System

Abstract

A system is provided.SOLUTION: The system includes a means for receiving a request for a camp plan from a user, a means for requesting recommendation information of a campground to a server, a means for generating the recommendation information of the campground based on position information of the user and a past history, and a means for presenting the recommendation information to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In conventional camping planning, users have to manually research and select the optimal campsite, clothing, equipment, activities, and stops along the way, which requires time and effort. In addition, there is a lack of a way to provide optimal suggestions based on individual user preferences and past history, making it difficult for users to make optimal choices due to information overload. [Means for solving the problem]

[0005] The present invention provides a system including means for receiving a camping plan request from a user, means for requesting campsite recommendation information from a server, means for generating the campsite recommendation information based on the user's location information and past history, and means for presenting the recommendation information to the user. The system also provides means for receiving from the user suggestions for clothing suitable for camping, generating appropriate clothing information based on the suggestions, and presenting the information to the user. A list of camping gear is received from the user, generating gear setup information based on the list, and presenting the information to the user. A system for receiving from the user suggestions for activities to be performed during camping, generating appropriate activity information based on the suggestions, and presenting the information to the user. Information about scenic spots and hidden hot springs that can be visited along the way is received from the user, generating route spot information based on the information, and presenting the information to the user. This allows users to efficiently plan and execute a comfortable and fulfilling camping experience.

[0006] "User" refers to an individual or organization that uses this system to make camping plans or obtain information.

[0007] "Camp planning" refers to the process of preparing everything before a camp, selecting activities, arranging equipment, etc.

[0008] A "campground" is a designated area for outdoor lodging and activities.

[0009] "Recommendation information" refers to the best options and suggestions that the system presents to the user.

[0010] "Location information" refers to geographic data about a user's current location or a specific place.

[0011] "Past history" refers to data on past actions and choices made by the user using this system.

[0012] "Clothing suggestions" refers to the system instructing the user on appropriate clothing for camping.

[0013] "Equipment setup" refers to preparing the equipment and supplies needed for camping and making them ready for use.

[0014] "Activities" refers to the various experiences and activities that take place during camp.

[0015] "Scenic spots" refer to scenic locations that are worth visiting along the way or at the user's destination.

[0016] "Secret hot springs" refer to particularly quiet hot springs with fewer people than regular tourist destinations.

[0017] "System" refers to the entire structure including the user interface, server, communication means, and other related hardware and software. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a 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.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also 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).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] This invention relates to an interactive system that allows users to efficiently plan camping trips. The system according to this invention receives a camping trip plan request from a user, generates appropriate information in response to the request, and presents it to the user. This system is mainly implemented with the following configuration.

[0040] User Interface

[0041] This is the interface through which users enter details of their camping plans and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about spots along the way.

[0042] server

[0043] The server generates information in response to user requests and returns it to the device. Specifically, it implements databases and algorithms for generating campsite recommendations, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on road spots.

[0044] Processing flow

[0045] 1. Select a campsite

[0046] The user launches the app and requests to select a campsite.

[0047] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[0048] The server refers to the user's location information and past history and recommends the most suitable campsite.

[0049] The device will display recommended campsites. "The recommended campsites are as follows: 1. Mt. Fuji Campsite 2. Mt. Mitake Campsite."

[0050] 2. Clothing suggestions

[0051] The user asks about clothing.

[0052] User: "What should I wear when I go camping?"

[0053] The server will suggest appropriate clothing based on weather and seasonal data: "Consider light layers, long-sleeved shirts, waterproof jackets, and hiking boots."

[0054] The device will display clothing suggestions.

[0055] 3. Tool Setup

[0056] A user asks about camping equipment.

[0057] User: "What equipment do I need for camping?"

[0058] The server generates a list of basic camping equipment: "You'll need a tent, sleeping bag, cooking equipment, a lantern, and a first aid kit."

[0059] The terminal displays the tool list to the user.

[0060] 4. Outdoor cooking recipe suggestions

[0061] A user asks about camping recipes.

[0062] User: "Tell me some easy camping recipes."

[0063] The server generates recipe information for simple camping meals. "You can easily make things like foil-roasted vegetables, campfire burgers, and s'mores."

[0064] The device displays the cooking recipe to the user.

[0065] 5. Activity suggestions

[0066] Ask about activities users can enjoy while camping.

[0067] User: "What activities can I enjoy while camping?"

[0068] The server generates the appropriate activity information: "Enjoy hiking, kayaking, fishing, stargazing around a campfire, and more."

[0069] The terminal displays the activity information to the user.

[0070] 6. Information on scenic spots and hidden hot springs along the way

[0071] Ask about places users can stop along the way.

[0072] User: "Are there any scenic spots or hidden hot springs I can stop at on the way to the campsite?"

[0073] The server generates information about scenic spots and hidden hot springs that can be visited along the way. "Shiraito Falls and Gotemba Onsen are popular."

[0074] The terminal displays this information to the user.

[0075] Processing example

[0076] For example, suppose a user launches an app to select a campsite for a weekend camping trip. In this case, if the user asks, "Which campsites are recommended?", the device sends this question to the server. The server identifies the best campsite based on location information and past history, and returns it to the device as recommended information. The device then displays this information to the user, allowing the user to choose from among the options.

[0077] Similarly, the selection of clothing, equipment setup, cooking recipe suggestions, activity selection, and provision of information on spots along the way are all done efficiently through collaboration between the user, device, and server. This series of processes allows users to easily create detailed and optimal camping plans.

[0078] Implementation Requirements

[0079] In terms of implementation, the user interface must have an intuitive and easy-to-use design, and the server must have a fast and reliable database and algorithms. Real-time data processing capabilities are also important, allowing for the immediate incorporation of local weather information and user history. This system will enable users to streamline their preparations and enjoy a quality camping experience.

[0080] The processing flow will be explained below.

[0081] Specific steps for planning a camp

[0082] Campsite selection

[0083] Step 1:

[0084] The user launches the app and is presented with an interface for planning a camping trip.

[0085] Step 2:

[0086] A user types, "I want to go camping next weekend. What are some recommended campgrounds?"

[0087] Step 3:

[0088] The terminal receives the user's input information and sends a request for campsite recommendations to the server.

[0089] Step 4:

[0090] The server refers to the user's current location information and a database of past camping history to select the most suitable campsite candidate.

[0091] Step 5:

[0092] The server generates recommended campsite information, such as "Mt. Fuji Campsite" and "Mt. Mitake Campsite," and sends it back to the terminal as a response.

[0093] Step 6:

[0094] The terminal displays the received campsite recommendation information to the user.

[0095] Clothes suggestions

[0096] Step 1:

[0097] A user types, "What should I wear when I go camping?"

[0098] Step 2:

[0099] The terminal receives the user's input information and sends a request for clothing suggestions to the server.

[0100] Step 3:

[0101] The server obtains weather forecasts and seasonal information in real time and generates appropriate clothing suggestions.

[0102] Step 4:

[0103] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[0104] Step 5:

[0105] The clothing suggestion information received by the terminal is displayed to the user.

[0106] Tool Setup

[0107] Step 1:

[0108] A user types, "What gear do I need for camping?"

[0109] Step 2:

[0110] The terminal receives the user's input information and sends a tool setup request to the server.

[0111] Step 3:

[0112] The server references a list of basic camping equipment and generates information on "tent, sleeping bag, cooking equipment, lantern, first aid kit."

[0113] Step 4:

[0114] The server sends the generated tool list to the terminal.

[0115] Step 5:

[0116] The terminal displays the received tool setup information to the user.

[0117] Outdoor cooking recipe suggestions

[0118] Step 1:

[0119] A user types, "Tell me some easy camping recipes."

[0120] Step 2:

[0121] The terminal receives the user's input information and sends a cooking recipe request to the server.

[0122] Step 3:

[0123] The server refers to a recipe database for camping dishes and generates recipe information for "Foil-baked vegetables, campfire burgers, and s'mores."

[0124] Step 4:

[0125] The server transmits the generated cooking recipe information to the terminal.

[0126] Step 5:

[0127] The terminal displays the received cooking recipe information to the user.

[0128] Activity suggestions

[0129] Step 1:

[0130] A user types, "What activities can I enjoy while camping?"

[0131] Step 2:

[0132] The terminal receives the user's input information and sends a request for activity suggestions to the server.

[0133] Step 3:

[0134] The server references a database of activity suggestions and generates information such as "hiking, kayaking, fishing, and stargazing around a campfire."

[0135] Step 4:

[0136] The activity information generated by the server is sent to the terminal.

[0137] Step 5:

[0138] The terminal displays the received activity information to the user.

[0139] Suggestions for information on scenic spots and hidden hot springs along the way

[0140] Step 1:

[0141] The user types in, "What are some great scenic spots and secret hot springs I can stop at on the way to the campsite?"

[0142] Step 2:

[0143] The terminal receives the user's input information and sends a request for information on scenic spots and secret hot springs to the server.

[0144] Step 3:

[0145] The server references a database of spots along the way and generates information on "Shiraito Falls" and "Gotemba Onsen."

[0146] Step 4:

[0147] The server transmits the generated route spot information to the terminal.

[0148] Step 5:

[0149] The device displays the information about scenic spots and secret hot springs received by the device to the user.

[0150] This allows users to efficiently obtain all the necessary information from planning to preparation and execution of their camping plans, enabling them to have a comfortable and fulfilling camping experience.

[0151] Example 1

[0152] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0153] When planning a camping trip, it is difficult for users to efficiently gather and prepare a wide range of information, such as selecting an appropriate campsite, necessary equipment, appropriate clothing, cooking recipes, activity selection, and information about spots along the way. A system that can resolve this difficulty is needed.

[0154] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0155] In this invention, the server includes means for generating recommended campsite information based on the user's location information and past history, means for generating appropriate clothing information based on weather and seasonal data, means for generating a list of camping equipment, means for generating simple cooking recipe information, means for generating information on activities that can be enjoyed while camping, and means for generating information on scenic spots and hidden hot springs along the way, thereby enabling the user to efficiently plan a series of camping trips.

[0156] "User" refers to a person who uses this system to plan a camping trip.

[0157] A "camping plan request" refers to a user requesting the system for information and suggestions necessary for carrying out a camping trip.

[0158] A "server" refers to a device that receives requests from users, generates the necessary information using a database or algorithm, and returns it.

[0159] "Recommended campsite information" refers to information about campsites recommended by the server based on the user's location information and past history.

[0160] "Clothing suggestions" refers to suggesting clothing and equipment suitable for camping based on weather and seasonal data.

[0161] "Equipment setup" refers to making a list of the equipment and tools needed for camping and preparing based on that.

[0162] "Cooking recipes" refers to information showing how to prepare meals that can be easily prepared while camping.

[0163] "Activity Information" refers to information about activities and events that can be enjoyed while camping.

[0164] "Information about spots along the way" refers to information about tourist spots such as famous places and hot springs that you can stop at on the way to the campsite.

[0165] "Request" refers to a request that a user sends to the system for specific information.

[0166] A "database" refers to a collection of digital information that stores various information about camping.

[0167] An "algorithm" refers to a procedure or computational method for solving a specific problem.

[0168] "Location information" refers to geographical information based on a user's current location and past behavioral history.

[0169] "Weather Data" means current and forecasted weather information for the proposed campsite.

[0170] "Seasonal data" refers to information about weather and environmental changes in a particular region or period.

[0171] This invention relates to an interactive system that allows users to efficiently plan camping trips. The system based on this invention receives a camping trip plan request from a user, generates appropriate information in response to the request, and presents it to the user. This system is generally implemented as a smartphone app or a web application.

[0172] User Interface

[0173] This is the interface through which users enter details of their camping plans and interact with the system, requesting campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about stops along the way.

[0174] server

[0175] The server generates information in response to user requests and returns it to the device. The server implements the following functions:

[0176] Recommendation information for campsites is generated based on the user's location information and past history.

[0177] Appropriate clothing information is generated based on weather and seasonal data.

[0178] Generate a list of camping gear.

[0179] To generate cooking recipe information that can be easily prepared.

[0180] Generate information about activities you can enjoy while camping.

[0181] Generates information on scenic spots and hidden hot springs along the way.

[0182] Processing flow

[0183] Campsite selection

[0184] When a user starts the app and asks, "I want to go camping next weekend. Where are some recommended campsites?", the device sends this question and the user's location information to the server. The server searches the database based on the location information and past history, generates recommendations for the best campsites, and sends them back to the device. The device then displays this information to the user.

[0185] Clothes suggestions

[0186] When a user asks, "What should I wear when I go camping?", the device sends the request and location information to the server. The server retrieves weather and seasonal data, generates information suggesting appropriate clothing, and sends it back to the device. The device then displays this information to the user.

[0187] Tool Setup

[0188] When a user asks, "What equipment do I need for camping?", the device sends the request to the server. The server generates a list of camping equipment and sends it back to the device. The device displays this information to the user.

[0189] Outdoor cooking recipe suggestions

[0190] When a user asks, "Tell me some easy camping recipes," the device sends the request to the server. The server generates simple cooking recipe information and returns it to the device. The device then displays this information to the user.

[0191] Activity suggestions

[0192] When a user asks, "Tell me about activities I can enjoy while camping," the device sends the request to the server, which generates appropriate activity information and sends it back to the device, which then displays it to the user.

[0193] Suggestions for information on scenic spots and hidden hot springs along the way

[0194] When a user asks, "What are some scenic spots and hidden hot springs I can stop at on the way to the campsite?", the device sends the request to the server. The server generates information about spots that can be stopped at along the way and sends it back to the device. The device then displays this information to the user.

[0195] Specific examples

[0196] For example, if a user launches an app to plan a weekend camping trip and asks, "Where are some recommended campsites?", the device will send this question to the server. The server will identify the best campsites based on location information and past history, and return it to the device as recommended information. The device will then display this information to the user, who can then choose from it. Similarly, the selection of clothing, equipment setup, cooking recipe suggestions, activity selection, and provision of information on spots along the way are all done efficiently through collaboration between the user, device, and server. This series of processes enables users to easily create detailed and optimal camping plans.

[0197] This system allows users to streamline the entire preparation process and enjoy a high-quality camping experience.

