Claims:We Claim:
1. A processor-implemented method (400) comprising steps of:
receiving (402), via an input/output interface, a plurality of observations from one or more sources, wherein the one or more sources include Internet of Things (IoTs), enterprise systems and crowd sourced data;
processing (404), via a one or more hardware processors, the plurality of observations to determine a category and a sub-category of the plurality of observations based on a source out of the one or more sources and a context of the plurality of observations;
mapping (406), via the one or more hardware processors, the determined category and the sub-category based on the context of the plurality of the observations to determine a plurality of interventions;
invoking (408), via the one or more hardware processors, the plurality of interventions based on the mapped category and sub-category of the plurality of observations to determine types of impacts;
analyzing (410), via the one or more hardware processors, the determined types of impacts based on a predefined format of ontology;
appropriating (412), via the one or more hardware processors, at least one of the plurality of invoked interventions based on the processed plurality of observations, and the analyzed types of impacts; and
recommending (414), via the one or more hardware processors, the appropriated at least one intervention for the received plurality of observations.
2. The processor-implemented method (400) of claim 1, wherein the category comprises activity, behavior, and bio-vital, and the subcategory comprises no kitchen activity, social isolation, and body temperature.

3. The processor-implemented method (400) of claim 1, wherein the plurality of invoked interventions comprises of a care to a person, a mobility service for a cab, an appointment with a hospital, a service of ambulance, and a grocery purchase.

4. The processor-implemented method (400) of claim 1, wherein the plurality of observations comprises of one or more activities, bio-vital information, traffic congestion, and falls of a person.

5. A system (100) comprising:
an input/output interface (104) to receive a plurality of observations from one or more sources, wherein the one or more sources include Internet of Things (IoTs), enterprise systems and crowd sourced data;
one or more hardware processors (108),
a memory (110) in communication with the one or more hardware processors (108), wherein the one or more hardware processors (108) are configured to execute programmed instructions stored in the memory (110), to:
process the plurality of observations to determine a category and a sub-category of the plurality of observations based on a source out of the one or more sources and a context of the plurality of observations;
map the determined category and the sub-category based on the context of the plurality of the observations to determine a plurality of interventions;
invoke the plurality of interventions based on the mapped category and sub-category of the plurality of observations to determine types of impacts;
analyze the determined types of impacts based on a predefined format of ontology;
appropriate at least one of the plurality of invoked interventions based on the processed plurality of observations, and the analyzed types of impacts; and
recommend the appropriated at least one intervention for the received plurality of observations.

6. A non-transitory computer readable medium storing one or more instructions which when executed by one or more processors on a system, cause the one or more processors to perform method comprising:
receiving, via an input/output interface, a plurality of observations from one or more sources, wherein the one or more sources include Internet of Things (IoTs), enterprise systems and crowd sourced data;
processing, via a one or more hardware processors, the plurality of observations to determine a category and a sub-category of the plurality of observations based on a source out of the one or more sources and a context of the plurality of observations;
mapping, via the one or more hardware processors, the determined category and the sub-category based on the context of the plurality of the observations to determine a plurality of interventions;
invoking, via the one or more hardware processors, the plurality of interventions based on the mapped category and sub-category of the plurality of observations to determine types of impacts;
analyzing, via the one or more hardware processors, the determined types of impacts based on a predefined format of ontology;
appropriating, via the one or more hardware processors, at least one of the plurality of invoked interventions based on the processed plurality of observations, and the analyzed types of impacts; and
recommending, via the one or more hardware processors, the appropriated at least one intervention for the received plurality of observations.

Dated this 27th day of December 2021

Tata Consultancy Services Limited
By their Agent & Attorney

(Adheesh Nargolkar)
of Khaitan & Co
Reg No IN-PA-1086
, Description:FORM 2

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

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:
METHOD AND SYSTEM FOR IMPLEMENTING A FRAMEWORK OF ADAPTIVE COMPLEX EVENT HANDLING AND INTERVENTION ORCHESTRATION

Applicant
Tata Consultancy Services Limited
A company Incorporated in India under the Companies Act, 1956
Having address:
Nirmal Building, 9th floor,
Nariman point, Mumbai 400021,
Maharashtra, India

Preamble to the description:
The following specification particularly describes the invention and the manner in which it is to be performed.

