Patent ID: 12200065

DETAILED DESCRIPTION

FIG.1shows a system for multi-platform content normalization indicated generally at100. System100comprises a plurality of interaction platforms104104-1,104-2. . .104-n. (Collectively, platforms104-1,104-2. . .104-nare referred to as platforms104, and generically, as platform104. This nomenclature is used elsewhere herein.) Platforms104can be based on any present or future interactive communication platforms such as a simple messaging service (SMS) interactive service, a browser-based e-commerce travel booking environment such as Travelocity™, Expedia™ or any of the individual airline or hotel booking engines. Interactive communication platforms also include social media environments like Facebook™, Tiktok™, or even communication channel such as Whatsapp™, or a massively multi-player environment such as Second Life™, MineCraft™, Fortnite™, or a virtual reality 3D metaverse environment such as Roblox™ or Horizon Worlds™. Certain non-limiting examples for each platform104are labelled inFIG.1for purpose of discussion. Namely, platform104-1is labelled with the example “Metaverse 1” (such as Roblox™ or Horizon Worlds™); platform104-2is labelled with the example “Metaverse 2”; platform104-3is labelled with the example “Multimedia Platform 1” (such as Second Life™); platform104-4is labelled with the “Multimedia Platform 2” (such as Expedia™); platform104-nis labelled with the “Travel Website”; These examples are nonlimiting and purely illustrative. Other platforms and combinations thereof are contemplated.

In system100, platforms104connect to a network106. Any network topology is contemplated, such as, by way of non-limiting example, the Internet, one or more intranets, or combinations thereof. Network106interconnects platforms104, with: a) at least one content engine108; b) at least one content aggregation engine112that is coupled with a platform adaptation engine116; and, c) a plurality of client devices120. (In a variant, a single content engine108would obviate the need for content aggregation engine112).

As will be explained in greater detail below, each content engine108can be based upon its own computing architecture and will periodically send content to aggregation engine112for access by one or more client devices120via one or more platforms104. Content engines108can be based on any type of known or future Internet content. In a present illustrative, but non-limiting embodiment, content engines108are operated by travel actors within the travel industry, including, but not limited to, airlines, railway systems, car rental agencies, cruise line operators, hotels, restaurants, resorts, and spas.

Thusly, content aggregation engine112periodically receives data files including content that has been sent by content engines108via network106. In the present example embodiment, content aggregation engine112can be operated by, or accessed by, for example, a travel booking engine. To elaborate, a travel booking engine that could operate content aggregation engine112could include well-known travel booking engines such as Expedia™, Travelocity™ or Hotels.com™. There are many other travel booking engines. Content engine112can thus be operated directly by such a travel booking engine, or can be hosted by a travel data aggregator, often referred to as a Global Distribution System (“GDS”), such as Amadeus™, Sabre™, Travelport™, Apollo™, Galileo™, Travelfusion™, or Duffel™ Aggregation engine112thus collects content from content engines108for generation on one or more platforms104, such that content from engines108can be accessed by devices120.

System100also includes adaptation engine116which normalizes content from engines108across platforms104and devices120. Adaptation engine116will be discussed in greater detail below.

Client devices120can be any type of human-machine interface for interacting with platforms104. For example, client devices120can include virtual reality gear, augmented reality gear or mixed reality gear, such as headsets, tracking headsets, holographic devices, hand controllers, full body sensors, haptic feedback, temperature feedback, smell feedback, treadmill or other foot tracking and feedback technology, and/or combinations of any of the foregoing. In addition, client devices120can include smart televisions, traditional laptop computers, desktop computers, mobile phones, tablet computers and any other device that can be used by consumers to receive content via one or more of the platforms104that complement the input and output hardware devices associated with a given client device120. Such traditional client devices120can also have connected lights, lightstrips, speakers to provide a multi-media experience on such traditional client devices.

According to the specific example inFIG.1, device120-1is a virtual reality headset; device120-2is a first virtual reality station comprising a headset with head, hand and feet tracking technology; device120-3is a virtual reality headset with haptic feedback hand controllers; device120-4is a second virtual reality station comprising a headset with hand, feet, and torso tracking and haptic feedback technology; device120-5is a traditional laptop computer and device120-pis a traditional mobile telephone. Again, these are non-limiting examples, but their diversity of input and output devices is illustrative of the diverse human-machine interface aspects of the present specification.

