DESC:FIELD OF INVENTION
This invention relates to an artificial intelligence system and method for detecting, recording, analyzing and predicting events of the human performances. More specifically this invention provides for an artificial intelligence system and method aimed to enable a user to imagine, create, transact, record, archive, broadcast and monetize their human performance experiences.

BACKGROUND OF INVENTION
In today’s day and age with incremental use of mobile, computer and internet there are various technologies available in mobile and computer to analyse various human performance data such as sports data, human medical data etc. But with available technologies, we are facing a scenario where we cannot analyse the live data of human performance such as sports data, and human medical data. Various methods are available which help to score matches in limited function and independent solutions for video streaming. However, a few methods are also available which can provide solution related to medicine such as diabetic patients, patients admitted in hospitals. Further, few methods are available which provide independent solution of video streaming of human performances and separate solution of the analysis of human performances.

The most common method of scoring matches is still manual scoring through physical (paper) scoring sheets. These are unwieldy and difficult to manage for the users. To the extent there exists no clear record, e.g.,
• any player’s and team’s performances,
• a historical directory of sports venues with record of matches played at those venues,
• a record of how a player or team has evolved over time,
• a record of how active different geographical regions are over time, etc.

Further, various artificial intelligence systems are available which are used in other fields. Some of the artificial intelligence systems are as follows:
US20200058386 relates to an artificial intelligence insulin pump that processes glucose data, wellness data, external data, and port information to determine the appropriate amount and timing of insulin to deliver to a person. External data includes data from sources remote from the insulin pump and the user such as social media data, GPS location data, historical data including energy and food intake at locations visited prior, data from third party sources. Such external data may include that the use is registered for a marathon and in at the marathon venue and the user's exertion level indicates that the user is running has begun to run the marathon. The AI engine would than adjust the insulin appropriately. Thus, artificial intelligence system in the medical field is available to detect the glucose data of a user/patient.

WO2019178380 relates to a system and method for detecting, recording and communicating events involved in the care and treatment of cognitively impaired persons through detection, video recording, storage and communication. The system includes video cameras that typically begin recording upon detecting motion, a local computing unit at the care location that detects alerts, and a cloud or other remote computing and transmission unit. The local computing unit aggregates, stores, processes, and transmits data including performing event detection through an artificial intelligence technique and generating appropriate alerts. The cloud computing aggregates data from many managed care communities, trains new convolutional neural networks from this data, distributes these networks to the local computing units to perform event detection, and provides a platform for various stakeholders to view the collected video data and generated alerts. Further, artificial intelligence system is also present in the medical field to detect, record and communicate events of patients.

US7848548 discloses a face-based automatic demographics classification system that is robust to pose changes of the target faces and to accidental scene variables, by using a pose-independent facial image representation which comprises multiple pose-dependent facial appearance models. Given a sequence of people's faces in a scene, the two-dimensional variations are estimated and corrected using a novel machine learning based method. We estimate the three-dimensional pose of the people, using a machine learning based approach. The face tracking module keeps the identity of the person using geometric and appearance cues, where multiple appearance models are built based on the poses of the faces. Each separately built pose-dependent facial appearance model is fed to the demographics classifier, which is trained using only the faces having the corresponding pose. The classification scores from the set of pose-dependent classifiers are aggregated to determine the final face category, such as gender, age, and ethnicity. Thus, artificial intelligence system is present to detect and analyse the face data of a user.

US20180152809 relates to methods, systems, and devices for preventing the loss of valuable items using beacon notifications. A loss prevention tag is a small, discreet electronic tag which can be attached to belongings in order to prevent them from being lost. The tag may communicate with a computer or mobile device (e.g., a smartphone or a smartwatch) and may transmit a notification when the object it is attached to moves beyond a threshold distance from the device it is communicating with. A loss prevention tag system may utilize a system of smart notifications. One function of the smart notification system is to remove false alarm notifications. Another function of the smart notification system may be to modify the mode or format of the notification. So, artificial intelligence system is present to prevent the loss of valuable items.

US10528962 relates to systems and methods for providing AI-based cost estimates for services. The method may comprise receiving, at one or more processors, data from a scanning of a location, the scanning performed by one or more of cameras, a computer vision device, an inertial measurement unit, or a depth sensor. Data may be received, at one or more processors, related to the identification of one or more key elements at the location. An itemized statement and quote of work to be performed may be generated at one or more processors.

Further, systems and methods are available which are used to work on the basis of artificial intelligence. However, despite the aforesaid systems/methods, a need is felt for more effective, competent, specific, efficient, and accurate artificial intelligence system and method to imagine, create, transact, record, archive, broadcast and monetize their human performances and especially sports experiences. Also, no artificial intelligence system is present that provides a 360 degree sports-tech platform that enables users to imagine, create, transact, record, archive, broadcast and monetize their sports experiences.

