Claims:Patent Claims:
1. A computing system (122) for facilitating management of operational tasks in an airport environment (100), the computing system (122) comprising:
one or more hardware processors (202); and
a memory (204) coupled to the one or more hardware processors (202), wherein the memory (204) comprises a plurality of modules (210) in the form of programmable instructions executable by the one or more hardware processors (202), wherein the plurality of modules (210) comprises:
a data obtaining module (212) configured to obtain passenger details associated with a passenger from a plurality of devices;
a data validation module (214) configured to validate the obtained passenger details based on pre-stored passenger details;
a pattern determination module (216) configured to determine one or more patterns associated with the passenger within premises of airport environment (100) by using an Artificial Intelligence (AI) based pattern determination model upon successful validation of the obtained passenger detail, wherein the one or more patterns comprise: one or more threat patterns, one or more buying patterns and one or more passenger movement patterns; and
a task performing module (220) configured to perform one or more operational tasks associated with the airport environment (100) based on the determined one or more patterns, wherein the one or more operational tasks comprise: notifying one or more authorized personnel of the airport environment (100) relating to a security threat, generating and transmitting one or more optimized recommendations for optimizing airport operations and generating and transmitting one or more promotional recommendations to a passenger device (124).

2. The computing system (122) as claimed in claim 1, wherein in obtaining the passenger details associated with the passenger from the plurality of devices, the data obtaining module (212) is configured to:
receive passenger details from the plurality of devices; and
generate an electronic boarding pass associated with the passenger, wherein the generated electronic boarding pass comprises a unique Quick Response (QR) code specific to the passenger.

3. The computing system (122) as claimed in claim 1, wherein in validating the obtained passenger details based on the pre-stored passenger details, the data validation module (214) is configured to:
extract the unique QR code from the electronic boarding pass;
validate the unique QR code based on the prestored passenger details; and
provide access to one or more access points within the airport environment (100) upon successful validation of the unique QR code associated with the passenger.

4. The computing system (122) as claimed in claim 1, wherein in performing the one or more operational tasks associated with the airport environment (100) based on the determined one or more patterns, the task performing module (220) is configured to:
determine whether there exists a security threat within the airport environment (100) based on the determined one or more threat patterns by using an AI based threat determination model;
generate one or more notifications for the determined security threat; and
transmit the generated one or more notifications to one or more airport personnel devices (126) associated with the one or more authorized personnel of the airport environment (100) via one or more secure communication networks (110).

5. The computing system (122) as claimed in claim 1, wherein in determining the one or more patterns associated with the passenger within premises of airport environment (100), the pattern determination module (216) comprises a threat pattern determination module (218) configured to:
receive data representative of multimedia associated with the passenger from a plurality of sensors, wherein the data representative of multimedia comprises: image, audio, video and geolocation of the passenger;
determine identity of the passenger based on the received data representative of multimedia by using one or more image processing techniques;
identify one or more objects in proximity to the passenger based on the received data representative of multimedia by using one or more image processing techniques;
determine one or more activities performed by the passenger based on the received data representative of multimedia by using one or more image processing techniques;
correlate the determined identity, the identified one or more objects in proximity to the passenger and the determined one or more activities to generate an AI based threat pattern determination model; and
determine the one or more threat patterns associated with the passenger by using the generated AI based threat determination model.

6. The computing system (122) as claimed in claim 4, wherein in determining whether there exists the security threat within the airport environment (100) based on the determined one or more threat patterns associated with the passenger using the AI based threat determination model, the task performing module (220) comprises a security threat determination module (222) configured to:
determine type of the one or more threat patterns associated with the passenger by using the AI based threat determination model, wherein the type of the one or more threat patterns comprise: one or more behavior patterns, one or more security violation patterns, one or more boarding violation patterns and one or more objects in proximity pattern to the passenger;
classify the determined type of the one or more threat patterns as at least one of: a security threatening pattern and a non-threatening pattern based on a pre-stored look-up table;
generate a threat score for each of the classified one or more threat patterns using the AI based threat determination model; and
determine whether there exists the security threat based on the generated threat score.

7. The computing system (122) as claimed in claim 1, wherein in performing the one or more operational tasks associated with the airport environment (100) based on the determined one or more patterns, the task performing module (220) is configured to:
determine one or more airport environment parameters based on the data representative of multimedia by using one or more image processing techniques, wherein the one or more airport environment parameters comprise: status of one or more boarding gates, number of security checks in access points of the airport, number of security personnel and position of the security personnel;
generate one or more optimized recommendations for optimizing airport operations based on the determined one or airport parameters and the one or more passenger movement patterns by using AI based operation optimization model, wherein the one or more passenger movement patterns comprise: direction of movement of the passengers, dwell time, stroll preference of passengers, number of passengers at each access point of the airport, store checkout and activities performed by the passengers; and
transmit the generated one or more optimized recommendations to the one or more airport personnel devices (126) associated with the one or more authorized personnel of the airport environment (100) via the one or more secure communication networks (110).

8. The computing system (122) as claimed in claim 1, wherein in performing the one or more operational tasks associated with the airport environment (100) based on the determined one or more patterns, the task performing module (220) is configured to:
obtain data representative of passenger preference from passenger device (124), wherein the data representative of passenger preference comprises: order history, previous search queries, activity, visits to websites, demographic information and locations visited by the passenger;
generate one or more promotional recommendations based on the obtained data representative of passenger preference and the one or more buying patterns associated with the passenger by using AI based promotional recommendation model, wherein the one or more promotional recommendations comprise: advertisements, offers and discounts associated with products and services, and wherein the one or more buying patterns comprise: one or more shopping stores within premises of the airport environment (100) visited by the passenger and one or more items purchased by the passenger from the one or more shopping stores; and
transmit the generated one or more promotional recommendations to the passenger device (124) via the one or more secure communication networks (110).