[0198] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0199] Campsite selection

[0200] Processing Steps

[0201] Step 1:

[0202] A user launches a smartphone app or web application.

[0203] Input: None

[0204] Output: The app is launched.

[0205] Step 2:

[0206] The user types into the interface, "I want to go camping next weekend. What are some recommended campgrounds?"

[0207] Input: User question

[0208] Output: Question typed into terminal

[0209] Step 3:

[0210] The device acquires the user's location information and sends it to the server along with the question.

[0211] Input: User question, location information

[0212] Output: The location and question are sent to the server.

[0213] Step 4:

[0214] The server searches a database based on the location information received and past history to identify the best campsite.

[0215] Input: Location information, past history

[0216] Output: Campsite recommendation information

[0217] Step 5:

[0218] The server returns the generated campsite recommendation information to the terminal.

[0219] Input: Campsite recommendation information

[0220] Output: Recommendation information is sent to the device

[0221] Step 6:

[0222] The terminal analyzes the campsite recommendation information received from the server and displays it to the user.

[0223] Input: Campsite recommendation information

[0224] Output: User is shown the recommendation

[0225] Clothes suggestions

[0226] Processing Steps

[0227] Step 1:

[0228] The user types into the interface, "What should I wear when I go camping?"

[0229] Input: User question

[0230] Output: Question typed into terminal

[0231] Step 2:

[0232] The device acquires the user's location information and sends it to the server along with the question.

[0233] Input: User question, location information

[0234] Output: The location and question are sent to the server.

[0235] Step 3:

[0236] The server retrieves current weather and season data and identifies appropriate clothing.

[0237] Input: Weather data, seasonal data, location information

[0238] Output: Clothes suggestion information

[0239] Step 4:

[0240] The server returns the generated clothing suggestion information to the terminal.

[0241] Input: Clothing suggestion information

[0242] Output: Suggestion information is sent to the device

[0243] Step 5:

[0244] The terminal analyzes the clothing suggestion information received from the server and displays it to the user.

[0245] Input: Clothing suggestion information

[0246] Output: The user is presented with the suggested information

[0247] Tool Setup

[0248] Processing Steps

[0249] Step 1:

[0250] The user types into the interface, "What equipment do I need for camping?"

[0251] Input: User question

[0252] Output: Question typed into terminal

[0253] Step 2:

[0254] The terminal sends a question to the server.

[0255] Input: User question

[0256] Output: The question is sent to the server

[0257] Step 3:

[0258] The server generates a basic camping equipment list from a database.

[0259] Input: None

[0260] Output: Tool list

[0261] Step 4:

[0262] The server returns the generated tool list to the terminal.

[0263] Input: Tool list

[0264] Output: The list is sent to the terminal.

[0265] Step 5:

[0266] The terminal analyzes the tool list received from the server and displays it to the user.

[0267] Input: Tool list

[0268] Output: The list is displayed to the user

[0269] Outdoor cooking recipe suggestions

[0270] Processing Steps

[0271] Step 1:

[0272] A user types into the interface, "Can you give me some easy camping recipes?"

[0273] Input: User question

[0274] Output: Question typed into terminal

[0275] Step 2:

[0276] The terminal sends a question to the server.

[0277] Input: User question

[0278] Output: The question is sent to the server

[0279] Step 3:

[0280] The server generates easy-to-make cooking recipe information from the database.

[0281] Input: None

[0282] Output: Cooking recipe information

[0283] Step 4:

[0284] The server returns the generated cooking recipe information to the terminal.

[0285] Input: Cooking recipe information

[0286] Output: Recipe information is sent to the device

[0287] Step 5:

[0288] The terminal analyzes the cooking recipe information received from the server and displays it to the user.

[0289] Input: Cooking recipe information

[0290] Output: The recipe information is displayed to the user.

[0291] Activity suggestions

[0292] Processing Steps

[0293] Step 1:

[0294] The user types into the interface, "Tell me some fun activities to do while camping."

[0295] Input: User question

[0296] Output: Question typed into terminal

[0297] Step 2:

[0298] The terminal sends a question to the server.

[0299] Input: User question

[0300] Output: The question is sent to the server

[0301] Step 3:

[0302] The server generates the appropriate activity information from the database.

[0303] Input: None

[0304] Output: Activity information

[0305] Step 4:

[0306] The server returns the generated activity information to the terminal.

[0307] Input: Activity information

[0308] Output: Activity information is sent to the device

[0309] Step 5:

[0310] The terminal analyzes the activity information received from the server and displays it to the user.

[0311] Input: Activity information

[0312] Output: User is shown activity information

[0313] Suggestions for information on scenic spots and hidden hot springs along the way

[0314] Processing Steps

[0315] Step 1:

[0316] The user types into the interface, "What are some great scenic spots and hidden hot springs I can stop at on the way to the campsite?"

[0317] Input: User question

[0318] Output: Question typed into terminal

[0319] Step 2:

[0320] The terminal sends a question to the server.

[0321] Input: User question

[0322] Output: The question is sent to the server

[0323] Step 3:

[0324] The server generates information on scenic spots and hidden hot springs from the database.

[0325] Input: None

[0326] Output: Spot information

[0327] Step 4:

[0328] The server returns the generated spot information to the terminal.

[0329] Input: Spot information

[0330] Output: Spot information is sent to the device

[0331] Step 5:

[0332] The device analyzes the spot information received from the server and displays it to the user.

[0333] Input: Spot information

[0334] Output: The spot information is displayed to the user

[0335] (Application example 1)

[0336] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0337] Conventional camping planning systems typically require users to obtain information through an interface, but there is a demand for a more interactive and intuitive shopping experience, such as a brick-and-mortar store. Furthermore, they lack the real-time and appropriate information required for on-site use, making it difficult for users to make optimal decisions on-site. This often leads to inefficient on-site preparation and execution, resulting in a poor camping experience.

[0338] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0339] In this invention, the server includes means for receiving a camping plan request from a user, means for requesting recommended campsite information from the server, means for generating the recommended campsite information based on the user's location information and past history, means for presenting the recommended information to the user, and means for cooperating with an in-store guidance device to present the user with optimal camping equipment and information, thereby enabling consistent support from in-store guidance to on-site preparations.

[0340] A "camping plan request" is information or a request regarding detailed plans for a user to go camping.

[0341] A "server" is a data processing device that generates information based on a request from a user and returns it to the terminal.

[0342] "Campsite recommendation information" is data for suggesting suitable campsites based on the user's wishes and conditions.

[0343] "User location information" is information that indicates the geographical location where the user is currently located.

[0344] "Past history" refers to data relating to camping trips and campsites selected by the user in the past.

[0345] The "means for presenting recommendation information" refers to an interface or device for displaying the generated recommendation information to the user.

[0346] An "in-store guidance device" is a device that provides information and guidance to users within a physical store.

[0347] "Camping equipment" refers to the tools and equipment necessary for camping.

[0348] "Appropriate clothing information" is suggestions and data about clothing suitable for camping.

[0349] "Equipment Setup Information" means specific guides and instructions for preparing and setting up camping equipment.

[0350] This invention is an interactive system for efficiently planning camping trips, and can be implemented as a user assistant in a physical store. This system is mainly composed of a user interface, a server, and a guide device in the store.

[0351] System configuration

[0352] 1. User Interface

[0353] The user interface allows users to input details of their camping plans and interact with the system. Implemented as smart glasses or a smartphone app, the user can request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about stops along the way.

[0354] 2. Server

[0355] The server generates information in response to user requests and returns it to the device. This server is equipped with a fast and reliable database and algorithms. Specifically, it includes databases and algorithms for generating campsite recommendations, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on road spots.

[0356] 3. Guidance devices in stores

[0357] The in-store guidance device provides users with information and guidance on camping equipment. When a user wearing smart glasses visits a physical store, the system provides the necessary information in real time.

[0358] Processing flow

[0359] The server receives a camping plan request from the user and generates information based on the request. For example, if a user requests, "Where are some recommended campsites?", the server automatically references the user's location information and past history to generate recommendations for the best campsites. The generated information is then displayed on the user's smart glasses.

[0360] Hardware and software used

[0361] Hardware: Smart glasses (e.g., Google® Glass®), smartphones

[0362] Software: Python programs, natural language processing libraries (e.g., SpaCy), databases (e.g., SQLite)

[0363] Data processing and calculation

[0364] The server references the database based on the user's request and generates information appropriate for the user. At this time, it uses natural language processing to analyze the user's input and extract appropriate information. It also generates customized recommendation information based on location information and past history.

[0365] Specific examples

[0366] When a user wears the smart glasses in a physical store and requests "outfit suggestions" through the app, the system will provide optimal outfit suggestions based on the current season and weather information. Specifically, the following dialogue takes place:

[0367] example:

[0368] User: "I want to go camping next weekend. Where can I find some recommended campgrounds?"

[0369] System: "The recommended campsites are as follows: 1. Mt. Fuji Campground 2. Mt. Mitake Campground"

[0370] User: "What should I wear when I go camping?"

[0371] System: "Here are some recommended outfits for this season: consider light layers, long-sleeve shirts, waterproof jackets, and hiking boots."

[0372] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0373] Program processing flow

[0374] Step 1:

[0375] A user puts on smart glasses and inputs a camping plan request through the application. A request is sent to the server. This input includes text data such as "What are some recommended campsites?"

[0376] Step 2:

[0377] The server receives the user's request. Using a natural language processing library (e.g., SpaCy), it analyzes the request to determine what the user is looking for. This analysis process involves tokenizing the input text and extracting keywords.

[0378] Step 3:

[0379] The server retrieves the user's location and past history from a database. It uses location services and a built-in history database (e.g., SQLite) to retrieve the user's current geographic location and previously visited campsites.

[0380] Step 4:

[0381] The server generates campsite recommendations based on the captured location information and past history, using an algorithm to list the best campsites based on geographic proximity and past user preferences.

[0382] Step 5:

[0383] The server returns the generated campsite recommendation information to the user's device. The information is displayed on the smart glasses. At this time, the recommended information (e.g., "Campsite at the foot of Mt. Fuji," "Campsite at Mt. Mitake," etc.) is displayed.

[0384] Step 6:

[0385] The user inputs the next request, for example, "What should I wear when I go camping?" and sends it to the server again. This request is again handled by the server.

[0386] Step 7:

[0387] The server obtains the current season and weather information. It uses a weather API to obtain current weather data and determines the season information from the internal clock.

[0388] Step 8:

[0389] The server generates appropriate clothing suggestions based on the acquired season and weather information, and selects and lists clothing items suitable for the weather conditions from a clothing database.

[0390] Step 9:

[0391] The server then sends the generated clothing suggestion information back to the user's device, and specific items such as "light layers, long-sleeved shirt, waterproof jacket, and hiking boots" are displayed on the smart glasses.

[0392] Specific processing operations

[0393] Input and Output:

[0394] Input: User voice or text input

[0395] Output: Generated camping plans and proposal information

[0396] Data processing and calculation:

[0397] Natural language processing: Analysis of input requests (tokenization, keyword extraction)

[0398] Data reference: Location information and past history database reference

[0399] Data generation: Generating optimal recommendations and proposals

[0400] Specific behavior:

[0401] Retrieving information from a database (e.g. SQLite)

[0402] Real-time external API requests (e.g. weather API)

[0403] Recommendation algorithms make optimal choices

[0404] This allows the user to efficiently prepare for camping and carry out activities on the day.

[0405] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0406] This invention relates to a system that personalizes camping plans and makes optimal suggestions based on the user's emotions. The system based on this invention combines an emotion engine that recognizes the user's emotions and adjusts camping plans and suggestions based on the user's emotion data. The main components and specific processing of this system are described below.

[0407] User Interface

[0408] This is the interface through which users input their camping planning requests and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information on spots along the way.

[0409] server

[0410] The server generates information in response to user requests and returns it to the device. Specifically, it implements databases and algorithms for generating campsite recommendations using an emotion engine, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on spots along the way.

[0411] Emotion Engine

[0412] The emotion engine is responsible for recognizing the user's emotions and adjusting camping plans and suggestions based on that emotional data. Emotion recognition is achieved using biometric sensors such as cameras and microphones, or natural language processing technology based on the user's text input.

[0413] Processing flow

[0414] Campsite selection

[0415] A user launches the app and enters a request to plan a camping trip.

[0416] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[0417] The server refers to the user's current location information and a database of past camping history, and selects the most suitable campsite candidate using an emotion engine, taking into account emotional data.

[0418] The server recommends "Mt. Fuji Campground" and "Mt. Mitake Campground" and sends them as a response to the terminal.

[0419] The terminal displays recommended campsite information to the user.

[0420] Clothes suggestions

[0421] The user asks about clothing.

[0422] User: "What should I wear when I go camping?"

[0423] The server generates appropriate clothing suggestions taking into consideration weather information, seasonal data, and emotion data from an emotion engine.

[0424] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[0425] The terminal displays clothing suggestion information to the user.

[0426] Tool Setup

[0427] A user asks about camping equipment.

[0428] User: "What equipment do I need for camping?"

[0429] The server refers to a list of basic camping equipment and generates a list that takes emotion data into consideration using an emotion engine.

[0430] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[0431] The terminal displays the tool setup information to the user.

[0432] Outdoor cooking recipe suggestions

[0433] A user asks about camping recipes.

[0434] User: "Tell me some easy camping recipes."

[0435] The server refers to a recipe database for camping cooking and generates an appropriate recipe by taking into consideration the emotional data using an emotion engine.

[0436] The server sends recipe information for "Foil-roasted vegetables, campfire burgers, and s'mores" to the device.

[0437] The terminal displays cooking recipe information to the user.

[0438] Activity suggestions

[0439] Ask about activities users can enjoy while camping.

[0440] User: "What activities can I enjoy while camping?"

[0441] The server refers to the activity suggestion database and generates appropriate activity information using an emotion engine, taking into account emotion data.

[0442] The server sends information such as "hiking, kayaking, fishing, stargazing around a campfire" to the device.

[0443] The terminal displays the activity information to the user.

[0444] Suggestions for information on scenic spots and hidden hot springs along the way

[0445] Ask about places users can stop along the way.

[0446] User: "Are there any scenic spots or hidden hot springs I can stop at on the way to the campsite?"

