Claims:We claim:
1. An Interactive platform and associated technique to capture live continuous emotional feedback (B) at hosted events by digital as well as digital methods comprises of method to identify, extract Intelligent Emotional Indicators (E) from the Event Objectives (2) or Goals to measure and improve the quality to determine the Quality and Effectiveness of the Communication Stream individually or collectively; the said event objective or event goals or event purpose can be template driven (1b) in addition to on demand method; capturing the feedback continuously physically or by using machine learning module; said technique consists of positive (E1) and negative (E2) emotional indicators via a digital tool wherein recording feedback information against the Intelligent Emotional Indicators can be done on Periodic Recording (B3), On-Demand Request (B4), Participant Pulse (B5); said technique provides a feature to add comments/tag; said technique additionally provides a gamification System (F) to the participant Post the Event to further engage based on one or more KPI (9) generated by the system; said emotional feedback indicators are plotted against the event objective.
2. Interactive platform and associated technique as claimed in claim 1, wherein said physical method involves printed chart containing all the positive (E1) and negative (E2) emotional attributes manually extracted.
3. Interactive platform and associated technique as claimed in claim 1, wherein said digital methods digital method uses AI and Machine Learning that intelligently identify and extract the positive and negative the Intelligent Emotional Indicators from the event objective (2) such as description of the text, voice inputs or data repository (4).
4. Interactive platform and associated technique as claimed in claim 1, wherein said positive and negative emotional indicators would be shown to the participants via a digital tool such as meeting organizing system or an Add-on-Plugin (7) to record their feedback information against the Intelligent Emotional Indicators throughout the event in multiple modes such as periodic recording (B1), On Demand Request (B4), on participant emotion change which is called as the participant’s pulse.
5. Interactive platform and associated technique as claimed in claim 1, wherein at a single event, the participant can record one or more value at multiple times against a single Intelligent Emotional Indicator.
6. Interactive platform and associated technique as claimed in claim 1, wherein multiple values captured over a single Intelligent Emotional Indicator over a period of time are used to define trend data or emotional transformation towards a single emotional Indicator. Platform Key Metrics (PKM) (75) describe the various values and trends derived towards the event goals or objectives from respect to a participant or group of participants IEI, D-IEI, O-IEI feedback or observed data.
7. Interactive platform and associated technique as claimed in claim 1, wherein said tool provides a feature to add comments/tag on the each recorded data point wherein the comments/tag is optional for positive emotional indicators and mandatory or optional for negative emotional indicators.
8. Interactive platform and associated technique as claimed in claim 1, wherein said technique also captures observed meta-attributes, such as capturing the physical engagement or physical emotions of participants via digital camera or keyboard analytics or mouse analytics or its combination at the duration of the user feeds above feedback over Intelligent Emotional Indicator.
9. Interactive platform and associated technique as claimed in claim 1, wherein said technique involves the Machine Learning and high-level solutions using a combination of Artificial Intelligence, Image Processing and Computer Vision techniques are used to extract the user engagement from facial expression (17), hand expression (19), audio expression (15), Keystroke dynamics, typing dynamics are the methods for keyboard analytics and Mouse heatmap are used at mouse analytics.
10. Interactive platform and associated technique as claimed in claim 1, wherein said system or Machine Learning System consumes real-time or cumulative or historical data from one or more of the following trend data, emotional transformation, observed Intelligent Emotional Attributes (O-IEI), Platform Key Metrics (PKM) meta-attributes to generate performance or predictive KPIs that are aligned to the primary Event Objectives and Goals as well as their dependent Objectives and Goals.
11. Interactive platform and associated technique as claimed in claim 1, wherein said technique additionally provides a gamification System to the participant post the event to further engage based on one or more above KPI (74) generated by the system.
12. Interactive platform and associated technique as claimed in claim 1, wherein said technique gamification system personalizes the experience for each participant based on the KPI and offers a virtual interactive system and journey, such as quizzes (32), survey (33), polls (34) to capture the drill down feedback; Risk register (35), navigate, add, get opinion; to discover information/s or resource/s align to the Event or its Dependents Objectives or Goals; validate the recorded IEI, D-IEI and O-IEI; to play, learn and collaborate virtually with the event stakeholder/s, resource/s who are aligned to the Event Goals/Objective Directly or indirectly.
13. Interactive platform and associated technique as claimed in claim 1, wherein said gamification system can run or one or more platform such in Mobile, Computer, AR, VR, MR, device with display device.
14. Interactive platform and associated technique as claimed in claim 1, wherein said recorded trend is plotted as the emotional transformation of a person/group/department etc. at the event rather getting a single value on single attribute.
15. Interactive platform and associated technique as claimed in claim 1, wherein said technique Monitor the Behavioural Analysis (82) of the participant from the derived Intelligent Emotional Indicators participant Meta Data in addition to the participant self-provided feedback data.
16. Interactive platform and associated technique as claimed in claim 1, wherein said technique involves participant from the digital source who joins from a mobile phone/computer through software/apps for the engagements on recording their emotional feedback and physical participant who joined physically on any physical events.
17. Interactive platform and associated technique as claimed in claim 1, wherein the invention is to the have the various models (IEI-AT) of threshold can be configured and read from the Data Repository at the IEI category level or Emotional Indicators (IEI) or Derived Intelligent Emotional Indicators (D-IEI) or Observed IEI Meta-Attributes(O-IEI) or Validate IEI Attributes (V-IEI) or Platform Key Metrics (PKM) (75) or any of its combination; thresholds can also be defined and read from the threshold templates available in the Data Repository (4); the Data Repository is constructed manually fed or externally curated or learned data from the source.

, Description:FIELD OF THE INVENTION:
The present invention relates to an interactive platform and associated method to capture Participant live continuous emotional feedback through Intelligent Emotional Indicators (IEI) at a Digital or Non-Digital Hosted Event on an AI (Artificial Intelligence) enabled digital platform as well in non-digital environment to determine, observe, measure, and improve Event's Communication Quality, Effectiveness, and its Outcomes.
More particularly, the present invention relates to a method to identify, extract Intelligent Emotional Indicators (IEI) from the event’s or its dependent’s objectives or goals for capturing and observing the participant feedback, expression, and emotions continuously, systematically and naturally to measure and improve through the Platform Event Communication Stream (PECS)
Furthermore, the invention provides an interactive and personalised gamification system to validate, improve and further engage participant based on recorded feedback and observed data from one or more participants. The Intelligent Emotional Indicators (IEI) are of two types positive (event’s favourable) and negative (event’s unfavourable) through which the multiple data points are captured from the event digitally and not digitally.
BACKGROUND OF THE INVENTION:
If an event is being held for a purpose, an objective, or to accomplish a goal, it is necessary to validate the performance. At times, certain event goals or purposes or objectives are highly dependent on other, larger objectives or purposes or goals. In those scenarios, the event's failure would result in greater damage or risk. As a result, it is necessary to conduct these Purpose driven meetings in a predictive, monitored, measured, and assisted manner. Communication is at the heart of any hosted event with a purpose or goal or objective. As a result, it is clear what needs to be captured, observed, validated, and assisted. Every organization or institution during the purpose driven hosted event (meeting/training etc.) records feedback for the overall improvement of the system. The methods involve is such events may be physical or digital. Some of the methods to record the emotional feedback have been discussed herein. There are various tool and method to track the communication in the organization such as Polls, Survey and participant emotions watch. But there are challenges on these tools. Polls/Quiz helps to find the engagement level of the participant but won’t help to find why the engagement level getting dropped. The Survey will collect overall feedback always, hence may miss to collect any concerns and feedback occurred during the meeting. Possibly the survey would be provided at the end of the event, hence people interest to finish it quickly bring less reliable data. Further survey kept answering any time increase the chance of reduction in quality on feedback. It is further difficult to trace all the temporal emotions over the meeting through facial and conversational attributes, because the participant presence of mind and other personal emotional factors would influence these attributes adversely sometimes. Hence our system provides most relevant performance attributes to capture the participant temporal emotions changes against the meeting or event objective through the Intelligent Emotional Indicators (IEI) continuously, more naturally and psychologically. The above results from the participant would provide a pattern of the engagement which can be translated how productive the event is, participant engagement, participant understanding, participant concerns, participants deviation, participants commitments etc. The data analysis of the pattern across multiple participants further gives the quantitative and qualitative outcomes of the events and its content. The method is extremely transparent, natural, and user-friendly, and it physically and psychologically accelerates participant attention due to its high level of interaction, focus, engagement, and context-driven nature.
Reference is made to a US patent no. US20160042648A1 by Ravikanth V. Kothuri dated 2003-12-23, titled “Emotion feedback based training and personalization system for aiding user performance in interactive presentations”. The present invention relates to a system and method for implementing an assistive emotional companion for a user, wherein the system is designed for capturing emotional as well as performance feedback of a participant participating in an interactive session either with a system or with a presenter participant and utilizing such feedback to adaptively customize subsequent parts of the interactive session in an iterative manner. The interactive presentation can either be a live person talking and/or presenting in person, or a streaming video in an interactive chat session, and an interactive session can be a video gaming activity, an interactive simulation, an entertainment software, an adaptive education training system, or the like. The physiological responses measured will be a combination of facial expression analysis, and voice expression analysis. Optionally, other signals such as camera based heart rate and/or touch based skin conductance may be included in certain embodiments.
Another reference is made to a US patent no. US10438172B2 by Clari Inc dated 2015-08-06, titled “Automatic ranking and scoring of meetings and its attendees within an organization”. The present invention Systems and methods are provided for analyzing a history of meetings, the attendees, date of occurrence, and other content to determine the value of the meetings and the attendees. The importance of people and the meetings they attend can be derived based on patterns of attendees. In one embodiment, the meta-data of meetings and the attendees can be used to determine value without requiring time-consuming manual steps or manual evaluation of people and their titles. A graph of meetings and its attendees can be generated and used by one or more automated software agents to place value to the content of the meeting, its agenda, and other meeting collateral such as meeting briefs/attachments of meetings. Accordingly, embodiments dramatically reduce the need for human examination of meeting history.