It is therefore the object of the present invention to provide an artificial intelligence system and method to offer tools and technology to users to be able to record and livestream high quality of human performances such as sports matches and capture sports performance data through industry-grade broadcasting and scoring tools. This data is then statistically modelled into a huge range of sports insights, analysis and performance matrices.

SUMMARY OF THE INVENTION
The present invention relates to an artificial intelligence system and method for detecting, recording, analyzing and predicting events of human performances. More specifically this invention provides for an artificial intelligence system and method aimed to enable a user to imagine, create, transact, record, archive, broadcast and monetize their human performance experiences.

The present invention relates to an artificial intelligence system for analyzing and predicting human performance data, the system comprising:
a processor;
a memory coupled to the processor, the memory comprising:

an artificial intelligence module configured to determine type of human performance from a video data based on a plurality of predetermined human performances data associated with the type of human performance;

an event identification module configured to identify event associated with the human performance type based on predetermined event identifier associated with the human performance type;

an event categorization module configured to categorize the event in a plurality of predetermined categories;

an event data extraction module configured to extract event data from each category of plurality of predetermined categories;

a data intelligence module configured to analyse the event data and to make and generate report based on
• a predetermined event analysis and a predetermined format and
• an evolving new event analysis and new format.

The present invention also relates to a method for analyzing and predicting human performance data, the method comprising steps of:

Determining a human performance type from a video data based on a plurality of predetermined data associated with the human performance type, wherein the determination of the human performance type is performed by an artificial intelligence module;

identifying an event associated with the human performance type based on predetermined event identifier associated with the human performance type, wherein the identification of the event associated with the human performance type is performed by an event identification module;

categorizing of the event in a plurality of predetermined categories, wherein the categorization of the event is performed by an event categorization module;

extracting of event data from each category of the plurality of predetermined categories, wherein the extraction of the event data is performed by an event data extraction module; and

analyzing the event data and to make a report based on
• a predetermined event analysis and a predetermined format, and
• a new event analysis and a new format,
wherein the analyzation of the event data is performed by a data intelligence module.

According to another aspect of the invention, the artificial intelligence system and method is more effective, competent, specific, efficient, and accurate artificial intelligence system and method to imagine, create, transact, record, archive, broadcast and monetize their human performances and especially sports experiences. Also, the artificial intelligence system provides a 360 degree human performance analysis, especially those that are performed and/or streamed through a sports-tech platform that enables users to imagine, create, transact, record, archive, broadcast and monetize their human performances especially sports experiences.

It is therefore, the object of the present invention to provide an artificial intelligence system and method to offer tools and technology to users to be able to record and livestream high quality human performances especially sports matches and capture sports performance data through industry-grade broadcasting and scoring tools. This data is then statistically modelled into a huge range of sports insights, analysis and performance matrices.

The summary is provided to introduce the system and method of representative concepts in a simplified form that are further described below in the detailed description. This summary is not intended to limit the key essential features of the present invention nor its scope and application.

Other advantages and details about the system and method will become more apparent to a person skilled in the art from the below detailed description of the invention when taken in conjugation with the drawings.

BRIEF DESCRIPTION OF DRAWINGS
The following drawings are illustrative of particular embodiments for enabling system and method of the present invention and are not intended to limit the scope of the invention. The drawings are not to scale (unless so stated) and are intended for use in conjunction with the explanations in the following detailed description.

FIG 1. is a schematic representation of an artificial intelligence system where the invention may be implemented.
FIG. 2 is an exemplary system illustrating an artificial intelligence system in accordance with one or more implementations.
FIG. 3 is a flow chart to illustrate a method for analyzing human performance data using an artificial intelligence system.
FIG. 4 illustrate an artificial intelligence model that may be trained to analyse and predict events of human performance, in accordance with one or more implementations.

Persons skilled in the art will appreciate that elements in the figures are illustrated for simplicity and clarity and may represent both hardware/software components of the system. Further, the dimensions of some of the elements in the figure may be exaggerated relative to other elements to help to improve understanding of various exemplary embodiments of the present disclosure.

Throughout the drawings, it should be noted that like reference numbers are used to depict the same or similar elements, features, and structures.

DETAILED DESCRIPTION OF DRAWINGS
The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of exemplary embodiments of the invention in respect of which patent protection is being claimed. It includes various specific details to assist in that understanding but these are to be regarded as merely exemplary. Accordingly, persons skilled in the art will recognize that various changes and modifications to the embodiments described herein can be made without departing from the scope and spirit of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.

