system

Abstract

The system according to this embodiment aims to optimize the accommodation experience based on customer reservation information and preference information. [Solution] The system according to the embodiment comprises an acquisition unit, a procedure unit, and an environment adjustment unit. The acquisition unit acquires reservation information regarding the customer's accommodation reservation and preference information regarding the customer's preferences. The procedure unit performs check-in and check-out procedures for the accommodation based on the reservation information acquired by the acquisition unit. The environment adjustment unit adjusts the environment of the accommodation based on the preference information acquired by the acquisition unit.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, the customer's accommodation experience has not been sufficiently optimized individually, and there is room for improvement.

[0005] The system according to the embodiment aims to optimize the accommodation experience based on the customer's reservation information and preference information.

Means for Solving the Problems

[0006] The system according to this embodiment comprises an acquisition unit, a procedure unit, and an environment adjustment unit. The acquisition unit acquires reservation information regarding the customer's accommodation reservation and preference information regarding the customer's preferences. The procedure unit performs check-in and check-out procedures for the accommodation based on the reservation information acquired by the acquisition unit. The environment adjustment unit adjusts the environment of the accommodation based on the preference information acquired by the acquisition unit. [Effects of the Invention]

[0007] The system according to this embodiment can optimize the accommodation experience based on customer reservation information and preference information. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, etc. The communication I / F manages communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) An embodiment of the present invention provides an AI assistant for hotel accommodations that simplifies check-in and check-out procedures and provides information on hotel facilities and services, as well as nearby tourist attractions, based on the customer's reservation information and preferences. The AI ​​assistant acquires the customer's accommodation reservation information and preference information, performs check-in and check-out procedures, customizes the room environment, and provides an optimal stay experience. It also provides information on hotel facilities and services, as well as nearby tourist attractions. For example, when a customer makes a reservation online, the AI ​​assistant receives reservation information for the accommodation along with preference information such as preferred room temperature, lighting, and music. This information is entered into the AI ​​assistant. Next, the AI ​​assistant performs check-in and check-out procedures based on the acquired reservation information. For example, when the customer arrives at the accommodation, the AI ​​assistant automatically performs the check-in procedure and sends the smart key for the room to the customer's terminal device. Also, at check-out, the AI ​​assistant automatically creates an invoice and sends it to the customer's terminal device. Furthermore, the AI ​​assistant customizes the room environment based on the acquired preference information. For example, it sets the customer's preferred temperature, lighting, and music to provide an optimal stay experience. This allows guests to enjoy a comfortable environment tailored to their preferences. The AI-powered accommodation support assistant also provides information on facilities and services within the accommodation, as well as nearby tourist attractions. For example, it can provide information on restaurant reservation availability, spa hours, and nearby tourist spots and events. This makes it easy for guests to understand the facilities, services, and tourist information available during their stay. This system simplifies check-in and check-out procedures, resulting in a more comfortable stay. Providing information on facilities, services, and nearby tourist attractions also improves guest convenience and increases satisfaction. As a result, the AI-powered accommodation support assistant can simplify check-in and check-out procedures based on guest reservation information and preferences, providing an optimal stay experience.

[0029] The accommodation support AI assistant according to this embodiment comprises an acquisition unit, a procedure unit, and an environment adjustment unit. The acquisition unit acquires reservation information regarding the customer's accommodation reservation and preference information regarding the customer's preferences. For example, when a customer makes a reservation online, the acquisition unit inputs preference information such as preferred room temperature, lighting, and music along with the accommodation reservation information. This information is input to the accommodation support AI assistant. The acquisition unit can use AI to analyze the customer's reservation information and preference information and store it in an appropriate format. The procedure unit performs check-in and check-out procedures for the accommodation based on the reservation information acquired by the acquisition unit. For example, when a customer arrives at the accommodation, the procedure unit has the AI ​​assistant automatically perform the check-in procedure and send the smart key for the room to the customer's terminal device. The procedure unit can also automatically create an invoice at check-out and send it to the customer's terminal device. The procedure unit can use AI to efficiently perform check-in and check-out procedures. The environment adjustment unit customizes the environment of the accommodation based on the preference information acquired by the acquisition unit. The environmental adjustment unit, for example, sets the temperature, lighting, and music preferred by the customer to provide an optimal stay experience. The environmental adjustment unit can use AI to automatically adjust the room environment based on the customer's preferences. As a result, the accommodation support AI assistant according to this embodiment can simplify check-in and check-out procedures and provide an optimal stay experience based on the customer's reservation information and preferences.

[0030] The acquisition unit acquires reservation information regarding the customer's accommodation bookings and preference information regarding the customer's preferences. For example, when a customer makes a reservation online, the acquisition unit inputs preference information such as preferred room temperature, lighting, and music, along with the accommodation reservation information. This information is entered into the accommodation support AI assistant. The acquisition unit can use AI to analyze the customer's reservation and preference information and store it in an appropriate format. Specifically, the acquisition unit collects information entered by the customer in the reservation form in real time, and the AI ​​analyzes that information. For example, if the customer's preferred room temperature setting is 22 degrees, the AI ​​analyzes this information and stores it in the customer preference database. Similarly, if the customer prefers a particular music genre, that information is also stored. Furthermore, the acquisition unit can update preference information based on the customer's past stay history and feedback. For example, if the customer changed a specific temperature setting during a previous stay, the AI ​​will use that information to suggest the optimal setting for their next stay. This allows the acquisition unit to gain a detailed understanding of customer preferences and build a foundation for providing personalized services. In addition, the acquisition unit can also link customer preference information with other systems. For example, by acquiring preference information provided by customers through other services and integrating it into the accommodation support AI assistant, a more consistent service can be provided. This allows the data acquisition unit to respond to diverse customer needs and provide a more personalized accommodation experience.

[0031] The Procedures Department handles check-in and check-out procedures for accommodations based on reservation information acquired by the Acquisition Department. For example, when a guest arrives at the accommodation, the Procedures Department's AI assistant automatically completes the check-in process and sends a smart key to the guest's device. The Procedures Department can also automatically create an invoice at check-out and send it to the guest's device. The Procedures Department can efficiently perform check-in and check-out procedures using AI. Specifically, the Procedures Department prepares the check-in process in advance based on the guest's estimated arrival time. When the guest arrives at the accommodation, the AI ​​assistant automatically detects the guest's arrival and starts the check-in process. For example, it sends a notification to the guest's smartphone to confirm the necessary information. Once confirmation is complete, a smart key is sent to the guest's device, allowing the guest to enter their room smoothly. At check-out, the Procedures Department automatically creates an invoice and sends it to the guest's device. The invoice includes the accommodation fee and any additional service charges, and the guest can complete the payment online. Furthermore, the Procedures Department can collect customer feedback to help improve services. For example, it can send a survey after check-out to understand customer satisfaction and areas for improvement. This allows the procedures department to process check-in and check-out efficiently and quickly, improving customer convenience.