Another reference is made to a US patent no US10546235B2 by Pearson Education Inc. dated 2015-04-08, titled “Relativistic sentiment analyser”. The invention relates to sentiment analyser systems may include feedback analytics servers configured to receive and analyse feedback data from various client devices. Feedback data may be received and analysed to determine feedback context and sentiment scores. In some embodiments, natural language processing neural networks may be used to determine sentiment scores for the feedback data. Feedback data also may be grouped into feedback aggregations based on context, and sentiment scores may be calculated for each feedback aggregation. Sentiment analyzer outputs and corresponding output devices may be determined based on the sentiment scores and feedback contexts.
Another reference is made to a US patent no US7933226B2 by Palo Alto Research Center Inc. dated 2003-10-22, titled “system and method for providing communication channels that each comprise at least one property dynamically changeable during social interactions”. One embodiment of the invention is a computer controlled method for use with a communication system. The method includes a step of receiving a plurality of communications, where each one of the plurality of communications is from one of a plurality of communication sources; includes a step of mixing (that is responsive to a plurality of floor controls) the plurality of communications for a plurality of outputs associated with plurality of communication sources; and includes a step of analyzing, for a plurality of users associated with the plurality of communication sources, one or more conversational characteristics of two or more of the plurality of users. The method also includes a step of automatically adjusting the plurality of floor controls responsive to the step of analyzing. Other embodiments include systems and devices that use the method as well as program products that cause a computer to execute the method.
Another reference is made to a US patent no US20150089399A1 by POLIS TECHNOLOGY Inc. dated 2013-09-26 titled “System and methods for real-time formation of groups and decentralized decision making”. The invention relates to a systems and methods for enabling the formation and analysis of social structures, such as groups, in real-time among a number of participants. Embodiments of the invention are also directed to systems and methods for enabling an understanding of the responses, opinions, or decisions of individual members of a group and how those may change and coalesce into one or more consensus views of a majority of the group. Embodiments of the invention may be applied to better understand the opinions and dynamically changing membership and characteristics of social structures in a variety of settings, including but not limited to educational, business, political, marketing and related environments.
Another reference is made to a US patent no US10524715B2 by Nedim T. SAHIN dated 2018-09-14 titled “Systems, environment and methods for emotional recognition and social interaction coaching”. The systems, environment, and methods, described herein support evaluation of an individual for ASD while in the home environment. Through data collected by a wearable data collection device donned by the individual, eye contact with the caregiver, verbal interaction, and repetitive verbalizations and motions of the head and body may be tracked and objectively quantified during evaluation. Further, the wearable data collection device may support monitoring of brain activity and other physiology which, in turn, may be analysed by the systems and environment described herein during evaluation to recognize patterns that predict evaluation outcome and other clinical features. Various software modules and tools supported by the wearable data collection device provide training, on-going progress tracking and management solutions for individuals living with ASD.
Another reference is made to a US patent no US10956875B2 by Ricoh Co Ltd dated 2018-09-14 titled “Attendance tracking, presentation files, meeting services and agenda extraction for interactive whiteboard appliances”. The present invention relates to Artificial intelligence is introduced into an electronic meeting context to perform various tasks before, during, and/or after electronic meetings. The artificial intelligence may analyse a wide variety of data such as data pertaining to other electronic meetings, data pertaining to organizations and users, and other general information pertaining to any topic. Capability is also provided to create, manage, and enforce meeting rules templates that specify requirements and constraints for various aspects of electronic meetings. Embodiments include improved approaches for translation and transcription using multiple translation/transcription services. Embodiments also include using sensors in conjunction with interactive whiteboard appliances to perform person detection, person identification, attendance tracking, and improved meeting start. Embodiments further include improvements to the presentation of content on interactive whiteboard appliances, providing meeting services for meeting attendees, agenda extraction, and learning to aid in creating new electronic meetings.
Another reference is made to a US patent no US8135711B2 by Adobe Inc dated 2002-02-04 titled “Method and apparatus for sociological data analysis”. The present invention relates a method to enable improved analysis and use of sociological data, the method comprising identifying causal relationships between a plurality of documents, identifying a plurality of characteristics of a communication, including a modality used, actors involved, proximate events of relevance, and enabling a user to query based on available characteristics.
Another reference is made to a US patent no EP3780589A1 by Adobe Inc dated 2002-02-04 titled “Post-conference playback system having higher perceived quality than originally heard in the conference”. Some aspects of the present disclosure involve the recording, processing and playback of audio data corresponding to conferences, such as teleconferences. In some teleconference implementations, the audio experience heard when a recording of the conference is played back may be substantially different from the audio experience of an individual conference participant during the original teleconference. In some implementations, the recorded audio data may include at least some audio data that was not available during the teleconference. In some examples, the spatial characteristics of the played-back audio data may be different from that of the audio heard by participants of the teleconference.
None of the above invention provides an Interactive platform and associated method to capture live continuous emotional feedback on Intelligent Emotional Indicators (IEI), extracted from the event’s or its dependent’s objectives or goals at a Digital or Non-Digital Hosted Event on an AI (Artificial Intelligence) enabled digital platform as well in non-digital environment to determine, observe, measure, and improve Event's Communication Quality, Effectiveness, and its Outcomes. The present invention provides physical as well as digital methods of capturing live emotional feedback continuously. The objective is to capture and observe the participant feedback, expression, and emotions continuously, systematically and naturally to measure and improve through the Platform Event Communication Stream (PECS) individually or collectively. The method is extremely transparent, natural, and user-friendly, and it physically and psychologically accelerates participant attention due to its high level of interaction, focus, engagement, and context-driven nature. In addition, the participant can engage into an interactive and personalized gamification system to discover, validate, play, learn, improve, and collaborate based on the participant recorded feedback and observed data.
OBJECTS OF THE INVENTION:
The principal object of this invention is to provides an interactive platform and associated method to identify, extract Intelligent Emotional Indicators (IEI) from the Event Objectives or Goals for capturing the continuous Participant Emotional Feedback at hosted event to determine Communication Stream (CS) Quality, Effectiveness, and Outcomes individually or collectively; to measure Communication Stream (CS) Quality, Effectiveness, and Outcomes for the Event or its dependencies individually or collectively; to predict Communication Stream (CS) Quality, Effectiveness, and Outcomes to predict the Outcomes for the Event or its dependencies individually or collectively; to provide the recommendation to it individually or collectively.
Another objective of the invention is to provide interactive platform and associated method where the Event can be either Person or multiple persons Hosted or System Hosted or both.
Yet another objective of the invention is to provide the Event Objective or Event Goals or event purpose as template driven in addition to on demand method so that it can reuse across for similar purposes.
Yet another objective of the invention is to provide physical as well as digital methods to capture live continuous Participant emotional Feedback over the Intelligent Emotional Indicators (IEI).
Yet another objective of the invention is to provide physical method wherein printed chart contains all the positive and negative emotional attributes that are manually extracted.
Yet another objective of the invention is to provide digital method wherein the system uses AI and Machine Learning that intelligently identify and extract the positive and negative Intelligent Emotional Indicators (IEI) from the event objective such as description of the Text; from Voice Input which talks about the objective and details about the purpose of the event, or its dependent event and its goals required to achieve from the participant or collectively; a mapped weightage optionally attached to each Intelligent Emotional Indicators from the Data Repository; the Data Repository is constructed manually fed or externally curated or learned data from this source.
Yet another objective of the invention is to present the Intelligent Emotional Indicators to event attendees via a digital tool such as a meeting organizing system or an Add-on-Plugin that could be added on top of any existing Meeting Organizing Software. During and for the event, event participants would be able to use the digital tool to continuously record their emotional feedback aligned to Intelligent Emotional Indicators.
Yet another objective of the invention is to categorize the Intelligent Emotional Indicators (IEI) into one or more IEI Categories under general communication terms; the Data Repository can be used to store and read the category and its mapping; the Data Repository is constructed manually fed or externally curated or learned data from this source.
Yet another objective of the invention is to the have group of the IEI Attributes called as Relationship and Contextual Attribute Set (RCAS), which is a collective term for the relationally and contextually dependent IEI attributes within the same IEI category or across different IEI Categories. It is a collection of attributes are linked together by a "has a" or "is a" relationship; the Data Repository can be used to store the RCAS data set and its mapping; the Data Repository is constructed manually fed or externally curated or learned data from this source.
Yet another objective of the invention is to the have the various models (IEI-AT) of threshold can be configured and read from the Data Repository at the IEI Category level or Emotional Indicators (IEI) or Derived Intelligent Emotional Indicators (D-IEI) or Observed IEI Meta-Attributes(O-IEI) or Validate IEI Attributes(V-IEI) or Platform Key Metrics (PKM) or any of its combination; thresholds can also be defined and read from the Threshold templates available in the Data Repository; the Data Repository is constructed manually fed or externally curated or learned data from this source; The Threshold are of multiple types
1. Threshold at Single Point Range
2. Threshold at Range of Values
3. Threshold at Rate of Change over the Period – Multiple Point Evaluation
4. Threshold at Rule Based – Can be a Combination of above on multiple IEI Categories or IEI or D-IEI or O-IEI or V-IEI or Platform Key Metrics (PKM) or any of its combination.
Yet another objective of the invention is to present the Intelligent Emotional Indicators (IEI) to event attendees via a digital tool such as a meeting organizing system or an Add-on-Plugin that could be added on top of any existing Meeting Organizing Software. During and for the event objective, event participants would be able to use the digital tool to continuously record their emotional feedback aligned to Intelligent Emotional Indicators (IEI).
Yet another objective of the invention is to provide the participant three options for recording feedback information against the Intelligent Emotional Indicators (IEI) displayed on the digital tool such as Periodic Recording wherein the digital system is designed to provide alerts and notifications to participants for them to provide feedback on the Intelligent Emotional Indicators (IEI) on a periodic basis; On Demand Request wherein the Organizer/Host/Admin/Participant can use the digital system to request feedback on one or more of the Intelligent Emotional Indicators (IEI) at any given time On Demand Based; capture at the time of Participant Emotion Cue or Feed Anytime or Participant Pulse wherein the participant can record the feedback at time during the temporal emotions change occurs over the Intelligent Emotional Indicators (IEI) attributes – Participant Self Recording, More Natural way of the recording the feedback. In other way the Participant can provide update to the emotional parameter upon his emotion change towards it.
Yet another objective of the invention, at a single event, the participant can record one or more value at multiple times against a single Intelligent Emotional Indicator.