TERMS

Macro-level data is defined as data pertaining to a broad dataset such as those which are used to examine equipment used and purchased in a particular event such as those of match.

Micro-level data is defined as data pertaining to a broad dataset such as those which are used to examine human performance in relation to the event in which they perform.

It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.

The terms and words used in the following description are to be understood in the manner used by the inventor to enable and describe the invention. For further clarity and to enable better understanding of the invention, certain key terms are being defined hereinunder.

DESCRIPTION
Some embodiments according to the present technology provide a novel way of providing record live human performances such as sports activity, accurate detection of live sports activity, analyzing and predicting events and sports by using a deep learning/natural language processing powered system. The present technology provides the user more interactive experience. The user may imagine, create, transact, record, archive, broadcast and monetize their human performance experiences

Some embodiments according to the present technology may provide the ability to perform targeted actions based on a predetermined event analysis and a predetermined format. Further, the present technology may provide the ability to perform targeted actions which are new event analysis using new format after learning the predetermined event analysis using predetermined format.

Some embodiments according to the present technology may include the ability to ask targeted questions automatically based on predetermined event analysis using a predetermined format. In some other embodiments, the ability for a user to provide new event analysis of the human performances such as sports and the artificial intelligence system will learn from the predetermined formats and is able to provide new event analysis using the stored data. So, the technology has an ability to analyse the human performances and learn from the experiences of event analysis and can predict the future aspect of the live performances of any human performances.

The artificial intelligence system for analyzing human performance data, the system comprising:
a processor;
a memory coupled to the processor, the memory comprising:

an artificial intelligence module configured to determine type of human performance from a video data based on a plurality of predetermined human performances data associated with the type of human performance;

an event identification module configured to identify event associated with the human performance type based on predetermined event identifier associated with the human performance type;

an event categorization module configured to categorize the event in a plurality of predetermined categories;

an event data extraction module configured to extract event data from each category of plurality of predetermined categories;

a data intelligence module configured to analyse the event data and to make report based on
• a predetermined event analysis and a predetermined format and
• an evolving new event analysis and new format.

The artificial intelligence system is able to analyze human performance activity such as sports activity, medical activity, etc.

FIG 1. is a schematic representation of an artificial intelligence system where the invention may be implemented. The artificial intelligence system 100 includes two components i.e. processor 101 and memory 102. In accordance with one embodiment of the present invention, the memory 102 includes an artificial intelligence module 201, an event identification module 202, an event categorization module 203, an event data extraction module 204 and a data intelligence module 205.

The artificial intelligence module 201 is configured inside the memory 102 to determine type of human performance from a video data, based on a plurality of predetermined human performances data associated with the type of human performance. Based on the video received from the user, the artificial intelligence module 201 is able to determine the type of human performance.
In furtherance of this, the determination of the type of human performance done by the artificial intelligence module (201) is done on the basis of the following factors:
- type of equipment;
- number of equipment;
- surroundings in which human action is performed;
- weather in which the human action is performed;
- type of human action performed;
- surface on which human action is performed;
- number of players and the colour of their jersey;
- number of umpires or refere;
- position of the referee/umpire;
- time duration for which human action is performed;
- whole time duration of the video.

Such as when the artificial intelligence module 201 receives a video where stumps, bat, ball, players, two umpires are present, then the artificial intelligence module 201 will recognize that the cricket match is ongoing i.e. the user is watching cricket match.

The artificial intelligence module 201 is connected to the event identification module 202 which is configured to identify event associated with the human performance type based on predetermined event identifier associated with the human performance type. The event identification module 202 identifies the sports based on the event identifier and will inform the user regarding the event. The factors on the basis of which the event identification module (202) is able to carry out its function is as follows:
- colour of the jerseys of the player;
- action performed by the player;
- manner of interaction between the player the and equipment used;
- time duration for which the player and the equipment interact with each other;
- weather in which human action is performed;
- surface on which human action is performed;
- angle with which equipment is placed and arranged on the surface by the player;
- angle with which the person/player interacts with the equipment.
In one of the embodiments, the event identification module (202) identifies that a first player throws a ball at an angle towards a second player and accordingly, the second player strikes the ball at an angle using the bat. This data will help in identifying that in a cricket match there is a bowling session and a batting session that is performed.
Thereafter, the event categorization module 203 will categorize the event in a plurality of predetermined categories and will inform the user regarding the category of the event. The categorization of the event is analyzed on the basis of the following factors:
- action performed by the player/person in accordance with the colour of their jersey;
manner of interaction between the equipment and the player/person;
- time duration for which the player and the equipment is interacted including the whole-time duration of the event;
- weather in which human action is performed;
- surface on which human action is performed;
- angle with which equipment is placed and arranged on the surface;
- angle with which the person/player interacts with the equipment.