FIG.2shows a schematic diagram of a non-limiting example of internal components of a computing device200. The infrastructure of computing device200, or a variant thereon, can be used to implement any of the computing nodes, including data source engine108, data aggregation engine112, adaption engine116or client devices120. Other than client devices120which are based on their own unique input and output hardware form factors as human-machine interfaces, where desired and/or the context permits, one or more of the remaining nodes in system100can be implemented virtually inside a single computing device200.

In this example, computing device200includes at least one input device204. Input from device204is received at a processor208which in turn controls an output device212. In the context of all the nodes of system100, input device204can be a traditional keyboard and/or mouse may be connected to provide physical input. Likewise output device212can be a display or audio speakers. In variants, additional and/or other input devices204or output devices212are contemplated or may be omitted altogether as the context requires.

In the specific context of client devices120, input devices may include physical or virtual keyboards, accelerometers, input buttons, pointing devices, treadmills, temperature sensors, cameras, microphones, global positioning systems (GPS), gyroscopes, olfactometers, velocity sensors, accelerometers, medical sensors (such as pulse rate, blood pressure, stress level, skin moisture level) or any other known or future contemplated input device associated with human-machine interfaces. In the context of client devices120, output devices may include traditional displays, head-set stereoscope virtual reality displays, augmented or mixed reality displays, haptic feedback, heating or cooling apparatuses, smell generators, sound devices, surround sound systems, smart light bulbs, smart light strips, or any other known or future contemplated output devices associated with human-machine interfaces. Client devices120are configured to interact with one or more platforms104via network106according to the hardware capabilities of a given client device and the corresponding interactive communication capabilities of a given platform104. (Such hardware, software and interactive communication capabilities may be generically referred to herein as computing resource capabilities.)

Processor208may be implemented as a plurality of processors or one or more multi-core processors. The processor208may be configured to execute different programing instructions responsive to the input received via the one or more input devices204and to control one or more output devices212to generate output on those devices.

To fulfill its programming functions, the processor208is configured to communicate with one or more memory units, including non-volatile memory216and volatile memory220. Non-volatile memory216can be based on any persistent memory technology, such as an Erasable Electronic Programmable Read Only Memory (“EEPROM”), flash memory, solid-state hard disk (SSD), other type of hard-disk, or combinations of them. Non-volatile memory216may also be described as a non-transitory computer readable media. Also, more than one type of non-volatile memory216may be provided.

Volatile memory220is based on any random access memory (RAM) technology. For example, volatile memory220can be based on a Double Data Rate (DDR) Synchronous Dynamic Random-Access Memory (SDRAM). Other types of volatile memory220are contemplated.

Processor208also connects to network106via a network interface232which includes a buffer, a modulator/demodulator or MODEM, over the various links and/or internet that connects the server equipment to other server equipment. Depending on the node in system100, network interface232can also be used to connect a given node to another computing device that has an input and output device, thereby obviating the need for input device204and/or output device212altogether.

Programming instructions in the form of applications224are typically maintained, persistently, in non-volatile memory216and used by the processor208which reads from and writes to volatile memory220during the execution of applications224. One or more tables or databases228can also be maintained in non-volatile memory216for use by applications224.

FIG.3shows adaptation engine116in greater detail, identifying its sub-elements according to the structure of computing device200fromFIG.2. The nomenclature to identify sub-elements of engine116inFIG.3borrows from the analogue elements inFIG.2. Specifically, elements inFIG.3are of the format “116-2##” whereby the “116” prefix identifying adaptation engine116while the “2##” suffix refers to the corresponding two-hundred series element fromFIG.2. Thus, specific discussion of sub-elements on engine116will use this nomenclature hereafter. (This nomenclature may also be used to reference other sub-elements of nodes in system100without necessarily specifically showing a corresponding Figure.)