[0447] The server refers to a database of spots along the way and generates appropriate spot information using an emotion engine, taking into account emotion data.

[0448] The server sends information about Shiraito Falls and Gotemba Onsen to the terminal.

[0449] The device displays information about scenic spots and hidden hot springs along the way to the user.

[0450] Processing example

[0451] For example, if a user is anxious and planning a camping trip, the emotion engine will recognize that emotion. When the emotion engine detects "anxiety," the server will suggest relaxing campsites and easy activities accordingly. If a user asks, "Where should I go camping next weekend?", the server will recommend a campsite in a quiet plain as a "relaxing environment."

[0452] Similarly, clothing suggestions, tool setup, cooking recipe suggestions, activity selection, and information on spots along the way are also optimized based on the user's emotional data. This process enables personalized camping plans based on the user's emotional state, making the user's experience more comfortable and fulfilling.

[0453] Implementation Requirements

[0454] When implementing the system, the user interface must have an intuitive and easy-to-use design, and the server must have a fast and reliable database and algorithms. Furthermore, the emotion engine must integrate sensors capable of highly accurate emotion recognition and natural language processing technology. This system will enable users to consistently receive personalized information and enjoy the best camping experience.

[0455] The processing flow will be explained below.

[0456] Specific processing steps for camping planning (embedded emotion engine)

[0457] Campsite selection

[0458] Step 1:

[0459] The user launches the app and is presented with an interface for planning a camping trip.

[0460] Step 2:

[0461] A user types, "I want to go camping next weekend. What are some recommended campgrounds?"

[0462] Step 3:

[0463] The terminal receives the user's input information and sends a request for campsite recommendations to the server.

[0464] Step 4:

[0465] The device activates an emotion engine and acquires emotion data from the user's facial expressions and tone of voice.

[0466] Step 5:

[0467] The server refers to a campsite database to select the most suitable campsite based on the location information and emotion data of the arriving user.

[0468] Step 6:

[0469] The server takes into account the emotional data and recommends "Mt. Fuji Campground" and "Mt. Mitake Campground," and sends this as a response to the device.

[0470] Step 7:

[0471] The terminal displays recommended campsite information to the user.

[0472] Clothes suggestions

[0473] Step 1:

[0474] A user types, "What should I wear when I go camping?"

[0475] Step 2:

[0476] The terminal receives the user's input information and sends a request for clothing suggestions to the server.

[0477] Step 3:

[0478] The terminal starts an emotion engine and acquires the user's emotion data.

[0479] Step 4:

[0480] The server generates data to suggest appropriate clothing based on weather information, seasonal data, and emotional data.

[0481] Step 5:

[0482] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[0483] Step 6:

[0484] The terminal displays clothing suggestion information to the user.

[0485] Tool Setup

[0486] Step 1:

[0487] A user types, "What gear do I need for camping?"

[0488] Step 2:

[0489] The terminal receives the user's input information and sends a tool setup request to the server.

[0490] Step 3:

[0491] The terminal starts an emotion engine and acquires the user's emotion data.

[0492] Step 4:

[0493] The server refers to a list of basic camping equipment and generates equipment setup information that takes emotion data into consideration.

[0494] Step 5:

[0495] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[0496] Step 6:

[0497] The terminal displays the tool setup information to the user.

[0498] Outdoor cooking recipe suggestions

[0499] Step 1:

[0500] A user types, "Tell me some easy camping recipes."

[0501] Step 2:

[0502] The terminal receives the user's input information and sends a cooking recipe request to the server.

[0503] Step 3:

[0504] The terminal starts an emotion engine and acquires the user's emotion data.

[0505] Step 4:

[0506] The server refers to a recipe database for camping cooking and generates cooking recipe information that takes emotion data into consideration.

[0507] Step 5:

[0508] The server sends recipe information for "Foil-roasted vegetables, campfire burgers, and s'mores" to the device.

[0509] Step 6:

[0510] The terminal displays cooking recipe information to the user.

[0511] Activity suggestions

[0512] Step 1:

[0513] A user types, "What activities can I enjoy while camping?"

[0514] Step 2:

[0515] The terminal receives the user's input information and sends a request for activity suggestions to the server.

[0516] Step 3:

[0517] The terminal starts an emotion engine and acquires the user's emotion data.

[0518] Step 4:

[0519] The server refers to the activity proposal database and generates activity information that takes emotion data into consideration.

[0520] Step 5:

[0521] The server sends information such as "hiking, kayaking, fishing, stargazing around a campfire" to the device.

[0522] Step 6:

[0523] The terminal displays the activity information to the user.

[0524] Suggestions for information on scenic spots and hidden hot springs along the way

[0525] Step 1:

[0526] The user types in, "What are some great scenic spots and secret hot springs I can stop at on the way to the campsite?"

[0527] Step 2:

[0528] The terminal receives the user's input information and sends a request for information on scenic spots and secret hot springs to the server.

[0529] Step 3:

[0530] The terminal starts an emotion engine and acquires the user's emotion data.

[0531] Step 4:

[0532] The server refers to a database of road spots and generates road spot information taking emotion data into consideration.

[0533] Step 5:

[0534] The server sends information about Shiraito Falls and Gotemba Onsen to the terminal.

[0535] Step 6:

[0536] The device displays information about scenic spots and hidden hot springs to the user.

[0537] This makes it possible to provide personalized information according to the user's emotional state, allowing the user to enjoy a comfortable and fulfilling camping experience.

[0538] Example 2

[0539] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0540] Conventional camping planning support systems make suggestions without considering the user's emotional state, which often results in suggestions that are not optimal for the user's current emotional state. Furthermore, while optimal suggestions vary depending on the user's emotional state, there is a lack of a means to recognize emotions and provide personalized suggestions accordingly. This creates a demand for a system that allows users to plan appropriate camping trips without feeling anxious or stressed.

[0541] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a camping plan request from a user, means for requesting recommended campsite information from the server, means for generating the recommended campsite information based on the user's location information, past history, and emotion data, means for presenting the recommended information to the user, and means for recognizing the user's emotion using an emotion recognition engine. This makes it possible to recommend appropriate campsites, suggest clothing, and suggest tool setups that take into account the user's emotion data.

[0542] "User" refers to an individual who uses the system to make camping plans.

[0543] A "camping planning request" refers to a user's request for campsite recommendations and information about camping.

[0544] A "server" refers to a computer system that receives requests from users, processes the data, generates appropriate information, and returns it to the terminal.

[0545] "Campsite recommendation information" refers to information about suitable locations for camping, and is generated based on the user's location information, past camping history, and emotion data.

[0546] "Location information" refers to data about where a user is currently located or where a user has previously visited.

[0547] "Camping history" refers to records of campsites the user has visited in the past and the activities they performed there.

[0548] "Emotion data" is data that indicates the user's current emotional state and is generated by an emotion recognition engine.

[0549] An "emotion recognition engine" refers to a system that recognizes a user's emotions using a camera, microphone, or text analysis and generates that data.

[0550] "Clothing Information" refers to information about appropriate clothing for camping.

[0551] "Equipment Setup Information" refers to a list of equipment needed for camping and information on how to set it up.

[0552] The "means for generating recommendation information" refers to a process in which the server creates recommendation information about camping based on the user's location information, past history, and emotional data.

[0553] The "means for presenting recommendation information" refers to a process for displaying the generated recommendation information to the user through a user interface.

[0554] This invention relates to a system that personalizes camping plans and provides optimal suggestions based on the user's emotions. This system consists of three main components: a user interface, a server, and an emotion recognition engine.

[0555] User Interface

[0556] The user interface is where users input their camping planning requirements and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users can request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about spots along the way. This allows users to easily obtain information that meets their needs and desires.

[0557] server

[0558] The server generates information in response to user requests and returns it to the device. Specifically, the following databases and algorithms are implemented:

[0559] Database: MySQL (registered trademark) and MongoDB are used to store user location information, past history, and information on various campsites.

[0560] Algorithm: A machine learning model using Python generates optimal recommendations based on user sentiment data and past history.

[0561] Emotion Recognition Engine

[0562] The emotion recognition engine is responsible for recognizing the user's emotions and adjusting camping plans and suggestions based on that emotion data. The following technologies are used for emotion recognition:

[0563] Biometric sensors: Use cameras and microphones to detect the user's facial expressions and voice sounds and recognize emotions (e.g., Amazon Rekognition, Microsoft® Azure® Emotion API).

[0564] Natural language processing: Analyzing user text input and recognizing sentiment (e.g., Google Cloud Natural Language API).

[0565] Specific examples of processing

[0566] Campsite selection

[0567] A user launches the app and enters a request: "I want to go camping next weekend. What are some recommended campgrounds?"

[0568] The server references the user's current location information and past camping history data, and selects the most suitable campsite candidate using an emotion recognition engine, taking into account the emotion data.

[0569] The server recommends "Mt. Fuji Campground" and "Mt. Mitake Campground" and sends them as a response to the terminal.

[0570] The terminal displays recommended campsite information to the user.

[0571] Clothes suggestions

[0572] A user asks, "What should I wear when I go camping?"

[0573] The server generates appropriate clothing suggestions taking into consideration weather information, seasonal data, and emotion data from an emotion recognition engine.

[0574] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[0575] The terminal displays clothing suggestion information to the user.

[0576] Tool Setup

[0577] A user asks, "What equipment do I need for camping?"

[0578] The server refers to a list of basic camping equipment and generates a list that also takes into account emotional data using an emotion recognition engine.

[0579] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[0580] The terminal displays the tool setup information to the user.

[0581] Prompt Sentence Examples

[0582] Describe how the system responds to the following user questions:

[0583] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[0584] The emotion engine detects anxiety. Please describe what campsites you recommend and how you tailor the information based on the user's emotions.

[0585] Through the above process, the system can take into account the user's emotional data and propose personalized camping plans, allowing the user to enjoy camping more comfortably and with peace of mind.

[0586] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0587] Step 1:

[0588] User Interface Input

[0589] A user launches a smartphone app or web application and inputs a camping plan request.

[0590] Input: User request (e.g., "I want to go camping next weekend. What campsites do you recommend?").

[0591] Output: The request data is sent to the server.

[0592] Specific operation: The user enters a question into the app's input form and presses the submit button.

[0593] Step 2:

[0594] Receiving and parsing the request

[0595] The server receives the request from the user interface and parses the content.

[0596] Input: The request data sent by the user.

[0597] Output: Parsed request information (e.g., a user's campsite recommendation request).

[0598] Specific operation: The server analyzes the received request data and performs a process to extract the necessary information.

[0599] Step 3:

[0600] Location information and history reference

[0601] The server references a location information database and a past camp history database.

[0602] Input: User's current location and past camping history.

[0603] Output: Referenced location information and camp history data.

[0604] Specific operation: The server sends a query to the database and collects the relevant location information and history data.

[0605] Step 4:

[0606] Emotion Recognition and Data Integration

[0607] An emotion recognition engine recognizes the user's emotion and generates emotion data.

[0608] Input: User biometric information and text input information.

[0609] Output: The generated emotion data.

[0610] How it works: The emotion recognition engine uses the camera, microphone, and text analysis to recognize the user's emotions in real time.

[0611] Step 5:

[0612] Data Processing and Information Generation

[0613] The server integrates location information, past history, and emotion data to generate optimal campsite recommendation information.

[0614] Input: location information, past history, emotional data.

[0615] Output: The generated campsite recommendations.

[0616] What it does: The server uses machine learning algorithms to select and aggregate the best campsite candidates.

[0617] Step 6:

[0618] Sending and Displaying Information

[0619] The server transmits the generated recommendation information to the terminal.

[0620] Input: Generated campsite recommendations.

[0621] Output: Recommendations sent to the device.

[0622] Specific operation: The server packages the recommendation information and sends the data to the terminal.

[0623] Step 7:

[0624] User interface display

[0625] The terminal displays the received recommendation information to the user.

[0626] Input: Recommendation information sent to the device.

[0627] Output: Recommendation information displayed on the user interface.

[0628] Specific operation: The terminal analyzes the received data and displays the information on the user interface.

[0629] (Application example 2)

[0630] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0631] Modern camping plans require more personalized suggestions based on the user's individual requests and emotional state. However, conventional systems struggle to recognize users' emotions and optimize suggestions based on that data. Even in brick-and-mortar stores, there is a lack of a way to provide optimal products and plans based on user emotions through dialogue. This leads to a decline in the quality of the user experience and a lack of fulfillment in the overall camping plan.

[0632] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving a camping plan request from a user; means for requesting recommended campsite information from the server; means for generating recommended campsite information based on the user's location information and past history; means for presenting the recommended information to the user; means for having an engine that recognizes the user's emotions and adjusting the campsite plan based on the emotion data; and means for using an interactive robot installed in a physical store to suggest optimal camping equipment and plans to the user. This makes it possible to suggest personalized camping plans based on the user's emotions, improving the customer experience in the physical store and increasing the overall quality of the user's campsite plans.

[0633] The "means for receiving a camping plan request from a user" refers to an interface that allows a user to input requests or questions about camping plans and a mechanism for receiving such requests.

[0634] The "means for requesting recommended campsite information from the server" is a communication means for requesting recommended campsite information from the server based on a user request.

[0635] "Means for generating recommended campsite information based on the user's location information and past history" is a function that utilizes the user's current location information and past behavioral history to select the most suitable campsite and generate recommended information.

[0636] The "means for presenting recommended information to the user" is a mechanism for displaying the generated recommended information for campsites on the user's device.

[0637] An "engine that recognizes user emotions" is software and hardware that analyzes and recognizes emotions from a user's facial expressions, tone of voice, text input, etc.

[0638] The "means for adjusting the camping plan based on emotion data" is a function for optimizing and adjusting the contents of the camping plan using the recognized emotion data of the user.

[0639] An "interactive robot installed in a physical store" is a robot that is placed in a physical store such as a camping equipment store and makes optimal suggestions based on emotions while directly interacting with the user.

[0640] The "means for suggesting camping equipment and plans" is a mechanism for suggesting appropriate camping equipment and plans of action based on the user's input and emotional data.

[0641] The system for implementing this invention mainly consists of a server, a user interface, an emotion engine, and an interactive robot installed in a physical store.