Accordingly, in one of the embodiments, the event categorization in relation to the cricket match is shot with which the second player strikes the ball is categorized as a batting session performed by the second player while the event of throwing the ball to the second player by the first player is categorized as bowling session performed by the first player.

- The event categorization module (203) will deliver the information to the event data extraction module 204 which is configured to extract event data from each category of plurality of predetermined categories. The extraction of the event data from each category is done on the basis of the following factors:action performed by the player in relation to the equipment used;
- manner of interaction between the equipment and the player in accordance with the time-duration of the interaction;
- weather in which human action is performed;
- whole time duration of the event;
Further, based on the information received from the user, the categorized event will be informed to the user and the user by using the data intelligence module 205 will analyse the event data and will make a report. The data intelligence module 205 may make the report of the information based on a predetermined event analysis and a predetermined format. The factors on the basis of which the report of the information is prepared are as follows:
- action performed by different players in accordance with the color of their jerseys;
- manner of interaction of the players with the equipment/component;
- weather of the surroundings in which human action is performed;
- surface on which human action is performed;
- human action performed by the player in a particular time duration in accordance with the whole-time duration of the event;

Further, the data intelligence module 205 may make the report of the information based on an evolving new event analysis and novel format.
The data intelligence module 205 is capable to learn from the predetermined events and predetermined formats and analyse and predict future aspect of the sports or any human performances. The data intelligence module 205 is capable to learn from the predetermined events and predetermined formats and make a report of the information for any new events and new formats.
In furtherance of this, the new event analysis and the new format is done on the basis of the ranking of the players wherein the ranking is determined on the basis of the following factors:
- weather in which event/ human action is performed;
- surface on which event/human action performed;
- manner of interaction between the equipment in accordance with the time duration of the interaction and whole-time duration of the event;
- sequence of the players;
- combination among the different players.
Additionally, the report includes a ranking of the team as a whole which is in relation to the event to be analyzed. Additionally, the data intelligence module (205) is able to generate highlights of the event of the sports activity. In the highlights of the event, the maximum runs scored by the particular player during the batting session will be highlighted in a pre-determined color wherein the highlight also includes a pre-determined expression and a pre-determined gesture. In one of the embodiments the pre-determined expression can be a happy and cheerful face with a pre-determined gesture of roaring lion.

The artificial intelligence module 201, event identification module 202, event categorization module 203, event data extraction module 204, and data intelligence module 205 are deployed logically and physically as separate housing and are connected with each other inside the memory 102.

FIG. 2 is an exemplary system wherein an artificial intelligence system in accordance with one or more implementations. In some implementations, the artificial intelligence system 100 may be configured to communicate with one or more user computing platforms 111. The users may access the artificial intelligence system 100 via using the user computing platform(s) 111. The data of artificial intelligence system 100 and the user computing platforms 111 are stored in the cloud 115 in order to use the data to determine the report of the information based on a predetermined event analysis and a predetermined format. Further, using the data of cloud 115 the data intelligence module of artificial intelligence system 100 will learn as a result is capable to make report of new event analysis using new format.

The artificial intelligence system 100 will perform using the method for analyzing and predicting human performance data, the method comprising steps of:

determining human performance type from a video data based on a plurality of predetermined data associated with the human performance type, wherein the determination of the human performance type is perform by an artificial intelligence module;

identifying of an event associated with the human performance type based on predetermined event identifier associated with the human performance type, wherein the identification of the event associated with the human performance type is perform by an event identification module;

categorizing of the event in a plurality of predetermined categories, wherein the categorization of the event is perform by an event categorization module;

extracting of event data from each category of the plurality of predetermined categories, wherein the extraction of the event data is perform by an event data extraction module; and

analyzing the event data and to make a report based on
• a predetermined event analysis and a predetermined format, and
• a new event analysis and a new format,
wherein the analyzation of the event data is perform by a data intelligence module.

FIG. 3 is a flow chart to illustrate method for analyzing human performance data using artificial intelligence system in accordance with aspects of the present disclosure. In some examples, a flowchart may execute a set of codes to control functional elements of the flowchart to perform the described functions. Additionally or alternatively, a flow chart may use special - purpose hardware.