[0032] The Environmental Adjustment Unit customizes the accommodation environment based on preference information acquired by the Acquisition Unit. For example, the Environmental Adjustment Unit sets the temperature, lighting, and music preferred by the customer to provide an optimal stay experience. The Environmental Adjustment Unit can use AI to automatically adjust the room environment based on customer preferences. Specifically, the Environmental Adjustment Unit adjusts the room environment based on pre-set preference information before the customer enters the room. For example, if the customer prefers a temperature of 22 degrees Celsius, the unit sets the room temperature to 22 degrees and plays music preferred by the customer. It can also adjust the brightness and color temperature of the lighting to match the customer's preferences. Furthermore, the Environmental Adjustment Unit can adjust the environment in real time during the customer's stay. For example, if the customer changes the room temperature, it will use that information to suggest the optimal settings for their next stay. The Environmental Adjustment Unit can also collect customer feedback and use it to improve services. For example, it can check whether the customer is satisfied with a particular setting and make adjustments as needed. In this way, the Environmental Adjustment Unit can optimize the room environment based on customer preferences and provide a more comfortable stay experience. Furthermore, the environmental control unit can work in conjunction with other systems to perform more advanced environmental adjustments. For example, it can integrate with smart home devices to adjust lighting, music, and temperature based on customer preferences. This allows the environmental control unit to respond to diverse customer needs and provide a more personalized stay experience.

[0033] The procedure unit can perform check-in procedures and send a smart key to the room to the customer's terminal device based on the reservation information acquired by the acquisition unit. For example, when a customer arrives at the accommodation, the procedure unit's AI assistant can automatically perform check-in procedures and send a smart key to the room to the customer's terminal device. The procedure unit can send the smart key in the form of a digital key, QR code (registered trademark), NFC, etc. This automates the check-in procedure and enables a smooth check-in by sending the smart key to the customer's terminal device. Some or all of the above processing in the procedure unit may be performed using AI or not. For example, the procedure unit can input the reservation information acquired by the acquisition unit into the AI ​​and have the AI ​​perform the check-in procedure.

[0034] The procedures department can automatically create an invoice at checkout and send it to the customer's terminal device. For example, the procedures department can have an AI assistant automatically create an invoice at checkout and send it to the customer's terminal device. The invoice would include accommodation charges, additional service charges, taxes, etc. This automates the checkout process and enables a smooth checkout by sending the invoice to the customer's terminal device. Some or all of the above processes in the procedures department may be performed using AI or not. For example, the procedures department can have the AI ​​create the invoice at checkout.

[0035] The environmental control unit can control the room temperature, lighting, and music. For example, the environmental control unit can set the temperature, lighting, and music to the customer's preference to provide an optimal stay experience. The environmental control unit can adjust the temperature range, lighting brightness, music type, etc. This allows for the provision of an optimal stay experience by adjusting the room environment based on the customer's preferences. Some or all of the above processing in the environmental control unit may be performed using AI or not. For example, the environmental control unit can input customer preference information into the AI ​​and have the AI ​​perform the adjustment of the room environment.

[0036] The data acquisition unit can analyze a customer's past accommodation history and select a data acquisition method. For example, the data acquisition unit can prioritize acquiring reservation information for similar accommodations based on information about accommodations the customer has used in the past. The data acquisition unit can also estimate a customer's preferred room type from their past accommodation history and acquire that information. Furthermore, the data acquisition unit can acquire relevant reservation information based on services the customer has used in the past. By selecting the optimal data acquisition method based on the customer's past accommodation history, more appropriate information can be obtained. Some or all of the above processing in the data acquisition unit may be performed using AI or not. For example, the data acquisition unit can input the customer's past accommodation history data into AI and have the AI ​​select the optimal data acquisition method.

[0037] The data acquisition unit can filter reservation information based on the customer's current travel purpose and areas of interest. For example, if the customer is traveling for business, the data acquisition unit will prioritize information on meeting rooms and business centers. If the customer is traveling for sightseeing, the data acquisition unit can also acquire information on tourist attractions and activities. Furthermore, if the customer is traveling for relaxation, the data acquisition unit can acquire information on spas and relaxation facilities. By filtering information based on the customer's travel purpose and areas of interest, more relevant information can be provided. Some or all of the above processing in the data acquisition unit may be performed using AI or not. For example, the data acquisition unit can input data on the customer's travel purpose and areas of interest into the AI ​​and have the AI ​​perform the information filtering.

[0038] The acquisition unit can prioritize the acquisition of highly relevant information by considering the customer's geographical location when acquiring reservation information. For example, the acquisition unit can prioritize the acquisition of information on accommodations close to the customer's current location. If the customer is staying in a specific region, the acquisition unit can also prioritize the acquisition of tourist information for that region. Furthermore, if the customer is on the move, the acquisition unit can prioritize the acquisition of information related to their next destination. This allows for the provision of more relevant information by considering the customer's geographical location. Some or all of the above processing in the acquisition unit may be performed using AI or not. For example, the acquisition unit can input the customer's geographical location information into the AI ​​and have the AI ​​perform the acquisition of highly relevant information.

[0039] The data acquisition unit can analyze the customer's social media activity and acquire relevant information when acquiring reservation information. For example, the data acquisition unit can acquire information about places and events mentioned by the customer on social media. The data acquisition unit can also acquire information about activities the customer is interested in from the content of the customer's social media posts. Furthermore, the data acquisition unit can acquire information about places visited by the customer's social media followers. This allows for the provision of more relevant information by analyzing the customer's social media activity. Some or all of the above processing in the data acquisition unit may be performed using AI or not. For example, the data acquisition unit can input the customer's social media activity data into an AI and have the AI ​​perform the acquisition of relevant information.

[0040] The procedures department can select the most suitable procedure during the check-in process by referring to the customer's past check-in history. For example, the procedures department may prioritize suggesting check-in methods the customer has used in the past. The procedures department can also estimate and suggest preferred procedures based on the customer's past check-in history. Furthermore, the procedures department can suggest similar procedures based on information about accommodations the customer has used in the past. This allows for a smoother check-in process by selecting the most suitable procedure based on the customer's past check-in history. Some or all of the above processes in the procedures department may be performed using AI or not. For example, the procedures department can input the customer's past check-in history data into an AI and have the AI ​​select the most suitable procedure.

[0041] The procedures department can adjust the check-in process based on the customer's current travel purpose. For example, if the customer is traveling for business, the procedures department can provide a faster check-in process. If the customer is traveling for sightseeing, the procedures department can also provide a check-in process that includes sightseeing information. Furthermore, if the customer is traveling for relaxation, the procedures department can also provide a check-in process that includes information on relaxation facilities. This allows for a more appropriate check-in process by customizing the process based on the customer's travel purpose. Some or all of the above processing in the procedures department may be performed using AI or not. For example, the procedures department can input customer travel purpose data into the AI ​​and have the AI ​​perform the adjustments to the process.

[0042] The procedures unit can select the most appropriate procedure during the check-in process, taking into account the customer's geographical location. For example, the procedures unit can suggest the most appropriate check-in procedure based on information about accommodations near the customer's current location. If the customer is staying in a specific region, the procedures unit can also suggest a check-in procedure that includes information about that region. Furthermore, if the customer is on the move, the procedures unit can suggest a check-in procedure related to their next destination. This allows for the provision of a more appropriate check-in procedure by considering the customer's geographical location. Some or all of the above processing in the procedures unit may be performed using AI or not. For example, the procedures unit can input the customer's geographical location information into the AI ​​and have the AI ​​select the most appropriate procedure.