[0642] server

[0643] The server plays a central role in the system and performs the following processes:

[0644] 1. Receive a camping planning request from a user.

[0645] 2. Obtain the user's location information and past history data and generate campsite recommendation information.

[0646] 3. Use the emotion engine to adjust the camping plan based on the user's emotion data.

[0647] 4. Present recommendations to the user.

[0648] The server is equipped with a high-performance database and algorithms for fast and reliable data processing. The emotion engine works in conjunction with cameras and microphones for image recognition and voice analysis to recognize the user's emotions in real time.

[0649] User Interface

[0650] The user interface is the means by which users input their camping plan requests and interact with the system. It is implemented as a smartphone app or web application and allows the following operations:

[0651] Choosing a campsite

[0652] Clothing suggestions

[0653] Tool Setup

[0654] Outdoor Cooking Recipes

[0655] Activity suggestions

[0656] Request information on spots along the way

[0657] The interface has an intuitive and user-friendly design, allowing users to easily access the system.

[0658] Emotion Engine

[0659] The emotion engine is a key component that recognizes user emotions and makes suggestions based on that data. It uses biometric sensors and natural language processing technology to analyze emotion data from users' facial expressions, tone of voice, and text input.

[0660] For example, if a user is feeling anxious and asks, "I want to go camping next weekend. What campsites do you recommend?", the emotion engine will detect the anxiety and recommend a relaxing campsite.

[0661] Interactive robots in brick-and-mortar stores

[0662] The interactive robot, installed in a brick-and-mortar store, interacts with customers to recommend camping gear and plans. It operates as follows:

[0663] 1. The robot uses a camera and microphone to read the customer's emotions.

[0664] 2. Send the emotion data and your camping-related request to the server.

[0665] 3. Based on the recommendation information obtained from the server, suggestions are made via voice or display.

[0666] As a concrete example, here is an example of a conversation between a robot and a customer:

[0667] Robot: "Hello! What are your camping plans for today?"

[0668] Customer: "I'd like to go camping next weekend. Where can you recommend a campground?"

[0669] Robot: "Please wait a moment. We will find the best campsite for you based on the current weather and your preferences."

[0670] With the above system configuration, users can receive suggestions for optimal camping plans based on their emotional state, improving their in-store experience. Furthermore, the following prompt sentences can be used to facilitate information generation by the generative AI model:

[0671] Example prompt sentence:

[0672] I want to go camping next weekend. Where can I get some recommendations?

[0673] The system uses emotional data to personalize the user experience and provide a more comprehensive camping experience than ever before.

[0674] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0675] Step 1:

[0676] The user inputs a camping plan request. The user inputs a question or request about camping through a smartphone app or web application. For example, they input a prompt such as, "I want to go camping next weekend. Where is a recommended campsite?" Input data: Camping plan request. Output data: Request data from the user.

[0677] Step 2:

[0678] The user interface sends input data to the server. The terminal (smartphone or PC) receives the user's requested data and sends it to the server via the Internet. Input data: Data requested by the user. Output data: Requested data sent to the server.

[0679] Step 3:

[0680] The server obtains the user's location information and past history. The server obtains the user's current location information from GPS or IP address, and obtains related information by referring to a database of past camping history. Input data: User's request data, location information, and past history data. Output data: Complete request data including the user's location information and past history.

[0681] Step 4:

[0682] The emotion engine recognizes the user's emotions. The emotion engine analyzes the user's video and audio data acquired from the camera and microphone, or text input, and classifies the user's emotions. For example, it detects anxiety, excitement, joy, etc. Input data: User's video, audio, and text data. Output data: User's emotional data.

[0683] Step 5:

[0684] The server generates recommended campsite information. The server uses an algorithm to select the most suitable campsite based on the user's request data, location information, past history, and emotional data. A generative AI model is used to generate highly accurate recommendation information. Input data: User's request data, location information, past history, emotional data. Output data: Recommended campsite information.

[0685] Step 6:

[0686] The server sends the recommendation information to the terminal. The server returns the generated campsite recommendation information to the user interface again via the communication means. Input data: recommended campsite information. Output data: recommendation information sent to the terminal.

[0687] Step 7:

[0688] The terminal presents the recommendation information to the user. The terminal visually displays the received campsite recommendation information to the user. For example, detailed information and images of the campsite are displayed on the screen. Input data: recommendation information received from the server. Output data: campsite information presented to the user.

[0689] Step 8:

[0690] An interactive robot in a physical store makes suggestions to the user. The robot uses cameras and microphones inside the store to check the user's emotions again and sends the emotion data and the user's request to the server. It then makes suggestions for camping equipment and plans based on the latest recommendation information obtained from the server. Input data: The user's repeated request and emotion data. Output data: Suggestions for optimal camping equipment and plans.

[0691] As a result, users can receive suggestions for optimal camping plans and equipment based on their emotional state, enabling a personalized customer experience even in physical stores.

[0692] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0693] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0694] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0695] [Second embodiment]

[0696] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0697] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0698] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also 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).

[0699] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0700] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0701] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0702] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0703] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0704] The specific processing program 56 is an example of a "program" according to the technology of the present 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0705] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0706] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0707] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0708] This invention relates to an interactive system that allows users to efficiently plan camping trips. The system according to this invention receives a camping trip plan request from a user, generates appropriate information in response to the request, and presents it to the user. This system is mainly implemented with the following configuration.

[0709] User Interface

[0710] This is the interface through which users enter details of their camping plans and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about spots along the way.

[0711] server

[0712] The server generates information in response to user requests and returns it to the device. Specifically, it implements databases and algorithms for generating campsite recommendations, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on road spots.

[0713] Processing flow

[0714] 1. Select a campsite

[0715] The user launches the app and requests to select a campsite.

[0716] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[0717] The server refers to the user's location information and past history and recommends the most suitable campsite.

[0718] The device will display recommended campsites. "The recommended campsites are as follows: 1. Mt. Fuji Campsite 2. Mt. Mitake Campsite."

[0719] 2. Clothing suggestions

[0720] The user asks about clothing.

[0721] User: "What should I wear when I go camping?"

[0722] The server will suggest appropriate clothing based on weather and seasonal data: "Consider light layers, long-sleeved shirts, waterproof jackets, and hiking boots."

[0723] The device will display clothing suggestions.

[0724] 3. Tool Setup

[0725] A user asks about camping equipment.

[0726] User: "What equipment do I need for camping?"

[0727] The server generates a list of basic camping equipment: "You'll need a tent, sleeping bag, cooking equipment, a lantern, and a first aid kit."

[0728] The terminal displays the tool list to the user.

[0729] 4. Outdoor cooking recipe suggestions

[0730] A user asks about camping recipes.

[0731] User: "Tell me some easy camping recipes."

[0732] The server generates recipe information for simple camping meals. "You can easily make things like foil-roasted vegetables, campfire burgers, and s'mores."

[0733] The device displays the cooking recipe to the user.

[0734] 5. Activity suggestions

[0735] Ask about activities users can enjoy while camping.

[0736] User: "What activities can I enjoy while camping?"

[0737] The server generates the appropriate activity information: "Enjoy hiking, kayaking, fishing, stargazing around a campfire, and more."

[0738] The terminal displays the activity information to the user.

[0739] 6. Information on scenic spots and hidden hot springs along the way

[0740] Ask about places users can stop along the way.

[0741] User: "Are there any scenic spots or hidden hot springs I can stop at on the way to the campsite?"

[0742] The server generates information about scenic spots and hidden hot springs that can be visited along the way. "Shiraito Falls and Gotemba Onsen are popular."

[0743] The terminal displays this information to the user.

[0744] Processing example

[0745] For example, suppose a user launches an app to select a campsite for a weekend camping trip. In this case, if the user asks, "Which campsites are recommended?", the device sends this question to the server. The server identifies the best campsite based on location information and past history, and returns it to the device as recommended information. The device then displays this information to the user, allowing the user to choose from among the options.

[0746] Similarly, the selection of clothing, equipment setup, cooking recipe suggestions, activity selection, and provision of information on spots along the way are all done efficiently through collaboration between the user, device, and server. This series of processes allows users to easily create detailed and optimal camping plans.

[0747] Implementation Requirements

[0748] In terms of implementation, the user interface must have an intuitive and easy-to-use design, and the server must have a fast and reliable database and algorithms. Real-time data processing capabilities are also important, allowing for the immediate incorporation of local weather information and user history. This system will enable users to streamline their preparations and enjoy a quality camping experience.

[0749] The processing flow will be explained below.

[0750] Specific steps for planning a camp

[0751] Campsite selection

[0752] Step 1:

[0753] The user launches the app and is presented with an interface for planning a camping trip.

[0754] Step 2:

[0755] A user types, "I want to go camping next weekend. What are some recommended campgrounds?"

[0756] Step 3:

[0757] The terminal receives the user's input information and sends a request for campsite recommendations to the server.

[0758] Step 4:

[0759] The server refers to the user's current location information and a database of past camping history to select the most suitable campsite candidate.

[0760] Step 5:

[0761] The server generates recommended campsite information, such as "Mt. Fuji Campsite" and "Mt. Mitake Campsite," and sends it back to the terminal as a response.

[0762] Step 6:

[0763] The terminal displays the received campsite recommendation information to the user.

[0764] Clothes suggestions

[0765] Step 1:

[0766] A user types, "What should I wear when I go camping?"

[0767] Step 2:

[0768] The terminal receives the user's input information and sends a request for clothing suggestions to the server.

[0769] Step 3:

[0770] The server obtains weather forecasts and seasonal information in real time and generates appropriate clothing suggestions.

[0771] Step 4:

[0772] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[0773] Step 5:

[0774] The clothing suggestion information received by the terminal is displayed to the user.

[0775] Tool Setup

[0776] Step 1:

[0777] A user types, "What gear do I need for camping?"

[0778] Step 2:

[0779] The terminal receives the user's input information and sends a tool setup request to the server.

[0780] Step 3:

[0781] The server references a list of basic camping equipment and generates information on "tent, sleeping bag, cooking equipment, lantern, first aid kit."

[0782] Step 4:

[0783] The server sends the generated tool list to the terminal.

[0784] Step 5:

[0785] The terminal displays the received tool setup information to the user.

[0786] Outdoor cooking recipe suggestions

[0787] Step 1:

[0788] A user types, "Tell me some easy camping recipes."

[0789] Step 2:

[0790] The terminal receives the user's input information and sends a cooking recipe request to the server.

[0791] Step 3:

[0792] The server refers to a recipe database for camping dishes and generates recipe information for "Foil-baked vegetables, campfire burgers, and s'mores."

[0793] Step 4:

[0794] The server transmits the generated cooking recipe information to the terminal.

[0795] Step 5:

[0796] The terminal displays the received cooking recipe information to the user.

[0797] Activity suggestions

[0798] Step 1:

[0799] A user types, "What activities can I enjoy while camping?"

[0800] Step 2:

[0801] The terminal receives the user's input information and sends a request for activity suggestions to the server.

[0802] Step 3:

[0803] The server references a database of activity suggestions and generates information such as "hiking, kayaking, fishing, and stargazing around a campfire."

[0804] Step 4:

[0805] The activity information generated by the server is sent to the terminal.

[0806] Step 5:

[0807] The terminal displays the received activity information to the user.

[0808] Suggestions for information on scenic spots and hidden hot springs along the way

[0809] Step 1:

[0810] The user types in, "What are some great scenic spots and secret hot springs I can stop at on the way to the campsite?"

[0811] Step 2:

[0812] The terminal receives the user's input information and sends a request for information on scenic spots and secret hot springs to the server.

[0813] Step 3:

[0814] The server references a database of spots along the way and generates information on "Shiraito Falls" and "Gotemba Onsen."

[0815] Step 4:

[0816] The server transmits the generated route spot information to the terminal.

[0817] Step 5:

[0818] The device displays the information about scenic spots and secret hot springs received by the device to the user.

[0819] This allows users to efficiently obtain all the necessary information from planning to preparation and execution of their camping plans, enabling them to have a comfortable and fulfilling camping experience.

[0820] Example 1

[0821] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0822] When planning a camping trip, it is difficult for users to efficiently gather and prepare a wide range of information, such as selecting an appropriate campsite, necessary equipment, appropriate clothing, cooking recipes, activity selection, and information about spots along the way. A system that can resolve this difficulty is needed.

[0823] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0824] In this invention, the server includes means for generating recommended campsite information based on the user's location information and past history, means for generating appropriate clothing information based on weather and seasonal data, means for generating a list of camping equipment, means for generating simple cooking recipe information, means for generating information on activities that can be enjoyed while camping, and means for generating information on scenic spots and hidden hot springs along the way, thereby enabling the user to efficiently plan a series of camping trips.

[0825] "User" refers to a person who uses this system to plan a camping trip.

[0826] A "camping plan request" refers to a user requesting the system for information and suggestions necessary for carrying out a camping trip.

[0827] A "server" refers to a device that receives requests from users, generates the necessary information using a database or algorithm, and returns it.

[0828] "Recommended campsite information" refers to information about campsites recommended by the server based on the user's location information and past history.

[0829] "Clothing suggestions" refers to suggesting clothing and equipment suitable for camping based on weather and seasonal data.

[0830] "Equipment setup" refers to making a list of the equipment and tools needed for camping and preparing based on that.

[0831] "Cooking recipes" refers to information showing how to prepare meals that can be easily prepared while camping.

[0832] "Activity Information" refers to information about activities and events that can be enjoyed while camping.

[0833] "Information about spots along the way" refers to information about tourist spots such as famous places and hot springs that you can stop at on the way to the campsite.

[0834] "Request" refers to a request that a user sends to the system for specific information.

[0835] A "database" refers to a collection of digital information that stores various information about camping.

[0836] An "algorithm" refers to a procedure or computational method for solving a specific problem.

[0837] "Location information" refers to geographical information based on a user's current location and past behavioral history.

[0838] "Weather Data" means current and forecasted weather information for the proposed campsite.

[0839] "Seasonal data" refers to information about weather and environmental changes in a particular region or period.