TECHNICAL FIELD
[001] The disclosure herein generally relates to the field of event processing framework and more specifically, to a method and system for implementing a framework of an adaptive complex event handling and intervention orchestration.

BACKGROUND
[002] Complex event processing (CEP) also known as event, stream or event stream processing is the use of technology for querying data before storing it within a database or in some cases, without it ever being stored. Complex event processing is an organizational tool that helps to aggregate a lot of different information and that identifies and analyzes cause-and-effect relationships among events in real time. CEP matches continuously incoming events against a pattern and provides insight into what is happening and allows you to proactively take effective actions.
[003] Personalized interventions as actions post an event and nudging of intervention through appropriate channel in required frequency considering the personas need lot of manual interventions and it is not dynamic. Many of the personalization and complex event processing engine/framework does not have the feature of discovering action for any event and orchestrating those actions through specific channels, on a specific frequency and with specific stakeholders.
[004] In order to process complex events, an auto discovery mechanism of intervention and orchestration does not exist. Contextualization and business enrichment of these event handling is not happening as expected. Multiple types of events, interventions as actions and variety of possible orchestration are not considered yet. Furthermore, interventions as actions lack personalization as the personas represented by person is baselined while discovering interventions. There are no event processing engines which use ontology based information exchange and this challenge the interoperability and adaptability.