At step 301, the human performance type is determined from a video data based on a plurality of predetermined data associated with the human performance type, wherein the determination of the human performance type is performed by an artificial intelligence module 201.
Then at step 302, the event associated with the human performance type based on predetermined event identifier associated with the human performance type is identified, wherein the identification of the event associated with the human performance type is perform by an event identification module 202.
Further, at step 303, the event is categorised in a plurality of predetermined categories, wherein the categorization of the event is performed by an event categorization module 203. Then at step 304, the event data is extracted from each category of the plurality of predetermined categories, wherein the extraction of the event data is performed by an event data extraction module 204. Finally, at step 305 the event data will be analysed and a report is made using the data intelligence module 205.
In one instance and at step 306, the data intelligence module 205 will make report based on a predetermined event analysis and a predetermined format. However, in other instance the data intelligence module 205 may learn from the predetermined categories and predetermined formats and make report based on a novel event analysis and a novel format at step 307.

These operations may be performed according to the methods and processes described in accordance with aspects of the present disclosure. For example, the operations may be composed of various substeps, or may be performed in conjunction with other operations described herein. In certain examples, aspects of the described operations may be performed by the artificial intelligence system 100 as described with reference to FIG . 1.

FIG. 4 illustrates an artificial intelligence model that may be trained to analyse and predict events of human performance, in accordance with one or more implementations.
Through the present technology, the artificial intelligence system 100 provide an integrated tool to help the user to uplift every aspect of the human performance such as sports. The artificial intelligence model will begin by signing up the user on the user computing platform 111 and will work using social engagement across demographics and geographic 501, Broadcasting and OTT 502, real-time hyper local sports ecosystem 503 and grassroots sports insights and intelligence 504.

The artificial intelligence model will begin and at step 511 of the flowchart, the user/individual will sign up in his/her accounts and thereafter may perform following activities:
- either at step 512, the user will create tournaments and thereafter at step 513 the user will watch or play the tournament; or
- at step 514, the user will invite friends, family and others to join teams and the user may also create teams
Further, at step 515, the teams as created by the user may play matches and the matches may also be played as a result of the tournaments as created and scheduled by the user.

The video of matches 515 as played between the teams will be recorded for the analysis of the sports data. Thereafter, at step 517, the matches may be streamed live through the user computing platform 111. The user may then store the data of the sports activity in the memory 102 as a result of step 516 wherein the user generates content of the sports activity.
The stored data of the generated content in the memory (102) interacts and communicates with the artificial intelligence module 201, the event identification module 202, the event categorization module 203, the event data extraction module 204 and the data intelligence module 205.
The artificial intelligence module 201 is configured to perform a method of determination of type of human performance form the video of the sports activity on the basis of the following factors:
• type of an equipment;
• number of the equipment;
• surroundings in which human action is performed;
• weather in which the human action is performed;
• type of human action performed;
• surface on which human action is performed;
• number of players and the colour of their jersey;
• number of umpires or referee;
• position of the referee/umpire;
• time duration for which human action is performed;

The event identification module 202 performs a method of identifying an event associated with the human performance type from the video of the sports activity on the basis of the following factors:
• colour of the jerseys of the player;
• action performed by the player;
• manner of interaction between the player and the equipment used;
• time duration for which the player and the equipment interact with respect to each other;
• weather in which human action is performed;
• surface on which human action is performed;
• angle with which equipment is placed and arranged on the surface by the player;
• angle with which the player interacts with the equipment.
The event categorization module 203 performs a method of categorizing the event associated with the human performance type from the video of the sports activity on the basis of the following factors
• action performed by the player/person in accordance with the colour of their jersey;
• manner of interaction between the equipment and the player;
• time duration for which the player and the equipment interacted including the whole-time duration of the event;
• weather in which human action is performed;
• surface on which human action is performed;
• angle with which equipment is placed and arranged on the surface;
• angle with which the person/player interacts with the equipment.

Thereafter, on the basis of user generated content the artificial intelligence module 205 will automatically generate
highlights of the sports activity at step 518; and
showreels of the sports activity at step 519

Further, at step 520, the user purchases goods and services for better tournaments and better matches. After purchasing the goods and services, the user will get higher quality matches for better experience. The good and services will include details of
- grounds/venues 521
- scores and streamers 522;
- commentators and entertainers 523;
- professional kits and equipment 524;
- Coaches and trainers 525;
- Academies and clubs 526;
- Consumer goods and services 527 and
- Business goods and services 528.

Based on the above details and intelligent recommendations, the scorers score matches through a robust scoring tool at step 529. After scoring of the matches, the artificial intelligent system 100 will record the sports activity at step 530 and at last step 531 the artificial intelligence system 100 will contain all details of players, details of matches, records of players, records of teams and records of tournaments.

Thus, the artificial intelligence system and method to offer tools and technology to users to be able to record and livestream high quality sports matches and capture sports performance data through industry-grade broadcasting and scoring tools. This data is then statistically modelled into a huge range of sports insights, analysis and performance matrices.