Yet another objective of the invention is to facilitates multiple values captured over a single Intelligent emotional Indicator over a period of time are used to define trend data or emotional transformation towards a single emotional Indicator. Platform Key Metrics (PKM) describe the various values and trend data derived towards the event goals or objectives from a participant or group of participants Intelligent Emotional Indicators (IEI) or Derived Intelligent Emotional Indicators (D-IEI) or Observed IEI Meta-Attributes(O-IEI) or Validate IEI Attributes(V-IEI) or any of its combinations feedback data or observed data or validated data
Yet another objective of the invention is to provide the tool that provides a feature to add comments/tag on each recorded data point wherein the comments/tag is optional for positive (event’s favourable) and mandatory or optional for negative (event’s unfavourable) Intelligent Emotional Indicators (IEI).
Yet another objective of the invention is to monitor the Participant Feedback and Emotions Continuously during the Participant Feedback towards Intelligent Emotional Indicators (IEI) wherein in addition to the participant self-provided feedback data. The Observed IEI Meta-Attributes (O-IEI), to observe and capture the physical engagement or physical emotions, environmental awareness of participants via
1. Audio Response (15) (microphone, digital camera)
2. Video Response (17) (digital camera)
3. Input Device Response (14a) (keyboard)
4. Other Peripheral Response (14b) (wearables)
5. Environmental Awareness (14c)
Yet in another objective of the invention the Machine Learning and high-level solutions using a combination of Artificial Intelligence, Image Processing and Computer Vision techniques are used to extract and define Observed IEI Meta-Attributes(O-IEI); the user engagement from facial expression such as Facial Landmarks, Sentiment Expressed, Image Quality, Facial Pose, General Attributes), hand expression and audio expression (Speech Style and quality markers such as articulation, intonation, pitch, speed, together speech etc). Keystroke dynamics, typing dynamics are the methods for keyboard analytics. Mouse Heat map are used at mouse analytics.
Yet another objective is to have a system or Machine Learning System consumes real-time or cumulative or historical data from one or more of the Communication Stream (CS) data includes Intelligent Emotional Indicators (IEI) or Derived Intelligent Emotional Indicators (D-IEI) or Observed IEI Meta-Attributes(O-IEI) or Validate IEI Attributes(V-IEI) or Platform Key Metrics (PKM) or any of its combinations to generate various Platform Key Metrics(PKM) and Platform Key Performance Indictors (KPI) that are aligned to the primary Event Objectives and Goals as well as their Dependent Objectives and Goals.
Yet another objective of the invention is to the show or present the dynamic attributes set (D-IEI Attribute from RCAS Group) to the participant based on the recorded or observed or computed values at Emotional Indicators (IEI) or Derived Intelligent Emotional Indicators (D-IEI) or Observed IEI Meta-Attributes (O-IEI) or Validate IEI Attributes (V-IEI) or Platform Key Metrics (PKM) matched against the configured Threshold (IEI-AT).
Yet another objective of the invention is sharing the summary of the Participant’s Feedback or summary of Observed data against the Event Objective or The Platform Key Metrics (PKM) or its KPI or any of its combination along with the Minutes of Meeting (MOM) which can be shared through email or thought URL or through a platform feature to the corresponding Participants or the Event Objective Stake Holders.
A further objective is to additionally provide a gamification System to the participant Post the Event to validate, improve and further engage participant based on one or more above Platform Key Metrics (PKM) and KPI generated by the System.
I. The gamification system personalizes the experience for each participant based on the recorded Emotional Indicators (IEI) or Derived Intelligent Emotional Indicators (D-IEI) or Observed IEI Meta-Attributes(O-IEI) or Validate IEI Attributes(V-IEI) data and its derived KPI to offers a virtual interactive system and journey for validate and collect further more contextual data from the Participants using various engaging gamification methods such Quizzes (32), Survey (33), Polls (34), Risk Drop, Challenge Milestone, Navigate, Challenge Options, take part on challenge(digital or non-digital aligned to the Purpose and Context). The gamification elements add Motivating, Engaging, Relevant, relatable, Challenging, Rewarding, practicing and proficiency gain, create a sticky learning. The outcome and key performance indicator (KPI) derived from gamification are also considered as an outcome under V-IEI Attributes; to discover information/s or resource/s align to the Event’s or its dependent’s Objectives or Goals; validate the recorded IEI, D-IEI and O-IEI; to play, learn and collaborate virtually with the event stakeholder/s, resource/s who are aligned to the Event Goals/Objective Directly or indirectly.
II. The gamification system can run or one or more platform such in Mobile, Computer, AR, VR, MR, Device with Display Device.
SUMMARY OF THE INVENTION:
The Novelty here is to identify, extract Intelligent Emotional Indicators (IEI) (E) from the Event’s or its dependent’s Objectives or Goals for Capturing and Observing the Participant Feedback, Expression and Emotions continuously, systematically and naturally to determine, measure and improve Event's Communication Quality, Effectiveness, and its Outcomes through the Platform Event Communication Stream (PECS) individually or collectively, further provides an interactive and personalised gamification system (F) to validate, improve and further engage participant based on recorded feedback and observed data from one or more participants. The Intelligent Emotional Indicators (IEI) are of two types positive (E1) (event’s favourable) and negative (E2) (event’s unfavourable) through which the multiple data points are captured from the event digitally and not digitally.
The present invention provides solution to find out real purpose, determine, measure, and improve the performance of the hosted event by implementing the advanced methodology. The methods involve in the invention helps to prepare an agenda with clear purpose and objectives for the hosted event with prior planning. As the clear agenda prevent the hosted event from being derailed by tangents or cross conversation. The present invention overcomes the old tradition of obtaining feedback with the help of polls/quiz, survey etc. The invention provides multiple options to capture the feedback such as Capture at the time of Participant emotional changes (Participant Pulse (B5), Periodic (B3) Recording, On Demand Request (B4)) which generates the feedback trend data through IEI and D-IEI (B6) (derived attribute data based on the threshold assigned at the corresponding IEI Attribute), system observed meta data (O-IEI) collected during the event or for the event objective, various Platform Key Metrics (PKM) and various KPI. The two types of Intelligent Emotional Indicators (IEI) are provided such as positive (E1) (event’s favourable) and negative (E2) (event’s unfavourable) through which the multiple data points are captured from the event digitally and not digitally. Further provides an interactive and personalized gamification system to validate, improve and further engage participant aligns to the Event’s or its dependent’s objectives or goals, play to learn and collaborate based on the recorded feedback to one or more participant.
STATEMENT OF THE INVENTION:
The present invention provides an interactive platform and associated technique to capture live continuous emotional feedback at hosted events by digital as well as digital methods comprises of method to identify and extract Intelligent Emotional Indicators (IEI) from the Event’s or its dependent’s Objectives or Goals to determine, observe, measure and improve the Communication Stream (CS) Quality, Effectiveness, and Outcomes individually or collectively; the said Event objective or event goals or event purpose can be template (1b) driven in addition to on demand method; capturing the feedback continuously physically or by using machine learning module; said technique consists of positive (event’s favourable) and negative (event’s unfavourable) emotional attribute wherein emotional transformation of the participants is plotted against the event objective.
BRIEF DESCRIPTION OF DRAWINGS:
Figure 1, represents the consolidated diagram of intelligent emotional attributes extractors objective analysis which constitutes of various Input, processing unit, data storage, interactive module, analytics module. It shows intelligent emotional attributes extractors (A) module, feedback capture feedback analysis (B), behavioural observer over feedback capture (C), non-digital model (D), emotional indicator extractor (E), the System depicts all Input Dependencies required for Intelligent Emotional Attribute Extractor Engine, feedback capture module on the intelligent emotional attributes extractors including the Behavioural Data Collections the system collects the Participant Behavioural Data during the event or for the event objective. non-digital model (positive (event’s favourable) and negative (event’s unfavourable), Gamification post feedback capture (F), the feedback aggregator (8), feedback trend analytics (AI and machine learning), the KPI generating system the feedback aggregator (8), collects the feedback recorded on the basis of periodic feedback, on demand feedback and participants pulse. It collects the feedback recorded on the basis of periodic feedback, on demand feedback and participant's pulse. In addition, system collects the participant behavioural data, Participant Meta Data (monitored metadata). Various KPI and reports (9) are received on the basis of feedback trend analytics. The feedback aggregated are analysed using feedback aggregator (8) analytics and machine learning (G).
Figure 2: the diagram shows output engine (H), Emotional Indicators (E), and participant trend analyser data over emotional indicators (10). The diagram identify, extract intelligent emotional indicators (IEI) from the event dependents objectives or goals using methods of predict ratings from reviews, emotion analysis, keyword extraction, sentiment analysis. The input to the system is textual input or voice input. The engine has IEI attributes which may be favourable (H1) or unfavourable (H2).
Figure 3: Inference Engine (AI) (I), here the figure represents textual data inference, trend data inference, video data inference, and audio data inference. The inference engine (I) is a system component that uses logical rules to deduce new information from the knowledge base. It is a component of a knowledge base – when used in combination with the knowledge base, the inference engine assists the system in gaining logical insights from the vast amount of data available. The inference engine extracts facts from a knowledge base, such as pre trained and custom trained NLP model (12f), and makes inferences which are used to identify the emotions, sentiment, and important keywords. In ML Training Engine (AI), the training data is generated through augmentation and manual human effort. The quality and quantity of the training data is used to determine the accuracy and performance of the machine learning model. Ensemble machine learning models are selected using hyper parameter optimization, which are later used to train the trend data. State of the art models such as encoder-decoder based transformer models are used to train the textual data. The ML models are then validated to ensure the accuracy of model prediction that suits the application.
Figure 4, represents the Behavioural Validator over Feedback Capture (c). The validator enable the system and method to intelligently observe and find the participant behaviour on the meeting behaviour validator monitoring tool at the time of the above intelligent emotional attributes aggregation. The response can be audio (15) video (17), input device response (14a) other peripheral response (14b), environmental awareness (14c). The audio responses are validated by vocal analytics (16) and video response by eye movement (18) and hand coordination (19). The system database consists of IEI feedback data (14f), D-IEI feedback data (14g), O-IEI observed data (14h), V-IEI feedback data (14i).