FIG.4shows a flowchart depicting a method for multi-platform content normalization indicated generally at400. Method400can be implemented on system100. Persons skilled in the art may choose to implement method400on system100or variants thereon, or with certain blocks omitted, performed in parallel or in a different order than shown. Method400can thus also be varied. However, for purposes of explanation, method400as per the flow chart ofFIG.4and will be described in relation to its performance on system100with a specific focus on adaptation engine116and its interactions with the other nodes in system100.

Block404comprises receiving a content request. The content request can originate from a given client device120during a session within a session between that client device120and a given platform104. (Alternatively, or in addition, the content request can originate from a given platform104based on an inference made by platform104of an experience that is to be tailored to a given client device120.) The establishment of the session is governed by the architecture of the platform104, according to the credential management and authentication protocols employed by the platform104, and according to the account associated with a user of the relevant client device120. As will be discussed in greater detail below, the specific nature of the content request at block404thus depends on the context of the session, but in general terms includes sending the request to content aggregation engine112from the platform104.

FIG.5shows system100illustrating an example session504between virtual reality station client device120-4and metaverse platform104-2expressed as a dotted line between these two nodes.FIG.5also shows an example request508(representing performance of block404) from metaverse platform104-2to content aggregation engine112expressed as a dotted line between these two nodes.

The nature of the content request is not particularly limited, but with a few illustrative examples a person of skill in the art will come to appreciate the scope of the present embodiment. As noted earlier, system100can have broad application to the travel industry, and thus session504can include the opportunity, within a virtual reality environment, to browse, interact with, select and, if desired, provide the technology infrastructure to purchase various travel services.FIG.6shows an example illustration of a point in time of session504-1within a virtual reality session within metaverse platform104-2. (The -1 suffix in session504-1representing the rendering by platform104-2point in time of the session, and this nomenclature is repeated). A person skilled in the art will recognize that the view inFIG.6is from a third person perspective, and not from the first-person perspective that could be experienced by the user of client device120-4during session504. ThusFIG.6shows a client avatar606associated with the user account of client device120-4.FIG.6also shows a travel agent avatar608that may be automated or controlled by a human via another client device120. The entire scene within session504-1represents a rendering of a travel agency environment, with client avatar606engaging a travel agent avatar608to browse travel services. Travel agent avatar608is thus shown inFIG.6as demonstrating various objects associated with vacation travel including an aircraft612, palm trees616, a beach chair620and associated umbrella624and a pair of airline seats628.

According toFIG.6, at this point in session504-1client avatar606is shown in the seat selection stage of purchasing an airline ticket respective to a given flight on aircraft612, and thus travel agent avatar608is represented as showing airline seats628to avatar606. Thus, according to this example, the request508inFIG.5can represent a portion of seat selection sub-routine, within an overall flight seat purchasing routine, where that sub-routine includes a request for the seat map associated with aircraft612so that a seat within the aircraft612for the selected flight can be chosen as part of the purchase of the airline ticket.

At this point the overall context of system100should be re-emphasized. In a travel industry context, content aggregation engine112can access content from a number of travel industry actors who each host content engines108. Thus the information regarding the specific flight number that utilizes aircraft612and the associated seat map from that flight can be sent from the content engine108that manages the flight schedules for that specific flight and aircraft612. In this manner the travel agent avatar608within the metaverse platform104-2has access, via content aggregation, to a plurality of travel assets hosted by different content engines108as aggregated by content engine112. Thus the specific seat selection exercise represented within session504-1is merely one of many different types of hospitality or travel selection exercises that can be effected within session504, such as, by way of non-limiting examples, airline ticket purchases, hotel room selection, car rental selection, taxi bookings, excursion bookings, concerts, indoor or outdoor events and festivals, dining receptions, exhibitions, and/or any other travel experience that can occur from the beginning of travel to its conclusion. The client avatar606can thus be presented with a complete simulation of the complete travel experience, with browsing and selection options offered throughout the entire simulation. The seat selection request508and the seat selection exercise in session504-1is thus but one non-limiting illustrative example of the travel purchase interactions contemplated by the present specification. Where system100is applied to other industries beyond travel, even more possible types of interactions are possible.

Continuing now with the example of the seat selection, once request508(from block404) is received at content aggregation engine112, then method400advances to block408.