The artificial intelligence system and method is more effective, competent, specific, efficient, and accurate artificial intelligence system and method to imagine, create, transact, record, archive, broadcast and monetize their human performances and specially sports experiences. Also the artificial intelligence system provides a 360 degree sports-tech platform that enables users to imagine, create, transact, record, archive, broadcast and monetize their sports experiences.

Through the present technology, all local sports that happens across demographics and geographies in India and outside India are organised. Thus, the present technology provides an integrated tool to help the users uplift every aspect of their sport. It begins with the users signing up on the user computing platform and creating teams of their friends and families and others that they play with. These teams can then participate in matches and tournaments created by users on the user computing platform. These can be existing tournaments that are organically organised in the local ecosystem, or new tournaments that our platform facilitates creation of. In effect, the present technology is creating net new creators in the overall sports ecosystem in India and world.

Through a rich hyper-local marketplace, the users are able to purchase goods and services to improve the quality of their matches and tournaments. Ranging from venues where they can play, equipment needed to play, experts and officials required to organise standard format matches, better training and performance opportunities and other B2B/Consumer products. This helps create a rich and self-sustaining local economy and empowers more employment and value creation in grassroots ecosystems.

The matches are then executed on the user computing platform using industry-grade broadcasting and scoring tools built with cutting edge technology. Thus, the present technology provides a full range of Artificial Intelligence and Machine Learning powered technologies to automate all aspects of match coverage and umpiring. This results in collecting and organising data at a granular level, and thus creating a full range of sports insights and intelligence for every locality, village, town, city, district, state and the country; enabling millions of players with rich career records of their sports engagement. This is further bolstered through a real-time livestreaming solution through which these matches are being broadcast to the general population, creating visibility and access to this immense sports talent. The broadcasting system leverages the sports intelligence abilities, to identify key moments of the match and create automated highlights for each player, team, tournament and match in real time. These highlights are then further processed into system-generated showreels for these constituents, and presents their performance in a highly consumable and shareable format.
With this core loop, the present invention creates multiple opportunities for empowering all constituents of the sports ecosystem and enables them to build viable career opportunities and value creation all across the country.

OPERATION/FUNCTION/USE
The present invention is democratizing sports by giving industry-grade tools to all demographics, in spite of their purchasing power for free. It creates a whole new platform by providing tools limited to a select group of entities in sports production and broadcasting to the masses and enabling everyone to create higher value within their local ecosystems.

This way, the present technology provides the tools and technologies available to the premium Short Head entities to the Long Tail of sports in the country and activating them. This creates more viable economic opportunities, upstream, as a young kid participates in the sports ecosystem, as well as, provide downstream opportunities for retired players to have a second innings as coaches, grounds managers, commentators, etc.

The present technology replaces traditional/conventional methods of executing sports experiences which require high capital investments, as well as, high production capabilities with a set of tools and technologies that radically transforms these use cases into experiences that can be organised and executed by any person with the cheapest of smartphones and other electronic devices.

The present invention provides a series of new key features for the sports ecosystem that enable users to imagine, create, transact, record, archive, broadcast and monetize sports experiences. The present invention has following features:
• a new user computing platform for sports consumers and fans to express their emotions for ongoing matches and support their favourite players and teams
• an artificial intelligence module that creates two-way interactions between all ground participants of matches and tournaments and the online audience consuming those matches
• an artificial intelligence module that provides viable opportunities to local sellers and experts to uplift the quality of individual matches and tournaments being organised all over the country
• a new broadcasting tool that provides the ability to broadcast in real-time and live stream matches on the cloud as well as identify key moments of the match and automatically process them into key highlights and system generated show reels and showcases of individual players teams and matches
• a robust scoring solution that allows for handling complex scoring scenarios for all sports such that deep level data can be captured and recorded to enable Rich intelligence functionalities such as maintaining various milestones and records along with full career stats of players teams and tournaments across the country
• a data verification module that works with the broadcasting and scoring solution to create a cross verifiable player performance repository and can be easily accessed to validate authentic sports performances and enable real life applications
• an AI/ML enabled Sports Intelligence module to process statistics and player performances to identify trends and patterns and create advanced statistical functionalities such as player comparison, ranking, and ratings at a verifiable and common scale all across geographies in India and world.
• an Intelligent Recommendation engine that leverages the sports intelligence available all across the platform to help players and teams find the right training and growth opportunities, as well as identify the right equipment and resources needed to take their sports to the next level.

ADVANTAGES
As stated, the prior existing technology which was mostly manual in nature was difficult to apply at scale as well as difficult to store and maintain. There is hardly any available record for sports performances even for some of the biggest superstars in various sports in India due to this manual and physical method of recording and archiving data.