Figure 5, represents System Overview (AI) (L) i.e. the overview of the ML System. It begins with input database which is then classified at the classification engine (L1). The classified data is processed (L2) to train. If yes it goes for ML training engine else inference engine.
Figure 6, represents data pre-processing Engine (L2) that consists of textual data cleaning (23), voice data reprocessing (25), trend data reprocessing (26), rating data reprocessing (27), video data reprocessing (27a).
Figure 7, represents Data Type Classification Engine (AI) (L1). The data is analysed and then transformed by the preprocessing Engine routine. Textual data, voice data, video data, and participant trend data are the four major types of data sets. Several preprocessing steps such as data cleaning, dealing with missing values, outlier identification, speech to text conversion, tokenization, spell checking are carried out.
Figure 8, represents sample Participant Feedback Trend. The emotional feedback indicators are plotted against X-axis (horizontal) and Y-axis (vertical). In the diagram, positive IEI (marked as green) and negative IEI (marked as red) are shown. The objective is to ensure, task committed by team member was able to complete and made confidence on sprint Goals, enable the team member to discuss and resolve impediments on task given to them. Team member can raise any risk execution status and can pause the meeting on deviation from topic event occur. The entire figure represents the emotional indicators (E).
Figure 9 represents Sample Participant Feedback Collected on a Scrum Meeting. The feedback gathered during a Scrum Meeting yielded the following inferred results: high risk of execution, meeting deviating from topic, participant confidence declining, and he feels more impediments to address. It could be because of the increased risk, or because the meeting is not staying on topic, as mentioned earlier. In the diagram, positive IEI (marked as green) and negative IEI (marked as red) are shown. The objective is to ensure, task committed by team member was able to complete and made confidence on sprint Goals, enable the team member to discuss and resolve impediments on task given to them. Team member can raise any risk execution status and can pause the meeting on deviation from topic event occur. The entire figure represents the emotional indicators (E).
Figure 10 represents the sample participant Feedback Collected at the Event of On boarding to a new Team. The diagram depicts feedback from participants at the on boarding to a New Team event. The objective is to educate the new team member about the project and strategy, to stir up his interest in the concept we're presenting, and to actively engage him in it. Finally, compile data on participant engagement, interest, confidence, and emotional transformation throughout the duration of the event. The positive emotional indicators are exclusively defined and captured here.
Figure 11 represents Gamification - Post Feedback Capture (F). The system shows method to intelligently find the method using Gamification tailored over our intelligent emotional attributes post event activity to find how the objectives are understood and perceived by the audience, providing an interacting to clarify and collaborating (24). The system capture the participants understanding over the event objectives (28), capture the risk and potential unknown (29), intelligent repository where to refer and clarify (30), a Gamification collaborative system to interact with other participant (31).
Figure 12 represents participant Gamification post feedback engagement (AI). The diagram depicts how Gamification is a system that encourages participants to interact with the generated KPI reprocessor (39).
Figure 13 represents derived intelligent emotional indicators (D-IEI) all generated from feedback aggregator (40).
Figure 14 represents sample over IEI (Q) that consists of modules such as intelligent attributes set, derived intelligent emotional attribute, relationship and contextual attribute set.
Figure 15 represents overview of the platform (R) wherein it consists of DB (73), KPI (74), PKM (75), meeting event invitation which may be manually created (77) or template based (78). The meeting objective comprises of objective analysis (80), feedback analysis (81), behavioural analysis (82), and post-analysis (83).
Figure 16 represents various attributes and features of the entire emotional indicators process.
DETAILED DESCRIPTION OF THE INVENTION:
It should be noted that the particular description and embodiments set forth in the specification below are merely exemplary of the wide variety and arrangement of instructions which can be employed with the present invention. The present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. All the features disclosed in this specification may be replaced by similar other or alternative features performing similar or same or equivalent purposes. Thus, unless expressly stated otherwise, they all are within the scope of present invention. Various modifications or substitutions are also possible without departing from the scope or spirit of the present invention. Therefore, it is to be understood that this specification has been described by way of the most preferred embodiments and for the purposes of illustration and not limitation.
Definitions for various terms:
Hosted Event: The Hosted Event is referred to as Event in various places of the document. The type of the hosted event can be majorly classified to status update event, information sharing event, decision making event, problem solving event, team building event, feedback collection event, announcement event. Some of the event which are all aligned to a specific purpose are mentioned below.
• Online and OFFLINE Training / Workshops: These are the sessions where participants learn a skill or complete a course or certification. The trainer can have one on one interaction with the attendee, solve queries via live Q&A, share content via screen and more.
• One or more Speaker session.
• Virtual Summits / Conferences: Best suited for small groups of participants. You can invite multiple speakers, host several tracks and sessions, have breakout sessions in between, conduct live polls & surveys. Speakers and attendees can have two-way communication between them over audio/video in real-time.
• Seminar/Webinars: A seminar is a form of academic instruction, either at an academic institution or offered by a commercial or professional organization. It has the function of bringing together small groups for recurring meetings, focusing each time on some subject, in which everyone present is requested to participate. A webinar is an online event that is hosted by an organization/company and broadcast to a select group of individuals through their computers via the Internet. (A webinar is sometimes also referred to as a “webcast”, “online event” or “web seminar”.).
• Virtual Meetups: In-person gatherings may have their own benefits. But just like social media, online meetups are the best medium to connect people you share common interests with, but in real-time. Privacy of the participants is maintained by allowing access to only the invitees
• Ask me anything: Ever heard of AMA-ask me anything? a session with an expert or guest speaker. It’s a unique way of interviewing where the guest takes questions from the audience in real-time as well as some pre-submitted questions.
• Podcasts: Podcasts are a series of episodes consisting only audio files which can be downloaded by the listener. Typically, they are pre-recorded high-quality audios.
• Virtual Keynotes: It can be a Webcast or a keynote address by the speaker which is broadcasted LIVE over the internet on a source website. Keynotes can help promote your virtual event as it amplifies the message of the event by storytelling and branding of your event.
• Fireside Chats: Hugely popular among the startup community. It is an informal discussion with a guest and the moderator. Its comfortable setting makes it engaging for the audience as it seems like you are listening to your close friend sharing deep insights.
• Awards/Competition/Concerts where the participants considered to provide their feedback or opinion, here the audience can consider as participant.
• Trade Show and Expos: A trade show is an event held to bring together members of a particular industry to display, demonstrate, and discuss their latest products and service, where the participants considered to provide their feedback or opinion, here the audience can consider as participant
• Board Meeting/Shareholder meetings: A Board Meeting is a formal meeting of the board of directors of an organization and any invited guests, held at definite intervals and as needed to review performance, consider policy issues, address major problems, and perform the legal business of the board. Shareholders Meeting means a meeting of the stockholders of the corporation wherein resolution are placed before the shareholders to discuss about the corporate matters and other matters required by the bylaws of the company (such as company’s performance over the relevant statutory period is reviewed and approved, Board of Directors (BOD) of the company are appointed, decisions regarding increase in share capital, major acquisitions, mergers are taken, etc.) and may be conducted at frequent intervals (like annually or six-monthly or quarter or in exceptional circumstances).
• A Product or Service Feedback: Customer feedback is the information, insights, issues, and input shared by your community about their experiences with your company, product, or services. This feedback guides improvements of the customer experience and can empower positive change in any business — even (and especially) when it's negative.
• Product Sale/Promotion/Launch
• Brainstorming/Scrum/Retrospective Meeting: A brainstorming session is a tool for generating as many ideas or solutions as possible to a problem or issue. It is not a tool for determining the best solution to a problem or issue. Before beginning any effective brainstorming session, ground rules must be set. Scrum is an agile framework that teams use to produce products faster by breaking large development projects into smaller pieces that can be completed in short timeframes. Scrum meeting is a catch-all term that can describe different types of meetings held by Scrum teams. A retrospective is a meeting held after a product ships to discuss what happened during the product development and release process, with the goal of improving things in the future based on those learnings and conversations.
Digital Events: Digital events are interactive, staged and experience-oriented events, which are realized in digital space (online) with a wide variety of platforms and tools. Provides larger benefits such as Flexible, Cost-effective, Scalable, Engaging, environmentally friendly, Reliable, Provide comprehensive analytics and reporting data.
Digital Participant: The term digital participant refers to the active involvement on digital platform or digital society through the use of modern information and communication technology (ICT), such as the Internet. This participation includes access to not only the Internet but also various online services and content.
Non-Digital Events: Physical In Person Hosted Meeting.
Physical Participant: Physical and Person In Participation on an event may or may or may not connects with Digital Tools to engage.
Platform Key Metrics (PKM):
Platform Key Metrics refer to most of the system's analytics data and its modules. These are various elements that can be utilized to make various KPIs, which translate to insights that assist people or systems throughout the company, team, or system in making better decisions. Machine Learning and high-level solutions that combine Artificial Intelligence, Image Processing, and Computer Vision techniques use data from one or more of the following data sets: IEI, IEI Variant (IEI-VR), Platform Key Metrics (PKM).
Key Performance Indicators (KPI):
The KPI refers to a measurable measure of performance over time for a specific goal. KPIs provide goals for teams or individuals or a system to strive for, as well as milestones to track progress and insights that help people or system all over the company or team or system make better decisions. Some of the KPIs that the system derives at various stages are single value or trend data (values that are captured or derived over a period of time and saved in a time series dataset) or range data (should have a min or max range) or named data (a named data set) from various Platform Key Metrics (PKM).
Intelligent Emotional Indicators (IEI): Intelligent Emotional Indicators, extracted from the event’s or its dependent’s objectives or event goals. The Intelligent Emotional Indicators are of two type Positive (Event’s favourable (H1) Attributes) and Negative (Event’s unfavourable (H2) Attributes) through which the multiple data points are captured from the event digitally and not digitally. The purpose of having two types is to make the presentation and recording more convenient to the participant. The highest value in the Positive IEI Attribute is the most event’s favourable stage, whereas the highest value in the Negative IEI Attribute is the most event’s unfavourable stage).
The IEI attributes are primarily classified under one or more standard communication objectives called IEI Category
The attribute set are extracted and modelled under network relational attribute dataset (Relationship and Contextual Attribute Set).