SUMMARY
[005] Embodiments of the disclosure present technological improvements as solutions to one or more of the above-mentioned technical problems recognized by the inventors in conventional systems. For example, in one embodiment, a method and system for implementing a framework of an adaptive complex event handling and intervention orchestration is provided.
[006] In one aspect, a processor-implemented method for implementing a framework of an adaptive complex event handling and intervention orchestration is provided. The method includes one or more steps such as receiving a plurality of observations from one or more sources, wherein one or more sources include Internet of Things (IoTs), enterprise systems and crowd sourced data. The plurality of observations is processed to determine category and sub-category of the plurality of observations based on the source and context of the observation. The determined category and sub-category are mapped, wherein the category includes activity, behavior, bio-vital etc., and subcategory includes no kitchen activity, social isolation, and body temperature. A plurality of interventions is invoked based on the mapped category and sub-category of the plurality of observations to determine types of impacts based on a predefined ontology. Furthermore, the determined types of impacts are analyzed based on a predefined format of ontology and appropriating at least one of the plurality of invoked interventions based on processed plurality of observations, and the analyzed types of impacts to recommend the appropriated at least one intervention for the received plurality of observations.
[007] In another aspect, a system for implementing a framework of an adaptive complex event handling and intervention orchestration is provided. The system includes an input/output interface configured to receive a plurality of observations from one or more sources, wherein one or more sources include Internet of Things (IoTs), enterprise systems and crowd sourced data, one or more hardware processors and at least one memory storing a plurality of instructions, wherein the one or more hardware processors are configured to execute the plurality of instructions stored in the at least one memory.
[008] Further, the system is configured to process the plurality of observations to determine category and sub-category of the plurality of observations based on the source and context of the observation, map the determined category and sub-category, wherein the category includes activity, behavior, bio-vital etc., and the subcategory includes no kitchen activity, social isolation, body temperature etc. Further, the system is configured to invoke a plurality of intervention based on the mapped category and sub-category of the plurality of observations to determine types of impacts based on a predefined ontology and analyze the determined types of impacts based on a predefined format of ontology. Furthermore, the system is configured to appropriate at least one of the plurality of invoked interventions based on processed plurality of observations, and the analyzed types of impacts to recommend the appropriated at least one intervention for the received plurality of observations.
[009] In yet another aspect, one or more non-transitory machine-readable information storage mediums are provided comprising one or more instructions, which when executed by one or more hardware processors causes a method for implementing a framework of an adaptive complex event handling and intervention orchestration is provided. The method includes one or more steps such as receiving a plurality of observations from one or more sources, wherein one or more sources include Internet of Things (IoTs), enterprise systems and crowd sourced data. The plurality of observations is processed to determine category and sub-category of the plurality of observations based on the source and context of the observation. The determined category and sub-category are mapped, wherein the category includes activity, behavior, bio-vital etc., and subcategory includes no kitchen activity, social isolation, and body temperature. A plurality of interventions is invoked based on the mapped category and sub-category of the plurality of observations to determine types of impacts based on a predefined ontology. Furthermore, the determined types of impacts are analyzed based on a predefined format of ontology and appropriating at least one of the plurality of invoked interventions based on processed plurality of observations, and the analyzed types of impacts to recommend the appropriated at least one intervention for the received plurality of observations.
[010] It is to be understood that the foregoing general descriptions and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS
[011] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles:
[012] FIG. 1 illustrates an exemplary system for implementing a framework of an adaptive complex event handling and intervention orchestration, according to an embodiment of the present disclosure.
[013] FIG. 2 is block diagram to illustrate the system for implementing a framework of an adaptive complex event handling and intervention orchestration, according to an embodiment of the present disclosure.
[014] FIG. 3 is a functional block diagram to illustrate an adaptive complex event handling, according to an embodiment of the present disclosure.
[015] FIG. 4 is a flow diagram to illustrate a method for implementing a framework of an adaptive complex event handling and intervention orchestration, in accordance with some embodiments of the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS
[016] Exemplary embodiments are described with reference to the accompanying drawings. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the scope of the disclosed embodiments.
[017] The embodiments herein provide a method and system for implementing a framework of an adaptive complex event handling and intervention orchestration is provided. It has been observed that personalized intervention as actions post an event and nudging of intervention through appropriate channel in required frequency considering the personas need lot of manual intervention and it is not dynamic. This framework addresses the problem in handling the events by processing the observation and invoking appropriate rules based on event category. Impact/outcome derived leveraged for discovering the intervention from a catalog based on the type of impact, nudging through appropriate channel on defined frequency to right stakeholders complete the end to end processes.
[018] Herein, the system is configured to listen to data streams including contextualized sensor observation, run the impact analyzer, which will invoke a rule, algorithm or short and long running process based on event category and derive the impact with qualified impact type. Based on the impact type which includes anomaly, behavior change, persistent condition etc., the orchestrator invoke the intervention factory which in turn create appropriate discoverer to discover appropriate intervention from the intervention catalog. The intervention discovery also uses the persona represented by the person who had the instance of that specific event. The discovered intervention from the intervention repository will also carry information for orchestrating and nudging the interventions. This includes channels, respondents, intervention itself, frequency etc.