9. A method for facilitating management of operational tasks in an airport environment (100), the method comprising:
obtaining, by one or more hardware processors (202), passenger details associated with a passenger from a plurality of devices;
validating, by the one or more hardware processors (202), the obtained passenger details based on pre-stored passenger details;
determining, by the one or more hardware processors (202), one or more patterns associated with the passenger within premises of airport environment (100) by using an Artificial Intelligence (AI) based pattern determination model upon successful validation of the obtained passenger detail, wherein the one or more patterns comprise: one or more threat patterns, one or more buying patterns and one or more passenger movement patterns; and
performing, by the one or more hardware processors (202), one or more operational tasks associated with the airport environment (100) based on the determined one or more patterns, wherein the one or more operational tasks comprise: notifying one or more authorized personnel of the airport environment (100) relating to a security threat, generating and transmitting one or more optimized recommendations for optimizing airport operations and generating and transmitting one or more promotional recommendations to a passenger device (124);

10. The method as claimed in claim 9, wherein obtaining the passenger details associated with the passenger from the plurality of devices comprises:
receiving passenger details from the plurality of devices; and
generating an electronic boarding pass associated with the passenger, wherein the generated electronic boarding pass comprises a unique Quick Response (QR) code specific to the passenger.

11. The method as claimed in claim 10, wherein validating the obtained passenger details based on the pre-stored passenger details comprises:
extracting the unique QR code from the electronic boarding pass;
validating the unique QR code based on the prestored passenger details; and
providing access to one or more access points within the airport environment (100) upon successful validation of the unique QR code associated with the passenger.

12. The method as claimed in claim 9, wherein performing the one or more operational tasks associated with the airport environment (100) based on the determined one or more patterns comprises:
determining whether there exist a security threat within the airport environment (100) based on the determined one or more threat patterns by using an AI based threat determination model;
generating one or more notifications for the determined security threat; and
transmitting the generated one or more notifications to one or more airport personnel devices (126) associated with the one or more authorized personnel of the airport environment (100) via one or more secure communication networks (110).

13. The method as claimed in claim 9, wherein determining the one or more threat patterns comprises:
receiving data representative of multimedia associated with the passenger from a plurality of sensors, wherein the data representative of multimedia comprises: image, audio, video and geolocation of the passenger;
determining identity of the passenger based on the received data representative of multimedia by using one or more image processing techniques;
identifying one or more objects in proximity to the passenger based on the received data representative of multimedia by using one or more image processing techniques;
determining one or more activities performed by the passenger based on the received data representative of multimedia by using one or more image processing techniques;
correlating the determined identity, the identified one or more objects in proximity to the passenger and the determined one or more activities to generate an AI based threat pattern determination model; and
determining the one or more threat patterns associated with the passenger by using the generated AI based threat determination model.

14. The method as claimed in claim 12, wherein determining whether there exists the security threat within the airport environment (100) based on the determined one or more threat patterns associated with the passenger using the AI based threat determination model comprises:
determining type of the one or more threat patterns associated with the passenger by using the AI based threat determination model, wherein the type of the one or more threat patterns comprise: one or more behavior patterns, one or more security violation patterns, one or more boarding violation patterns and one or more objects in proximity pattern to the passenger;
classifying the determined type of the one or more threat patterns as at least one of: a security threatening pattern and a non-threatening pattern based on a pre-stored look-up table;
generate a threat score for each of the classified one or more threat patterns using the AI based threat determination model; and
determining whether there exists the security threat based on the generated threat score.

15. The method as claimed in claim 9, wherein performing the one or more operational tasks associated with the airport environment (100) based on the determined one or more patterns comprises:
determining one or more airport environment parameters based on the data representative of multimedia by using one or more image processing techniques, wherein the one or more airport environment parameters comprise: status of one or more boarding gates, number of security checks in access points of the airport, number of security personnel and position of the security personnel;
generating one or more optimized recommendations for optimizing airport operations based on the determined one or airport parameters and the one or more passenger movement patterns by using AI based operation optimization model, wherein the one or more passenger movement patterns comprise: direction of movement of the passengers, dwell time, stroll preference of passengers, number of passengers at each access point of the airport, store checkout and activities performed by the passengers; and
transmitting the generated one or more optimized recommendations to the one or more airport personnel devices (126) associated with the one or more authorized personnel of the airport environment (100) via the one or more secure communication networks (110).

16. The method as claimed in claim 9, wherein performing the one or more operational tasks associated with the airport environment (100) based on the determined one or more patterns comprises:
obtaining data representative of passenger preference from passenger device (124), wherein the data representative of passenger preference comprises: order history, previous search queries, activity, visits to websites, demographic information and locations visited by the passenger;
generating one or more promotional recommendations based on the obtained data representative of passenger preference and the one or more buying patterns associated with the passenger by using AI based promotional recommendation model, wherein the one or more promotional recommendations comprise: advertisements, offers and discounts associated with products and services, and wherein the one or more buying patterns comprise: one or more shopping stores within premises of the airport environment (100) visited by the passenger and one or more items purchased by the passenger from the one or more shopping stores; and
transmitting the generated one or more promotional recommendations to the passenger device (124) via the one or more secure communication networks (110).