[0840] This invention relates to an interactive system that allows users to efficiently plan camping trips. The system based on this invention receives a camping trip plan request from a user, generates appropriate information in response to the request, and presents it to the user. This system is generally implemented as a smartphone app or a web application.

[0841] User Interface

[0842] This is the interface through which users enter details of their camping plans and interact with the system, requesting campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about stops along the way.

[0843] server

[0844] The server generates information in response to user requests and returns it to the device. The server implements the following functions:

[0845] Recommendation information for campsites is generated based on the user's location information and past history.

[0846] Appropriate clothing information is generated based on weather and seasonal data.

[0847] Generate a list of camping gear.

[0848] To generate cooking recipe information that can be easily prepared.

[0849] Generate information about activities you can enjoy while camping.

[0850] Generates information on scenic spots and hidden hot springs along the way.

[0851] Processing flow

[0852] Campsite selection

[0853] When a user starts the app and asks, "I want to go camping next weekend. Where are some recommended campsites?", the device sends this question and the user's location information to the server. The server searches the database based on the location information and past history, generates recommendations for the best campsites, and sends them back to the device. The device then displays this information to the user.

[0854] Clothes suggestions

[0855] When a user asks, "What should I wear when I go camping?", the device sends the request and location information to the server. The server retrieves weather and seasonal data, generates information suggesting appropriate clothing, and sends it back to the device. The device then displays this information to the user.

[0856] Tool Setup

[0857] When a user asks, "What equipment do I need for camping?", the device sends the request to the server. The server generates a list of camping equipment and sends it back to the device. The device displays this information to the user.

[0858] Outdoor cooking recipe suggestions

[0859] When a user asks, "Tell me some easy camping recipes," the device sends the request to the server. The server generates simple cooking recipe information and returns it to the device. The device then displays this information to the user.

[0860] Activity suggestions

[0861] When a user asks, "Tell me about activities I can enjoy while camping," the device sends the request to the server, which generates appropriate activity information and sends it back to the device, which then displays it to the user.

[0862] Suggestions for information on scenic spots and hidden hot springs along the way

[0863] When a user asks, "What are some scenic spots and hidden hot springs I can stop at on the way to the campsite?", the device sends the request to the server. The server generates information about spots that can be stopped at along the way and sends it back to the device. The device then displays this information to the user.

[0864] Specific examples

[0865] For example, if a user launches an app to plan a weekend camping trip and asks, "Where are some recommended campsites?", the device will send this question to the server. The server will identify the best campsites based on location information and past history, and return it to the device as recommended information. The device will then display this information to the user, who can then choose from it. Similarly, the selection of clothing, equipment setup, cooking recipe suggestions, activity selection, and provision of information on spots along the way are all done efficiently through collaboration between the user, device, and server. This series of processes enables users to easily create detailed and optimal camping plans.

[0866] This system allows users to streamline the entire preparation process and enjoy a high-quality camping experience.

[0867] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0868] Campsite selection

[0869] Processing Steps

[0870] Step 1:

[0871] A user launches a smartphone app or web application.

[0872] Input: None

[0873] Output: The app is launched.

[0874] Step 2:

[0875] The user types into the interface, "I want to go camping next weekend. What are some recommended campgrounds?"

[0876] Input: User question

[0877] Output: Question typed into terminal

[0878] Step 3:

[0879] The device acquires the user's location information and sends it to the server along with the question.

[0880] Input: User question, location information

[0881] Output: The location and question are sent to the server.

[0882] Step 4:

[0883] The server searches a database based on the location information received and past history to identify the best campsite.

[0884] Input: Location information, past history

[0885] Output: Campsite recommendation information

[0886] Step 5:

[0887] The server returns the generated campsite recommendation information to the terminal.

[0888] Input: Campsite recommendation information

[0889] Output: Recommendation information is sent to the device

[0890] Step 6:

[0891] The terminal analyzes the campsite recommendation information received from the server and displays it to the user.

[0892] Input: Campsite recommendation information

[0893] Output: User is shown the recommendation

[0894] Clothes suggestions

[0895] Processing Steps

[0896] Step 1:

[0897] The user types into the interface, "What should I wear when I go camping?"

[0898] Input: User question

[0899] Output: Question typed into terminal

[0900] Step 2:

[0901] The device acquires the user's location information and sends it to the server along with the question.

[0902] Input: User question, location information

[0903] Output: The location and question are sent to the server.

[0904] Step 3:

[0905] The server retrieves current weather and season data and identifies appropriate clothing.

[0906] Input: Weather data, seasonal data, location information

[0907] Output: Clothes suggestion information

[0908] Step 4:

[0909] The server returns the generated clothing suggestion information to the terminal.

[0910] Input: Clothing suggestion information

[0911] Output: Suggestion information is sent to the device

[0912] Step 5:

[0913] The terminal analyzes the clothing suggestion information received from the server and displays it to the user.

[0914] Input: Clothing suggestion information

[0915] Output: The user is presented with the suggested information

[0916] Tool Setup

[0917] Processing Steps

[0918] Step 1:

[0919] The user types into the interface, "What equipment do I need for camping?"

[0920] Input: User question

[0921] Output: Question typed into terminal

[0922] Step 2:

[0923] The terminal sends a question to the server.

[0924] Input: User question

[0925] Output: The question is sent to the server

[0926] Step 3:

[0927] The server generates a basic camping equipment list from a database.

[0928] Input: None

[0929] Output: Tool list

[0930] Step 4:

[0931] The server returns the generated tool list to the terminal.

[0932] Input: Tool list

[0933] Output: The list is sent to the terminal.

[0934] Step 5:

[0935] The terminal analyzes the tool list received from the server and displays it to the user.

[0936] Input: Tool list

[0937] Output: The list is displayed to the user

[0938] Outdoor cooking recipe suggestions

[0939] Processing Steps

[0940] Step 1:

[0941] A user types into the interface, "Can you give me some easy camping recipes?"

[0942] Input: User question

[0943] Output: Question typed into terminal

[0944] Step 2:

[0945] The terminal sends a question to the server.

[0946] Input: User question

[0947] Output: The question is sent to the server

[0948] Step 3:

[0949] The server generates easy-to-make cooking recipe information from the database.

[0950] Input: None

[0951] Output: Cooking recipe information

[0952] Step 4:

[0953] The server returns the generated cooking recipe information to the terminal.

[0954] Input: Cooking recipe information

[0955] Output: Recipe information is sent to the device

[0956] Step 5:

[0957] The terminal analyzes the cooking recipe information received from the server and displays it to the user.

[0958] Input: Cooking recipe information

[0959] Output: The recipe information is displayed to the user.

[0960] Activity suggestions

[0961] Processing Steps

[0962] Step 1:

[0963] The user types into the interface, "Tell me some fun activities to do while camping."

[0964] Input: User question

[0965] Output: Question typed into terminal

[0966] Step 2:

[0967] The terminal sends a question to the server.

[0968] Input: User question

[0969] Output: The question is sent to the server

[0970] Step 3:

[0971] The server generates the appropriate activity information from the database.

[0972] Input: None

[0973] Output: Activity information

[0974] Step 4:

[0975] The server returns the generated activity information to the terminal.

[0976] Input: Activity information

[0977] Output: Activity information is sent to the device

[0978] Step 5:

[0979] The terminal analyzes the activity information received from the server and displays it to the user.

[0980] Input: Activity information

[0981] Output: User is shown activity information

[0982] Suggestions for information on scenic spots and hidden hot springs along the way

[0983] Processing Steps

[0984] Step 1:

[0985] The user types into the interface, "What are some great scenic spots and hidden hot springs I can stop at on the way to the campsite?"

[0986] Input: User question

[0987] Output: Question typed into terminal

[0988] Step 2:

[0989] The terminal sends a question to the server.

[0990] Input: User question

[0991] Output: The question is sent to the server

[0992] Step 3:

[0993] The server generates information on scenic spots and hidden hot springs from the database.

[0994] Input: None

[0995] Output: Spot information

[0996] Step 4:

[0997] The server returns the generated spot information to the terminal.

[0998] Input: Spot information

[0999] Output: Spot information is sent to the device

[1000] Step 5:

[1001] The device analyzes the spot information received from the server and displays it to the user.

[1002] Input: Spot information

[1003] Output: The spot information is displayed to the user

[1004] (Application example 1)

[1005] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1006] Conventional camping planning systems typically require users to obtain information through an interface, but there is a demand for a more interactive and intuitive shopping experience, such as a brick-and-mortar store. Furthermore, they lack the real-time and appropriate information required for on-site use, making it difficult for users to make optimal decisions on-site. This often leads to inefficient on-site preparation and execution, resulting in a poor camping experience.

[1007] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1008] In this invention, the server includes means for receiving a camping plan request from a user, means for requesting recommended campsite information from the server, means for generating the recommended campsite information based on the user's location information and past history, means for presenting the recommended information to the user, and means for cooperating with an in-store guidance device to present the user with optimal camping equipment and information, thereby enabling consistent support from in-store guidance to on-site preparations.

[1009] A "camping plan request" is information or a request regarding detailed plans for a user to go camping.

[1010] A "server" is a data processing device that generates information based on a request from a user and returns it to the terminal.

[1011] "Campsite recommendation information" is data for suggesting suitable campsites based on the user's wishes and conditions.

[1012] "User location information" is information that indicates the geographical location where the user is currently located.

[1013] "Past history" refers to data relating to camping trips and campsites selected by the user in the past.

[1014] The "means for presenting recommendation information" refers to an interface or device for displaying the generated recommendation information to the user.

[1015] An "in-store guidance device" is a device that provides information and guidance to users within a physical store.

[1016] "Camping equipment" refers to the tools and equipment necessary for camping.

[1017] "Appropriate clothing information" is suggestions and data about clothing suitable for camping.

[1018] "Equipment Setup Information" means specific guides and instructions for preparing and setting up camping equipment.

[1019] This invention is an interactive system for efficiently planning camping trips, and can be implemented as a user assistant in a physical store. This system is mainly composed of a user interface, a server, and a guide device in the store.

[1020] System configuration

[1021] 1. User Interface

[1022] The user interface allows users to input details of their camping plans and interact with the system. Implemented as smart glasses or a smartphone app, the user can request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about stops along the way.

[1023] 2. Server

[1024] The server generates information in response to user requests and returns it to the device. This server is equipped with a fast and reliable database and algorithms. Specifically, it includes databases and algorithms for generating campsite recommendations, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on road spots.

[1025] 3. Guidance devices in stores

[1026] The in-store guidance device provides users with information and guidance on camping equipment. When a user wearing smart glasses visits a physical store, the system provides the necessary information in real time.

[1027] Processing flow

[1028] The server receives a camping plan request from the user and generates information based on the request. For example, if a user requests, "Where are some recommended campsites?", the server automatically references the user's location information and past history to generate recommendations for the best campsites. The generated information is then displayed on the user's smart glasses.

[1029] Hardware and software used

[1030] Hardware: smart glasses (e.g., Google Glass), smartphones

[1031] Software: Python programs, natural language processing libraries (e.g., SpaCy), databases (e.g., SQLite)

[1032] Data processing and calculation

[1033] The server references the database based on the user's request and generates information appropriate for the user. At this time, it uses natural language processing to analyze the user's input and extract appropriate information. It also generates customized recommendation information based on location information and past history.

[1034] Specific examples

[1035] When a user wears the smart glasses in a physical store and requests "outfit suggestions" through the app, the system will provide optimal outfit suggestions based on the current season and weather information. Specifically, the following dialogue takes place:

[1036] example:

[1037] User: "I want to go camping next weekend. Where can I find some recommended campgrounds?"

[1038] System: "The recommended campsites are as follows: 1. Mt. Fuji Campground 2. Mt. Mitake Campground"

[1039] User: "What should I wear when I go camping?"

[1040] System: "Here are some recommended outfits for this season: consider light layers, long-sleeve shirts, waterproof jackets, and hiking boots."

[1041] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1042] Program processing flow

[1043] Step 1:

[1044] A user puts on smart glasses and inputs a camping plan request through the application. A request is sent to the server. This input includes text data such as "What are some recommended campsites?"

[1045] Step 2:

[1046] The server receives the user's request. Using a natural language processing library (e.g., SpaCy), it analyzes the request to determine what the user is looking for. This analysis process involves tokenizing the input text and extracting keywords.

[1047] Step 3:

[1048] The server retrieves the user's location and past history from a database. It uses location services and a built-in history database (e.g., SQLite) to retrieve the user's current geographic location and previously visited campsites.

[1049] Step 4:

[1050] The server generates campsite recommendations based on the captured location information and past history, using an algorithm to list the best campsites based on geographic proximity and past user preferences.

[1051] Step 5:

[1052] The server returns the generated campsite recommendation information to the user's device. The information is displayed on the smart glasses. At this time, the recommended information (e.g., "Campsite at the foot of Mt. Fuji," "Campsite at Mt. Mitake," etc.) is displayed.

[1053] Step 6:

[1054] The user inputs the next request, for example, "What should I wear when I go camping?" and sends it to the server again. This request is again handled by the server.

[1055] Step 7:

[1056] The server obtains the current season and weather information. It uses a weather API to obtain current weather data and determines the season information from the internal clock.

[1057] Step 8:

[1058] The server generates appropriate clothing suggestions based on the acquired season and weather information, and selects and lists clothing items suitable for the weather conditions from a clothing database.

[1059] Step 9:

[1060] The server then sends the generated clothing suggestion information back to the user's device, and specific items such as "light layers, long-sleeved shirt, waterproof jacket, and hiking boots" are displayed on the smart glasses.

[1061] Specific processing operations

[1062] Input and Output:

[1063] Input: User voice or text input

[1064] Output: Generated camping plans and proposal information

[1065] Data processing and calculation:

[1066] Natural language processing: Analysis of input requests (tokenization, keyword extraction)

[1067] Data reference: Location information and past history database reference

[1068] Data generation: Generating optimal recommendations and proposals

[1069] Specific behavior:

[1070] Retrieving information from a database (e.g. SQLite)

[1071] Real-time external API requests (e.g. weather API)

[1072] Recommendation algorithms make optimal choices

[1073] This allows the user to efficiently prepare for camping and carry out activities on the day.