Block408comprises determining the platform capability. In system100, block408is performed by adaption engine116working in concert with aggregation engine112. Adaption engine116is thus configured to maintain dataset116-228-1which includes all of the capabilities of the various platforms104. Alternatively, such capabilities may be sent dynamically along with request508, or a hybrid approach may be employed where some capabilities are stored locally in dataset116-228-1while others are sent along with the request508. Overall, block408can be based on an application programming interface (API) or similar functionality provided by the operator of each platform104. Thus, before a response to the request508is made, adaptation engine116is configured to assess what forms a response may take that will complement the functionality of the platform104that issued the request508at block404.

Continuing with the present example, at block408, based on the fact that request508came from metaverse platform104-2, the capability determination will note that platform104-2is a metaverse environment with a given set of parameters for generating virtual objects and having interactions with those objects according to the specific technological architecture of metaverse platform104-2. As can be noted from scene504-1, the metaverse environment is rich and contemplates a virtual reality environment.

Block412comprises determining the client device capability. More specifically, block412comprises determining the capability of the client device that generated the request508at block404. In system100, block408is performed by adaption engine116working in concert with aggregation engine112. Adaption engine116can thus be configured to maintain a second dataset116-228-2which includes all of the capabilities of the various client devices120. Alternatively, such capabilities may be dynamically sent along with request508, or a hybrid approach is possible where some capabilities are sent with the request508and others are maintained within dataset116-228-2. Indeed, like block408, block412can also be effected as part of any API associated with the relevant platform104. Such client device capabilities are determined based on the specific input and output device hardware configurations of the human machine interface associated with the requesting client device120. In the example ofFIG.5, virtual reality station client device120-4is noted to be a full body virtual reality rig, complete with haptic feedback and sensing for the eyes, hands, torso, and feet.

Block416comprises accessing the requested content. In the specific example being discussed in relation to a seat map for aircraft612, it is contemplated thus that content aggregation engine112will access content with a respective content engine108, such as a content engine108operated by the airline that owns aircraft612and is offering the flight of interest to avatar606.

Block420comprises selecting essential content that is responsive to the request from block404. (Selecting can be effected in different ways, such as through an inclusion process by choosing from a plurality of stored content, or by an exclusion process by filtering out certain content from the plurality of stored content.) Such essential content is the minimum set of content required to fulfill the transaction (or other interaction) occurring in session504-1; namely, in the present non limiting example, the selection of a seat on aircraft612. Thus, the minimum information would include what seats remain available on the aircraft in association the pricing of those seats.

Block424comprises determining if there is capability for providing enriched content beyond what was filtered at block420. In the context of the present example, indeed the rich 3D virtual environment of metaverse platform104-2combined with the extensive set of virtual reality input and output devices on client machine120-4would lead to a “yes” determination at block424.

Block428comprises selecting additional content. (As noted above, selecting can be effected in different ways, such as through an inclusion process by choosing from a plurality of stored content, or by an exclusion process by filtering out certain content from the plurality of stored content.) The additional selected content is responsive to the request from block404and matches any enhanced hardware and software capabilities of the platform104and the corresponding client device104that is carrying the respective session504. To clarify, such enhanced hardware and software capabilities refer to any capabilities that go beyond the ability to generate the essential content from block420. Continuing with the present example, block428would take the full set of rich content from block416to generate a very rich seat map of all available seats on aircraft612. As will be explained further below, the degree of “richness” corresponds directly to the hardware of client machine120and the platform104that generated the request.

Block432comprises generating a response to the request from block404according to the selections applied at block420and block428. Where different platforms104can accommodate the same content, but have different capabilities for presenting that content, then the generation of the response can include adaptations to the selected content respective to the specific capabilities of the target platform104. To help elaborate, and referring again to our specific example, in association with a fully capable metaverse platform104-2and client device120-4, the full seat map could include a nearly complete rendering of the entirety of the interior cabin of aircraft612, having very rich textures and visual appearance of seat628, such as the view of seat628inFIG.7. Processor116-208in adaptation engine116can thus be configured to interact with target platform104-2so that all features of the seat can be viewed at client device120-4over session504. Furthermore, by shifting to a third person perspective avatar606can be shown sitting in the seat and accessing its various virtual features, all of which would mimic the actual performance of the seat on the aircraft612. Using method400, additional seat choices can be loaded and rendered within session504in similar fashion, until an actual selection of seat was made thus advancing the entire workflow of selecting various travel services. Note that the same content may be possible to generate on platform104-3, but with different limitations, such as number of pixels or colours, or other variables, then block432can include an adaptation that is effected to accommodate the different limitations of platforms104that are otherwise capable of generating substantially the same content.

