Claims:A system to auto plan a travel event (10) comprising:
a processing subsystem (20) comprising:
an input module (40) configured to capture one or more inputs from a user;
a travel retrieving module (50) configured to retrieve ecosystem information associated with at least one selected service from at least one travel database;
a planning module (60) operatively coupled to the input module (40), and configured to:
process the one or more inputs and ecosystem information based on one or more factors by using at least one of an analysis technique and a prediction technique in real time; and
generate a plurality of travel plans based on a processed result;
an update travel module (70) operatively coupled to the planning module (60), and configured to select one of the plurality of travel plans for the travel event.
a memory subsystem (30) operatively coupled to the processing subsystem (20), and configured to store the one or more inputs from a user and the plurality of travel plans to auto plan a travel event.
2. The system (10) as claimed in claim 1, wherein the at least one selected service comprises an accommodation service, a transport service, a location to location connectivity service, an activity, a place of attraction booking service, a vehicle renting service, a human service and a service of renting products.
3. The system (10) as claimed in claim 1, wherein the one or more inputs comprises a name, a source, a destination, a date, a duration, a travel itinerary, a stage of planning and a traveller means.
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4. The system (10) as claimed in claim 1, wherein the one or more factors comprises availability, best time, weather or natural disasters, ticket sales time, best route, traffic congestion, localized news, user persona or behavior.
5. A method for operating a system to auto plan a travel event (130) comprising:
capturing, by an input module, one or more inputs from a user (140);
retrieving, by a travel retrieving module, ecosystem information associated with at least one selected service from at least one travel database (150);
processing, by a planning module, the one or more inputs and ecosystem information based on one or more factors by using at least one of an analysis technique and a prediction technique in real time (160);
generating, by the planning module, a plurality of travel plans based on a processed result (170); and
selecting, by an updating module, one of the plurality of travel plans for the travel event (180).
6. The method (130) as claimed in claim 5, wherein capturing, by the input module, the one or more inputs from a user comprising of a name, a source, a destination, a date, a duration, a travel itinerary, a stage of planning and a traveller means.
7. The method (130) as claimed in claim 5, wherein processing, by the planning module, the one or more inputs and ecosystem information based on the one or more factors like availability, best time, weather or natural disasters, ticket sales time, best route, traffic congestion, localized news, user persona and behaviour.
8. The method (130) as claimed in claim 5, wherein further comprising storing, by a memory subsystem, the one or more inputs from a user and the plurality of travel plans to auto plan a travel event.
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Dated this the 16th day of January 2019
Signature
VIDYA BHASKAR SINGH NANDIYAL
IN/PA 2912
Agent for the Applicant , Description:FIELD OF INVENTION
[0001] Embodiments of a present disclosure relates to a platform for online booking of travel itinerary, and more particularly to a system to auto plan a travel event and a method to operate the same.
BACKGROUND
[0002] Event planning is a process of managing one or more events such as a meeting, convention, ceremony, team building activity, party, corporate outing or travelling. For travel event, it is very important to manage budgeting, establishing timelines, selecting and reserving travel sites, coordinating transportation, arranging for activities, developing contingency plans and the like. Travel planning not only helps visitors but also enables in developing the economy of the places the visitors are visiting. Special visiting references may be introduced in real time.
[0003] Conventionally, the event planning system for fulfilment of the travelling by one or more customers includes a plurality of subsystems for planning and booking of one or more services. However, travel planning system lacks the incorporation of one or more services from the plurality of systems in real time. Moreover, such systems lack analysing capability for a plan to suite the needs of the customers according to previous preferences. More efficient would be to provide multiple travel itinerary for choice to the customer.
[0004] Hence, there is a need for an improved system to auto plan a travel event and method to operate the same in order to address the aforementioned issues.
BRIEF DESCRIPTION
[0005] In accordance with an embodiment of the present disclosure, a system to auto plan a travel event is provided. A system to auto plan a travel event comprises of a processing subsystem. The processing subsystem comprises an input module. The input module is configured to capture one or more inputs from a user. The processing subsystem also comprises a travel retrieving module. The travel retrieving module is
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configured to retrieve ecosystem information associated with at least one selected service from at least one travel database.
[0006] The processing subsystem also includes a planning module. The planning module operatively coupled to the input module. The planning module is configured to process the one or more inputs and ecosystem information based on one or more factors by using at least one of an analysis technique and a prediction technique in real time. The planning module is also configured to generate a plurality of travel plans based on a processed result. The processing subsystem also includes an update travel module. The update travel module is operatively coupled to the planning module. The update travel module is configured to select one of the plurality of travel plans for the travel event. The processing subsystem is also operatively coupled is a memory subsystem. The memory subsystem is configured to store the one or more inputs from a user and the plurality of travel plans to auto plan a travel event.