Dated this 12th day of October 2021

Vidya Bhaskar Singh Nandiyal
Patent Agent (IN/PA-2912)
Agent for the Applicant
, Description:FIELD OF INVENTION
[0001] Embodiments of the present disclosure relate to an airport management system, and more particularly to a system and method for facilitating management of one or more operational tasks associated with an airport environment.
BACKGROUND
[0002] In aviation industry, authorized personnel of airports manage various operational tasks, such as detecting security threats and managing flow of passengers, for providing a seamless travel experience to the passengers. Conventionally, security system at the airports includes metal detectors, imaging test, chemical test and the like for detecting security threats within the airports, such as smuggling drugs and theft. However, accuracy of the security systems to detect the security threats depends on alertness and judgement of the authorized personnel. For example, authorized personnel performing the image test have to review images of bags being scanned for detecting suspect bags based on the image test. Since, the authorized personnel are susceptive to fatigue and distractions, the conventional security system that depends on human judgment fails to accurately detect the security threats within the airport. Also, the authorized personnel are required to manually monitor activities of the passengers to detect suspicious activities. Thus, there are high chances of missing out suspicious activities of the passengers. Further, the authorized personnel manage inflow and the outflow of the passengers. Since, the management of flow of the passengers also depends on human judgement, it is very difficult to efficiently and timely manage the flow of passengers which results in airport congestion.
[0003] Hence, there is a need for a system and method for facilitating management of operational tasks in an airport environment in order to address the aforementioned issues.
SUMMARY
[0004] This summary is provided to introduce a selection of concepts, in a simple manner, which is further described in the detailed description of the disclosure. This summary is neither intended to identify key or essential inventive concepts of the subject matter nor to determine the scope of the disclosure.
[0005] In accordance with an embodiment of the present disclosure, a computing system for facilitating management of operational tasks in an airport environment is disclosed. The computing system includes one or more hardware processors and a memory coupled to the one or more hardware processors. The memory includes a plurality of modules in the form of programmable instructions executable by the one or more hardware processors. The plurality of modules include a data obtaining module configured to obtain passenger details associated with a passenger from a plurality of devices. The plurality of modules also include a data validation module configured to validate the obtained passenger details based on pre-stored passenger details. The plurality of modules further include a pattern determination module configured to determine one or more patterns associated with the passenger within premises of airport environment by using an Artificial Intelligence (AI) based pattern determination model upon successful validation of the obtained passenger detail. The one or more patterns include one or more threat patterns, one or more buying patterns and one or more passenger movement patterns. Furthermore, the plurality of modules include a task performing module configured to perform one or more operational tasks associated with the airport environment based on the determined one or more patterns. The one or more operational tasks include notifying one or more authorized personnel of the airport environment (100) relating to a security threat, generating and transmitting one or more optimized recommendations for optimizing airport operations and generating and transmitting one or more promotional recommendations to a passenger device.
[0006] In accordance with another embodiment of the present disclosure, a method for facilitating management of operational tasks in an airport environment is disclosed. The method includes obtaining passenger details associated with a passenger from a plurality of devices. The method also includes validating the obtained passenger details based on pre-stored passenger details. The method further includes determining one or more patterns associated with the passenger within premises of airport environment by using an Artificial Intelligence (AI) based pattern determination model upon successful validation of the obtained passenger detail. The one or more patterns include one or more threat patterns, one or more buying patterns and one or more passenger movement patterns. Further, the method includes performing one or more operational tasks associated with the airport environment based on the determined one or more patterns. The one or more operational tasks include notifying one or more authorized personnel of the airport environment (100) relating to a security threat, generating and transmitting one or more optimized recommendations for optimizing airport operations and generating and transmitting one or more promotional recommendations to a passenger device.
[0007] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF DRAWINGS
[0008] The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
[0009] FIG. 1 is a block diagram illustrating an exemplary airport environment capable of facilitating management of operational tasks, in accordance with an embodiment of the present disclosure;
[0010] FIG. 2 is a block diagram illustrating an exemplary computing system, such as those shown in FIG.1, capable of facilitating management of operational tasks in the airport environment, in accordance with an embodiment of the present disclosure;
[0011] FIG. 3 is a process flow chart illustrating an exemplary method for facilitating management of operational tasks in the airport environment, in accordance with an embodiment of the present disclosure; and
[0012] FIG. 4 is a system architecture of an Open API Banking Platform (OBP) for facilitating management of operational tasks in the airport environment, in accordance with an embodiment of the present disclosure.
[0013] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.