[019] Referring now to the drawings, and more particularly to FIG. 1 through 4, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments and these embodiments are described in the context of the following exemplary system and/or method.
[020] FIG. 1 illustrates a schematic diagram of a system (100) for implementing a framework of an adaptive complex event handling and intervention orchestration, in accordance with an example embodiment. Although the present disclosure is explained considering that the system (100) is implemented on a server, it may be understood that the system (100) may comprise one or more computing devices (102), such as a laptop computer, a desktop computer, a notebook, a workstation, a cloud-based computing environment and the like. It will be understood that the system (100) may be accessed through one or more input/output interfaces 104-1, 104-2... 104-N, collectively referred to as I/O interface (104). Examples of the I/O interface (104) may include, but are not limited to, a user interface, a portable computer, a personal digital assistant, a handheld device, a smartphone, a tablet computer, a workstation, and the like. The I/O interface (104) are communicatively coupled to the system (100) through a network (106).
[021] In an embodiment, the network (106) may be a wireless or a wired network, or a combination thereof. In an example, the network (106) can be implemented as a computer network, as one of the different types of networks, such as virtual private network (VPN), intranet, local area network (LAN), wide area network (WAN), the internet, and such. The network (106) may either be a dedicated network or a shared network, which represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), and Wireless Application Protocol (WAP), to communicate with each other. Further, the network (106) may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices. The network devices within the network (106) may interact with the system (100) through communication links.
[022] The system (100) supports various connectivity options such as BLUETOOTH®, USB, ZigBee, and other cellular services. The network environment enables connection of various components of the system (100) using any communication link including Internet, WAN, MAN, and so on. In an exemplary embodiment, the system (100) is implemented to operate as a stand-alone device. In another embodiment, the system (100) may be implemented to work as a loosely coupled device to a smart computing environment. Further, the system (100) comprises at least one memory with a plurality of instructions, one or more databases (112), and one or more hardware processors (108) which are communicatively coupled with the at least one memory to execute a plurality of modules (114) therein. The components and functionalities of the system (100) are described further in detail.
[023] The one or more I/O interfaces (104) of the system (100) are configured to receive a plurality of observations/events from one or more sources, wherein one or more sources include Internet of Things (IoTs), enterprise systems and crowd sourced data. The one or more I/O interfaces (104) are also configured to recommend the appropriated at least one intervention/event for the received plurality of observations back to the user. It is to be noted that the input to the system (100) is used to listen to data streams and frame events for an interceptor of the system (100). The interceptor may intercept and call an event processing component. Based on the determined category of event, interventions as impact analyzer is invoked to determine types of impacts based on a predefined ontology.
[024] Referring FIG. 2, illustrates a block diagram (200) of the system (100) for implementing a framework of an adaptive complex event handling and intervention orchestration, in accordance with an example embodiment. Herein, the observation comes from various sources to platform (IoT observations primarily). A listener in the adaptive event processing framework may listen and based on observation type the interceptor may call event processing (Interaction leveraging standard ontology). Based on the type of observation and mapped category and subcategory the framework invokes interventions to analyze the impact. An intervention factory may discover a collection of interventions with nudging details in a standardized format (ontology). Further, an orchestration engine part of the framework may nudge the intervention based on the channel definition in the intervention discovered.
[025] It is to be noted that what to invoke for which observation and event is defined in a standardized format within the ontology. The types of impact analysis can be based on a rule, algorithm, process etc. Once the framework instantiates appropriate intervention, the call back facility will respond once the analysis is over with an impact type ontology and impact ontology. In case, the event processing is for an individual, the persona represented by the person is also picked and passed to impact analysis interventions.
[026] In another embodiment, wherein the system (100) is configured to process the plurality of observations/events to determine category and sub-category of the plurality of observations based on the source and context of the observation. The determined category and sub-category are mapped for finding right set of interventions for the persona.
[027] Further, the system (100) is configured to analyze the determined types of impacts based on a predefined format of ontology. It is to be noted that the intervention also provides the attributes of persona represented by the person for whom the event/observation is processed.
[028] Referring FIG. 3, illustrates a functional block diagram (300) of the system (100) for adaptive complex event handling and intervention orchestration framework, according to one or more embodiment. Herein, a listener in the system (100) may look for events as data and calls (ontology) an interceptor. The interceptor may call (ontology) the impact analyzer to understand the category and subcategory of event and its type. Further, the interceptor may call the event processing (ontology) based on the category, subcategory, the event type, and the impact are derived. The impact type can be anomaly, behavior change, persistent condition etc. Based on the impact type, impact, event, and the persona for which the impact is derived, intervention factory will discover the interventions (ontology). Orchestrator will orchestrate the interventions based on channel and respondent of the interventions.