[0007] In accordance with another embodiment of the present disclosure, a method for operating a system to auto plan a travel event system is provided. The method includes capturing one or more inputs from a user. The method also includes retrieving ecosystem information associated with at least one selected service from at least one travel database. The method also includes processing the one or more inputs and ecosystem information based on one or more factors by using at least one of an analysis technique and a prediction technique in real time. The method also includes generating a plurality of travel plans based on a processed result. The method also includes selecting one of the plurality of travel plans for the travel event.
[0008] 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 THE DRAWINGS
[0009] The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
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[0010] FIG. 1 is a block diagram of a system to auto plan a travel event in accordance with an embodiment of the present disclosure;
[0011] FIG. 2 illustrates a schematic representation of an exemplary embodiment of a system to auto plan a travel event of FIG. 1 in accordance with an embodiment of the present disclosure;
[0012] FIG. 3 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure; and
[0013] FIG. 4 is a flow chart representing the steps of a method for operating a system to auto plan a travel event in accordance with the embodiment of the present disclosure.
[0014] 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
[0015] 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.
[0016] The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps
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not expressly listed or inherent to such a process or method. Similarly, 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, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. 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] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
[0019] Embodiments of the present disclosure relate to a system to auto plan a travel event. A system to auto plan a travel event comprises of a processing subsystem. The processing subsystem comprises an input module. The input module is configured to capture one or more inputs from a user. The processing subsystem also comprises a travel retrieving module. The travel retrieving module is configured to retrieve ecosystem information associated with at least one selected service from at least one travel database.
[0020] The processing subsystem also includes a planning module. The planning module operatively coupled to the input module. The planning module is configured to process the one or more inputs and ecosystem information based on one or more factors by using at least one of an analysis technique and a prediction technique in real time. The planning module is also configured to generate a plurality of travel plans based on a processed result. The processing subsystem also includes an update travel module. The update travel module is operatively coupled to the planning module. The update travel module is configured to select one of the plurality of travel plans for the
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travel event. The processing subsystem is also operatively coupled is a memory subsystem. The memory subsystem is configured to store the one or more inputs from a user and the plurality of travel plans to auto plan a travel event.
[0021] FIG. 1 is a block diagram of a system to auto plan a travel event (10) in accordance with an embodiment of the present disclosure. In one embodiment, the travel event refers to travelling plan of a user from a starting location to a destination location.
[0022] The system to auto plan a travel event (10) includes a processing subsystem (20). The processing subsystem (20) includes an input module (40). The input module (40) is configured to capture one or more inputs from a user. In one embodiment, the one or more inputs comprises at least one of a name, a source, a destination, a date, a duration, a travel itinerary, a stage of planning, a traveller means and the like.
[0023] As used herein, the term “travel itinerary” refers to a schedule of events relating to planned travel, generally including destinations to be visited at specified times and means of transportation to move between those destinations. In another embodiment, the traveller means refers to vehicles used during travelling event.
[0024] The processing subsystem (10) includes a travel retrieving module (50). The travel retrieving module (50) is configured to retrieve ecosystem information associated with at least one selected service from at least one travel database. As used herein, the term “ecosystem” refers to a complex network or interconnected travel database. As used herein, the term “database” refers to a structured set of data held in a computer, especially data that is associated with travel service. In one embodiment, the travel database associated information is data stored by the at least one selected service vendor. In such embodiment, the data stored may be retrieved automatically.
[0025] In one embodiment, the at least one selected service comprises an accommodation service, a transport service, a location to location connectivity service, an activity, a place of attraction booking service, a vehicle renting service, a human service, a service of renting products and robotics services. In such embodiment, the ecosystem information associated with the at least one selected service indicates to the travel associated information about any of the at least one selected service.
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[0026] In one embodiment, accommodation services include hotels, resorts, house/villa rentals, tents, hostels, dormitories and the like. In another embodiment, the transport services include travelling via a flight, a train, a bus, a chopper and the like.
[0027] Furthermore, in one embodiment, location to location connectivity services includes cabs, barge, boats, rides on animals such as a horse, a camel, a cart and the like. In another embodiment, vehicle renting services includes a car, a bike, a mini bus, a cycle and the like. In another embodiment, the robotics services may be included in the travel services.
[0028] Moreover, in one embodiment, human services include a tour guide, a translator, an astrologer, a photographer, a fashion designer and the like. In another embodiment, rented products include winter clothes, swimming gears and the like.
[0029] In one embodiment, the availability of the one or more inputs are also made available to the user for booking according to the need. The one or more inputs comprises at least one of a name, a source, a destination, a date, a duration, a travel itinerary, a stage of planning, a traveller means and the like.