[0043] The procedures department can analyze a customer's social media activity and adjust the check-in process accordingly. For example, the procedures department can customize the check-in process based on information about accommodations mentioned by the customer on social media. The procedures department can also suggest check-in procedures that include services the customer is interested in, based on the content of the customer's social media posts. Furthermore, the procedures department can customize the check-in process based on information about accommodations used by the customer's social media followers. This allows for the provision of more appropriate check-in procedures by analyzing the customer's social media activity. Some or all of the above processes in the procedures department may be performed using AI or not. For example, the procedures department can input customer social media activity data into AI and have the AI ​​perform the adjustments to the procedure.

[0044] The environment adjustment unit can set the optimal environment by referring to the customer's past stay history when adjusting the room environment. For example, the environment adjustment unit can adjust the room temperature based on the customer's preferred temperature settings in the past. The environment adjustment unit can also estimate and adjust the customer's preferred lighting settings from their past stay history. Furthermore, the environment adjustment unit can set the room's music based on the music the customer has listened to in the past. In this way, by setting the optimal environment based on the customer's past stay history, a more comfortable stay experience can be provided. Some or all of the above processes in the environment adjustment unit may be performed using AI or not. For example, the environment adjustment unit can input the customer's past stay history data into AI and have the AI ​​perform the optimal environment setting.

[0045] The environmental adjustment unit can adjust the room environment based on the customer's current health condition. For example, if the customer is tired, the environmental adjustment unit can set up a relaxing environment. If the customer is seeking healthy exercise, the environmental adjustment unit can also set up an environment suitable for exercise. Furthermore, if the customer is feeling unwell, the environmental adjustment unit can set up a comfortable environment. This allows for a more comfortable stay experience by customizing the environment according to the customer's health condition. Some or all of the above processes in the environmental adjustment unit may be performed using AI or not. For example, the environmental adjustment unit can input customer health data into AI and have the AI ​​perform the environmental adjustments.

[0046] The environmental adjustment unit can set the optimal environment when adjusting the room environment, taking into account the customer's geographical location information. For example, if the customer is staying in a cold region, the environmental adjustment unit can set a warm environment. If the customer is staying in a hot region, the environmental adjustment unit can also set a cool environment. Furthermore, if the customer is staying in a humid region, the environmental adjustment unit can adjust the humidity. In this way, a more appropriate environment can be provided by taking into account the customer's geographical location information. Some or all of the above processing in the environmental adjustment unit may be performed using AI or not. For example, the environmental adjustment unit can input the customer's geographical location information into the AI ​​and have the AI ​​perform the optimal environment setting.

[0047] The environment adjustment unit can analyze the customer's social media activity and adjust the environment when adjusting the room environment. For example, the environment adjustment unit can set the room based on the customer's preferred environment mentioned on social media. The environment adjustment unit can also set the environment based on the customer's interests from the content of their social media posts. Furthermore, the environment adjustment unit can set the room based on the environment preferred by the customer's social media followers. In this way, by analyzing the customer's social media activity, a more appropriate environment can be provided. Some or all of the above processing in the environment adjustment unit may be performed using AI or not. For example, the environment adjustment unit can input the customer's social media activity data into AI and have the AI ​​perform the environment adjustment.

[0048] The information provider can select the most relevant information by referring to the customer's past usage history when providing information. For example, the provider can provide information on similar restaurants based on information about restaurants the customer has used in the past. The provider can also estimate the customer's preferred services from their past usage history and provide that information. Furthermore, the provider can provide relevant event information based on information about events the customer has participated in in the past. By providing the most relevant information based on the customer's past usage history, the provider can provide more appropriate information. Some or all of the above processing in the information provider may be performed using AI or not. For example, the provider can input the customer's past usage history data into AI and have the AI ​​select the most relevant information.

[0049] The information provider can tailor the information provided based on the customer's current travel purpose. For example, if the customer is traveling for business, the provider can provide information on meeting rooms and business centers. If the customer is traveling for sightseeing, the provider can also provide information on tourist attractions and activities. Furthermore, if the customer is traveling for relaxation, the provider can provide information on spas and relaxation facilities. This allows for the provision of more relevant information by customizing it based on the customer's travel purpose. Some or all of the above processing in the information provider may be performed using AI or not. For example, the service provider can input customer travel purpose data into AI and have the AI ​​perform the information tailoring.

[0050] The information provider can select the most relevant information by considering the customer's geographical location when providing information. For example, the provider can prioritize providing information about restaurants close to the customer's current location. If the customer is staying in a specific area, the provider can also prioritize providing tourist information for that area. Furthermore, if the customer is on the move, the provider can prioritize providing information related to their next destination. This allows for the provision of more appropriate information by considering the customer's geographical location. Some or all of the above processing in the information provider may be performed using AI or not. For example, the service provider can input the customer's geographical location into an AI and have the AI ​​select the most relevant information.

[0051] The information provider can analyze the customer's social media activity and tailor the information provided. For example, the provider can provide information about places and events mentioned by the customer on social media. The provider can also provide information about activities the customer is interested in based on the content of their social media posts. Furthermore, the provider can provide information about places visited by the customer's social media followers. This allows for the provision of more relevant information by analyzing the customer's social media activity. Some or all of the above processing in the information provider may be performed using AI or not. For example, the provider can input the customer's social media activity data into an AI and have the AI ​​perform the information tailoring.

[0052] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0053] The AI ​​assistant for hotel accommodations can acquire guests' health data and customize services during their stay based on their health status. For example, if a guest uses a health management app, the AI ​​can acquire that data and suggest meal menus tailored to their health condition. It can also provide allergy-friendly meals if a guest has specific allergies. Furthermore, if a guest enjoys exercise, the AI ​​can provide information on the hotel's gym or nearby running routes. This allows for a more comfortable and healthy stay experience by providing services tailored to the guest's health needs.

[0054] The AI ​​assistant for accommodation support can analyze a guest's past stay history and suggest activities they might enjoy. For example, if a guest has previously used a spa, it can suggest spa use during their stay. Similarly, if a guest has previously visited a tourist destination, it can suggest nearby attractions. Furthermore, if a guest has previously dined at a specific restaurant, it can suggest making a reservation there. This allows for a more fulfilling stay experience by suggesting optimal activities based on the guest's past stay history.

[0055] The AI ​​assistant for hotel accommodations can provide nearby transportation information, taking into account the customer's geographical location. For example, if a customer arrives at the airport, it can suggest the best mode of transportation to the hotel. It can also provide transportation options and travel times to tourist destinations. Furthermore, if a customer is already on the move, it can provide information on the nearest transportation options from their current location. This allows for smoother travel by considering the customer's geographical location.

[0056] The AI ​​assistant for hotel accommodations can analyze customers' social media activity and suggest events and activities that might interest them. For example, if a customer has shown interest in a particular event on social media, the AI ​​can provide information about that event. It can also provide information about places visited by influencers the customer follows. Furthermore, it can suggest related activities based on activities the customer has mentioned on social media. This allows for a more fulfilling stay experience by suggesting the most suitable events and activities based on the customer's social media activity.

[0057] The AI-powered accommodation support assistant can suggest room layouts that guests prefer based on their past stay history. For example, if a guest previously preferred a spacious room, it can prioritize suggesting such rooms. It can also suggest rooms with specific views if a guest previously enjoyed a particular view. Furthermore, if a guest previously preferred a particular amenity, it can suggest rooms equipped with that amenity. This allows for a more comfortable stay experience by suggesting the optimal room layout based on the guest's past stay history.