DETAILED DESCRIPTION OF THE DISCLOSURE
[0014] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure. It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.
[0015] In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
[0016] The terms "comprise", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, additional sub-modules. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
[0018] A computer system (standalone, client or server computer system) configured by an application may constitute a “module” (or “subsystem”) that is configured and operated to perform certain operations. In one embodiment, the “module” or “subsystem” may be implemented mechanically or electronically, so a module include dedicated circuitry or logic that is permanently configured (within a special-purpose processor) to perform certain operations. In another embodiment, a “module” or “subsystem” may also comprise programmable logic or circuitry (as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations.
[0019] Accordingly, the term “module” or “subsystem” should be understood to encompass a tangible entity, be that an entity that is physically constructed permanently configured (hardwired) or temporarily configured (programmed) to operate in a certain manner and/or to perform certain operations described herein.
[0020] Although the explanation is limited to airport environment, it should be understood by the person skilled in the art that the computing system is applied in other public places, such as shopping malls, hotels, museums, and the like. Further, the explanation is limited to a single passenger. However, it should be understood by the person skilled in the art that the computing system is applied if there is more than one passenger.
[0021] Referring now to the drawings, and more particularly to FIGs. 1 through FIG. 5, 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.
[0022] FIG. 1 is a block diagram illustrating an exemplary airport environment 100 capable of facilitating management of operational tasks, in accordance with an embodiment of the present disclosure. According to FIG. 1, the computing environment includes one or more access points including an entry area 102, a security hold area 104, a boarding area 106 and a ramp area 108. The entry area 102 may be communicatively coupled with the security hold area 104, the security hold area 104 may be communicatively coupled with the boarding area 106 and the boarding area 106 may be communicatively coupled with the ramp area 108 via one or more secure communication networks 110. In an exemplary embodiment of the present disclosure, the one or more secure communication networks 110 may be internet, or any wireless communication networks. Further, the airport environment 100 includes a plurality of devices, a plurality of sensors and a plurality of display units. In an embodiment of the present disclosure, the plurality of devices may be optical sensors, such as two-dimensional (2D) barcode scanners. In an exemplary embodiment of the present disclosure, the plurality of sensors may be Internet of Things (IOT) sensors, such as high definition (HD) cameras and video cameras. The plurality of sensors capture data representative of multimedia associated with passenger. The plurality of sensors provide a holistic view of the airport environment 100 to one or more authorized personnel environment 100. In an embodiment of the present disclosure, the plurality of sensors are on wired kiosks. The one or more authorized personnel may be operational, ground staff, security agency and the like. In an exemplary embodiment of the present disclosure, the data representative of multimedia includes image, audio, video, geolocation of the passenger and the like. Furthermore, the plurality of display units are LCD (Liquid crystal display) screens, touch screen displays, Light Emitting Diode (LED) displays, Organic Light-Emitting Diode (OLED) displays and the like. In an embodiment of the present disclosure, the plurality of devices include one or more entry area devices and one or more boarding area devices. Further, the plurality of sensors include one or more entry area sensors 112, one or more security hold area sensors 114 and one or more boarding area sensors 116. In an embodiment of the present disclosure, the ramp area 108 may include wireless sensors to capture the data representative of multimedia associated with the passenger. The plurality of display units include one or more entry area display units 118 and one or more security hold area display units 120.
[0023] In an embodiment of the present disclosure, the one or more entry area devices, one or more entry area sensors 112 and one or more entry area display units 118 are associated with the entry area 102, as shown in Fig. 1. Further, the one or more security hold area sensors 114 and the one or more security hold area display units 120 are associated with the security hold area 104. The one or more boarding area sensors 116 and the one or more boarding area devices are associated with the boarding area 106. In an embodiment of the present disclosure, the entry area 102, the security hold area 104, the boarding area 106 and the ramp area 108 are communicatively coupled to a computing system 122 via the one or more secure communication networks 110. The computing system 122 may be a central server, such as cloud server or a remote server. Furthermore, the airport environment 100 includes a passenger device 124 associated with the passenger communicatively coupled to the computing system 122 via the one or more secure communication networks 110. In an exemplary embodiment of the present disclosure, the passenger device 124 may be a tablet computer, smartphone or the like. The passenger may use the passenger device 124 to receive boarding pass in electronic format. Further, the passenger may also use the passenger device 124 to receive one or more promotional recommendations. The one or more promotional recommendations include advertisements, offers and discounts associated with products and services and the like. Furthermore, the airport environment 100 includes one or more airport personnel devices 126 associated with the one or more authorized personnel of the airport environment (100) communicatively coupled to the computing system 122 via the one or more secure communication networks 110. In an exemplary embodiment of the present disclosure, the one or more airport personnel devices 126 may be a laptop computer, desktop computer, tablet computer, smartphone, wearable device and the like. Furthermore, the one or more airport personnel devices 126 includes a web browser and a mobile application to access the computing system 122 via the one or more secure communication networks 110. In an embodiment of the present disclosure, the one or more authorized personnel may use a web application through the web browser to access the computing system 122. Further, the one or more authorized personnel may use the one or more airport personnel devices 126 to receive notifications associated with security threats within the airport environment 100. The one or more authorized personnel may also use the one or more airport personnel devices 126 to receive one or more optimized recommendations for optimizing airport operations. The computing system 122 includes a plurality of modules. Details on the plurality of modules have been elaborated in subsequent paragraphs of the present description with reference to FIG. 2.
[0024] Further, the passenger device 124 generates a security code for the passenger. The security code of the passenger is scanned by using one or more entry area devices. In an exemplary embodiment of the present disclosure, the security code may be a two-dimensional (2D) barcode or QR code. Further, the one or more entry area sensors 112 verifies physical appearance of the passenger by using one or more image processing techniques. In an embodiment of the present disclosure, the one or more entry area display units 118 display the scanned security code comprising passenger details for validation by the one or more authorized personnel. In an exemplary embodiment of the present disclosure, the passenger details include name of the passenger, arrival time of the flight, departure time of the flight, passenger flight destination, date of travel, flight number, contact details of the passenger and the like. The one or more authorized personnel (CISF) allows or rejects the passenger based on the displayed passenger details. If the passenger details matches, the passenger is validated successfully and is allowed to enter the next stage of the boarding process. In case, the passenger details do not match, the one or more authorized personnel inform airport management and necessary actions are taken. In an embodiment of the present disclosure, the passenger details may also be validated by the computing system 122.
[0025] Furthermore, the one or more security hold area sensors 114 captures the data representative of multimedia corresponding to the security hold area 104. The data representative of multimedia captured by the one or more security hold area sensors 114 is sent to the computing system 122. Further, the passenger details are again validated by showing the security code on the one or more security hold area devices. The one or authorized personnel may update the passenger details into the computing system 122 and respective boarding gates are assigned to the passenger upon successful validation of the passenger details. Further, when the passenger does not reach the boarding area 106, the one or more authorized personnel may access the computing system 122 to know the access points crossed by the passenger. Furthermore, the one or more boarding area devices again scans the security code associated with the passenger and passenger details such as the requirements related to luggage, gate number and the like are validated by the one or more authorized personnel. In an embodiment of the present disclosure, the passenger details may also be validated by the computing system 122. On successful validation, the passenger is allowed to enter the next stage of the boarding process.
