in each category.

[088] At step 612, the method clusters the user's inputs and the corresponding responder input into different clusters. Herein, the responder corresponds to any response that address the requirements of the user based on the user's input/determined user's requirement. Responder (may be referred to as 'respondent' interchangeably) includes any entity that responds to the requirements and is in the form of (but not limited to) a system's user, Vendor, and an Online Database entity. The method ensures that even if an exact match for the search parameter is not available, the closest match is given a matching score.

[089] In an embodiment, the method treats every data type differently but the parameter (input) is the same. Each input parameter is to be put into clusters of different levels. With each higher level, the cluster becomes wider and the matching score becomes lower. In an embodiment, at one particular level, the receptor inputs in a particular level might match with the responder' s input at the same level, which indicates a match. As the cluster level keeps increasing, the matching score keeps decreasing.

[090] Furthermore, at step 614, the method take into account all the receptor's inputs and match each one with the corresponding responder' s inputs. The matching score is a function of how close the receptor input is to the responder input. Herein, the matching score not only considers the proximity but also takes into account, if the input is better for the user if it is closer to the lower bound or the upper bound of the response. [091] Further, at step 616, the method retrieve the best match based on the matching score and also based on the situation of the user at the time of the search as well as the system itself would alert the user by intelligent triggers from the engine. These parameters, that may not be put in(Input) directly for the search but are important in suggesting a relevant response based on the context. Additionally, the method repackages the output parameters of the responses after the match and translates it into answers to the question based model (understandable form by the user) using language referencing.

[092] In an embodiment, the method stores the relevant information corresponding to the user and further corresponding to the Collective intelligence in a database, such as the database 500. The method utilizes such information to manage multiple users' lives performances. The examples and embodiments corresponding to the method can be understood in conjunction with FIGS. 1-5 and thus not be repeated herein again for the sake of brevity.

[093] It is to be appreciated by a person skilled in the art that the method is not restricted to the aforementioned description. Further, many more examples and embodiments can be implemented without departing from the scope of the invention.

ADVANTAGES

1. The system intuitively assists the user to manage individual's own life and empowers the user to increase the quality and enhance performance at each stage. The present invention acts as a holistic Life Guide and provides proactive guidance and options at right time. The guidance is facilitated based on insights (information derived from user data, statistics, population data, process data, demographic data, market data) gathered from various functionalities of the system and intelligent sources.

2. The present invention act as a family management system that assists multiple users (dependent family members). It also helps the dependent users to become independent based on the progression of life (ability to manage life independently). Furthermore, the system provides capability to transfer the complete details of a particular dependent to any other dependents in the user's dependents list.

3. The system help users to keep day to day activities and information more organized through facilitating conscientiousness and security by the system and helps users to react to situations and manage life in a better ways.

4. System continuously learns, updates its intelligence and evolves with the user as a companion by understanding the user's likes, dislikes, moods, needs, behaviors, patterns, attributes, emotions and intelligence through and up-dates its consciousness with the use of cognitive module to proactively help the users with decision making abilities.

5. The system understand the needs through users' input or automatically through keen observations on users' choices, activities, actions, preferences, patterns of the users' and provides apt guidance, suggestions as per their needs and situations and helps users to make better life choices as opposed to people taking their needs to online sources for searching, digesting data to decide the right option in general. 6. The present invention provides user interest and location based relevant and proximate options as the result for each search with the help of its own intelligence. Apart from this, it also suggests the best choices. This makes the decision making even easier for the user. In addition to this, the system automatically detects the current location and searches for the people in their circle (contacts) during emergencies.

7. The present invention provides guidance based on the past, present and probable future of the user. In case of necessity, the present invention generates an emergency alert that is provided even in offline mode through SMS (Short Message Service).

It is to be appreciated by a person skilled in the art that the present invention shall not be limited to the various advantages as mentioned here above.