[0058] The following briefly describes the processing flow for example form 1.

[0059] Step 1: The acquisition unit acquires reservation information regarding the customer's accommodation booking and preference information regarding the customer's preferences. For example, when a customer makes a reservation online, they input preference information such as their preferred room temperature, lighting, and music, along with their accommodation reservation information. This information is entered into the accommodation support AI assistant. The acquisition unit can use AI to analyze the customer's reservation information and preference information and save it in an appropriate format. Step 2: The Procedures Unit performs check-in and check-out procedures for the accommodation based on the reservation information acquired by the Acquisition Unit. For example, when a customer arrives at the accommodation, the AI ​​assistant automatically performs the check-in procedure and sends the smart key for the room to the customer's device. The Procedures Unit can also automatically create an invoice at check-out and send it to the customer's device. The Procedures Unit can use AI to efficiently perform check-in and check-out procedures. Step 3: The environment adjustment unit customizes the accommodation environment based on the preference information acquired by the acquisition unit. For example, it sets the temperature, lighting, and music preferred by the customer to provide the optimal stay experience. The environment adjustment unit can use AI to automatically adjust the room environment based on the customer's preferences.

[0060] (Example of form 2) An embodiment of the present invention provides an AI assistant for hotel accommodations that simplifies check-in and check-out procedures and provides information on hotel facilities and services, as well as nearby tourist attractions, based on the customer's reservation information and preferences. The AI ​​assistant acquires the customer's accommodation reservation information and preference information, performs check-in and check-out procedures, customizes the room environment, and provides an optimal stay experience. It also provides information on hotel facilities and services, as well as nearby tourist attractions. For example, when a customer makes a reservation online, the AI ​​assistant receives reservation information for the accommodation along with preference information such as preferred room temperature, lighting, and music. This information is entered into the AI ​​assistant. Next, the AI ​​assistant performs check-in and check-out procedures based on the acquired reservation information. For example, when the customer arrives at the accommodation, the AI ​​assistant automatically performs the check-in procedure and sends the smart key for the room to the customer's terminal device. Also, at check-out, the AI ​​assistant automatically creates an invoice and sends it to the customer's terminal device. Furthermore, the AI ​​assistant customizes the room environment based on the acquired preference information. For example, it sets the customer's preferred temperature, lighting, and music to provide an optimal stay experience. This allows guests to enjoy a comfortable environment tailored to their preferences. The AI-powered accommodation support assistant also provides information on facilities and services within the accommodation, as well as nearby tourist attractions. For example, it can provide information on restaurant reservation availability, spa hours, and nearby tourist spots and events. This makes it easy for guests to understand the facilities, services, and tourist information available during their stay. This system simplifies check-in and check-out procedures, resulting in a more comfortable stay. Providing information on facilities, services, and nearby tourist attractions also improves guest convenience and increases satisfaction. As a result, the AI-powered accommodation support assistant can simplify check-in and check-out procedures based on guest reservation information and preferences, providing an optimal stay experience.

[0061] The accommodation support AI assistant according to this embodiment comprises an acquisition unit, a procedure unit, and an environment adjustment unit. The acquisition unit acquires reservation information regarding the customer's accommodation reservation and preference information regarding the customer's preferences. For example, when a customer makes a reservation online, the acquisition unit inputs preference information such as preferred room temperature, lighting, and music along with the accommodation reservation information. This information is input to the accommodation support AI assistant. The acquisition unit can use AI to analyze the customer's reservation information and preference information and store it in an appropriate format. The procedure unit performs check-in and check-out procedures for the accommodation based on the reservation information acquired by the acquisition unit. For example, when a customer arrives at the accommodation, the procedure unit has the AI ​​assistant automatically perform the check-in procedure and send the smart key for the room to the customer's terminal device. The procedure unit can also automatically create an invoice at check-out and send it to the customer's terminal device. The procedure unit can use AI to efficiently perform check-in and check-out procedures. The environment adjustment unit customizes the environment of the accommodation based on the preference information acquired by the acquisition unit. The environmental adjustment unit, for example, sets the temperature, lighting, and music preferred by the customer to provide an optimal stay experience. The environmental adjustment unit can use AI to automatically adjust the room environment based on the customer's preferences. As a result, the accommodation support AI assistant according to this embodiment can simplify check-in and check-out procedures and provide an optimal stay experience based on the customer's reservation information and preferences.

[0062] The acquisition unit acquires reservation information regarding the customer's accommodation bookings and preference information regarding the customer's preferences. For example, when a customer makes a reservation online, the acquisition unit inputs preference information such as preferred room temperature, lighting, and music, along with the accommodation reservation information. This information is entered into the accommodation support AI assistant. The acquisition unit can use AI to analyze the customer's reservation and preference information and store it in an appropriate format. Specifically, the acquisition unit collects information entered by the customer in the reservation form in real time, and the AI ​​analyzes that information. For example, if the customer's preferred room temperature setting is 22 degrees, the AI ​​analyzes this information and stores it in the customer preference database. Similarly, if the customer prefers a particular music genre, that information is also stored. Furthermore, the acquisition unit can update preference information based on the customer's past stay history and feedback. For example, if the customer changed a specific temperature setting during a previous stay, the AI ​​will use that information to suggest the optimal setting for their next stay. This allows the acquisition unit to gain a detailed understanding of customer preferences and build a foundation for providing personalized services. In addition, the acquisition unit can also link customer preference information with other systems. For example, by acquiring preference information provided by customers through other services and integrating it into the accommodation support AI assistant, a more consistent service can be provided. This allows the data acquisition unit to respond to diverse customer needs and provide a more personalized accommodation experience.

[0063] The Procedures Department handles check-in and check-out procedures for accommodations based on reservation information acquired by the Acquisition Department. For example, when a guest arrives at the accommodation, the Procedures Department's AI assistant automatically completes the check-in process and sends a smart key to the guest's device. The Procedures Department can also automatically create an invoice at check-out and send it to the guest's device. The Procedures Department can efficiently perform check-in and check-out procedures using AI. Specifically, the Procedures Department prepares the check-in process in advance based on the guest's estimated arrival time. When the guest arrives at the accommodation, the AI ​​assistant automatically detects the guest's arrival and starts the check-in process. For example, it sends a notification to the guest's smartphone to confirm the necessary information. Once confirmation is complete, a smart key is sent to the guest's device, allowing the guest to enter their room smoothly. At check-out, the Procedures Department automatically creates an invoice and sends it to the guest's device. The invoice includes the accommodation fee and any additional service charges, and the guest can complete the payment online. Furthermore, the Procedures Department can collect customer feedback to help improve services. For example, it can send a survey after check-out to understand customer satisfaction and areas for improvement. This allows the procedures department to process check-in and check-out efficiently and quickly, improving customer convenience.