[0026] In an embodiment of the present invention, the plurality of devices may also include a handheld device 128 associated with the ramp area 108. In an exemplary embodiment of the present disclosure, the handheld device 128 may be a 2D barcode scanner. The security code associated with the passenger may be shown by the passenger device 124 to the handheld device 128. Furthermore, this security code is scanned by the handheld device 128. The security code includes passenger details. All the passenger details are validated by the one or more authorized personnel, computing system 122 or a combination thereof. If the validation is successful, the passenger may finally board a flight and go to the respective destination. If the validation is not successful, the passenger is not allowed to board the flight. The handheld device 128 may include data associated with passengers such as boarded passenger details, infant details, total number of passengers and remaining passengers yet to report at the ramp area 108 with seat number.
[0027] In an embodiment of the present disclosure, the computing system 122 obtains the passenger details associated with the passenger from the plurality of devices. Further, the computing system 122 validates the obtained passenger details based on pre-stored passenger details. The computing system 122 determines one or more patterns associated with the passenger within premises of the airport environment 100 by using an Artificial Intelligence (AI) based pattern determination model upon successful validation of the obtained passenger detail. Furthermore, the computing system 122 performs one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns.
[0028] FIG. 2 is a block diagram illustrating an exemplary computing system 122, such as those shown in FIG.1, capable of facilitating management of operational tasks in the airport environment 100. The computing system 122 comprises one or more hardware processors 202, a memory 204 and a storage unit 206. The one or more hardware processors 202, the memory 204 and the storage unit 206 are communicatively coupled through a system bus 208 or any similar mechanism. The memory 204 comprises the plurality of modules 210 in the form of programmable instructions executable by the one or more hardware processors 202. Further, the plurality of modules 210 includes a data obtaining module 212, a data validation module 214, a pattern determination module 216, a threat pattern determination module 218, a task performing module 220 and a security threat determination module 222.
[0029] The one or more hardware processors 202, as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor unit, microcontroller, complex instruction set computing microprocessor unit, reduced instruction set computing microprocessor unit, very long instruction word microprocessor unit, explicitly parallel instruction computing microprocessor unit, graphics processing unit, digital signal processing unit, or any other type of processing circuit. The one or more hardware processors 202 may also include embedded controllers, such as generic or programmable logic devices or arrays, application specific integrated circuits, single-chip computers, and the like.
[0030] The memory 204 may be non-transitory volatile memory and non-volatile memory. The memory 204 may be coupled for communication with the one or more hardware processors 202, such as being a computer-readable storage medium. The one or more hardware processors 202 may execute machine-readable instructions and/or source code stored in the memory 204. A variety of machine-readable instructions may be stored in and accessed from the memory 204. The memory 204 may include any suitable elements for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like. In the present embodiment, the memory 204 includes the plurality of modules 210 stored in the form of machine-readable instructions on any of the above-mentioned storage media and may be in communication with and executed by the one or more hardware processors 202.
[0031] The storage unit 206 may be a cloud storage or a local file directory within a remote server. The storage unit 206 may store the pre-stored passenger details, security code associated with the passenger, airport and flight related information, airport Virtual Reality (VR) content and the pre-stored look-up table.
[0032] The data obtaining module 212 is configured to obtain the passenger details associated with the passenger from the plurality of devices. In an embodiment of the present disclosure, before obtaining the passenger details, the passenger device 124 generates the security code for the passenger. The security code includes passenger details. In an embodiment of the present disclosure, the security code is transmitted from the passenger device 124 to the computing system 122 by using the mobile application via the one or more secure communication networks 110. Further, the plurality of devices scans the security code displayed on the passenger device 124. In an embodiment of the present disclosure, the passenger details are displayed on the plurality of display units upon scanning the security code for validation of the passenger details by the one or more authorized personnel. When the passenger details are successfully validated by the one or more authorized personnel, the passenger is provided access to the one or more access points of the airport. The passenger details and the security code are stored in the storage unit 206. The passenger details may also be validated by the computing system 122.
[0033] In an embodiment of the present disclosure, in obtaining the passenger details associated with the passenger from the plurality of devices, the data obtaining module 212 receive passenger details from the plurality of devices. Further, the data obtaining module 212 generates an electronic boarding pass associated with the passenger. The generated electronic boarding pass includes a unique Quick Response (QR) code specific to the passenger. The data validation module 214 validates the obtained passenger details based on the pre-stored passenger details. In validating the obtained passenger details based on the pre-stored passenger details, the data validation module 214 extracts the unique QR code from the electronic boarding pass. Furthermore, the data validation module 214 validates the unique QR code based on the prestored passenger details. The data validation module 214 provides access to the one or more access points within the airport environment (100) upon successful validation of the unique QR code associated with the passenger.
[0034] The pattern determination module 216 is configured to determine one or more patterns associated with the passenger within premises of the airport environment 100 by using an Artificial Intelligence (AI) based pattern determination model upon successful validation of the obtained passenger detail. In an exemplary embodiment of the present disclosure, the one or more patterns include one or more threat patterns, one or more buying patterns and one or more passenger movement patterns. In an exemplary embodiment of the present disclosure, there are various types of one or more threat patterns, such as one or more behaviour patterns, one or more security violation patterns, one or more boarding violation patterns and one or more objects in proximity pattern to the passenger. The one or more behaviour patterns may be determined based on walking style, activities performed by the passenger, facial expressions, unusual mental or physical symptoms exhibited by the passenger and the like. In an exemplary embodiment of the present disclosure, the one or more behaviour patterns are aggressive, deceptive, threatening, anxious, passive-aggressive and the like. Further, the one or more security violation patterns may be determined based on the movement of passenger in a restricted area, tampering of security devices, such as wireless sensors, threatening life and property and the like. Furthermore, the one or more boarding violation patterns may be determined based on entrance of the passenger in wrong gate, not attaching baggage tags and the like. In an embodiment of the present disclosure, the one or more objects in proximity to the passenger may also include objects with the passenger. The one or more objects may be a bag, a stick, a knife and the like. The one or more objects in proximity pattern may be determined based on type of the one or more objects, distance of the one or more objects from the passenger, activities performed by the passenger using the one or more objects and the like. Further, the one or more passenger movement patterns include direction of movement of the passengers, dwell time, stroll preference of passengers, number of passengers at each access point of the airport, store checkout and activities performed by the passengers. The one or more buying patterns include one or more shopping stores within premises of the airport environment 100 visited by the passenger and one or more items purchased by the passenger from the one or more shopping stores.