IEI Variant (IEI-VR): The IEI Attribute Set has three variants: D-IEI, O-IEI, and V-IEI.
The Relationship and Contextual Attribute Set (RCAS): RCAS is a collective term for the relationally and contextually dependent IEI attributes within the same IEI category or across different IEI Categories. It is a network of attributes connected by a "has a" or "is a" relationship.
IEI Dependencies Attribute Set: The IEI Set, from the other dependent events.
Derived Intelligent Emotional Indicators (D-IEI): D-IEI is a type of IEI that shares all the characteristics and natures of IEI, the derived attribute set that would be optionally displayed or presented to participants in response to their individual/collectively provided feedback on IEI or IEI Variant (IEI-VR) Attribute or Platform Key Metrics (PKM) (75) or its one more combinations compared to the configured IEI Attribute Threshold (IEI-AT) (41). The derived Intelligent Emotional Indicators would be taken from either the IEI Dependencies Attribute Set or Relationship and Contextual Attribute Set (RCAS) or participant On Demand created.
Observed IEI Meta-Attributes (O-IEI): The observed meta-attributes data captured at physical engagement or physical emotions of participants via a digital camera, keyboard analytics, mouse analytics at the time the user feeds above feedback over Intelligent Emotional Indicator. This information (O-IEI data) would be used to further verify the authenticity of the IEI and D-IEI feedback that has been recorded. The Machine Learning and high-level solutions using a combination of Artificial Intelligence, Image Processing and Computer Vision techniques are used to extract the user engagement from facial expression such as Facial Landmarks, Sentiment Expressed, Image Quality, Facial Pose, General Attributes), hand expression and audio expression (Speech Style and quality markers such as articulation, intonation, pitch, speed, together speech etc). Keystroke dynamics, typing dynamics are the methods for keyboard analytics. Mouse Heat map are used at mouse analytics.
Validate IEI Attributes (V-IEI): The attributes derived from the Platform’s gamification system, a Post feedback analysis system. The system personalizes the experience for each participant based on the recorded IEI, D-IEI, O-IEI, V-IEI Attribute data and its derived KPI to offers a virtual interactive system and journey for validate and collect furthermore contextual data from the Participants using various engaging gamification methods such Quizzes (32), Survey, Polls, Risk Drop, Challenge Milestone, Navigate, Challenge Options. The gamification elements add Motivating, Engaging, Relevant, relatable, Challenging, Rewarding, practicing and proficiency gain, create a sticky learning. The outcome and key performance indicator (KPI) derived from gamification are also considered as an outcome under V-IEI Attributes.
IEI Attribute Threshold (IEI-AT) (41): The Threshold for IEI Attributes can be configured at the IEI Category level or IEI Attribute or any IEI Variant (IEI-VR) or Platform Key Metrics (PKM) (75) or any of its combination. The Threshold is to validate the participant individual or collective participants on IEI Categories or IEI or D-IEI or O-IEI or V-IEI or Platform Key Metrics (PKM) or any of its combination to show or present the D-IEI Attribute Set. The Threshold are of multiple types
• Threshold at Single Point Range.
• Threshold at Range of Values.
• Threshold at Rate of Change over the Period – Multiple Point Evaluation.
• Threshold at Rule Based – Can be a Combination of above on multiple IEI Categories or IEI or D-IEI or O-IEI or V-IEI or Platform Key Metrics (PKM) or any of its combination.
Augmented reality (AR) is an enhanced version of the real physical world that is achieved through the use of digital visual elements, sound, or other sensory stimuli delivered via technology.
Virtual Reality (VR) is the use of computer technology to create a simulated environment. Virtual Reality’s most immediately-recognizable component is the head-mounted display (HMD). Human beings are visual creatures, and display technology is often the single biggest difference between immersive Virtual Reality systems and traditional user interfaces.
Mixed reality is the merging of real and virtual worlds to produce new environments and visualizations, where physical and digital objects co-exist and interact in real time. Mixed reality does not exclusively take place in either the physical world or virtual world, but is a hybrid of reality and virtual reality.
AI/Machine Learning: Machine learning and deep learning are subfields of AI Machine learning automates analytical model building. It uses methods from neural networks, statistics, operations research and physics to find hidden insights in data without being explicitly programmed where to look or what to conclude;
Add-on-Plugin (7): In computing, a plug-in (or plugin, add-in, addin, add-on, or addon) is a software component that adds a specific feature to an existing computer program. When a program supports plug-ins, it enables customization.
Communication Stream: Communication is at the heart of any hosted event with a purpose or goal or objective. Hence the Communication Stream is the focused area need to validate, monitor, and assist for the succuss that Event and its dependencies.
Gamification System: Gamification system is any tool or platform used for applying game mechanics to non-game contexts in order to boost engagement and successful end-results. Common use cases include customer loyalty, e-learning, employee engagement, and performance management. The platform gamification Engagement would use the process to collect participant data, validate the recorded data, provide iterative engagement, and improve toward the event's objectives or goals.
Participant Pulse: The participant can record the feedback at time the temporal emotions change occurs over the Intelligent Emotional Indicators (IEI) attributes – Participant Self Recording, More Natural way of the recording the feedback. In other way the Participant can provide update to the emotional parameter upon his emotion change.
The present invention provides an interactive platform and associated method to capture live continuous emotional feedback at the meeting/training to determine the quality and effectiveness of the communication stream.
The present invention provides an interactive platform and associated method to capture Participant live continuous emotional feedback through Intelligent Emotional Indicators (IEI) at a Digital or Non-Digital Hosted Event on a digital platform as well in non-digital environment to determine, observe, measure, and improve Event's Communication Quality, Effectiveness, and its Outcomes. More particularly, the present invention relates to a method to identify, extract Intelligent Emotional Indicators (IEI) from the event’s or its dependent’s objectives or goals for capturing and observing the participant feedback, expression, and emotions continuously, systematically and naturally to measure and improve through the Event’s Communication Stream (ECS)
Furthermore, the invention provides an interactive and personalised gamification system to validate, improve and further engage participant based on recorded feedback and observed data from one or more participants. The Intelligent Emotional Indicators (IEI) are of two types positive (E1) (event’s favourable) and negative (E2) (event’s unfavourable) through which the multiple data points are captured from the event digitally and not digitally.
The present invention provides physical as well as digital methods of capturing live emotional feedback continuously over the Intelligent Emotional Indicators (IEI). The objective is to provide a very transparent, natural, and user-friendly system that physically and psychologically accelerates the participant attention because it is extremely interactive, focused, engaging, and contextually driven.
The Novelty here is to identify, extract Intelligent Emotional Indicators (IEI) from the Event’s or its dependent’s Objectives or Goals for Capturing and Observing the Participant Feedback, Expression and Emotions continuously, Systematically and Naturally to determine, measure and improve Event's Communication Quality, Effectiveness, and its Outcomes through the Event’s Communication Stream (ECS) individually or collectively, further provides an interactive and personalised gamification system to validate, improve and further engage participant based on recorded feedback and observed data from one or more participants. The Intelligent Emotional Indicators (IEI) are of two types positive (event’s favourable) and negative (event’s unfavourable) through which the multiple data points are captured from the event digitally and not digitally. The type of the hosted event can be majorly classified to status update event, information sharing event, decision making event, problem solving event, team building event, feedback collection event, announcement event. Some of the events which are aligned to a specific purpose are mentioned at definition of the various terms. With this method, the system should be able to monitor predict the Event Goals or Objectives or its dependent Goals or Objectives. One such use case is the health of an organization with respective to the various Communication Stream (Event with Stake Holders, Board of Team Meeting, Employee Meeting, Product Meeting, Customer Events) can be determined and improve to monitoring and tailoring the Communication Streams. For the convenience, the certain place in the document the hosted event (aligned with a purpose, objectives, or goals) is referred in the context of a meeting.
The Event can be either Person or multiple persons Hosted or System Hosted or both.
The present invention is based on various protocols and guidelines to enhance the event outcome.
The Invention are categorise into majorly four Operation Blocks for to determine, observe, measure, and improve Event's Communication Quality, Effectiveness, and its Outcomes through the Platform Event Communication Stream (PECS).
I. Objective Analysis/Analytics - Identify and Extract Intelligent Emotional Indicators (IEI).
II. Feedback Analysis/Analytics - Continuous Participant Feedback Capture through IEI and D-IEI.
III. Behavioural Analysis/Analytics - Observe Participant Behavioural Pattern (O-IEI System).
IV. Post Analysis/Analytics or Engagement System- Validate and Improve (V-IEI System).

1. Objective Analysis/Analytics
I. Clarify purpose and objective: The root cause for the negativity towards certain event/meeting is because the real purpose of the event is misunderstood or even inexistent. The present invention with its various embodiments ensures that the purpose and objective are properly demonstrated. Further, it is ensured to establish clear goals for the event/meeting by explaining how these goals align with what the host is trying to achieve. The present invention helps to demonstrate the participant as to why the event/meeting is relevant. If there is clear consensus on the event’s/meeting’s purpose, then it will be much easier to focus on making a decision during the event/meeting.
II. Provide a clear agenda: The event/meeting time must be managed against a clear agenda. The present invention ensures that everyone is on the same page before the event/meeting begins. Most of the times the agenda is vague or redundant with side conversations that have already occurred, so the event/meeting feel like a rubber-stamping of decisions made elsewhere. So, a clear agenda is prepared with clear purpose and objectives for the event/meeting with prior plan. A clear agenda prevents the event/meeting from being derailed by tangents or cross conversation. The present invention provides emotional data capturing in two dimensional plots where y-axis is time and x-axis is the emotion value with respect to each Intelligent Emotional Indicators. The generalized parameters (Intelligent Emotional Indicators) on meeting category make the method easier and smarter to implement.
III. Intelligent Emotional Indicators (IEI), extracted from the event’s or its dependent’s objectives or event goals. The Intelligent Emotional Indicators are of two type Positive (Event’s favourable Attributes) and Negative (Event’s unfavourable Attributes) through which the multiple data points are captured from the event digitally and not digitally. The purpose of having two types is to make the presentation and recording more convenient to the participant. The highest value in the Positive IEI Attribute is the most event’s favourable stage, whereas the highest value in the Negative IEI Attribute is the most event’s unfavourable stage). The Machine Learning and high-level solutions using a combination of Artificial Intelligences are also user to identify, extract and categorize (IEI Category) the IEI Attributes from the Event Objectives/Goals or its dependencies.