Embodiments of the invention are described above with reference to block diagrams and schematic illustrations of methods and systems according to embodiments of the invention. It will be understood that each block of the diagrams and combinations of blocks in the diagrams can be implemented by computer program instructions. These computer program instructions are loaded onto one or more general purpose computers, special purpose computers, or other programmable data processing translators to produce machines, such that the instructions that execute on the computers or other programmable data processing translator create means for implementing the functions specified in the block or blocks. Such computer program instructions are stored in a computer-readable memory that can direct a computer or other programmable data processing 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 that implement the function specified in the block or blocks.

While the invention has been described in connection with what is presently considered to be the most practical in various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. The invention has been described in the general context of computing devices, phone and computer- executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, characters, components, algorithms, data structures, etc., that perform particular tasks or implement particular abstract data types. A person skilled in the art will appreciate that the invention can be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs (Personal Computer), minicomputers, mainframe computers, and the like. Further, the invention can also be practiced in distributed computing worlds where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing world, program modules are located in both local and multiple remote memory storage devices.

This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods.

Claims

CLAIMS What is claimed is:

1. A life management system for enabling the holistic performance of life with adaptive intelligence comprising; a system which functions to guide a user with or without receiving any input for users' requirements by tracking the users' actions and monitor and evaluate moods, habits, situations of the users; a memory unit which stores hierarchical, temporal, volatile and persisted information as structured, semi -structured and unstructured data, such as knowledge, instructions, rules, logs, documents in different formats; a need identification module which identifies the need of the user and determine the type of request from the user and accordingly, performs one or more functionalities based on the type of the input; a cognitive module which performs various operations corresponding to life performance management of the user for providing guidance and intelligent options to the user; an output module which repackage the output parameters of the responses after the match and translates it into answers; a database which stores the information corresponding to various parameters; and a processor is collection of multiple physical processors in local and distributed environments capable of processing multiple inputs and requests and provide responses and output.

2. The life management system as claimed in claim 1, wherein said memory unit is coupled with said processor which is selected from the group consisting of industry standard highly available, scalable and efficient processors coupled with highly secured, reliable large databases.

3. The life management system as claimed in claim 1, wherein said need for identification module further consists of a receiving module which receives different types of multiple and simultaneous inputs like audio, video sensory data, visuals, gestures etc., corresponding to needs, questions, emotions, gestures, situations, locations, triggers etc., via multiple interfaces such as sensors, peripherals, gadgets, devices; a quizzing module which transforms the user's request into the system understandable form through one or more iterations and interactions facilitate effective conversations aided with proactive suggestions wherein such transformation is performed by utilizing question based model, language reference libraries, decisions, taxonomies, tree maps, semantics etc.; an emotional module which understand and analyze the emotional expressions by the user based on the user's information and other gathered information.

4. The life management system as claimed in claim 1, wherein said cognitive module further consists of an analysis module which analyze the one or more user's request based on one or more intelligence parameters; processing module which process the available options to determine relevancy of the available options based on the analyzed information including orchestration of the execution of processes, functions, methods involved in providing the right guidance, intelligence and options to the user's needs; a processing module which process the available options to determine relevancy of the available options based on the analyzed information including orchestration of the execution of processes, functions, methods involved in providing the right guidance, intelligence and options to the user's needs; an evolution module which be implemented to enhance the performance of said system connected to a managing module which manage the user's and system's actions, functions, preferences, processes, data, communications, triggers, mechanisms etc., manage family activities and enable them to customize features according to their needs, enhance the performance of the system and make the system evolve through adaptive learning, updating and tracking responses; and a managing module manage the user's and system's actions, functions, preferences, processes, data, communications, triggers, rules, mechanisms etc. and also manage life activities and enable them to customize and configure various features according to their needs; a suggestion module which retrieve the best match based on the user patterns, expertise, interests, preferences based on the matching scores, ranks depending on the users' needs, circumstances, received manually or automatically and provide the best suggestions, guidance and learning.