[0035] In determining the one or more patterns associated with the passenger within premises of the airport environment (100), the pattern determination module 216 includes the threat pattern determination module 218 configured to receive the data representative of multimedia associated with the passenger from the plurality of sensors. Further, the threat pattern determination module 218 determines identity of the passenger based on the received data representative of multimedia by using one or more image processing techniques. The threat pattern determination module 218 identifies one or more objects in proximity to the passenger based on the received data representative of multimedia by using one or more image processing techniques. Furthermore, the threat pattern determination module 218 determines one or more activities performed by the passenger based on the received data representative of multimedia by using one or more image processing techniques. The one or more activities may be walking, using the passenger device 124, speaking with other passengers and the like. The threat pattern determination module 218 correlates the determined identity, the identified one or more objects in proximity to the passenger and the determined one or more activities to generate an AI based threat pattern determination model. The threat pattern determination module 218 determines the one or more threat patterns associated with the passenger by using the generated AI based threat determination model.
[0036] The task performing module 220 is configured to perform one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns. The one or more operational tasks include notifying one or more authorized personnel of the airport environment (100) relating a security threat, generating and transmitting one or more optimized recommendations for optimizing airport operations and generating and transmitting one or more promotional recommendations to the passenger device 124. In an embodiment of the present disclosure, the operation task may also include managing digital content to be displayed on the plurality of display units within the airport environment 100. In performing the one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns, the task performing module 220 determines whether there exists a security threat within the airport environment 100 based on the determined one or more threat patterns by using an AI based threat determination model. In an exemplary embodiment of the present disclosure, the security threats may include theft, smuggling drugs, terrorist activity, explosive devices, chemical attack and the like. Further, the task performing module 220 generates one or more notifications for the determined security threat. The task performing module 220 transmits the generated one or more notifications to the one or more airport personnel devices 126 associated with the one or more authorized personnel of the airport environment (100) via the one or more secure communication networks 110.
[0037] Further, in determining whether there exists the security threat within the airport environment 100 based on the determined one or more threat patterns associated with the passenger using the AI based threat determination model, the task performing module 220 includes the security threat determination module 222 configured to determine type of the one or more threat patterns associated with the passenger by using the AI based threat determination model. Furthermore, the security threat determination module 222 classifies the determined type of the one or more threat patterns as security threatening pattern, a non-threatening pattern, or a combination thereof based on a pre-stored look-up table. Further, the security threat determination module 222 generates a threat score for each of the classified one or more threat patterns using the AI based threat determination model. The security threat determination module 222 determines whether there exists the security threat based on the generated threat score.
[0038] Furthermore, in performing the one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns, the task performing module 220 determine one or more airport environment parameters based on the data representative of multimedia by using one or more image processing techniques. In an exemplary embodiment of the present disclosure, the one or more airport environment parameters include status of one or more boarding gates, number of security checks in access points of the airport, number of security personnel, position of the security personnel and the like. Further, the task performing module 220 generates one or more optimized recommendations for optimizing airport operations based on the determined one or airport parameters and the one or more passenger movement patterns by using AI based operation optimization model. For example, the one or more optimized recommendations may be generated to open more boarding gates for managing passenger traffic congestion. The one or more optimized recommendations may also be generated to increase number of security check in the access points to enhance security. Furthermore, the task performing module 220 transmits the generated one or more optimized recommendations to the one or more airport personnel devices 126 associated with the one or more authorized personnel of the airport environment 100 via the one or more secure communication networks 110.
[0039] Furthermore, in performing the one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns, the task performing module 220 obtains data representative of passenger preference from the passenger device 124. The data representative of passenger preference includes order history, previous search queries, activity, visits to websites, demographic information, locations visited by the passenger and the like. Further, the task performing module 220 generates one or more promotional recommendations based on the obtained data representative of passenger preference and the one or more buying patterns associated with the passenger by using AI based promotional recommendation model. In an exemplary embodiment of the present disclosure, the one or more promotional recommendations include advertisements, offers, discounts associated with products and services and the like. Furthermore, the task performing module 220 transmit the generated one or more promotional recommendations to the passenger device 124 via the one or more secure communication networks 110.
[0040] In an embodiment of the present disclosure, the passenger may use the passenger device 124 to access the computing system 122 for viewing the airport and flight related information on the mobile application, such as flight take-off time and flight delay. The passenger may select a layout from predefined set of layouts to view the airport and flight related information. In an embodiment of the present disclosure, the selected layout displays airline, flight number, destination, schedule time, expected time, gate number, current flight status and the like in the passenger device 124. Further, the passenger may also use the passenger device 124 to view airport VR content on the smart application. The airport VR content includes virtual layout of the airport, virtual directions to locate a specific store or eatery within the airport environment (100), virtual assistance to find fastest route to the boarding area 106 at which the passenger’s flight is scheduled, virtual video feeds, virtual video advertisements and the like. In an exemplary embodiment of the present disclosure, the passenger may use the passenger device 124 to access third party applications, such as music applications and gaming applications via the mobile application.
[0041] In an embodiment of the present disclosure, the passenger may use the passenger device 124 to access one or more style tools and applications associated with the airport services. The one or more style tools and applications allows the passenger to access free services, such as internet access through local Wi-Fi, Touchless Common User Self-Service(CUSS) kiosks for taking the boarding passes, self-bag drop units for check-in baggage and the like. In an embodiment of the present disclosure, the passenger may connect the passenger device 124 to Airport free wi-fi to access internet from the Airport. When the passenger face any issue while connecting the passenger device 124 to Airport free wi-fi, the passenger may approach dedicated internet access zone and utilize desktop to connect internet. When the passenger may perform check-in on his/her own, the passenger may use the CUSS machine in the Airport.
[0042] In an embodiment of the present disclosure, the computing system 122 allows the passenger to use the QR code for security validation by means of interworking with existing airport systems to correlate passenger and airline booking information to allow the passenger to have a passenger device 124 for performing full security and aircraft boarding procedure. Further, the computing system 122 also allows for REST API for external 3rd party access, data filtering, data bucketing for the API to carry them, regulatory framework compliance and data dash boarding. Further, web services REST API fetches details about single passenger, single flight, passenger load details at each touch point and the like. In an embodiment of the present disclosure, data filtering may be performed per flight, per passenger and the like. All departed flight and passenger details may be moved to historic database within one hour of flight departure. Further, a plurality of dashboards are available to access data including airport operations dashboard, COO dashboard, CEO dashboard and the like.