[0064] The Environmental Adjustment Unit customizes the accommodation environment based on preference information acquired by the Acquisition Unit. For example, the Environmental Adjustment Unit sets the temperature, lighting, and music preferred by the customer to provide an optimal stay experience. The Environmental Adjustment Unit can use AI to automatically adjust the room environment based on customer preferences. Specifically, the Environmental Adjustment Unit adjusts the room environment based on pre-set preference information before the customer enters the room. For example, if the customer prefers a temperature of 22 degrees Celsius, the unit sets the room temperature to 22 degrees and plays music preferred by the customer. It can also adjust the brightness and color temperature of the lighting to match the customer's preferences. Furthermore, the Environmental Adjustment Unit can adjust the environment in real time during the customer's stay. For example, if the customer changes the room temperature, it will use that information to suggest the optimal settings for their next stay. The Environmental Adjustment Unit can also collect customer feedback and use it to improve services. For example, it can check whether the customer is satisfied with a particular setting and make adjustments as needed. In this way, the Environmental Adjustment Unit can optimize the room environment based on customer preferences and provide a more comfortable stay experience. Furthermore, the environmental control unit can work in conjunction with other systems to perform more advanced environmental adjustments. For example, it can integrate with smart home devices to adjust lighting, music, and temperature based on customer preferences. This allows the environmental control unit to respond to diverse customer needs and provide a more personalized stay experience.

[0065] The procedure unit can perform check-in procedures and send a smart key to the room to the customer's terminal device based on the reservation information acquired by the acquisition unit. For example, when the customer arrives at the accommodation, the procedure unit's AI assistant can automatically perform check-in procedures and send a smart key to the room to the customer's terminal device. The procedure unit can send the smart key in the form of a digital key, QR code, NFC, etc. This automates the check-in procedure and enables a smooth check-in by sending the smart key to the customer's terminal device. Some or all of the above processing in the procedure unit may be performed using AI or not. For example, the procedure unit can input the reservation information acquired by the acquisition unit into the AI ​​and have the AI ​​perform the check-in procedure.

[0066] The procedures department can automatically create an invoice at checkout and send it to the customer's terminal device. For example, the procedures department can have an AI assistant automatically create an invoice at checkout and send it to the customer's terminal device. The invoice would include accommodation charges, additional service charges, taxes, etc. This automates the checkout process and enables a smooth checkout by sending the invoice to the customer's terminal device. Some or all of the above processes in the procedures department may be performed using AI or not. For example, the procedures department can have the AI ​​create the invoice at checkout.

[0067] The environmental control unit can control the room temperature, lighting, and music. For example, the environmental control unit can set the temperature, lighting, and music to the customer's preference to provide an optimal stay experience. The environmental control unit can adjust the temperature range, lighting brightness, music type, etc. This allows for the provision of an optimal stay experience by adjusting the room environment based on the customer's preferences. Some or all of the above processing in the environmental control unit may be performed using AI or not. For example, the environmental control unit can input customer preference information into the AI ​​and have the AI ​​perform the adjustment of the room environment.

[0068] The acquisition unit can estimate the customer's emotions and control the timing of acquiring reservation information based on the estimated emotions. For example, if the customer is stressed, the acquisition unit will acquire the reservation information when the customer is relaxed. If the customer is busy, the acquisition unit can also acquire the reservation information during a less busy time. Furthermore, if the customer is traveling, the acquisition unit can acquire the reservation information after arrival. This allows for more appropriate timing of information acquisition by adjusting the timing of acquisition according to the customer's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the acquisition unit may be performed using AI or not. For example, the acquisition unit can input customer emotion data into AI and have the AI ​​adjust the timing of reservation information acquisition.

[0069] The data acquisition unit can analyze a customer's past accommodation history and select a data acquisition method. For example, the data acquisition unit can prioritize acquiring reservation information for similar accommodations based on information about accommodations the customer has used in the past. The data acquisition unit can also estimate a customer's preferred room type from their past accommodation history and acquire that information. Furthermore, the data acquisition unit can acquire relevant reservation information based on services the customer has used in the past. By selecting the optimal data acquisition method based on the customer's past accommodation history, more appropriate information can be obtained. Some or all of the above processing in the data acquisition unit may be performed using AI or not. For example, the data acquisition unit can input the customer's past accommodation history data into AI and have the AI ​​select the optimal data acquisition method.

[0070] The data acquisition unit can filter reservation information based on the customer's current travel purpose and areas of interest. For example, if the customer is traveling for business, the data acquisition unit will prioritize information on meeting rooms and business centers. If the customer is traveling for sightseeing, the data acquisition unit can also acquire information on tourist attractions and activities. Furthermore, if the customer is traveling for relaxation, the data acquisition unit can acquire information on spas and relaxation facilities. By filtering information based on the customer's travel purpose and areas of interest, more relevant information can be provided. Some or all of the above processing in the data acquisition unit may be performed using AI or not. For example, the data acquisition unit can input data on the customer's travel purpose and areas of interest into the AI ​​and have the AI ​​perform the information filtering.

[0071] The acquisition unit can estimate the customer's emotions and set priorities for acquiring reservation information based on the estimated emotions. For example, if the customer is tired, the acquisition unit may prioritize acquiring information about relaxation facilities. If the customer is excited, the acquisition unit may also prioritize acquiring information about activities and events. Furthermore, if the customer is relaxed, the acquisition unit may also prioritize acquiring information about restaurants and cafes. This allows for the provision of more appropriate information by determining the priority of information according to the customer's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the acquisition unit may be performed using AI or not. For example, the acquisition unit can input customer emotion data into AI and have the AI ​​perform the setting of reservation information priorities.

[0072] The acquisition unit can prioritize the acquisition of highly relevant information by considering the customer's geographical location when acquiring reservation information. For example, the acquisition unit can prioritize the acquisition of information on accommodations close to the customer's current location. If the customer is staying in a specific region, the acquisition unit can also prioritize the acquisition of tourist information for that region. Furthermore, if the customer is on the move, the acquisition unit can prioritize the acquisition of information related to their next destination. This allows for the provision of more relevant information by considering the customer's geographical location. Some or all of the above processing in the acquisition unit may be performed using AI or not. For example, the acquisition unit can input the customer's geographical location information into the AI ​​and have the AI ​​perform the acquisition of highly relevant information.

[0073] The data acquisition unit can analyze the customer's social media activity and acquire relevant information when acquiring reservation information. For example, the data acquisition unit can acquire information about places and events mentioned by the customer on social media. The data acquisition unit can also acquire information about activities the customer is interested in from the content of the customer's social media posts. Furthermore, the data acquisition unit can acquire information about places visited by the customer's social media followers. This allows for the provision of more relevant information by analyzing the customer's social media activity. Some or all of the above processing in the data acquisition unit may be performed using AI or not. For example, the data acquisition unit can input the customer's social media activity data into an AI and have the AI ​​perform the acquisition of relevant information.

[0074] The procedure unit can estimate the customer's emotions and control how the check-in procedure is presented based on the estimated emotions. For example, if the customer is nervous, the procedure unit can provide a simple and highly visible interface. If the customer is relaxed, the procedure unit can also provide an interface with more detailed information. Furthermore, if the customer is in a hurry, the procedure unit can provide an interface that allows for quick completion of the procedure. This allows for a more appropriate procedure to be provided by adjusting how the check-in procedure is presented according to the customer's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the procedure unit may be performed using AI or not. For example, the procedure unit can input customer emotion data into AI and have the AI ​​adjust how the check-in procedure is presented.