5. The life management system as claimed in claim 1 and 4, wherein the intelligence parameters comprises self-intelligence (Si), collective intelligence (Ci), market intelligence (Mi) and social intelligence (SOi).

6. The life management system as claimed in claim 1 and 4, wherein said analysis module consists of a monitoring module which continuously monitors events, triggers, logs, information, activities and performances within the system and external to the system and collects all the input and activity data.

7. The life management system as claimed in claim 1,4, and 5 wherein said monitoring module is selected from the group consisting of one or more servers, online and other knowledge base.

8. The life management system as claimed in claim 1 and 4 wherein said processing module further comprises of a determination module which perform the execution of the components, functions, logics orchestrated based on the request determine the weightage dynamically of each factor for every need, request, statistic, emotion etc. by taking input through feedback mechanisms, which correlates the guidance given and the guidance followed in each category; a cluster module which cluster the corresponding responder inputs into different clusters and ensure that the matching score is given for search parameters based on the user's input or system determined user's requirement and patterns and cluster the user's inputs and the corresponding responder input into different clusters; and a ranking module which consider all the receptor's inputs and match one or more of the corresponding responder' s inputs.

9. The life management system as claimed in claim 1 and 4 wherein said evolution module further consists of a learning module which continuously understand and learn from the system, from all sources of intelligence, from the trainings provided by the users, learns as to how users are receptive to the system's guidance and also prepares learning methods and content and evaluate performance of said system every time an action is performed; a response module which produce responses as options to user's requests and also determine the user's selection of particular option and that is utilized to build a probable answers set for providing options to other users having the similar needs and situations and is upgraded every time based on the users' reaction corresponding to the system's actions; an updating module which update the said system and the database based on the learning to make the system self-improving intelligently and maintain equilibrium within the system's functionalities.

10. The life management system as claimed in claim 1, wherein said output module repackage the output parameters of the responses after the match and translate it into answers to the questions and delivers those answers based on nature of the users, their emotions and their preferences using language reference and validation model.

11. The life management system as claimed in claim l,wherein said database is selected from the group consisting of master data, user data, system data, transactional data, analytical data, streaming data, universal taxonomy, system taxonomy, hierarchies, tree maps, rules, language references, transactional model, statistical model, object model, file management etc. capable of evolving along with the system.

12. The life management system as claimed in claim 1, wherein said system is built-in human determination capabilities embedded in the cognitive module which is capable of developing and providing the state of consciousness and conscientiousness based on situational & self- awareness, characteristics, patterns, emotions, modulations, behaviors, personal and professional attributes and habits, sensory perception, abilities, guidance, intellectuality for providing intelligence (intelligent quotient, emotional quotient, personality quotient, self- intelligence, collective intelligence, marketing intelligence, social intelligence etc.,) to the user by providing better life choices and options.

13. The life management system as claimed in claim 1, wherein said system continuously evolves to provide a holistic life solution and intelligence to achieve maximum performance and enlightenment.

14. The life management system as claimed in claim 1, wherein said system can be implemented with computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs (Personal Computer), minicomputers, mainframe computers, and the like.

15. The life management system as claimed in claim 1, wherein the user access medium is selected from the group consisting of, devices, machines, peripherals such as laptop, tablet computer, smart phone, personal digital assistant, cell phone, personal computer, robots, gaming gadgets, sensory devices and sensory devices integrated with camera.

16. A process for managing personal intelligence using life management system as claimed in claim 1 comprising:

A. receiving input from a user;

B. determining the type of input to perform one or more functionalities accordingly;

C. transforming the user request to system understandable information feeds;

D. determining the users' habit, practices and patterns to derive data corresponding to the users' request;

E. determining significant scores for both defined and derived data;

F. creating request and response cluster;

G. matching and ranking all the clusters between requestor and responders;

H. filtering suitable guidance to guide intelligently based on the perception and update the cognitive module with learning data.