[1074] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1075] This invention relates to a system that personalizes camping plans and makes optimal suggestions based on the user's emotions. The system based on this invention combines an emotion engine that recognizes the user's emotions and adjusts camping plans and suggestions based on the user's emotion data. The main components and specific processing of this system are described below.

[1076] User Interface

[1077] This is the interface through which users input their camping planning requests and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information on spots along the way.

[1078] server

[1079] The server generates information in response to user requests and returns it to the device. Specifically, it implements databases and algorithms for generating campsite recommendations using an emotion engine, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on spots along the way.

[1080] Emotion Engine

[1081] The emotion engine is responsible for recognizing the user's emotions and adjusting camping plans and suggestions based on that emotional data. Emotion recognition is achieved using biometric sensors such as cameras and microphones, or natural language processing technology based on the user's text input.

[1082] Processing flow

[1083] Campsite selection

[1084] A user launches the app and enters a request to plan a camping trip.

[1085] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[1086] The server refers to the user's current location information and a database of past camping history, and selects the most suitable campsite candidate using an emotion engine, taking into account emotional data.

[1087] The server recommends "Mt. Fuji Campground" and "Mt. Mitake Campground" and sends them as a response to the terminal.

[1088] The terminal displays recommended campsite information to the user.

[1089] Clothes suggestions

[1090] The user asks about clothing.

[1091] User: "What should I wear when I go camping?"

[1092] The server generates appropriate clothing suggestions taking into consideration weather information, seasonal data, and emotion data from an emotion engine.

[1093] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[1094] The terminal displays clothing suggestion information to the user.

[1095] Tool Setup

[1096] A user asks about camping equipment.

[1097] User: "What equipment do I need for camping?"

[1098] The server refers to a list of basic camping equipment and generates a list that takes emotion data into consideration using an emotion engine.

[1099] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[1100] The terminal displays the tool setup information to the user.

[1101] Outdoor cooking recipe suggestions

[1102] A user asks about camping recipes.

[1103] User: "Tell me some easy camping recipes."

[1104] The server refers to a recipe database for camping cooking and generates an appropriate recipe by taking into consideration the emotional data using an emotion engine.

[1105] The server sends recipe information for "Foil-roasted vegetables, campfire burgers, and s'mores" to the device.

[1106] The terminal displays cooking recipe information to the user.

[1107] Activity suggestions

[1108] Ask about activities users can enjoy while camping.

[1109] User: "What activities can I enjoy while camping?"

[1110] The server refers to the activity suggestion database and generates appropriate activity information using an emotion engine, taking into account emotion data.

[1111] The server sends information such as "hiking, kayaking, fishing, stargazing around a campfire" to the device.

[1112] The terminal displays the activity information to the user.

[1113] Suggestions for information on scenic spots and hidden hot springs along the way

[1114] Ask about places users can stop along the way.

[1115] User: "Are there any scenic spots or hidden hot springs I can stop at on the way to the campsite?"

[1116] The server refers to a database of spots along the way and generates appropriate spot information using an emotion engine, taking into account emotion data.

[1117] The server sends information about Shiraito Falls and Gotemba Onsen to the terminal.

[1118] The device displays information about scenic spots and hidden hot springs along the way to the user.

[1119] Processing example

[1120] For example, if a user is anxious and planning a camping trip, the emotion engine will recognize that emotion. When the emotion engine detects "anxiety," the server will suggest relaxing campsites and easy activities accordingly. If a user asks, "Where should I go camping next weekend?", the server will recommend a campsite in a quiet plain as a "relaxing environment."

[1121] Similarly, clothing suggestions, tool setup, cooking recipe suggestions, activity selection, and information on spots along the way are also optimized based on the user's emotional data. This process enables personalized camping plans based on the user's emotional state, making the user's experience more comfortable and fulfilling.

[1122] Implementation Requirements

[1123] When implementing the system, the user interface must have an intuitive and easy-to-use design, and the server must have a fast and reliable database and algorithms. Furthermore, the emotion engine must integrate sensors capable of highly accurate emotion recognition and natural language processing technology. This system will enable users to consistently receive personalized information and enjoy the best camping experience.

[1124] The processing flow will be explained below.

[1125] Specific processing steps for camping planning (embedded emotion engine)

[1126] Campsite selection

[1127] Step 1:

[1128] The user launches the app and is presented with an interface for planning a camping trip.

[1129] Step 2:

[1130] A user types, "I want to go camping next weekend. What are some recommended campgrounds?"

[1131] Step 3:

[1132] The terminal receives the user's input information and sends a request for campsite recommendations to the server.

[1133] Step 4:

[1134] The device activates an emotion engine and acquires emotion data from the user's facial expressions and tone of voice.

[1135] Step 5:

[1136] The server refers to a campsite database to select the most suitable campsite based on the location information and emotion data of the arriving user.

[1137] Step 6:

[1138] The server takes into account the emotional data and recommends "Mt. Fuji Campground" and "Mt. Mitake Campground," and sends this as a response to the device.

[1139] Step 7:

[1140] The terminal displays recommended campsite information to the user.

[1141] Clothes suggestions

[1142] Step 1:

[1143] A user types, "What should I wear when I go camping?"

[1144] Step 2:

[1145] The terminal receives the user's input information and sends a request for clothing suggestions to the server.

[1146] Step 3:

[1147] The terminal starts an emotion engine and acquires the user's emotion data.

[1148] Step 4:

[1149] The server generates data to suggest appropriate clothing based on weather information, seasonal data, and emotional data.

[1150] Step 5:

[1151] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[1152] Step 6:

[1153] The terminal displays clothing suggestion information to the user.

[1154] Tool Setup

[1155] Step 1:

[1156] A user types, "What gear do I need for camping?"

[1157] Step 2:

[1158] The terminal receives the user's input information and sends a tool setup request to the server.

[1159] Step 3:

[1160] The terminal starts an emotion engine and acquires the user's emotion data.

[1161] Step 4:

[1162] The server refers to a list of basic camping equipment and generates equipment setup information that takes emotion data into consideration.

[1163] Step 5:

[1164] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[1165] Step 6:

[1166] The terminal displays the tool setup information to the user.

[1167] Outdoor cooking recipe suggestions

[1168] Step 1:

[1169] A user types, "Tell me some easy camping recipes."

[1170] Step 2:

[1171] The terminal receives the user's input information and sends a cooking recipe request to the server.

[1172] Step 3:

[1173] The terminal starts an emotion engine and acquires the user's emotion data.

[1174] Step 4:

[1175] The server refers to a recipe database for camping cooking and generates cooking recipe information that takes emotion data into consideration.

[1176] Step 5:

[1177] The server sends recipe information for "Foil-roasted vegetables, campfire burgers, and s'mores" to the device.

[1178] Step 6:

[1179] The terminal displays cooking recipe information to the user.

[1180] Activity suggestions

[1181] Step 1:

[1182] A user types, "What activities can I enjoy while camping?"

[1183] Step 2:

[1184] The terminal receives the user's input information and sends a request for activity suggestions to the server.

[1185] Step 3:

[1186] The terminal starts an emotion engine and acquires the user's emotion data.

[1187] Step 4:

[1188] The server refers to the activity proposal database and generates activity information that takes emotion data into consideration.

[1189] Step 5:

[1190] The server sends information such as "hiking, kayaking, fishing, stargazing around a campfire" to the device.

[1191] Step 6:

[1192] The terminal displays the activity information to the user.

[1193] Suggestions for information on scenic spots and hidden hot springs along the way

[1194] Step 1:

[1195] The user types in, "What are some great scenic spots and secret hot springs I can stop at on the way to the campsite?"

[1196] Step 2:

[1197] The terminal receives the user's input information and sends a request for information on scenic spots and secret hot springs to the server.

[1198] Step 3:

[1199] The terminal starts an emotion engine and acquires the user's emotion data.

[1200] Step 4:

[1201] The server refers to a database of road spots and generates road spot information taking emotion data into consideration.

[1202] Step 5:

[1203] The server sends information about Shiraito Falls and Gotemba Onsen to the terminal.

[1204] Step 6:

[1205] The device displays information about scenic spots and hidden hot springs to the user.

[1206] This makes it possible to provide personalized information according to the user's emotional state, allowing the user to enjoy a comfortable and fulfilling camping experience.

[1207] Example 2

[1208] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1209] Conventional camping planning support systems make suggestions without considering the user's emotional state, which often results in suggestions that are not optimal for the user's current emotional state. Furthermore, while optimal suggestions vary depending on the user's emotional state, there is a lack of a means to recognize emotions and provide personalized suggestions accordingly. This creates a demand for a system that allows users to plan appropriate camping trips without feeling anxious or stressed.

[1210] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a camping plan request from a user, means for requesting recommended campsite information from the server, means for generating the recommended campsite information based on the user's location information, past history, and emotion data, means for presenting the recommended information to the user, and means for recognizing the user's emotion using an emotion recognition engine. This makes it possible to recommend appropriate campsites, suggest clothing, and suggest tool setups that take into account the user's emotion data.

[1211] "User" refers to an individual who uses the system to make camping plans.

[1212] A "camping planning request" refers to a user's request for campsite recommendations and information about camping.

[1213] A "server" refers to a computer system that receives requests from users, processes the data, generates appropriate information, and returns it to the terminal.

[1214] "Campsite recommendation information" refers to information about suitable locations for camping, and is generated based on the user's location information, past camping history, and emotion data.

[1215] "Location information" refers to data about where a user is currently located or where a user has previously visited.

[1216] "Camping history" refers to records of campsites the user has visited in the past and the activities they performed there.

[1217] "Emotion data" is data that indicates the user's current emotional state and is generated by an emotion recognition engine.

[1218] An "emotion recognition engine" refers to a system that recognizes a user's emotions using a camera, microphone, or text analysis and generates that data.

[1219] "Clothing Information" refers to information about appropriate clothing for camping.

[1220] "Equipment Setup Information" refers to a list of equipment needed for camping and information on how to set it up.

[1221] The "means for generating recommendation information" refers to a process in which the server creates recommendation information about camping based on the user's location information, past history, and emotional data.

[1222] The "means for presenting recommendation information" refers to a process for displaying the generated recommendation information to the user through a user interface.

[1223] This invention relates to a system that personalizes camping plans and provides optimal suggestions based on the user's emotions. This system consists of three main components: a user interface, a server, and an emotion recognition engine.

[1224] User Interface

[1225] The user interface is where users input their camping planning requirements and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users can request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about spots along the way. This allows users to easily obtain information that meets their needs and desires.

[1226] server

[1227] The server generates information in response to user requests and returns it to the device. Specifically, the following databases and algorithms are implemented:

[1228] Database: MySQL and MongoDB are used to store user location information, past history, and information on various campsites.

[1229] Algorithm: A machine learning model using Python generates optimal recommendations based on user sentiment data and past history.

[1230] Emotion Recognition Engine

[1231] The emotion recognition engine is responsible for recognizing the user's emotions and adjusting camping plans and suggestions based on that emotion data. The following technologies are used for emotion recognition:

[1232] Biometric sensors: Use cameras and microphones to detect the user's facial expressions and voice sounds and recognize emotions (e.g., Amazon Rekognition, Microsoft Azure Emotion API).

[1233] Natural language processing: Analyzing user text input and recognizing sentiment (e.g., Google Cloud Natural Language API).

[1234] Specific examples of processing

[1235] Campsite selection

[1236] A user launches the app and enters a request: "I want to go camping next weekend. What are some recommended campgrounds?"

[1237] The server references the user's current location information and past camping history data, and selects the most suitable campsite candidate using an emotion recognition engine, taking into account the emotion data.

[1238] The server recommends "Mt. Fuji Campground" and "Mt. Mitake Campground" and sends them as a response to the terminal.

[1239] The terminal displays recommended campsite information to the user.

[1240] Clothes suggestions

[1241] A user asks, "What should I wear when I go camping?"

[1242] The server generates appropriate clothing suggestions taking into consideration weather information, seasonal data, and emotion data from an emotion recognition engine.

[1243] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[1244] The terminal displays clothing suggestion information to the user.

[1245] Tool Setup

[1246] A user asks, "What equipment do I need for camping?"

[1247] The server refers to a list of basic camping equipment and generates a list that also takes into account emotional data using an emotion recognition engine.

[1248] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[1249] The terminal displays the tool setup information to the user.

[1250] Prompt Sentence Examples

[1251] Describe how the system responds to the following user questions:

[1252] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[1253] The emotion engine detects anxiety. Please describe what campsites you recommend and how you tailor the information based on the user's emotions.

[1254] Through the above process, the system can take into account the user's emotional data and propose personalized camping plans, allowing the user to enjoy camping more comfortably and with peace of mind.

[1255] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1256] Step 1:

[1257] User Interface Input

[1258] A user launches a smartphone app or web application and inputs a camping plan request.

[1259] Input: User request (e.g., "I want to go camping next weekend. What campsites do you recommend?").

[1260] Output: The request data is sent to the server.

[1261] Specific operation: The user enters a question into the app's input form and presses the submit button.

[1262] Step 2:

[1263] Receiving and parsing the request

[1264] The server receives the request from the user interface and parses the content.

[1265] Input: The request data sent by the user.

[1266] Output: Parsed request information (e.g., a user's campsite recommendation request).

[1267] Specific operation: The server analyzes the received request data and performs a process to extract the necessary information.

[1268] Step 3:

[1269] Location information and history reference

[1270] The server references a location information database and a past camp history database.

[1271] Input: User's current location and past camping history.

[1272] Output: Referenced location information and camp history data.

[1273] Specific operation: The server sends a query to the database and collects the relevant location information and history data.

[1274] Step 4:

[1275] Emotion Recognition and Data Integration

[1276] An emotion recognition engine recognizes the user's emotion and generates emotion data.

[1277] Input: User biometric information and text input information.

[1278] Output: The generated emotion data.

[1279] How it works: The emotion recognition engine uses the camera, microphone, and text analysis to recognize the user's emotions in real time.

[1280] Step 5:

[1281] Data Processing and Information Generation

[1282] The server integrates location information, past history, and emotion data to generate optimal campsite recommendation information.

[1283] Input: location information, past history, emotional data.

[1284] Output: The generated campsite recommendations.