IV. The IEI attributes are primarily classified under one or more standard communication objectives called IEI Category.
V. IEI Variant (IEI-VR), The IEI Attribute Set has three variants: D-IEI, O-IEI, and V-IEI would be consumed or generated iteratively by the further Operation Blocks.

2. Feedback Analysis/Analytics
I. Multiple options to capture the emotional feedback: The invention provides multiple for recording feedback information against the Intelligent Emotional Indicators (IEI) displayed on the digital tool.
• Periodic Recording – The Digital System is designed to provide alerts and notifications to participants for them to provide feedback on the Intelligent Emotional Indicators on a periodic basis.
• On Demand Request – The Organizer/Host/Admin/Participant can use the digital system to request feedback on one or more of the Intelligent Emotional Indicators at any given time. – On Demand Based
• Capture at the time of Emotion Cue or Feed Anytime or Participant Pulse – The participant can record the feedback at time the temporal emotions change occurs over the Intelligent Emotional Indicators attributes – Participant Self Recording, More Natural way of the recording the feedback. In other way the Participant can provide update to the emotional parameter upon his emotion change.
II. Derived Intelligent Emotional Indicators (D-IEI), D-IEI is a type of IEI that shares all the characteristics and natures of IEI, the derived attribute set that would be optionally displayed or presented to participants in response to their individual/collectively provided feedback on IEI or IEI Variant (IEI-VR) Attribute or Platform Key Metrics(PKM) or its one more combinations compared to the configured IEI Attribute Threshold (IEI-AT). The derived Intelligent Emotional Indicators would be taken from either the IEI Dependencies Attribute Set or Relationship and Contextual Attribute Set (RCAS) or participant OnDemand created.
III. Various Key Platform Key Metrics (PKM) are generated such as Response Factor (RF), Influencing Factor (IF), Response Variant Factor (RVF), Decline Trend Factor on the IEI Response (DTF) etc determine and measure the event's objectives or goals or its dependencies. The System or Machine Learning and high-level solutions using a combination of Artificial Intelligence used to define Key Platform Key Metrics (PKM).
3. Behavioural Analysis/Analytics
I. Observe the Behavioural Data of the Participant or Behavioural Observer over Feedback Capture (O-IEI): The invention provides Observed IEI Meta-Attributes (O-IEI) in addition to the participant self-provided feedback data. The Observed IEI meta-attributes, to observe and capture the physical engagement or physical emotions, environmental awareness of participants via
I. Audio Response (microphone, digital camera such as)
II. Video Response (digital camera such as)
III. Input Device Response (keyboard, mouse such as)
IV. Other Peripheral Response (wearables such as)
V. Environmental Awareness
against the IEI or IEI Variant (IEI-VR) feedback data, observed data and engagements during event time or for the event objective. The Machine Learning and high-level solutions using a combination of Artificial Intelligence, Image Processing and Computer Vision techniques are used to extract the user engagement from facial expression such as Facial Landmarks, Sentiment Expressed, Image Quality, Facial Pose, General Attributes), hand expression and audio expression (Speech Style and quality markers such as articulation, intonation, pitch, speed, together speech etc). Keystroke dynamics, typing dynamics are the methods for keyboard analytics. Mouse Heat map are used at mouse analytics.
II. The Derived Intelligent Emotional Indicators (D-IEI) set can be optionally displayed or presented to participants in response to their individual/collectively observed data compared to the configured IEI Attribute Threshold (IEI-AT).
III. Various Key Platform Key Metrics (PKM) are generated such as Response Factor (RF), Influencing Factor (IF), Response Variant Factor (RVF), Decline Trend Factor on the IEI Response (DTF), Response Match Indicator (RMI) and etc determine and measure the event's objectives or goals or its dependencies. The System or Machine Learning and high-level solutions using a combination of Artificial Intelligence used to define Key Platform Key Metrics (PKM).
4. Post Analysis/Analytics or Engagement System: Validate IEI Attributes(V-IEI)
I. The platform gamification Engagement would use the process to collect participant data, validate the recorded data, provide iterative engagement, and improve toward the event's objectives or goals. The gamification elements add Motivating, Engaging, Relevant, relatable, Challenging, Rewarding, practicing and proficiency gain, create a sticky learning. Provide a personalizes the experience to each participant based on profile, Platform Key Metrics (PKM) and offers a virtual interactive system and journey, such as
I. Customised Game Play
II. Customised Levels
III. Reward System
IV. Challenge System
V. Quizzes, Survey, Polls to capture the drill down feedback against the Intelligent Emotional Indicators (IEI) or the derive KPI.
VI. Risk register, navigate, add, get opinion.
VII. to discover information/s or resource/s align to the Event’s or its dependent’s Objectives or Goals
VIII. to validate, engage, interact, play, learn and collaborate virtually with the event stakeholder/s, resource/s who are aligned to the Event Goals/Objective Directly or indirectly.
II. Validate IEI Attributes(V-IEI), The attributes derived from the Platform’s Gamification system, a Post feedback analysis system. The system personalizes the experience for each participant based on the recorded IEI, D-IEI, O-IEI, V-IEI Attribute data and its derived KPI to offers a virtual interactive system and journey for validate and collect furthermore contextual data from the Participants using various engaging gamification methods. The outcome and key performance indicator (KPI) derived from gamification are also considered as an outcome under V-IEI Attributes.
III. The Derived Intelligent Emotional Indicators (D-IEI) set can be optionally displayed or presented to participants in response to their individual/collectively V-IEI data compared to the configured IEI Attribute Threshold (IEI-AT).
IV. Various Key Platform Key Metrics (PKM) are generated such as Response Factor (RF), Influencing Factor (IF), Response Variant Factor (RVF), Decline Trend Factor on the IEI Response (DTF), Response Match Indicator (RMI) etc determine and measure the event's objectives or goals or its dependencies. The System or Machine Learning and high-level solutions using a combination of Artificial Intelligence used to define Key Platform Key Metrics (PKM).
There are two types of Intelligent Emotional Indicators (IEI) are used in the present invention to capture, measure, improve the Communication Stream (CS) Quality, Effectiveness, and Outcomes. The one is positive (event’s favourable) and other is negative (event’s unfavourable) through which the multiple data points are captured from the meeting. The data set capture on each Intelligent Emotional Indicator brings more accuracy on the employee feedback and helps to derive the Communication Stream Effectiveness KPI. At a single event, the participant can record one or more value at multiple times against a single Intelligent Emotional Indicator. Multiple values captured over a single Intelligent Emotional Indicator over a period of time are used to define trend data or participant emotional transformation towards a single Intelligent emotional Indicator. Platform Key Metrics (PKM) describe the various values and trend data derived towards the event goals or objectives from a participant or group of participants Intelligent Emotional Indicators (IEI) or Derived Intelligent Emotional Indicators (D-IEI) or Observed IEI Meta-Attributes(O-IEI) or Validate IEI Attributes(V-IEI) or any of its combinations feedback data or observed data or validated data.
The Intelligent Emotional Indicators (IEI) are identified and extracted from the Event Objective, Event Goals, Event Purpose from textual Input or Voice Input(which talks about the Objective and details about the purpose of the event, or its dependent event and its goals required to achieve from the participant or collectively) for Capturing the continuous Participant Emotional Feedback at Hosted Event to measure and improve the Communication Stream (CS) Quality, Effectiveness, and Outcomes individually or collectively, to predict the Outcomes of the Communication Stream (CS) for the Event or its dependencies individually or collectively, to provide the recommendation to it individually or collectively using system or machine learning technology or combination of both. Communication Stream (CS), the Communication Stream is the focal point for validating, monitoring, and assisting with the Event and its dependencies. Any data collected on individual IEI and its related is referred to as a Platform Communication Stream. The data set can be IEI feedback data or corresponding D-IEI feedback data, O-IEI observed data, V-IEI data, or any combination of these.
The Event objective or event goals or event purpose can be template (1b) driven in addition to on demand method so that it can reuse across for similar purposes.
The IEI and IEI Variant (IEI-VR) are primarily classified under one or more standard communication objectives to align to basic psychological communication principles called IEI Category such as.
• Completeness
a. Listening.
b. Understanding.
c. Agreement.
• Participation.
• Care
a. Commitment.
b. Positive Attitudes.
c. Empathetic.
• Identity
a. Courage.
• Protection
a. Openness.
• etc.
The attribute set are extracted and modelled under network relational attribute dataset (RCAS-Relationship and Contextual Attribute Set) which is align to basic communication.
The Intelligent Emotional Indicators (IEI) would be presented to event attendees via a digital tool such as a meeting organizing system or an Add-on-Plug in (7) that could be add on any existing Meeting Organizing Software (6). During and for the event, event participants would be able to use the digital tool to continuously record their emotional feedback aligned to Intelligent Emotional Indicators (IEI). The Intelligent Emotional Indicators (IEI) can also present to the participants using a non-digital method, such as a physical printout. The participant has multiple options for recording feedback information against the Intelligent Emotional Indicators (IEI) displayed on the digital tool as explained in the above section. Participants should be able to see their historical input data on the corresponding Intelligent Emotional Indicators (IEI) on a repetitive or follow-up meeting or depended on events. At a single event, the participant can record one or more value at multiple times against a single Intelligent Emotional Indicator. Multiple values captured over a single Intelligent emotional Indicator over a period of time are used to define trend data or emotional transformation towards a single Intelligent emotional Indicator. The platform would optionally derive, show, or present the Derived Intelligent Emotional Indicators (D-IEI) to the participants as explained in the above section.
The digital tool provides a feature to add comments/tag on each recorded data point wherein the comments/tag is optional for positive (event’s favourable) and mandatory or optional for negative (event’s unfavourable) Intelligent Emotional Indicators (IEI).
The data point comment/tag on the Intelligent Emotional Indicators (IEI) would always help on data analytics to find out root cause and which communication made the deviations.
The System additionally provides a gamification System, as a post feedback analysis system, a personalized experience for each participant based on the KPI offers a virtual interactive system and journey providing to discover the resources and collaborated with the resources which all are aligned to the Event Objectives/Goals/Purpose, or it Depended Objectives/Goals/Purpose. The gamification platform can run or one or more platform such in Mobile App, Computer, AR, VR, MR, Device with Display Device.