[0043] In operation, the passenger shows the security code associated with him/her to the plurality of devices. The plurality of devices scan the security code displayed on the passenger device 124 to obtain passenger details. Further, the data obtaining module 212 obtains the passenger details associated with the passenger from the plurality of devices. The data validation module 214 validates the obtained passenger details based on the pre-stored passenger details. The data validation module 214 provides access to the one or more access points of the airport to the passenger upon successful validation of the obtained passenger details. Furthermore, the pattern determination module 216 determines one or more patterns associated with the passenger within premises of the airport environment 100 by using the AI based pattern determination model upon successful validation of the obtained passenger detail. The one or more patterns include one or more threat patterns, one or more buying patterns and one or more passenger movement patterns. Further, the task performing module 220 performs the one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns. The one or more operational tasks include notifying one or more authorized personnel of the airport environment (100) relating to the security threat, generating and transmitting one or more optimized recommendations for optimizing airport operations and generating and transmitting one or more promotional recommendations to the passenger device 124.
[0044] FIG. 3 is a process flow chart illustrating an exemplary method 300 for facilitating management of operational tasks in the airport environment 100, in accordance with an embodiment of the present disclosure. At step 302, passenger details associated with a passenger is obtained from a plurality of devices. In an exemplary embodiment of the present disclosure, the passenger details include name of the passenger, arrival time of the flight, departure time of the flight, passenger flight destination, date of travel, flight number, contact details of the passenger and the like. In an embodiment of the present disclosure, the plurality of devices may be optical sensors, such as two-dimensional (2D) barcode scanners. In an embodiment of the present disclosure, before obtaining the passenger details, a security code is generated by a passenger device 124 for the passenger. The passenger device 124 may be a tablet computer, smartphone or the like. The security code includes passenger details. Further, the plurality of devices scans the security code displayed on the passenger device 124. In an embodiment of the present disclosure, the passenger details are displayed on a plurality of display units upon scanning the security code for validation of the passenger details by one or more authorized personnel. The plurality of display units are LCD (Liquid crystal display) screens, touch screen displays, Light Emitting Diode (LED) displays, Organic Light-Emitting Diode (OLED) displays and the like. In an embodiment of the present disclosure, the one or more authorized personnel may be operational, ground staff, security agency and the like. When the passenger details are successfully validated by the one or more authorized personnel, the passenger is provided access to the one or more access points of the airport. The passenger details and the security code are stored in a storage unit 206.
[0045] In an embodiment of the present disclosure, in obtaining passenger details associated with the passenger from the plurality of devices, the method 300 includes receiving passenger details from the plurality of devices. Further, the method 300 includes generating an electronic boarding pass associated with the passenger. The generated electronic boarding pass includes a unique Quick Response (QR) code specific to the passenger.
[0046] At step 304, the obtained passenger details are validated based on pre-stored passenger details. In validating the obtained passenger details based on the pre-stored passenger details, the method 300 includes extracting the unique QR code from the electronic boarding pass. Furthermore, the method 300 includes validating the unique QR code based on the prestored passenger details. The method 300 includes providing access to the one or more access points within the airport environment (100) upon successful validation of the unique QR code associated with the passenger.
[0047] At step 306, one or more patterns associated with the passenger within premises of airport environment 100 are determined by using an Artificial Intelligence (AI) based pattern determination model upon successful validation of the obtained passenger detail. In an exemplary embodiment of the present disclosure, the one or more patterns include one or more threat patterns, one or more buying patterns and one or more passenger movement patterns. In an exemplary embodiment of the present disclosure, there are various types of one or more threat patterns, such as one or more behaviour patterns, one or more security violation patterns, one or more boarding violation patterns and one or more objects in proximity pattern to the passenger. The one or more behaviour patterns may be determined based on walking style, activities performed by the passenger, facial expressions, unusual mental or physical symptoms exhibited by the passenger and the like. In an exemplary embodiment of the present disclosure, the one or more behaviour patterns are aggressive, deceptive, threatening, anxious, passive-aggressive and the like. Further, the one or more security violation patterns may be determined based on the movement of passenger in a restricted area, tampering of security devices, such as wireless sensors, threatening life and property and the like. Furthermore, the one or more boarding violation patterns may be determined based on entrance of the passenger in wrong gate, not attaching baggage tags and the like. In an embodiment of the present disclosure, the one or more objects in proximity to the passenger may also include objects with the passenger. The one or more objects may be a bag, a stick, a knife and the like. The one or more objects in proximity pattern may be determined based on type of the one or more objects, distance of the one or more objects from the passenger, activities performed by the passenger using the one or more objects and the like. Further, the one or more passenger movement patterns include direction of movement of the passengers, dwell time, stroll preference of passengers, number of passengers at each access point of the airport, store checkout and activities performed by the passengers. The one or more buying patterns include one or more shopping stores within premises of the airport environment 100 visited by the passenger and one or more items purchased by the passenger from the one or more shopping stores.
[0048] In determining the one or more threat patterns associated with the passenger within premises of the airport environment (100), the method 300 includes receiving the data representative of multimedia associated with the passenger from the plurality of sensors. Further, the method 300 includes determining identity of the passenger based on the received data representative of multimedia by using one or more image processing techniques. The method 300 includes identifying one or more objects in proximity to the passenger based on the received data representative of multimedia by using one or more image processing techniques. Furthermore, the method 300 includes determining one or more activities performed by the passenger based on the received data representative of multimedia by using one or more image processing techniques. The one or more activities may be walking, using passenger device 124, speaking with other passengers and the like. The method 300 includes correlating the determined identity, the identified one or more objects in proximity to the passenger and the determined one or more activities to generate an AI based threat pattern determination model. The method 300 includes determining the one or more threat patterns associated with the passenger by using the generated AI based threat determination model.
[0049] At step 308, one or more operational tasks associated with the airport environment 100 are performed based on the determined one or more patterns. The one or more operational tasks include notifying one or more authorized personnel of the airport environment (100) about a security threat, generating and transmitting one or more optimized recommendations for optimizing airport operations and generating and transmitting one or more promotional recommendations to the passenger device 124. In performing the one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns, the method 300 includes determining whether there exists a security threat within the airport environment 100 based on the determined one or more threat patterns by using an AI based threat determination model. In an exemplary embodiment of the present disclosure, the security threats may include theft, smuggling drugs, terrorist activity, explosive devices, chemical attack and the like. Further, the method 300 includes generating one or more notifications for the determined security threat. The method 300 includes transmitting the generated one or more notifications to the one or more airport personnel devices 126 associated with the one or more authorized personnel of the airport environment (100) via the one or more secure communication networks 110.