A person of skill in the art can now appreciate just where the virtual reality experience can extend to what additional filters may be applied at block428, as such that in a fully capable client device120-4such as client device120-4, the user of client device120-4could virtually “walk” through the cabin via feedback and input from the treadmill input/output device on client device120-4, providing visual feedback of the entire walk through the aircraft. Occupied seats would show avatars inside them, while available seats would be empty for the avatar606to simulate virtually sitting various empty seats. With the full set of haptic feedback provided to hands, torso and feet, and a mapping of the physical size of the user, the user of client device120-4could control virtual reclining and test out the widths and foot room of the various seats with appropriate feedback and control signals being sent to the input and output device hardware associated with that client device120-4. The inventors fully appreciate that the limits of this example correspond to the physical limits of the virtual reality input and output devices associated with client device120-4, but also note that the rapid development of such rigs suggests a continuum of greater offerings and such offerings are likely to extend over the coming years.

A person of skill in the art can now appreciate that system100also remains compatible with other client devices120and platforms104. Notably, where a platform104or a client device120does not have full metaverse capability then system100and adaption engine116remains flexible to accommodate different technologies. For example, where a seat map request was generated by a mere virtual reality headset120-1, the seat map response at block432would be limited to a virtual view of the inside of the aircraft, but the capability to “walk” through the aircraft would be limited to the mouse or keyboard attached to the computer that connects to the headset120-1. There would also be curtailed or no opportunity to virtually “sit” in the seat and test the reclining and foot room. As a second example, where the seat map request was generated by laptop computer client machine120-5, and the platform was travel website platform104-n, then the filters applied at block428would be limited to generating a seat map that is consistent with currently known browser-based seat mapping and seat selection technology, in the form of a two dimensional array of boxes roughly laid out in grid, such as the example seat map800inFIG.8. System100can also accommodate traditional travel service acquisitions through voice telephony and text such as short message service (SMS).

A person skilled in the art will now appreciate that the teachings herein can improve the technological efficiency and computational and communication resource utilization across system100. As the range of available hardware input and output devices for client devices expand, as metaverse and multimedia platform environments create additional contexts for the delivery of travel agency services. The richness of experience combined with the convenience for users creates the opportunity for greater expectation management as to what travel services are actually being acquired. At the same time the sheer diversity of client devices and platforms creates a pull the opposite direction, as there is a need to ensure that travel asset inventories (such as which airline seats, hotel rooms, restaurant booking times, have been sold and which remain open) are constantly updated in real time so that accurate inventory choices are being generated at the time a session for selection of such inventory is occurring between any given client machine and any given platform. The filtering of unneeded content for less capable client machines also reduces network resource stress on network106, by only delivering the content that can actually be utilized by the given client device120. The result is efficient use of computing resources, including processing, memory and communication resources, across system100and its variants, while providing as rich an experience as possible according to the resource capabilities of the client devices120and the platforms104.

In summary, the present specification provides a content normalization server and method. The specification can have particular application to client devices with augmented or virtual reality hardware that interact with different platforms with metaverse capabilities. Rich experiences are provided on client hardware while making efficient use of available processing, memory and communication resources.

In view of the above it will now be apparent that variants are contemplated. For example, the foregoing has been discussed in relation to the travel industry, it will now be understood that the above-described embodiments can be modified to other industries. For example, an online e-commerce environment such as Amazon™ that becomes enhanced through virtual reality metaverse offerings can be enhanced using the teachings herein. Example additional industries include vehicle purchases from dealerships, medical services from medical clinics, and real estate services from real estate agencies.

It should be recognized that features and aspects of the various examples provided above can be combined into further examples that also fall within the scope of the present disclosure. In addition, the figures are not to scale and may have size and shape exaggerated for illustrative purposes.