Some of the samples for physical meeting and Intelligent Emotional Indicators (IEI) Extraction are given below. (The positive indicators have been shown in bold and negative indicators have been shown in italic).
Example 1:
Objective of a status update meeting: Scrum Status Meeting. The objective is to ensure, task committed by the team member was able to complete and made Confidence on Sprint Goals, enable the team member to discuss and Resolve Impediments on tasks given to them. Team member can raise any Risk on Execution status and can pause the meeting on “Deviation from Topic” event occur.
Example 2:
Objective of Information sharing meeting: Backlog Discussion.
The objective is to ensure the feature/task do have enough Clarity which builds the team member good Confidence to estimation/design/develop. Team member can raise flag against the Time Constraint suggested on the action and can pause the meeting on deviation from topic event occur.
Example 3:
Objective of Information to conduct Risk Assessment Meting: A meeting in which the Hazards Evaluation becomes a positive Event Attribute IEI Attributes (Event favourable Attribute) (H1):
The objective of the meeting is to list down and evaluate all hazards exist at the current Release Milestone, then remove that hazard or minimize the level of its risk by adding control measures, as necessary.
Example 4:
Objective of an Innovation meeting: Brainstorm Session.
The objective is to ensure to have good Engagement between all the participants to bring more Informative and Innovative outcomes in the meeting. Team member can raise any Risk on Execution status.
Few Cases study explains identified and extracted Intelligent Emotional Indicators and its benefits.
Type 1: A Single Meeting, A Clear Objective in single session, Business Road Map Presentation to the Stake Holders
The method first understands the high-level objective which needs to achieve through the meeting, for eg: Confidence, Business Relevancy, Scale Opportunity, Competing Strategy, Risk, Business Defocus etc. These Performance Attributes would be placed Infront of the Stake Holders to record their observation throughout the meeting. It is obvious that the meeting objective is to make a good agreement from the Stakeholders though Interactive and Data Oriented Discussion. It is difficult to trace all the temporal emotions over the meeting through facial and conversational attributes, because the participant presence of mind and other personal emotional factors would influence these attributes adversely sometimes. Hence our system provides most relevant performance attributes to capture the stake holder’s temporal emotions changes against the meeting objective. The above results from the Stake holders would provide a pattern of the Engagement which can be translated how productive the discussion is, participant meeting engagement. The data analysis of the pattern across multiple stakeholders further gives the quality of the meeting presentation and content. our method is very transparent and user friendly and these innovations accelerates the participants attention since it is very focused, and content driven.
Type 2: Series of Meeting, - A clear objective in four session, a series of common meeting to make a team (group of people) familiarised and make confidence on the upcoming release backlogs(work items)
The method first understands the high-level objective which need to achieve through the series of meeting, for eg: Confidence, Clarity, Risk, Time Constraint etc. These Performance attributes would be placed Infront of the Team Members to record their observation throughout the meeting.
First meeting, the agenda is to make the Peoples familiar over the Objective and Work Items, Hence the Attributes rating would reflect with low rating which may obvious.
Second Meeting, the agenda is to engage the Peoples into the topics through some self-discovery. The expectation on the rating is slight rise from the previous and not to go below from the first meeting. If the pattern going down from the first meeting rating can be considered into escalation stage, improvement required and watches Stage.
Third Meeting, the agenda is to transform the peoples more positively aligned and reflects slightly higher rating. Depending on the pattern of the above result it can be considered that the meeting into escalation stage, improvement required and watch Stage.
Fourth Meeting, the agenda is to achieve the set goals and that would be reflected from the Participants feedback, if the results is not matching the expectation that is a serious concern. These are areas which are added as unplanned meeting and more non-productive work, some time we may discuss the things from beginning.
With the present system along with Data Analytics it is easy to predict the outcome of the Next Meeting from the previous iterative meeting and it allows to plan towards effectiveness. The collective metrics over the similar Meeting in Department would help to derive the Department Communication/Execution Effectiveness.
The Intelligent emotional indicators (IEI) for Training event under Positive feedback contains - Informative, New. and Negative feedback contains – Redundant etc. and for Product Demo, the Positive contains - Quality, Richness, Lovable, ... and Negative feedback contains – Damaged, Not Working, Slow, ….
In addition to capturing user-entered data, the system also captures observed meta-attributes, such as capturing the physical engagement or physical emotions, environmental awareness is explained at the above Section (Behavioural Analysis/Analytics)
The Machine Learning and high-level solutions using a combination of Artificial Intelligence, Image Processing and Computer Vision techniques on real-time or cumulative or historical data from one or more of the following IEI, IEI Variant (IEI-VR) to generate performance various Platform Key Metrics (PKM), KPIs which are aligned to the primary Event Objectives and Goals as well as their Dependent Objectives and Goals.
The present invention states that all user's emotional engagement such as recorded IEI from participants and system observed or computed IEI Variant (IEI-VR) and Platform Key Metrics (PKM) and KPI may or may not show lively to the Organizer/Host/Admin/Participant. The system or Organizer would be able to consider/add data along with the Minutes of the Meeting/Event while briefing using email or URL or Platform Feature.
The System additionally provides a gamification System to the participant Post the Event to validate, improve and further engage participant based on one or more above Platform Key Metrics (PKM) and KPI generated by the System. The gamification system personalizes the experience for each participant based on the recorded Emotional Indicators (IEI) or Derived Intelligent Emotional Indicators (D-IEI) or Observed IEI Meta-Attributes(O-IEI) or Validate IEI Attributes(V-IEI) data and its derived KPI to offers a virtual interactive system and journey for validate and collect further more contextual data from the Participants using various engaging gamification methods as explained in the above section “Post Analysis/Analytics or Engagement System: Validate IEI Attributes(V-IEI)”.The gamification elements add Motivating, Engaging, Relevant, relatable, Challenging, Rewarding, practicing and proficiency gain, create a sticky learning. The outcome and key performance indicator (KPI) derived from gamification are also considered as an outcome under V-IEI Attributes; to discover information/s or resource/s align to the Event’s or its dependent’s Objectives or Goals; validate the recorded IEI, D-IEI and O-IEI; to play, learn and collaborate virtually with the event stakeholder/s, resource/s who are aligned to the Event Goals/Objective Directly or indirectly. The gamification system can run or one or more platform such in Mobile, Computer, AR, VR, MR, Device with Display Device.
D-IEI, the derived attribute set that would be displayed or presented to participants in response to their individual/collectively provided feedback on IEI or IEI Variant (IEI-VR) Attribute or Platform Key Metrics (PKM) or its one more combinations compared to the configured IEI Attribute Threshold (IEI-AT). The Threshold is to validate the participant individual or collective participants on IEI Categories or IEI or D-IEI or O-IEI or V-IEI or Platform Key Metrics (PKM) or any of its combination to show or present the D-IEI Attribute Set. The Threshold are of multiple types
• Threshold at Single Point Range.
• Threshold at Range of Values.
• Threshold at Rate of Change over the Period – Multiple Point Evaluation.
• Threshold at Rule Based – Can be a Combination of above on multiple IEI Categories or IEI or D-IEI or O-IEI or V-IEI or Platform Key Metrics (PKM) or any of its combination.
The Derived Intelligent Emotional Indicators (D-IEI) would be taken from either the IEI Dependencies Attribute Set or Relationship and Contextual Attribute Set (RCAS) or participant On Demand created.
Based on the participant privilege to the system, the participant can initiate an On Demand Request on any IEI Attribute, so that other participants who have similar thoughts can also record the feedback. This method helps in the extraction of the most relevant, filtered feedback possible, relevant opinion, which is contextually relevant to the objectives, goals, and dependencies.
An example to demonstrate the IEI, IEI Category, IEI Weightage, RCAS, D-IEI based on the participant feedback at IEI and D-IEI.
For e.g.: On Scrum Call, the objective is to ensure, task committed by the team member was able to complete and made Confidence on Sprint Goals, enable the team member to discuss and Resolve Impediments on tasks given to them. Team member can raise any “Risk on Execution” status and can pause the meeting on “Deviation from Topic” event occur.
The Attributes are majorly two types positive (E1) (event’s favourable) and negative (E2) (event’s unfavourable) towards the Objectives which is marked above Green and Red, respectively.
The Scrum Meeting IEI attribute data set is shown in the table below – Regular Text Attributes are IEI, while Bold Text Attributes are D-IEI. The alignment ratio toward the current Event Objective is indicated by the indicator that appears after the Attribute display name. The low value (<1) indicates that the attribute set filtered from RCAS, whereas the = (1), indicates that it is directly extracted from the Event Goals or Objective. The below table heading are the IEI Category.

Listening Understanding Agreement Commitment Courage Openness
Resolve Impediments (1) Confidence on Sprint Goals (1) Resolve Impediments (1) Confidence on Sprint Goals (1) Reusable (.25) Risk on Execution (1)
Risk on Execution (1) Risk on Execution (1) Risk Appetite (.25) Timeline Concern (.25)
Deviation from Topic (1) Availability Concern (.25)
Quality Concern (.25)

The IEI and D-IEI Thresholds at Range of Values are shown below.
Attribute IEI Category Type Threshold Type Target D-IEI or IEI Category
Resolve Impediments Listening,
Agreement IEI Low – 0.00-0.2 Listening (IEI Category)
Low – 0.8-1.0 Agreement (IEI Category)
Confidence on Sprint Goals Understanding, Commitment IEI Low – 0.00-25 Understanding (IEI Category)
High - 0.80-1.0 Courage (IEI Category)
Risk on Execution Listening, Understanding, Protection
IEI
High - 0.80-1.0 Openness (IEI Category)
Deviation from Topic Listening, Empathetic IEI Any Openness (IEI Category)
Reusable Courage D-IEI
High - 0.70-1.0 Commitment (IEI Category)
Risk Appetite Courage, Care D-IEI
High - 0.70-1.0 Commitment (IEI Category)
Timeline Concern Openness D-IEI
High - 0.70-1.0 Empathetic (IEI Category)
Availability Concern Openness D-IEI
High - 0.70-1.0 Empathetic (IEI Category)
Quality Concern Openness D-IEI
High - 0.70-1.0 Empathetic (IEI Category)
In the above data set, one of the IEI is Confidence on Sprint Goals, which come under the Understanding, Commitment IEI Category. The feedback on this attribute would be monitored based on thresholds, such as recorded low value from the Participants, the RCAS attributes from Understanding IEI Category would be brought in, and the RCAS attributes from Openness IEI Category would be brought in further low on the Understanding IEI Category attribute. For a high values on the Confidence on Sprint Goals, the RCAS attributes from Courage IEI Category would be brought in and so on.