[0075] The procedures department can select the most suitable procedure during the check-in process by referring to the customer's past check-in history. For example, the procedures department may prioritize suggesting check-in methods the customer has used in the past. The procedures department can also estimate and suggest preferred procedures based on the customer's past check-in history. Furthermore, the procedures department can suggest similar procedures based on information about accommodations the customer has used in the past. This allows for a smoother check-in process by selecting the most suitable procedure based on the customer's past check-in history. Some or all of the above processes in the procedures department may be performed using AI or not. For example, the procedures department can input the customer's past check-in history data into an AI and have the AI ​​select the most suitable procedure.

[0076] The procedures department can adjust the check-in process based on the customer's current travel purpose. For example, if the customer is traveling for business, the procedures department can provide a faster check-in process. If the customer is traveling for sightseeing, the procedures department can also provide a check-in process that includes sightseeing information. Furthermore, if the customer is traveling for relaxation, the procedures department can also provide a check-in process that includes information on relaxation facilities. This allows for a more appropriate check-in process by customizing the process based on the customer's travel purpose. Some or all of the above processing in the procedures department may be performed using AI or not. For example, the procedures department can input customer travel purpose data into the AI ​​and have the AI ​​perform the adjustments to the process.

[0077] The procedure unit can estimate the customer's emotions and prioritize check-in procedures based on the estimated emotions. For example, if the customer is tired, the procedure unit may perform the check-in procedure quickly. If the customer is excited, the procedure unit may perform a check-in procedure that includes detailed information. If the customer is relaxed, the procedure unit may perform the check-in procedure at a leisurely pace. This allows for the provision of more appropriate procedures by determining the priority of check-in procedures according to the customer's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the procedure unit may be performed using AI or not. For example, the procedure unit can input customer emotion data into AI and have the AI ​​perform the setting of check-in procedure priorities.

[0078] The procedures unit can select the most appropriate procedure during the check-in process, taking into account the customer's geographical location. For example, the procedures unit can suggest the most appropriate check-in procedure based on information about accommodations near the customer's current location. If the customer is staying in a specific region, the procedures unit can also suggest a check-in procedure that includes information about that region. Furthermore, if the customer is on the move, the procedures unit can suggest a check-in procedure related to their next destination. This allows for the provision of a more appropriate check-in procedure by considering the customer's geographical location. Some or all of the above processing in the procedures unit may be performed using AI or not. For example, the procedures unit can input the customer's geographical location information into the AI ​​and have the AI ​​select the most appropriate procedure.

[0079] The procedures department can analyze a customer's social media activity and adjust the check-in process accordingly. For example, the procedures department can customize the check-in process based on information about accommodations mentioned by the customer on social media. The procedures department can also suggest check-in procedures that include services the customer is interested in, based on the content of the customer's social media posts. Furthermore, the procedures department can customize the check-in process based on information about accommodations used by the customer's social media followers. This allows for the provision of more appropriate check-in procedures by analyzing the customer's social media activity. Some or all of the above processes in the procedures department may be performed using AI or not. For example, the procedures department can input customer social media activity data into AI and have the AI ​​perform the adjustments to the procedure.

[0080] The environment adjustment unit can estimate the customer's emotions and control the room environment based on the estimated emotions. For example, if the customer is relaxed, the environment adjustment unit can set calming lighting and music. If the customer is excited, the environment adjustment unit can also set bright lighting and lively music. Furthermore, if the customer is tired, the environment adjustment unit can set a warm temperature and a quiet environment. This allows for a more comfortable stay experience by adjusting the room environment according to the customer's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the environment adjustment unit may be performed using AI or not. For example, the environment adjustment unit can input customer emotion data into AI and have the AI ​​perform the room environment adjustments.

[0081] The environment adjustment unit can set the optimal environment by referring to the customer's past stay history when adjusting the room environment. For example, the environment adjustment unit can adjust the room temperature based on the customer's preferred temperature settings in the past. The environment adjustment unit can also estimate and adjust the customer's preferred lighting settings from their past stay history. Furthermore, the environment adjustment unit can set the room's music based on the music the customer has listened to in the past. In this way, by setting the optimal environment based on the customer's past stay history, a more comfortable stay experience can be provided. Some or all of the above processes in the environment adjustment unit may be performed using AI or not. For example, the environment adjustment unit can input the customer's past stay history data into AI and have the AI ​​perform the optimal environment setting.

[0082] The environmental adjustment unit can adjust the room environment based on the customer's current health condition. For example, if the customer is tired, the environmental adjustment unit can set up a relaxing environment. If the customer is seeking healthy exercise, the environmental adjustment unit can also set up an environment suitable for exercise. Furthermore, if the customer is feeling unwell, the environmental adjustment unit can set up a comfortable environment. This allows for a more comfortable stay experience by customizing the environment according to the customer's health condition. Some or all of the above processes in the environmental adjustment unit may be performed using AI or not. For example, the environmental adjustment unit can input customer health data into AI and have the AI ​​perform the environmental adjustments.

[0083] The environment adjustment unit can estimate the customer's emotions and prioritize the room environment based on the estimated emotions. For example, if the customer is relaxed, the environment adjustment unit will prioritize lighting and music settings. If the customer is excited, the environment adjustment unit may also prioritize temperature and music settings. Furthermore, if the customer is tired, the environment adjustment unit may also prioritize temperature and lighting settings. This allows for a more comfortable stay experience by determining environmental priorities according to the customer's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the environment adjustment unit may be performed using AI or not. For example, the environment adjustment unit can input customer emotion data into AI and have the AI ​​perform the setting of environmental priorities.

[0084] The environmental adjustment unit can set the optimal environment when adjusting the room environment, taking into account the customer's geographical location information. For example, if the customer is staying in a cold region, the environmental adjustment unit can set a warm environment. If the customer is staying in a hot region, the environmental adjustment unit can also set a cool environment. Furthermore, if the customer is staying in a humid region, the environmental adjustment unit can adjust the humidity. In this way, a more appropriate environment can be provided by taking into account the customer's geographical location information. Some or all of the above processing in the environmental adjustment unit may be performed using AI or not. For example, the environmental adjustment unit can input the customer's geographical location information into the AI ​​and have the AI ​​perform the optimal environment setting.

[0085] The environment adjustment unit can analyze the customer's social media activity and adjust the environment when adjusting the room environment. For example, the environment adjustment unit can set the room based on the customer's preferred environment mentioned on social media. The environment adjustment unit can also set the environment based on the customer's interests from the content of their social media posts. Furthermore, the environment adjustment unit can set the room based on the environment preferred by the customer's social media followers. In this way, by analyzing the customer's social media activity, a more appropriate environment can be provided. Some or all of the above processing in the environment adjustment unit may be performed using AI or not. For example, the environment adjustment unit can input the customer's social media activity data into AI and have the AI ​​perform the environment adjustment.

[0086] The service provider can estimate the customer's emotions and control how the information is displayed based on the estimated emotions. For example, if the customer is nervous, the service provider can provide a simple and highly visible display method. If the customer is relaxed, the service provider can also provide a display method that includes detailed information. Furthermore, if the customer is in a hurry, the service provider can provide a concise display method. This allows for the provision of more appropriate information by adjusting the display method according to the customer's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the service provider may be performed using AI or not. For example, the service provider can input customer emotion data into AI and have the AI ​​adjust the display method of the information.