[1285] What it does: The server uses machine learning algorithms to select and aggregate the best campsite candidates.

[1286] Step 6:

[1287] Sending and Displaying Information

[1288] The server transmits the generated recommendation information to the terminal.

[1289] Input: Generated campsite recommendations.

[1290] Output: Recommendations sent to the device.

[1291] Specific operation: The server packages the recommendation information and sends the data to the terminal.

[1292] Step 7:

[1293] User interface display

[1294] The terminal displays the received recommendation information to the user.

[1295] Input: Recommendation information sent to the device.

[1296] Output: Recommendation information displayed on the user interface.

[1297] Specific operation: The terminal analyzes the received data and displays the information on the user interface.

[1298] (Application example 2)

[1299] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1300] Modern camping plans require more personalized suggestions based on the user's individual requests and emotional state. However, conventional systems struggle to recognize users' emotions and optimize suggestions based on that data. Even in brick-and-mortar stores, there is a lack of a way to provide optimal products and plans based on user emotions through dialogue. This leads to a decline in the quality of the user experience and a lack of fulfillment in the overall camping plan.

[1301] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving a camping plan request from a user; means for requesting recommended campsite information from the server; means for generating recommended campsite information based on the user's location information and past history; means for presenting the recommended information to the user; means for having an engine that recognizes the user's emotions and adjusting the campsite plan based on the emotion data; and means for using an interactive robot installed in a physical store to suggest optimal camping equipment and plans to the user. This makes it possible to suggest personalized camping plans based on the user's emotions, improving the customer experience in the physical store and increasing the overall quality of the user's campsite plans.

[1302] The "means for receiving a camping plan request from a user" refers to an interface that allows a user to input requests or questions about camping plans and a mechanism for receiving such requests.

[1303] The "means for requesting recommended campsite information from the server" is a communication means for requesting recommended campsite information from the server based on a user request.

[1304] "Means for generating recommended campsite information based on the user's location information and past history" is a function that utilizes the user's current location information and past behavioral history to select the most suitable campsite and generate recommended information.

[1305] The "means for presenting recommended information to the user" is a mechanism for displaying the generated recommended information for campsites on the user's device.

[1306] An "engine that recognizes user emotions" is software and hardware that analyzes and recognizes emotions from a user's facial expressions, tone of voice, text input, etc.

[1307] The "means for adjusting the camping plan based on emotion data" is a function for optimizing and adjusting the contents of the camping plan using the recognized emotion data of the user.

[1308] An "interactive robot installed in a physical store" is a robot that is placed in a physical store such as a camping equipment store and makes optimal suggestions based on emotions while directly interacting with the user.

[1309] The "means for suggesting camping equipment and plans" is a mechanism for suggesting appropriate camping equipment and plans of action based on the user's input and emotional data.

[1310] The system for implementing this invention mainly consists of a server, a user interface, an emotion engine, and an interactive robot installed in a physical store.

[1311] server

[1312] The server plays a central role in the system and performs the following processes:

[1313] 1. Receive a camping planning request from a user.

[1314] 2. Obtain the user's location information and past history data and generate campsite recommendation information.

[1315] 3. Use the emotion engine to adjust the camping plan based on the user's emotion data.

[1316] 4. Present recommendations to the user.

[1317] The server is equipped with a high-performance database and algorithms for fast and reliable data processing. The emotion engine works in conjunction with cameras and microphones for image recognition and voice analysis to recognize the user's emotions in real time.

[1318] User Interface

[1319] The user interface is the means by which users input their camping plan requests and interact with the system. It is implemented as a smartphone app or web application and allows the following operations:

[1320] Choosing a campsite

[1321] Clothing suggestions

[1322] Tool Setup

[1323] Outdoor Cooking Recipes

[1324] Activity suggestions

[1325] Request information on spots along the way

[1326] The interface has an intuitive and user-friendly design, allowing users to easily access the system.

[1327] Emotion Engine

[1328] The emotion engine is a key component that recognizes user emotions and makes suggestions based on that data. It uses biometric sensors and natural language processing technology to analyze emotion data from users' facial expressions, tone of voice, and text input.

[1329] For example, if a user is feeling anxious and asks, "I want to go camping next weekend. What campsites do you recommend?", the emotion engine will detect the anxiety and recommend a relaxing campsite.

[1330] Interactive robots in brick-and-mortar stores

[1331] The interactive robot, installed in a brick-and-mortar store, interacts with customers to recommend camping gear and plans. It operates as follows:

[1332] 1. The robot uses a camera and microphone to read the customer's emotions.

[1333] 2. Send the emotion data and your camping-related request to the server.

[1334] 3. Based on the recommendation information obtained from the server, suggestions are made via voice or display.

[1335] As a concrete example, here is an example of a conversation between a robot and a customer:

[1336] Robot: "Hello! What are your camping plans for today?"

[1337] Customer: "I'd like to go camping next weekend. Where can you recommend a campground?"

[1338] Robot: "Please wait a moment. We will find the best campsite for you based on the current weather and your preferences."

[1339] With the above system configuration, users can receive suggestions for optimal camping plans based on their emotional state, improving their in-store experience. Furthermore, the following prompt sentences can be used to facilitate information generation by the generative AI model:

[1340] Example prompt sentence:

[1341] I want to go camping next weekend. Where can I get some recommendations?

[1342] The system uses emotional data to personalize the user experience and provide a more comprehensive camping experience than ever before.

[1343] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1344] Step 1:

[1345] The user inputs a camping plan request. The user inputs a question or request about camping through a smartphone app or web application. For example, they input a prompt such as, "I want to go camping next weekend. Where is a recommended campsite?" Input data: Camping plan request. Output data: Request data from the user.

[1346] Step 2:

[1347] The user interface sends input data to the server. The terminal (smartphone or PC) receives the user's requested data and sends it to the server via the Internet. Input data: Data requested by the user. Output data: Requested data sent to the server.

[1348] Step 3:

[1349] The server obtains the user's location information and past history. The server obtains the user's current location information from GPS or IP address, and obtains related information by referring to a database of past camping history. Input data: User's request data, location information, and past history data. Output data: Complete request data including the user's location information and past history.

[1350] Step 4:

[1351] The emotion engine recognizes the user's emotions. The emotion engine analyzes the user's video and audio data acquired from the camera and microphone, or text input, and classifies the user's emotions. For example, it detects anxiety, excitement, joy, etc. Input data: User's video, audio, and text data. Output data: User's emotional data.

[1352] Step 5:

[1353] The server generates recommended campsite information. The server uses an algorithm to select the most suitable campsite based on the user's request data, location information, past history, and emotional data. A generative AI model is used to generate highly accurate recommendation information. Input data: User's request data, location information, past history, emotional data. Output data: Recommended campsite information.

[1354] Step 6:

[1355] The server sends the recommendation information to the terminal. The server returns the generated campsite recommendation information to the user interface again via the communication means. Input data: recommended campsite information. Output data: recommendation information sent to the terminal.

[1356] Step 7:

[1357] The terminal presents the recommendation information to the user. The terminal visually displays the received campsite recommendation information to the user. For example, detailed information and images of the campsite are displayed on the screen. Input data: recommendation information received from the server. Output data: campsite information presented to the user.

[1358] Step 8:

[1359] An interactive robot in a physical store makes suggestions to the user. The robot uses cameras and microphones inside the store to check the user's emotions again and sends the emotion data and the user's request to the server. It then makes suggestions for camping equipment and plans based on the latest recommendation information obtained from the server. Input data: The user's repeated request and emotion data. Output data: Suggestions for optimal camping equipment and plans.

[1360] As a result, users can receive suggestions for optimal camping plans and equipment based on their emotional state, enabling a personalized customer experience even in physical stores.

[1361] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1362] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1363] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1364] [Third embodiment]

[1365] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1366] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1367] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also 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).

[1368] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1369] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1370] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1371] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1372] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1373] The specific processing program 56 is an example of a "program" according to the technology of the present 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 in accordance with the specific processing program 56 executed on the RAM 30.

[1374] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1375] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1376] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1377] This invention relates to an interactive system that allows users to efficiently plan camping trips. The system according to this invention receives a camping trip plan request from a user, generates appropriate information in response to the request, and presents it to the user. This system is mainly implemented with the following configuration.

[1378] User Interface

[1379] This is the interface through which users enter details of their camping plans and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about spots along the way.

[1380] server

[1381] The server generates information in response to user requests and returns it to the device. Specifically, it implements databases and algorithms for generating campsite recommendations, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on road spots.

[1382] Processing flow

[1383] 1. Select a campsite

[1384] The user launches the app and requests to select a campsite.

[1385] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[1386] The server refers to the user's location information and past history and recommends the most suitable campsite.

[1387] The device will display recommended campsites. "The recommended campsites are as follows: 1. Mt. Fuji Campsite 2. Mt. Mitake Campsite."

[1388] 2. Clothing suggestions

[1389] The user asks about clothing.

[1390] User: "What should I wear when I go camping?"

[1391] The server will suggest appropriate clothing based on weather and seasonal data: "Consider light layers, long-sleeved shirts, waterproof jackets, and hiking boots."

[1392] The device will display clothing suggestions.

[1393] 3. Tool Setup

[1394] A user asks about camping equipment.

[1395] User: "What equipment do I need for camping?"

[1396] The server generates a list of basic camping equipment: "You'll need a tent, sleeping bag, cooking equipment, a lantern, and a first aid kit."

[1397] The terminal displays the tool list to the user.

[1398] 4. Outdoor cooking recipe suggestions

[1399] A user asks about camping recipes.

[1400] User: "Tell me some easy camping recipes."

[1401] The server generates recipe information for simple camping meals. "You can easily make things like foil-roasted vegetables, campfire burgers, and s'mores."

[1402] The device displays the cooking recipe to the user.

[1403] 5. Activity suggestions

[1404] Ask about activities users can enjoy while camping.

[1405] User: "What activities can I enjoy while camping?"

[1406] The server generates the appropriate activity information: "Enjoy hiking, kayaking, fishing, stargazing around a campfire, and more."

[1407] The terminal displays the activity information to the user.

[1408] 6. Information on scenic spots and hidden hot springs along the way

[1409] Ask about places users can stop along the way.

[1410] User: "Are there any scenic spots or hidden hot springs I can stop at on the way to the campsite?"

[1411] The server generates information about scenic spots and hidden hot springs that can be visited along the way. "Shiraito Falls and Gotemba Onsen are popular."

[1412] The terminal displays this information to the user.

[1413] Processing example

[1414] For example, suppose a user launches an app to select a campsite for a weekend camping trip. In this case, if the user asks, "Which campsites are recommended?", the device sends this question to the server. The server identifies the best campsite based on location information and past history, and returns it to the device as recommended information. The device then displays this information to the user, allowing the user to choose from among the options.

[1415] Similarly, the selection of clothing, equipment setup, cooking recipe suggestions, activity selection, and provision of information on spots along the way are all done efficiently through collaboration between the user, device, and server. This series of processes allows users to easily create detailed and optimal camping plans.

[1416] Implementation Requirements

[1417] In terms of implementation, the user interface must have an intuitive and easy-to-use design, and the server must have a fast and reliable database and algorithms. Real-time data processing capabilities are also important, allowing for the immediate incorporation of local weather information and user history. This system will enable users to streamline their preparations and enjoy a quality camping experience.

[1418] The processing flow will be explained below.

[1419] Specific steps for planning a camp

[1420] Campsite selection

[1421] Step 1:

[1422] The user launches the app and is presented with an interface for planning a camping trip.

[1423] Step 2:

[1424] A user types, "I want to go camping next weekend. What are some recommended campgrounds?"

[1425] Step 3:

[1426] The terminal receives the user's input information and sends a request for campsite recommendations to the server.

[1427] Step 4:

[1428] The server refers to the user's current location information and a database of past camping history to select the most suitable campsite candidate.

[1429] Step 5:

[1430] The server generates recommended campsite information, such as "Mt. Fuji Campsite" and "Mt. Mitake Campsite," and sends it back to the terminal as a response.

[1431] Step 6:

[1432] The terminal displays the received campsite recommendation information to the user.

[1433] Clothes suggestions

[1434] Step 1:

[1435] A user types, "What should I wear when I go camping?"

[1436] Step 2:

[1437] The terminal receives the user's input information and sends a request for clothing suggestions to the server.

[1438] Step 3:

[1439] The server obtains weather forecasts and seasonal information in real time and generates appropriate clothing suggestions.

[1440] Step 4:

[1441] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[1442] Step 5:

[1443] The clothing suggestion information received by the terminal is displayed to the user.

[1444] Tool Setup

[1445] Step 1:

[1446] A user types, "What gear do I need for camping?"

[1447] Step 2:

[1448] The terminal receives the user's input information and sends a tool setup request to the server.

[1449] Step 3:

[1450] The server references a list of basic camping equipment and generates information on "tent, sleeping bag, cooking equipment, lantern, first aid kit."

[1451] Step 4:

[1452] The server sends the generated tool list to the terminal.

[1453] Step 5:

[1454] The terminal displays the received tool setup information to the user.

[1455] Outdoor cooking recipe suggestions

[1456] Step 1:

[1457] A user types, "Tell me some easy camping recipes."

[1458] Step 2:

[1459] The terminal receives the user's input information and sends a cooking recipe request to the server.

[1460] Step 3:

[1461] The server refers to a recipe database for camping dishes and generates recipe information for "Foil-baked vegetables, campfire burgers, and s'mores."

[1462] Step 4:

[1463] The server transmits the generated cooking recipe information to the terminal.

[1464] Step 5:

[1465] The terminal displays the received cooking recipe information to the user.

[1466] Activity suggestions

[1467] Step 1:

[1468] A user types, "What activities can I enjoy while camping?"

[1469] Step 2:

[1470] The terminal receives the user's input information and sends a request for activity suggestions to the server.

[1471] Step 3:

[1472] The server references a database of activity suggestions and generates information such as "hiking, kayaking, fishing, and stargazing around a campfire."

[1473] Step 4:

[1474] The activity information generated by the server is sent to the terminal.

[1475] Step 5:

[1476] The terminal displays the received activity information to the user.