This feedback capturing method aids in gathering information from participants, such as why they have low confidence, whether it is due to a lack of understanding or a lack of commitment or whether it is because of the timeline or something else.
The platform intelligently derives various the Platform Key Metrics (PKM) and KPI across on the above data from the participant feedback at IEI, participant feedback at D-IEI, observed data at O-IEI, validated data and engagement data at V-IEI to provide the various quantitative, qualitative, predictive, informative KPI such as Event efficiency, Event Participation, Event engagement, Feedback and Pulse of the Participant, Time Optimization, Resource Utilization, and other Improvement KPI and so many. The platform further intelligently aggregates the KPI across multiple Communication Events (multiple events similar or depended), to provide the various quantitative, qualitative, predictive, informative KPI to support larger goals, objectives, purposes such as Organization/Department/Team Health, Product or Service Quality and Perception of the Costumers/Community towards it, Training Efficiency, Communication Improvement, Release Prediction, Time Management, Resource Utilization, Support team effectiveness etc. The majority of the system's analytics data, its associated systems are collectively referred to Platform Key Metrics (PKM). The KPI that the system derives at various stages are single value or trend data (values that are captured or derived over a period of time and saved in a timeseries dataset) or range data (should have a min or max range) or named data (a named data set) from various Platform Key Metrics (PKM). The Machine Learning and high-level solutions using a combination of Artificial Intelligence, Image Processing and Computer Vision techniques uses real-time or cumulative or historical data from one or more of the following IEI, IEI Variant (IEI-VR), Platform Key Metrics (PKM) data set to derive the platform Key Metrics (PKM) and KPI.
Various Platform Key Metrics (PKM) are
1. Response Factor (RF): A basic feedback response indicator. The event's favourable and unfavourable feedback would be determined by the positivity IEI and negative IEI, respectively.
2. Observe Factor (OF): A basic Observe factor indicator. The factor determines from the user behaviour (O-IEI) against the IEI feedback during event time or the for the event objective.
3. Influencing Factor (IF): The factor determines how a Participant or group of participants perceives and understands information and communication in relation to the Event objective. The IF factor helps in derive various KPI at Event Engagement, Performance, Productivity and so on.
4. Response Variant Factor (RVF): An indicator that can be used to determine the variance in responses from different participants at the same event. Individual feedback responses may not be identical and may not occur at the same time. The RVF factor helps in examining engagement and productivity in a measurable trend and value.
5. Decline Trend Factor on the IEI Response (DTF): Decline trend Factor (DTA) is used to understand the productivity and emotional transformation on the IEI during the event.
6. Pattern Analysis on the Trend Data (PATD): Analysis the Care, Positive, Risk Analysis
7. Identify Response Shift Analysis in Participant Realization (IRSA): The shift analysis would use to find the Engagement Ratio, Influence Ratio, Performance, Efficacy etc.
8. Response Match Indicator (RMI): The collected feedback would be matched with the D-IEI or O-IEI or V-IEI.
9. Various Other IEI Category Indicator (ICI)
Various Platform KPI are
I. Event Engagement Rate.
• Feedback Rate
• Information Adoption Rate
• Active V/s Inactive Participants Rate
• Information Agreement Rate.
• Employee Turnover Rates.
• Participant/Employee Advocacy Rate.
• Speaker Engagement Rate.
II. Performance and Productivity Rate.
• Event Performance Ratio.
• Information Influencing Rate.
• Say Do Ratio.
• Attendee Satisfaction Rate.
• Information Accuracy Rate.
• Risk Appetite Vs Risk Tolerance Ratio.
• Participant or Team Endurance Rate.
• Customer Satisfaction Ratio.
• Commitment Rate.
• Follow-up Required Statistics.
• Skill Ratio.
III. Care
• Openness Rate.
• Empathetical Rate.
• Challenge Taker (Courage Ratio).
• Positive Attitudes Ratio.
IV. Conflict Resolution
• Conflict Rate.
• Debate Rate.
V. Risk Rate.
VI. Hazard Ratio.
VII. Knowledge Base and Talent base
VIII. Efficacy vs efficiency etc.
The features in the present invention can be explained through the following exemplary embodiments.
In an exemplary embodiments the present invention provides an Interactive platform and associated technique to capture live continuous emotional feedback (B) at hosted events by digital as well as digital methods comprises of method to identify, extract Intelligent Emotional Indicators (E) from the Event Objectives (2) or Goals to measure and improve the quality to determine the Quality and Effectiveness of the Communication Stream individually or collectively; the said event objective or event goals or event purpose can be template (1b) driven in addition to on demand method; capturing the feedback continuously physically or by using machine learning module; said technique consists of positive and negative emotional indicators via a digital tool wherein recording feedback information against the Intelligent Emotional Indicators can be done on Periodic Recording (B1), On-Demand Request (B4), Participant Pulse (B5); said technique provides a feature to add comments/tag; said technique additionally provides a gamification System (F) to the participant Post the Event to further engage based on one or more KPI (9) generated by the system; said emotional feedback indicators are plotted against the event objective.
In another exemplary embodiment, the present invention provides physical method to capture the feedback involving printed chart containing all the positive (E1) (event’s favourable) and negative (E2) (event’s unfavourable) emotional attributes manually extracted.
In another exemplary embodiment, the present invention provides digital methods that uses AI and Machine Learning that intelligently identify and extract the positive (event’s favourable) and negative (event’s unfavourable) the Intelligent Emotional Indicators (IEI) from the event objective (2) such as description of the text, voice inputs or data repository (4).
In another exemplary embodiment, the present invention provides positive (E1) (event’s favourable (H1)) and negative (E2) (event’s unfavourable (H2)) emotional indicators would be shown to the participants via a digital tool such as meeting organizing system or an Add-on-Plugin (7) to record their feedback information against the Intelligent Emotional Indicators (IEI) throughout the event in multiple modes such as periodic recording (B3), On Demand Request (B4), on participant emotion change which is called as the participant’s pulse (B5).
In another exemplary embodiment, at a single event, the participant can record one or more value at multiple times against a single Intelligent Emotional Indicator.
In another exemplary embodiment, the present invention provides multiple values captured over a single Intelligent Emotional Indicator over a period of time are used to define trend data or emotional transformation towards a single emotional Indicator or derive Platform Key Metrics (PKM) (75) describe the various values and trends derived towards the event goals or objectives from respect to a participant or group of participants IEI, D-IEI, O-IEI feedback or observed data.
In another exemplary embodiment, the present invention provides tool to add comments/tag on each recorded data point wherein the comments/tag is optional for positive (E1) (event’s favourable) and mandatory or optional for negative (E2) (event’s unfavourable) Intelligent Emotional Indicators (IEI).
In another exemplary embodiment, the systems also capture derived observed meta-attributes, such as capturing the physical engagement or physical emotions of participants via digital camera or keyboard analytics or mouse analytics or any of its combination at the duration of the user feeds above feedback over Intelligent Emotional Indicator.
In another exemplary embodiment, the present invention involves the Machine Learning and high-level solutions using a combination of Artificial Intelligence, Image Processing and Computer Vision techniques are used to extract the user engagement from facial expression (18a), hand expression (19), audio expression, Keystroke dynamics, and typing dynamics are the methods for keyboard analytics and Mouse heat map are used at mouse analytics.
In another exemplary embodiment, the system or Machine Learning System consumes real-time or cumulative or historical data from one or more of the following trend data, emotional transformation from IEI O-IEI or Platform Key Metrics (PKM) (75) to generate performance or predictive KPIs that are aligned to the primary Event Objectives and Goals as well as their dependent Objectives and Goals.
In another exemplary embodiment, the present technique additionally provides a gamification System to the participant post the event to further engage based on one or more above KPI (9) generated by the system.
In another exemplary embodiment, the present technique provides gamification system (F) that personalizes the experience for each participant based on the KPI and offers a virtual interactive system and journey, such as quizzes (32), survey (33), polls to capture the drill down feedback; Risk register, navigate, add, get opinion; to discover information/s or resource/s align to the Event or its Dependents Objectives or Goals; to play, learn and collaborate virtually with the event stakeholder/s, resource/s who are aligned to the Event Goals/Objective Directly or indirectly.
In another exemplary embodiment, the gamification system (F) can run or one or more platform such in Mobile, Computer, AR, VR, MR, Device with Display Device.
In another exemplary embodiment, the present technique involves participant from the digital source who joins from a mobile phone/computer through software/apps for the engagements on recording their emotional feedback and physical participant who joined physically on any physical events.
ADVANTAGES OF THE INVENTION:
• Iterative collection of the feedback on emotional change helps to find out the pulse of the events/meeting in various duration.
• Able to find early risk through the participant’s emotional feedback.
• Any concerned from participants at the meeting would be recorded under one or more parameter.
• Know upfront any deviation of the Events/Meeting Objectives/Agenda.
• Know the engagement level of all participants.
• Know who are needed and who are not required at the Event/Meeting.
• Find the communication stream which are consistently not meeting objective which may cause (potential delay/risk).
• The Host would be able to act rightly based on the Live/Offline Responses from the Participant.
• The platform intelligently derives various the KPI across on the above data from the Communication Streams to provide the various quantitative, qualitative, predictive, informative KPI such as Event efficiency, Event Participation, Event engagement, Feedback and Pulse of the Participants, Time Optimization, Resource Utilization, Improvement KPI and so many and further it intelligently aggregates the KPI across multiple Communication Streams, to provide the various quantitative, qualitative, predictive, informative KPI to support larger goals, objective, purpose such as Organization/Department/Team Health, Product or Service Quality and Perception of the Costumers/Community towards it, Training Efficiency, Communication Improvement, Release Prediction, Time Management, Resource Utilization, support team effectiveness etc.