[0030] The processing subsystem (10) also includes a planning module (60). The planning module (60) is operatively coupled to the input module (40). The planning module (60) is configured to process the one or more inputs and ecosystem information based on one or more factors by using at least one of an analysis technique and a prediction technique in real time. In one embodiment, the one or more factors comprises availability, best time, weather or natural disasters, ticket sales time, best route, traffic congestion, localized news, user persona or behaviour. In another embodiment, query search is also performed for to check availability of particular needed service.
[0031] In one embodiment, the analysing technique includes at least one of artificial intelligence and machine learning. As used herein, the term “artificial intelligence” refers to sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals, such as visual perception, speech recognition, decision-making, and translation between languages. As used herein, the term “machine learning” refers to an application of artificial intelligence (AI) that provides system the ability to
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automatically learn and improve from experience without being explicitly programmed.
[0032] The planning module (60) is also configured to generate a plurality of travel plans based on a processed result. In one embodiment, every possible factor is taken care before planning, to provide users the most optimised approach. In one embodiment, a computing system may be optimised by providing scheduler application for generating a well-planned travel plan. In such embodiment, the computing device may be a portable device, handheld device and the like.
[0033] In one embodiment, the list of attractions, activities and events in the selected location may be filtered according to previous user’s ratings, the best time to visit and typical time spent. Mainly, the planning module (60) helps in filtering with the likes of the travelling user based on the persona. In such embedment, information like social media activities of the user is also taken into consideration while planning by planning module. In one such embodiment, the information is collected from linked account of the user.
[0034] In another embodiment, the online and offline behaviours of other users who are of same generation, gender, geolocation, profession and the like are also taken into consideration.
[0035] The processing subsystem (10) also includes an update travel module (70). The update travel module (70) operatively coupled to the planning module (60). The update travel module (70) is configured to select one of the plurality of travel plans for the travel event. In one embodiment, the user may select any one of the plurality of travel plans for the travel event.
[0036] A memory subsystem (30) is operatively coupled to the processing subsystem (10). The memory subsystem (30) is configured to store the one or more inputs from a user and the plurality of travel plans to auto plan a travel event. The memory stored may be used as reference in the form of database. The memory may be at least one of local storage unit or remote storage unit. In one embodiment, the remote storage unit may be used to store the user preference regarding one or more inputs.
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[0037] FIG. 2 illustrates a schematic representation of an exemplary embodiment of a system to auto plan a travel event of FIG. 1 in accordance with an embodiment of the present disclosure. The auto plan system (10) is used for planning and fulfilling one or more travel event. In an exemplary embodiment, user X (80) inputs a destination location and a starting location through the input module (40). The user X (80) further inputs the durations of travel tour along with budget (90).
[0038] A travel retrieving module (50) enables in retrieving information from hotel database of the destination location. The best mode of travel from the starting location to destination location and vice versa is also retrieved according to the budget input. A planning module (60) uses all the provided information to generate a plurality of travel plans. In one exemplary embodiment, the planning module (60) uses artificial intelligence and machine intelligence for booking flights according to user’s travel preferences. Here, user’s airline preferences, usual cost spent, travelling class, preferred time to travel and the availability is analysed. The plurality of travel plans is analysed based on factors like localized news, prior history of user, ticket sales time, best route, traffic congestion and the like.
[0039] In one exemplary embodiment, if the user X (80) is planning trip to Jammu during the month of January, the auto planning system (10) would at first take into consideration the user input and query of search to provide multiple plans. The search may be made more personalised, as the auto planning system (10) will take into consideration online and offline behaviours of other users who are of same generation, gender, geolocation, profession and the like. In such exemplary embodiment, children activity centres are also recommended according to reviews of other same age users.
[0040] The user X (80) may also input his or her preference hotels, cabs and like. For example, if the user X (80) prefer to travel only by particular vehicle he may choose in his or her preferences during input. In one embodiment, the user X (80) will be at first provided with availability of the preferred services.
[0041] The auto planning system (10) may also take in to consideration the localized news of the Jammu as well as temperature and weather condition. Thereby, the auto plan system (10) would plan multiple travel plans for visiting Jammu taking
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every basic factor in to consideration. Travel plans will all be provided in a scheduler and calendar panel.
[0042] The user X (80) during planning may filter the scheduler or calendar according to various factors. The factors comprise budget, duration, hotel checking time, travel options and the like. The travel auto planner thus provides a user-friendly approach to the user X (80).
[0043] In another exemplary embodiment, the auto plan system (10) provides a best mode to travel, a best transport service related to travel, a list of best accommodation services, a list of attractions, activities, events in the destination location, a best route related to the list of attractions and the like.