[029] In one example, wherein a person is monitored by a wearable, which has seen little location change and social interaction. Impact to person of type behavior change and qualified as social isolations. The person is represented by a socially interactive persona in age group 60 to 65. The impact is analyzed by executing an algorithm to deduce his movements outside home and how frequently he has moved out and how long he spent in each location when he moved out. The system may discover set of intervention from intervention catalog based on persona, impact, its type, other contextual information and expected target state which is socially interactive. The possible intervention here are encouraging person to go out and spent time with friends, asking family members to meet the person, suggesting the person to cook special dishes of his/her choice and have dinner with his/her neighbor, suggesting the person to interact with virtual companion etc. Each of these interventions may get orchestrated and monitored.
[030] In another example, wherein encouraging the person to go out for walk, would be through following channels via, a resident app sending notification and reminders informing cares and family member to speak to the person and capturing their feedback informing friends to take the person for a walk.
[031] In another embodiment, the impact analyzer of the system invokes rules based on rule category and subcategory. There could be more than one rule for an event. The system (100) may filter input/data stream to validate rule based on event observation and event observation type defined in the event. Post processing the event, the system generates outcomes, and the orchestrator part of the framework may call intervention discoverer through intervention factory based on the type of impact. Herein, the impact type includes anomaly, behavior, persistent condition etc. Based on the intervention, the orchestrator of the framework may orchestrate the intervention.
[032] Referring FIG. 4, to illustrate a flowchart (400) for implementing a framework of an adaptive complex event handling and intervention orchestration, in accordance with an example embodiment. Initially, at the step (402), receiving, via an input/output interface, a plurality of observations from one or more sources, wherein one or more sources include Internet of Things (IoTs), enterprise systems and crowd sourced data.
[033] At the next step (404), processing, via a one or more hardware processors, the plurality of observations to determine category and sub-category of the plurality of observations based on the source and context of the observation.
[034] At the next step (406), mapping, via the one or more hardware processors, the determined category and sub-category, wherein the category includes activity, behavior, bio-vital etc., and the subcategory includes no kitchen activity, social isolation, body temperature etc.
[035] At the next step (408), invoking, via the one or more hardware processors, a plurality of intervention based on the mapped category and sub-category of the plurality of observations to determine types of impacts based on a predefined ontology.
[036] At the next step (410), analyzing, via the one or more hardware processors, the determined types of impacts based on a predefined format of ontology.
[037] At the next step (412), appropriating, via the one or more hardware processors, at least one of the plurality of invoked interventions based on processed plurality of observations, and the analyzed types of impacts.
[038] At the last step (414), recommending, via the one or more hardware processors, the appropriated at least one intervention for the received plurality of observations.
[039] In yet another example, wherein a person is identified ‘inactive’ and to him to ‘active’ state, the person and his caregivers are suggested to observe and monitor the activity in an activity graph daily. Reminder will be sent to family members, caregiver, and self through mobiles with the source for viewing the activity graph.
[040] The written description describes the subject matter herein to enable any person skilled in the art to make and use the embodiments. The scope of the subject matter embodiments is defined by the claims and may include other modifications that occur to those skilled in the art. Such other modifications are intended to be within the scope of the claims if they have similar elements that do not differ from the literal language of the claims or if they include equivalent elements with insubstantial differences from the literal language of the claims.
[041] The embodiments of present disclosure herein address unresolved problem of personalized intervention as actions post an event and nudging of intervention through appropriate channel in required frequency considering the personas need lot of manual intervention and it is not dynamic. This framework addresses the problem in handling the events by processing the observation and invoking appropriate rules based on event category. Impact/outcome derived leveraged for discovering the intervention from a catalog based on the type of impact, nudging through appropriate channel on defined frequency to right stakeholders complete the end to end processes.
[042] It is to be understood that the scope of the protection is extended to such a program and in addition to a computer-readable means having a message therein; such computer-readable storage means contain program-code means for implementation of one or more steps of the method, when the program runs on a server or mobile device or any suitable programmable device. The hardware device can be any kind of device which can be programmed including e.g., any kind of computer like a server or a personal computer, or the like, or any combination thereof. The device may also include means which could be e.g., hardware means like e.g., an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination of hardware and software means, e.g., an ASIC and an FPGA, or at least one microprocessor and at least one memory with software modules located therein. Thus, the means can include both hardware means, and software means. The method embodiments described herein could be implemented in hardware and software. The device may also include software means. Alternatively, the embodiments may be implemented on different hardware devices, e.g., using a plurality of CPUs.
[043] The embodiments herein can comprise hardware and software elements. The embodiments that are implemented in software include but are not limited to, firmware, resident software, microcode, etc. The functions performed by various modules described herein may be implemented in other modules or combinations of other modules. For the purposes of this description, a computer-usable or computer readable medium can be any apparatus that can comprise, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
[044] The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope of the disclosed embodiments. Also, the words “comprising,” “having,” “containing,” and “including,” and other similar forms are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
[045] Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.