[0087] The information provider can select the most relevant information by referring to the customer's past usage history when providing information. For example, the provider can provide information on similar restaurants based on information about restaurants the customer has used in the past. The provider can also estimate the customer's preferred services from their past usage history and provide that information. Furthermore, the provider can provide relevant event information based on information about events the customer has participated in in the past. By providing the most relevant information based on the customer's past usage history, the provider can provide more appropriate information. Some or all of the above processing in the information provider may be performed using AI or not. For example, the provider can input the customer's past usage history data into AI and have the AI ​​select the most relevant information.

[0088] The information provider can tailor the information provided based on the customer's current travel purpose. For example, if the customer is traveling for business, the provider can provide information on meeting rooms and business centers. If the customer is traveling for sightseeing, the provider can also provide information on tourist attractions and activities. Furthermore, if the customer is traveling for relaxation, the provider can provide information on spas and relaxation facilities. This allows for the provision of more relevant information by customizing it based on the customer's travel purpose. Some or all of the above processing in the information provider may be performed using AI or not. For example, the service provider can input customer travel purpose data into AI and have the AI ​​perform the information tailoring.

[0089] The service provider can estimate the customer's emotions and prioritize the information it provides based on those emotions. For example, if the customer is tired, the service provider might prioritize information about relaxation facilities. If the customer is excited, it might prioritize information about activities and events. If the customer is relaxed, it might prioritize information about restaurants and cafes. By prioritizing information according to the customer's emotions, the service provider can provide more appropriate information. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the service provider may be performed using AI or not. For example, the service provider can input customer emotion data into an AI and have the AI ​​prioritize information.

[0090] The information provider can select the most relevant information by considering the customer's geographical location when providing information. For example, the provider can prioritize providing information about restaurants close to the customer's current location. If the customer is staying in a specific area, the provider can also prioritize providing tourist information for that area. Furthermore, if the customer is on the move, the provider can prioritize providing information related to their next destination. This allows for the provision of more appropriate information by considering the customer's geographical location. Some or all of the above processing in the information provider may be performed using AI or not. For example, the service provider can input the customer's geographical location into an AI and have the AI ​​select the most relevant information.

[0091] The information provider can analyze the customer's social media activity and tailor the information provided. For example, the provider can provide information about places and events mentioned by the customer on social media. The provider can also provide information about activities the customer is interested in based on the content of their social media posts. Furthermore, the provider can provide information about places visited by the customer's social media followers. This allows for the provision of more relevant information by analyzing the customer's social media activity. Some or all of the above processing in the information provider may be performed using AI or not. For example, the provider can input the customer's social media activity data into an AI and have the AI ​​perform the information tailoring.

[0092] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0093] The AI ​​assistant for hotel accommodations can acquire guests' health data and customize services during their stay based on their health status. For example, if a guest uses a health management app, the AI ​​can acquire that data and suggest meal menus tailored to their health condition. It can also provide allergy-friendly meals if a guest has specific allergies. Furthermore, if a guest enjoys exercise, the AI ​​can provide information on the hotel's gym or nearby running routes. This allows for a more comfortable and healthy stay experience by providing services tailored to the guest's health needs.

[0094] The AI ​​assistant for accommodation support can estimate a guest's emotions and change the room's decor based on that estimation. For example, if a guest is feeling stressed, it can place relaxing aromatherapy scents or plants in the room. If a guest is happy, it can place bright-colored decorations or flowers in the room. Furthermore, if a guest is tired, it can set the decor to calming colors and soft lighting. By providing room decorations that match the guest's emotions, it can offer a more comfortable stay experience.

[0095] The AI ​​assistant for accommodation support can analyze a guest's past stay history and suggest activities they might enjoy. For example, if a guest has previously used a spa, it can suggest spa use during their stay. Similarly, if a guest has previously visited a tourist destination, it can suggest nearby attractions. Furthermore, if a guest has previously dined at a specific restaurant, it can suggest making a reservation there. This allows for a more fulfilling stay experience by suggesting optimal activities based on the guest's past stay history.

[0096] The AI ​​assistant for accommodation support can estimate a guest's emotions and suggest activities during their stay based on those estimates. For example, if a guest is excited, it can suggest active events or parties. If a guest is relaxed, it can suggest quiet reading groups or yoga classes. Furthermore, if a guest is tired, it can suggest relaxation massages or use of the hot springs. This allows for a more appropriate stay experience by suggesting activities that match the guest's emotions.

[0097] The AI ​​assistant for hotel accommodations can provide nearby transportation information, taking into account the customer's geographical location. For example, if a customer arrives at the airport, it can suggest the best mode of transportation to the hotel. It can also provide transportation options and travel times to tourist destinations. Furthermore, if a customer is already on the move, it can provide information on the nearest transportation options from their current location. This allows for smoother travel by considering the customer's geographical location.

[0098] The AI ​​assistant for hotel accommodations can estimate a guest's emotions and customize the checkout process based on those emotions. For example, if a guest is in a hurry, the checkout process can be expedited. If a guest is relaxed, the checkout process can be conducted at a leisurely pace. Furthermore, if a guest is feeling anxious, the system can provide a checkout process that includes detailed explanations. This allows for a smoother checkout experience by providing a checkout process tailored to the guest's emotions.

[0099] The AI ​​assistant for hotel accommodations can analyze customers' social media activity and suggest events and activities that might interest them. For example, if a customer has shown interest in a particular event on social media, the AI ​​can provide information about that event. It can also provide information about places visited by influencers the customer follows. Furthermore, it can suggest related activities based on activities the customer has mentioned on social media. This allows for a more fulfilling stay experience by suggesting the most suitable events and activities based on the customer's social media activity.

[0100] The AI ​​assistant for accommodation support can estimate a guest's emotions and adjust the room cleaning schedule based on that estimation. For example, if a guest is relaxed, cleaning can be delayed to provide a quiet environment. Conversely, if a guest is active, cleaning can be done earlier to provide a clean environment. Furthermore, if a guest is tired, cleaning can be minimized to prioritize rest. This allows for a more comfortable stay experience by providing a cleaning schedule tailored to the guest's emotions.

[0101] The AI-powered accommodation support assistant can suggest room layouts that guests prefer based on their past stay history. For example, if a guest previously preferred a spacious room, it can prioritize suggesting such rooms. It can also suggest rooms with specific views if a guest previously enjoyed a particular view. Furthermore, if a guest previously preferred a particular amenity, it can suggest rooms equipped with that amenity. This allows for a more comfortable stay experience by suggesting the optimal room layout based on the guest's past stay history.

[0102] The AI ​​assistant for accommodation support can estimate a guest's emotions and adjust the schedule of activities during their stay based on those estimates. For example, if a guest is relaxed, relaxation activities can be prioritized. If a guest is excited, active activities can be prioritized. Furthermore, if a guest is tired, a schedule prioritizing rest can be provided. This allows for a more comfortable stay experience by providing activity schedules tailored to the guest's emotions.

[0103] The following briefly describes the processing flow for example form 2.