[0044] Furthermore, in one exemplary embodiment, the user X (80) may drag, delete and drop services within the timeline, calendar panel to rearrange the travel plan according to wish. An update travel module (70) enables in selecting one of the plurality of travel plans for the travel event to one destination location automatically. Thus, user action to personalize the travel plan is permitted.
[0045] The input module (40), the travel retrieving module (50), the planning module (60) and the update travel module (70) used in FIG. 2 is substantially similar to the input module (40), the travel retrieving module (50), the planning module (60) and the update travel module (70) of FIG. 1.
[0046] FIG. 3 is a block diagram of a computer or a server (100) in accordance with an embodiment of the present disclosure. The server (100) includes processor(s) (120), and memory (30) coupled to the processor(s) (120).
[0047] The processor(s) (120), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.
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[0048] The memory (30) includes a plurality of modules stored in the form of executable program which instructs the processor (120) to perform the method steps illustrated in Fig 1. The memory (30) has following modules: an input module (40), a travel retrieving module (50), a planning module (60) and an update travel module (70). The input module (40) is configured to capture one or more inputs from a user. The travel retrieving module (50) is configured to retrieve ecosystem information associated with at least one selected service from at least one travel database. The planning module (60) is configured to process the one or more inputs and ecosystem information based on one or more factors by using at least one of an analysis technique and a prediction technique in real time. The planning module (60) is also configured to generate a plurality of travel plans based on a processed result. The update travel module (70) is configured to select one of the plurality of travel plans for the travel event.
[0049] Computer memory elements may include any suitable memory device(s) for storing data and executable program, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, hard drive, removable media drive for handling memory cards and the like. Embodiments of the present subject matter may be implemented in conjunction with program modules, including functions, procedures, data structures, and application programs, for performing tasks, or defining abstract data types or low-level hardware contexts. Executable program stored on any of the above-mentioned storage media may be executable by the processor(s) (120).
[0050] FIG. 4 is a flow chart representing the steps of a method for operating a system to auto plan a travel event (130) in accordance with the embodiment of the present disclosure. The method includes capturing one or more inputs from a user in step 140. In one embodiment, capturing the one or more inputs from the user includes capturing the one or more inputs from the user by an input module. In another embodiment, capturing the one or more inputs from the user includes capturing the one or more inputs comprising of a name, a source, a destination, a date, a duration, a travel itinerary, a stage of planning and a traveller means.
[0051] The method (130) also includes retrieving ecosystem information associated with at least one selected service from at least one travel database in the
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step 150. In one embodiment, retrieving ecosystem information associated with the at least one selected service from the at least one travel database includes retrieving ecosystem information associated with the at least one selected service from the at least one travel database by a travel retrieving module.
[0052] The method (130) also includes processing the one or more inputs and ecosystem information based on one or more factors by using at least one of an analysis technique and a prediction technique in real time in the step 160. In one embodiment, processing the one or more inputs and ecosystem information based on the one or more factors by using the at least one of the analysis technique and the prediction technique in real time includes processing the one or more inputs and ecosystem information based on the one or more factors by using the at least one of the analysis technique and the prediction technique in real time by a planning module. In another embodiment, processing the one or more inputs and ecosystem information based on the one or more factors by using the at least one of the analysis technique and the prediction technique in real time includes processing the one or more inputs and ecosystem information based on the one or more factors comprising like availability, best time, weather or natural disasters, ticket sales time, best route, traffic congestion, localized news, user persona and behaviour.
[0053] The method (130) also includes generating a plurality of travel plans based on a processed result in the step 170. In one embodiment, generating the plurality of travel plans based on the processed result includes generating the plurality of travel plans based on the processed result by the planning module.
[0054] The method (130) also includes selecting one of the plurality of travel plans for the travel event in the step 180. In one embodiment, selecting the one of the plurality of travel plans for the travel event includes selecting the one of the plurality of travel plans for the travel event by an update travel module.
[0055] The method (130) also includes storing the one or more inputs from a user and the plurality of travel plans to auto plan a travel event. In one embodiment, storing the one or more inputs from a user and the plurality of travel plans to auto plan a travel event includes storing the one or more inputs from a user and the plurality of travel plans to auto plan a travel event by a memory subsystem.
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[0056] Present disclosure is related to a system to auto plan a travel event in one platform without wasting time and energy. Moreover, the present disclosed system utilizes the machine learning technique and the artificial intelligence technique to analyse and predict the one or more factors by considering real-time situation for suggesting a suitable plan to the user. The present disclosure gives travel planning system with incorporation of one or more services from the plurality of systems in real time.
[0057] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
[0058] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.