By making this present artificial intelligence system and method of creating, recording, and archiving data, technology-driven and cloud-enabled, the present technology enables and empowers each individual to create high-quality sports experiences that are easy to access and retrieve, with a high range of deep tech creator tools to automate and simplify the process of creating high-quality sports experiences across all tiers and stratas of the society. This way the sports will be democratised at a global scale, which is unimaginable with prior existing technology.

It should be understood that any of the embodiments of the present artificial intelligence system can be implemented by using hardware or by use of combination of hardware and software. Based on the disclosure and teaching provided herein, a person of skilled in the art will know and appreciate other ways and/or methods to implement embodiments of the present invention using ASICs, specialized processors.

Further, any of the methods described herein may be totally or partially performed using a computer, including one or more processors, which is configured to perform the steps described herein above. Thus, embodiments are directed towards computer system including specific components to perform specific steps of any of the methods described herein above. Additionally, any of the steps of any of the methods can be performed using specific circuits.

For better understanding, aspects of the invention are described in terms of sequences of steps/arrangements that can be performed by, for example, components of a programmable computer system. It will be recognized that various steps could be performed by specialized circuits (e.g., distinct logic gates interconnected to perform a specialized function or application-specific integrated circuits), by list of steps executed by one or more processors, or by a combination of both.

It would be obvious to those skilled in the art that, based on the concepts, ideas and issues described herein, several variations of the proposed method being considered as well as for artificial intelligence system with distinctly different steps and process, are possible without deviating from the scope of this invention.

In conclusion, the present invention provides an improved solution to attempt to provide analyse and predict the future aspect of the human performance. While detailed descriptions of one or more embodiments of the invention have been given above, various alternatives, modifications will be known to the person skilled in the art. Thus, the above description should not be taken as limiting the scope of the invention.

Dated this 7th April 2022

KAUBAN PRIVATE LIMITED
By their agent

Archana Singh and Shreya Chaudhary
(IN/PA-1936 & IN/PA-5145)
Of Singh & Singh Law Firm LLP
AGENTS FOR THE APPLICANT
,CLAIMS:We Claim:
1. The artificial intelligence system (100) for analyzing human performance data from a video of a sports activity, the system comprising:
a processor (101);
a memory (102) coupled to the processor (101), wherein the memory (102) comprising:

- an artificial intelligence module (201) configured to determine type of human performance from video data based on a plurality of predetermined human performances data associated with the type of human performance;
- an event identification module (202) configured to identify event associated with the human performance type based on predetermined event identifier associated with the human performance type;
- an event categorization module (203) configured to categorize the event in a plurality of predetermined categories;
- an event data extraction module (204) configured to extract event data from each category of plurality of predetermined categories;
- a data intelligence module (205) configured to analyse the event data and to make report based on
• a predetermined event analysis and a predetermined format and
• an evolving new event analysis and new format.

2. The artificial intelligence system (100) as claimed in claim 1, wherein the artificial intelligence module (201), the event identification module (202), the event categorization module (203), the event data extraction module (204), and the data intelligence module (205) are

deployed as separate housing and are connected with each other inside the memory (102).

3. The artificial intelligence system (100) as claimed in claim 1, wherein the artificial intelligence module (201) is configured to determine the type of the human performance from the video of the sports activity on the basis of following factors:
• type of an equipment;
• number of the equipment;
• surroundings in which human action is performed;
• weather in which the human action is performed;
• type of human action performed;
• surface on which human action is performed;
• number of players and the colour of their jersey;
• number of umpires or referee;
• position of the referee/umpire;
• time duration for which human action is performed;
• whole time duration of the sports activity as analyzed from the video.

4. The artificial intelligence system (100) as claimed in claim 1, wherein the event identification module (202) is configured to identify event associated with the human performance type from the video of the sports activity on the basis of the following factors:
• colour of jerseys of the players;
• action performed by the players;
• manner of interaction between the players and the equipment used;
• time duration for which the players and the equipment interact with respect to each other;

• weather in which human action is performed;
• surface on which human action is performed;
• angle with which equipment is placed and arranged on the surface by the players;
• angle with which the players interact with the equipment.

5. The artificial intelligence system (100) as claimed in claim 1, wherein the event categorization module (203) is configured to categorize the event associated with human performance type from the video/s in a plurality of pre-determined categories on the basis of the following factors:
• action performed by the players/persons in accordance with the colour of their jersey;
• manner of interaction between the equipment and the player;
• time duration for which players and equipment/s interacted including the whole-time duration of the sports activity;
• weather in which human action is performed;
• surface on which human action is performed;
• angle with which equipment is placed and arranged on the surface;
• angle with which the players interact with the equipment.