[0050] Further, in determining whether there exists the security threat within the airport environment 100 based on the determined one or more threat patterns associated with the passenger using the AI based threat determination model, the method 300 includes determining type of the one or more threat patterns associated with the passenger by using the AI based threat determination model. Furthermore, the method 300 includes classifying the determined type of one or more threat patterns as security threatening pattern, a non-threatening pattern or a combination thereof based on a pre-stored look-up table. Further, the method includes generating a threat score for each of the classified one or more threat patterns using the AI based threat determination model. The method 300 includes determining whether there exists the security threat based on the generated threat score.
[0051] Furthermore, in performing the one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns, the method 300 includes determining one or more airport environment parameters based on the data representative of multimedia by using one or more image processing techniques. In an exemplary embodiment of the present disclosure, the one or more airport environment parameters include status of one or more boarding gates, number of security checks in access points of the airport, number of security personnel, position of the security personnel and the like. Further, the method 300 includes generating one or more optimized recommendations for optimizing airport operations based on the determined one or airport parameters and the one or more passenger movement patterns by using AI based operation optimization model. For example, the one or more optimized recommendations may be generated to open more boarding gates for managing passenger traffic congestion. The one or more optimized recommendations may also be generated to increase number of security check in the access points to enhance security. Furthermore, the method 300 includes transmitting the generated one or more optimized recommendations to the one or more airport personnel devices 126 associated with the one or more authorized personnel of the airport environment (100) via the one or more secure communication networks 110.
[0052] Furthermore, in performing the one or more operational tasks associated with the airport environment 100 based on the determined one or more patterns, the method 300 includes obtaining data representative of passenger preference from the passenger device 124. The data representative of passenger preference includes order history, previous search queries, activity, visits to websites, demographic information, locations visited by the passenger and the like. Further, the method 300 includes generating one or more promotional recommendations based on the obtained data representative of passenger preference and the one or more buying patterns associated with the passenger by using AI based promotional recommendation model. In an exemplary embodiment of the present disclosure, the one or more promotional recommendations include advertisements, offers, discounts associated with products and services and the like. Furthermore, the method 300 includes transmitting the generated one or more promotional recommendations to the passenger device 124 via the one or more secure communication networks 110.
[0053] In an embodiment of the present disclosure, the passenger may use the passenger device 124 for viewing the airport and flight related information on the mobile application, such as flight take-off time and flight delay. The passenger may select a layout from predefined set of layouts to view the airport and flight related information. Further, the passenger may also use the passenger device 124 to view airport VR content on the smart application. The airport VR content includes virtual layout of the airport, virtual directions to locate a specific store or eatery within the airport environment (100), virtual assistance to find fastest route to the boarding area 106 at which the passenger’s flight is scheduled, virtual video feeds, virtual video advertisements and the like. In an exemplary embodiment of the present disclosure, the passenger may use the passenger device 124 to access third party applications, such as music applications and gaming applications via the mobile application.
[0054] The method 300 may be implemented in any suitable hardware, software, firmware, or combination thereof.
[0055] FIG. 4 is a system architecture of an Open API (Application Programming Interface) Airport Platform (OAP) 400 for facilitating management of operational tasks in the airport environment 100, in accordance with an embodiment of the present disclosure. In an embodiment of the present disclosure, AIaaS (Artificial Intelligent as a Service) is provided for the one or more authorized personnel operating withing the airport that deploy the OAP. The OAP includes a core application layer 402 for user data and the API. The OAP includes a plurality of techniques 404 including presentation view abstraction 406, north bound API implementation, a plurality of core platform modules 408, API, data abstraction and user authentication using OAuth 410. The OAP 400 includes an enterprise firewall 412 which provides network security. The OPI 400 includes third party developer application 414 and a private application store for airport 416. Further, a premise IT infrastructure is provided for the airport. The OAP 400 is an AIaaS for airports that deploys the OAP. In an embodiment of the present disclosure, a BK2BK interface module allows for the one or more authorized personnel to share data in a seamless manner. Furthermore, a data analytics overlay for the BK2BK data flow and insights associated with it are provided. In an embodiment of the present disclosure, prediction data points based on analytics engine are provided for the airport users.
[0056] Thus, various embodiments of the present computing system 122 provide a solution to facilitate management of operational tasks in the airport environment 100. Since, the computing system 122 automatically perform the one or more operational tasks without assistance of the one or more authorized personnel, the one or more operational tasks may be performed accurately. Thus, the computing system 122 may enhance security within premises of the airport environment 100, efficiently manage flow of passengers and provide precise one or more promotional recommendation to the passenger. Further, the computing system 122 eliminates the passenger from carrying any printed paper and having to show the printed paper at multiple security and check-in touch points. The computing system 122 also validates the passenger details based on the pre-stored passenger details, such that access to the one or more access points of the airport may be provided to the passenger upon successful validation of the passenger details.
[0057] 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.
[0058] 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.
[0059] The medium can be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) or a propagation medium. Examples of a computer-readable medium include a semiconductor or solid-state memory, magnetic tape, a removable computer diskette, a random-access memory (RAM), a read-only memory (ROM), a rigid magnetic disk and an optical disk. Current examples of optical disks include compact disk-read only memory (CD-ROM), compact disk-read/write (CD-R/W) and DVD.
[0060] Input/output (I/O) devices (including but not limited to keyboards, displays, pointing devices, scanners etc.) can be coupled to the system either directly or through intervening I/O controllers. Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks. Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters.
[0061] A representative hardware environment for practicing the embodiments may include a hardware configuration of an information handling/computer system in accordance with the embodiments herein. The system herein comprises at least one processor or central processing unit (CPU). The CPUs are interconnected via system bus 208 to various devices such as a random-access memory (RAM), read-only memory (ROM), and an input/output (I/O) adapter. The I/O adapter can connect to peripheral devices, such as disk units and tape drives, or other program storage devices that are readable by the system. The system can read the inventive instructions on the program storage devices and follow these instructions to execute the methodology of the embodiments herein.
[0062] The system further includes a user interface adapter that connects a keyboard, mouse, speaker, microphone, and/or other user interface devices such as a touch screen device (not shown) to the bus to gather user input. Additionally, a communication adapter connects the bus to a data processing network, and a display adapter connects the bus to a display device which may be embodied as an output device such as a monitor, printer, or transmitter, for example.
[0063] A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention. When a single device or article is described herein, it will be apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be apparent that a single device/article may be used in place of the more than one device or article, or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.
[0064] 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 and spirit 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.
[0065] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the embodiments of the present disclosure are intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.