[0104] Step 1: The acquisition unit acquires reservation information regarding the customer's accommodation booking and preference information regarding the customer's preferences. For example, when a customer makes a reservation online, they input preference information such as their preferred room temperature, lighting, and music, along with their accommodation reservation information. This information is entered into the accommodation support AI assistant. The acquisition unit can use AI to analyze the customer's reservation information and preference information and save it in an appropriate format. Step 2: The Procedures Unit performs check-in and check-out procedures for the accommodation based on the reservation information acquired by the Acquisition Unit. For example, when a customer arrives at the accommodation, the AI ​​assistant automatically performs the check-in procedure and sends the smart key for the room to the customer's device. The Procedures Unit can also automatically create an invoice at check-out and send it to the customer's device. The Procedures Unit can use AI to efficiently perform check-in and check-out procedures. Step 3: The environment adjustment unit customizes the accommodation environment based on the preference information acquired by the acquisition unit. For example, it sets the temperature, lighting, and music preferred by the customer to provide the optimal stay experience. The environment adjustment unit can use AI to automatically adjust the room environment based on the customer's preferences.

[0105] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0106] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0107] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0108] For example, the acquisition unit can acquire customer reservation information and preference information using the camera 42 and microphone 38B of the smart device 14, and analyze it using the control unit 46A. The procedure unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and efficiently performs check-in and check-out procedures. The environment adjustment unit is implemented, for example, by the control unit 46A of the smart device 14, and automatically adjusts the room environment based on customer preferences. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various modifications are possible.

[0109] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0110] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0111] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0112] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0113] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0114] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0115] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0116] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0117] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0118] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0119] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0120] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0121] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0122] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0123] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0124] For example, the acquisition unit can acquire customer reservation information and preference information using the camera 42 and microphone 238 of the smart glasses 214, and analyze it using the control unit 46A. The procedure unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and efficiently performs check-in and check-out procedures. The environment adjustment unit is implemented, for example, by the control unit 46A of the smart glasses 214, and automatically adjusts the room environment based on customer preferences. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various modifications are possible.

[0125] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0126] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0127] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0128] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0129] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0130] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0131] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0132] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0133] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0134] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0135] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0136] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0137] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0138] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0139] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0140] For example, the acquisition unit can acquire customer reservation information and preference information using the camera 42 and microphone 238 of the headset terminal 314, and analyze it using the control unit 46A. The procedure unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and efficiently performs check-in and check-out procedures. The environment adjustment unit is implemented, for example, by the control unit 46A of the headset terminal 314, and automatically adjusts the room environment based on customer preferences. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various modifications are possible.

[0141] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0142] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0143] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0144] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0145] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0146] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0147] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0148] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0149] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0150] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0151] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0152] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0153] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0154] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0155] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0156] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0157] For example, the acquisition unit can acquire customer reservation information and preference information using the camera 42 and microphone 238 of the robot 414, and analyze it using the control unit 46A. The procedure unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and efficiently performs check-in and check-out procedures. The environment adjustment unit is implemented, for example, by the control unit 46A of the robot 414, and automatically adjusts the room environment based on customer preferences. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various modifications are possible.

[0158] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0159] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0160] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0161] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0162] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0163] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0164] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0165] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0166] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0167] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0168] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0169] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0170] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0171] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0172] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0173] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0174] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0175] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0176] (Note 1) Customer booking information regarding accommodation reservations, An acquisition unit that acquires preference information relating to the customer's preferences, Based on the reservation information acquired by the aforementioned acquisition unit, a procedure unit performs check-in and check-out procedures for the accommodation facility. The facility includes an environment adjustment unit that adjusts the environment of the accommodation based on preference information acquired by the acquisition unit. A system characterized by the following features. (Note 2) The aforementioned procedural unit, Based on the reservation information acquired by the aforementioned acquisition unit, the check-in procedure is performed and the smart key for the room is sent to the customer's terminal device. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned procedural unit, The system automatically generates an invoice at checkout and sends it to the customer's terminal device. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned environmental adjustment unit is Control room temperature, lighting, and music. The system described in Appendix 1, characterized by the features described herein. (Note 5) The acquisition unit is, It estimates customer emotions and controls the timing of acquiring reservation information based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 6) The acquisition unit is, Analyze the customer's past stay history and select the method for obtaining it. The system described in Appendix 1, characterized by the features described herein. (Note 7) The acquisition unit is, When retrieving booking information, filtering is performed based on the customer's current travel purpose or areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 8) The acquisition unit is, The system estimates customer sentiment and prioritizes the reservation information to be retrieved based on that estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 9) The acquisition unit is, When retrieving reservation information, the system prioritizes retrieving highly relevant information based on the customer's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 10) The acquisition unit is, When acquiring reservation information, the system analyzes the customer's social media activity and retrieves relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned procedural unit, It estimates customer emotions and controls how the check-in process is presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned procedural unit, During the check-in process, the procedure is selected based on the customer's past check-in history. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned procedural unit, During the check-in process, we will adjust the procedure based on the customer's current travel purpose. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned procedural unit, The system estimates customer emotions and prioritizes check-in procedures based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned procedural unit, During the check-in process, the procedure is selected based on the customer's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned procedural unit, During the check-in process, we analyze the customer's social media activity and adjust the procedure accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned environmental adjustment unit is It estimates the customer's emotions and controls the room environment based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned environmental adjustment unit is When adjusting the room environment, the environment is set based on the customer's past stay history. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned environmental adjustment unit is When adjusting the room environment, we adjust it based on the customer's current health condition. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned environmental adjustment unit is It estimates customer emotions and prioritizes the room environment based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned environmental adjustment unit is When adjusting the room environment, the environment is set based on the customer's geographical location information. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned environmental adjustment unit is When adjusting the room environment, we analyze the customer's social media activity and adjust the environment accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned supply unit is, It estimates customer emotions and controls how information is displayed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned supply unit is, When providing information, we select information based on the customer's past usage history. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned supply unit is, When providing information, we adjust the information based on the customer's current travel purpose. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned supply unit is, Estimate customer emotions and prioritize the information provided based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned supply unit is, When providing information, select information based on the customer's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned supply unit is, When providing information, we analyze the customer's social media activity and adjust the information accordingly. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0177] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. An acquisition unit that acquires reservation information regarding the customer's accommodation reservations and preference information regarding the customer's preferences, Based on the reservation information acquired by the aforementioned acquisition unit, a procedure unit performs check-in and check-out procedures for the accommodation facility. The facility includes an environment adjustment unit that adjusts the environment of the accommodation based on preference information acquired by the acquisition unit. A system characterized by the following features.

2. The aforementioned procedural unit, Based on the reservation information acquired by the acquisition unit, the check-in procedure is performed and the smart key for the room is transmitted to the customer's terminal device. The system according to feature 1.

3. The aforementioned procedural unit, The system automatically generates an invoice at checkout and sends it to the customer's terminal device. The system according to feature 1.

4. The aforementioned environmental adjustment unit is Control room temperature, lighting, and music. The system according to feature 1.

5. The acquisition unit is, The system estimates the customer's emotions and controls the timing of acquiring reservation information based on the estimated customer emotions. The system according to feature 1.

6. The acquisition unit is, Analyze the customer's past accommodation history and select a method for obtaining that history. The system according to feature 1.

7. The acquisition unit is, When retrieving reservation information, filtering is performed based on the customer's current travel purpose or areas of interest. The system according to feature 1.

8. The acquisition unit is, The system estimates the customer's emotions and sets a priority for acquiring reservation information based on the estimated customer emotions. The system according to feature 1.

9. The acquisition unit is, When acquiring reservation information, the system prioritizes acquiring information that is highly relevant based on the customer's geographical location. The system according to feature 1.

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