6. The artificial intelligence system (100) as claimed in claim 1, wherein the event data extraction module (204) is configured to extract event

data from each category of the plurality of pre-determined categories on the basis of the following factors:
• action performed by the players in relation to the equipment/s used;
• manner of interaction between the equipment/s and the players in accordance with the time-duration of the interaction;
• weather in which human action is performed;
• whole time duration of the sports activity.

7. The artificial intelligence system (100) as claimed in claim 1, wherein the:
data intelligence module (204) is configured to make the report based on the predetermined event analysis and the predetermined format on the basis of the following factors:
• action performed by different players in accordance with the color of their jerseys;
• manner of interaction of the players with the equipment/s;
• weather of the surroundings in which human action is performed;
• surface on which human action is performed;
• human action performed by the players in a particular time duration in accordance with the whole-time duration of the sports activity.

8. The artificial intelligence system (100) as claimed in claim 1, wherein the
data intelligence module (204) is configured to make the report based on the new event analysis and the new format on the basis of the following factors:
• weather in which human action is performed;

• surface on which event/human action performed;
• manner of interaction between the equipment in accordance with the time duration of the interaction and whole-time duration of the sports activity;
• sequence of the players;
• combination among the different players.

9. The artificial intelligence system (100) as claimed in claim 8, wherein the data intelligence module (204) is configured to make the report based on the new event analysis and the new format on the basis of ranking of the team as a whole which is in relation to the event to be analyzed.

10. The artificial intelligence system (100) as claimed in claim 9, wherein the system (100) records the sports activity provided by a scoring tool which will feature a score of the player based on a micro and macro level data of the player.

11. A method for analyzing and predicting human performance data from a video of an sports activity, the method comprising steps of:
- at step 301, determining human performance type from a video data based on a plurality of predetermined data associated with the human performance type, wherein the determination of the human performance type is perform by an artificial intelligence module (201);
- at step 302, identifying of an event associated with the human performance type based on predetermined event identifier associated with the human performance type, wherein the identification of the event associated with the human

performance type is perform by an event identification module (202);
- at step 303, categorizing of the event in a plurality of predetermined categories, wherein the categorization of the event is perform by an event categorization module (203);
- at step 304, extracting of event data from each category of the plurality of predetermined categories, wherein the extraction of the event data is perform by an event data extraction module (204); and
- at step 305, analyzing the event data and to make a report based on
• at step 306, a predetermined event analysis and a predetermined format, and
• at step 307, a new event analysis and a new format,
wherein the analyzation of the event data is performed by a data intelligence module (205).

12. The method of analyzing and predicting human performance from the video of the sports activity as claimed in claim 11, the event of the sports activity is streamed live through an user computing platform 111.

13. The method of analyzing and predicting human performance from the video of the sports activity as claimed in claim 11, the user generates a plurality of content of the sports activity, and data of the generated content are stored in a memory (102).

14. The method of analyzing and predicting human performance from the video of the sports activity as claimed in claim 11, wherein the stored data in the memory (102) interacts and communicates with

the artificial intelligence module 201, the event identification module 202, the event categorization module 203, the event data extraction module 204 and the data intelligence module 205.

15. The method of analyzing and predicting human performance from the video of the sports activity as claimed in claim 11, wherein the artificial intelligence module 201 performs a method of determination of type of the human performance from the video of the sports activity on the basis of the following factors:
• type of an equipment;
• number of the equipment;
• surroundings in which human action is performed;
• weather in which the human action is performed;
• type of human action performed;
• surface on which human action is performed;
• number of players and the colour of their jersey;
• number of umpires or referee;
• position of the referee/umpire;
• time duration for which human action is performed;
• whole time duration of the sports activity as analyzed from the video.

16. The method of analyzing and predicting human performance from the video of the sports activity as claimed in claim 11, wherein the report based on the new event analysis and new format will provide details of the players in accordance with each category from a plurality of pre-determined categories.

17. The method of analyzing and predicting human performance from the video of the sports activity as claimed in claim 11, wherein after

analyzation of the data event by the data intelligence module 205 highlights of the sports activity will be generated.

18. The method of analyzing and predicting human performance from the video of the sports activity as claimed in claim 11, wherein after analyzation of the data event by the data intelligence module 205 showreels of the sports activity is generated.

Dated this 7th April 2022

KAUBAN PRIVATE LIMITED
By their agent

Archana Singh and Shreya Chaudhary
(IN/PA-1936 & IN/PA-5145)
Of Singh & Singh Law Firm LLP
AGENTS FOR THE APPLICANT