[1477] Suggestions for information on scenic spots and hidden hot springs along the way

[1478] Step 1:

[1479] The user types in, "What are some great scenic spots and secret hot springs I can stop at on the way to the campsite?"

[1480] Step 2:

[1481] The terminal receives the user's input information and sends a request for information on scenic spots and secret hot springs to the server.

[1482] Step 3:

[1483] The server references a database of spots along the way and generates information on "Shiraito Falls" and "Gotemba Onsen."

[1484] Step 4:

[1485] The server transmits the generated route spot information to the terminal.

[1486] Step 5:

[1487] The device displays the information about scenic spots and secret hot springs received by the device to the user.

[1488] This allows users to efficiently obtain all the necessary information from planning to preparation and execution of their camping plans, enabling them to have a comfortable and fulfilling camping experience.

[1489] Example 1

[1490] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1491] When planning a camping trip, it is difficult for users to efficiently gather and prepare a wide range of information, such as selecting an appropriate campsite, necessary equipment, appropriate clothing, cooking recipes, activity selection, and information about spots along the way. A system that can resolve this difficulty is needed.

[1492] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1493] In this invention, the server includes means for generating recommended campsite information based on the user's location information and past history, means for generating appropriate clothing information based on weather and seasonal data, means for generating a list of camping equipment, means for generating simple cooking recipe information, means for generating information on activities that can be enjoyed while camping, and means for generating information on scenic spots and hidden hot springs along the way, thereby enabling the user to efficiently plan a series of camping trips.

[1494] "User" refers to a person who uses this system to plan a camping trip.

[1495] A "camping plan request" refers to a user requesting the system for information and suggestions necessary for carrying out a camping trip.

[1496] A "server" refers to a device that receives requests from users, generates the necessary information using a database or algorithm, and returns it.

[1497] "Recommended campsite information" refers to information about campsites recommended by the server based on the user's location information and past history.

[1498] "Clothing suggestions" refers to suggesting clothing and equipment suitable for camping based on weather and seasonal data.

[1499] "Equipment setup" refers to making a list of the equipment and tools needed for camping and preparing based on that.

[1500] "Cooking recipes" refers to information showing how to prepare meals that can be easily prepared while camping.

[1501] "Activity Information" refers to information about activities and events that can be enjoyed while camping.

[1502] "Information about spots along the way" refers to information about tourist spots such as famous places and hot springs that you can stop at on the way to the campsite.

[1503] "Request" refers to a request that a user sends to the system for specific information.

[1504] A "database" refers to a collection of digital information that stores various information about camping.

[1505] An "algorithm" refers to a procedure or computational method for solving a specific problem.

[1506] "Location information" refers to geographical information based on a user's current location and past behavioral history.

[1507] "Weather Data" means current and forecasted weather information for the proposed campsite.

[1508] "Seasonal data" refers to information about weather and environmental changes in a particular region or period.

[1509] This invention relates to an interactive system that allows users to efficiently plan camping trips. The system based on this invention receives a camping trip plan request from a user, generates appropriate information in response to the request, and presents it to the user. This system is generally implemented as a smartphone app or a web application.

[1510] User Interface

[1511] This is the interface through which users enter details of their camping plans and interact with the system, requesting campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about stops along the way.

[1512] server

[1513] The server generates information in response to user requests and returns it to the device. The server implements the following functions:

[1514] Recommendation information for campsites is generated based on the user's location information and past history.

[1515] Appropriate clothing information is generated based on weather and seasonal data.

[1516] Generate a list of camping gear.

[1517] To generate cooking recipe information that can be easily prepared.

[1518] Generate information about activities you can enjoy while camping.

[1519] Generates information on scenic spots and hidden hot springs along the way.

[1520] Processing flow

[1521] Campsite selection

[1522] When a user starts the app and asks, "I want to go camping next weekend. Where are some recommended campsites?", the device sends this question and the user's location information to the server. The server searches the database based on the location information and past history, generates recommendations for the best campsites, and sends them back to the device. The device then displays this information to the user.

[1523] Clothes suggestions

[1524] When a user asks, "What should I wear when I go camping?", the device sends the request and location information to the server. The server retrieves weather and seasonal data, generates information suggesting appropriate clothing, and sends it back to the device. The device then displays this information to the user.

[1525] Tool Setup

[1526] When a user asks, "What equipment do I need for camping?", the device sends the request to the server. The server generates a list of camping equipment and sends it back to the device. The device displays this information to the user.

[1527] Outdoor cooking recipe suggestions

[1528] When a user asks, "Tell me some easy camping recipes," the device sends the request to the server. The server generates simple cooking recipe information and returns it to the device. The device then displays this information to the user.

[1529] Activity suggestions

[1530] When a user asks, "Tell me about activities I can enjoy while camping," the device sends the request to the server, which generates appropriate activity information and sends it back to the device, which then displays it to the user.

[1531] Suggestions for information on scenic spots and hidden hot springs along the way

[1532] When a user asks, "What are some scenic spots and hidden hot springs I can stop at on the way to the campsite?", the device sends the request to the server. The server generates information about spots that can be stopped at along the way and sends it back to the device. The device then displays this information to the user.

[1533] Specific examples

[1534] For example, if a user launches an app to plan a weekend camping trip and asks, "Where are some recommended campsites?", the device will send this question to the server. The server will identify the best campsites based on location information and past history, and return it to the device as recommended information. The device will then display this information to the user, who can then choose from it. Similarly, the selection of clothing, equipment setup, cooking recipe suggestions, activity selection, and provision of information on spots along the way are all done efficiently through collaboration between the user, device, and server. This series of processes enables users to easily create detailed and optimal camping plans.

[1535] This system allows users to streamline the entire preparation process and enjoy a high-quality camping experience.

[1536] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1537] Campsite selection

[1538] Processing Steps

[1539] Step 1:

[1540] A user launches a smartphone app or web application.

[1541] Input: None

[1542] Output: The app is launched.

[1543] Step 2:

[1544] The user types into the interface, "I want to go camping next weekend. What are some recommended campgrounds?"

[1545] Input: User question

[1546] Output: Question typed into terminal

[1547] Step 3:

[1548] The device acquires the user's location information and sends it to the server along with the question.

[1549] Input: User question, location information

[1550] Output: The location and question are sent to the server.

[1551] Step 4:

[1552] The server searches a database based on the location information received and past history to identify the best campsite.

[1553] Input: Location information, past history

[1554] Output: Campsite recommendation information

[1555] Step 5:

[1556] The server returns the generated campsite recommendation information to the terminal.

[1557] Input: Campsite recommendation information

[1558] Output: Recommendation information is sent to the device

[1559] Step 6:

[1560] The terminal analyzes the campsite recommendation information received from the server and displays it to the user.

[1561] Input: Campsite recommendation information

[1562] Output: User is shown the recommendation

[1563] Clothes suggestions

[1564] Processing Steps

[1565] Step 1:

[1566] The user types into the interface, "What should I wear when I go camping?"

[1567] Input: User question

[1568] Output: Question typed into terminal

[1569] Step 2:

[1570] The device acquires the user's location information and sends it to the server along with the question.

[1571] Input: User question, location information

[1572] Output: The location and question are sent to the server.

[1573] Step 3:

[1574] The server retrieves current weather and season data and identifies appropriate clothing.

[1575] Input: Weather data, seasonal data, location information

[1576] Output: Clothes suggestion information

[1577] Step 4:

[1578] The server returns the generated clothing suggestion information to the terminal.

[1579] Input: Clothing suggestion information

[1580] Output: Suggestion information is sent to the device

[1581] Step 5:

[1582] The terminal analyzes the clothing suggestion information received from the server and displays it to the user.

[1583] Input: Clothing suggestion information

[1584] Output: The user is presented with the suggested information

[1585] Tool Setup

[1586] Processing Steps

[1587] Step 1:

[1588] The user types into the interface, "What equipment do I need for camping?"

[1589] Input: User question

[1590] Output: Question typed into terminal

[1591] Step 2:

[1592] The terminal sends a question to the server.

[1593] Input: User question

[1594] Output: The question is sent to the server

[1595] Step 3:

[1596] The server generates a basic camping equipment list from a database.

[1597] Input: None

[1598] Output: Tool list

[1599] Step 4:

[1600] The server returns the generated tool list to the terminal.

[1601] Input: Tool list

[1602] Output: The list is sent to the terminal.

[1603] Step 5:

[1604] The terminal analyzes the tool list received from the server and displays it to the user.

[1605] Input: Tool list

[1606] Output: The list is displayed to the user

[1607] Outdoor cooking recipe suggestions

[1608] Processing Steps

[1609] Step 1:

[1610] A user types into the interface, "Can you give me some easy camping recipes?"

[1611] Input: User question

[1612] Output: Question typed into terminal

[1613] Step 2:

[1614] The terminal sends a question to the server.

[1615] Input: User question

[1616] Output: The question is sent to the server

[1617] Step 3:

[1618] The server generates easy-to-make cooking recipe information from the database.

[1619] Input: None

[1620] Output: Cooking recipe information

[1621] Step 4:

[1622] The server returns the generated cooking recipe information to the terminal.

[1623] Input: Cooking recipe information

[1624] Output: Recipe information is sent to the device

[1625] Step 5:

[1626] The terminal analyzes the cooking recipe information received from the server and displays it to the user.

[1627] Input: Cooking recipe information

[1628] Output: The recipe information is displayed to the user.

[1629] Activity suggestions

[1630] Processing Steps

[1631] Step 1:

[1632] The user types into the interface, "Tell me some fun activities to do while camping."

[1633] Input: User question

[1634] Output: Question typed into terminal

[1635] Step 2:

[1636] The terminal sends a question to the server.

[1637] Input: User question

[1638] Output: The question is sent to the server

[1639] Step 3:

[1640] The server generates the appropriate activity information from the database.

[1641] Input: None

[1642] Output: Activity information

[1643] Step 4:

[1644] The server returns the generated activity information to the terminal.

[1645] Input: Activity information

[1646] Output: Activity information is sent to the device

[1647] Step 5:

[1648] The terminal analyzes the activity information received from the server and displays it to the user.

[1649] Input: Activity information

[1650] Output: User is shown activity information

[1651] Suggestions for information on scenic spots and hidden hot springs along the way

[1652] Processing Steps

[1653] Step 1:

[1654] The user types into the interface, "What are some great scenic spots and hidden hot springs I can stop at on the way to the campsite?"

[1655] Input: User question

[1656] Output: Question typed into terminal

[1657] Step 2:

[1658] The terminal sends a question to the server.

[1659] Input: User question

[1660] Output: The question is sent to the server

[1661] Step 3:

[1662] The server generates information on scenic spots and hidden hot springs from the database.

[1663] Input: None

[1664] Output: Spot information

[1665] Step 4:

[1666] The server returns the generated spot information to the terminal.

[1667] Input: Spot information

[1668] Output: Spot information is sent to the device

[1669] Step 5:

[1670] The device analyzes the spot information received from the server and displays it to the user.

[1671] Input: Spot information

[1672] Output: The spot information is displayed to the user

[1673] (Application example 1)

[1674] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1675] Conventional camping planning systems typically require users to obtain information through an interface, but there is a demand for a more interactive and intuitive shopping experience, such as a brick-and-mortar store. Furthermore, they lack the real-time and appropriate information required for on-site use, making it difficult for users to make optimal decisions on-site. This often leads to inefficient on-site preparation and execution, resulting in a poor camping experience.

[1676] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1677] In this invention, the server includes means for receiving a camping plan request from a user, means for requesting recommended campsite information from the server, means for generating the recommended campsite information based on the user's location information and past history, means for presenting the recommended information to the user, and means for cooperating with an in-store guidance device to present the user with optimal camping equipment and information, thereby enabling consistent support from in-store guidance to on-site preparations.

[1678] A "camping plan request" is information or a request regarding detailed plans for a user to go camping.

[1679] A "server" is a data processing device that generates information based on a request from a user and returns it to the terminal.

[1680] "Campsite recommendation information" is data for suggesting suitable campsites based on the user's wishes and conditions.

[1681] "User location information" is information that indicates the geographical location where the user is currently located.

[1682] "Past history" refers to data relating to camping trips and campsites selected by the user in the past.

[1683] The "means for presenting recommendation information" refers to an interface or device for displaying the generated recommendation information to the user.

[1684] An "in-store guidance device" is a device that provides information and guidance to users within a physical store.

[1685] "Camping equipment" refers to the tools and equipment necessary for camping.

[1686] "Appropriate clothing information" is suggestions and data about clothing suitable for camping.

[1687] "Equipment Setup Information" means specific guides and instructions for preparing and setting up camping equipment.

[1688] This invention is an interactive system for efficiently planning camping trips, and can be implemented as a user assistant in a physical store. This system is mainly composed of a user interface, a server, and a guide device in the store.

[1689] System configuration

[1690] 1. User Interface

[1691] The user interface allows users to input details of their camping plans and interact with the system. Implemented as smart glasses or a smartphone app, the user can request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about stops along the way.

[1692] 2. Server

[1693] The server generates information in response to user requests and returns it to the device. This server is equipped with a fast and reliable database and algorithms. Specifically, it includes databases and algorithms for generating campsite recommendations, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on road spots.

[1694] 3. Guidance devices in stores

[1695] The in-store guidance device provides users with information and guidance on camping equipment. When a user wearing smart glasses visits a physical store, the system provides the necessary information in real time.

[1696] Processing flow

[1697] The server receives a camping plan request from the user and generates information based on the request. For example, if a user requests, "Where are some recommended campsites?", the server automatically references the user's location information and past history to generate recommendations for the best campsites. The generated information is then displayed on the user's smart glasses.

[1698] Hardware and software used

[1699] Hardware: smart glasses (e.g., Google Glass), smartphones

[1700] Software: Python programs, natural language processing libraries (e.g., SpaCy), databases (e.g., SQLite)

[1701] Data processing and calculation

[1702] The server references the database based on the user's request and generates information appropriate for the user. At this time, it uses natural language processing to analyze the user's input and extract appropriate information. It also generates customized recommendation information based on location information and past history.

[1703] Specific examples

[1704] When a user wears the smart glasses in a physical store and requests "outfit suggestions" through the app, the system will provide optimal outfit suggestions based on the current season and weather information. Specifically, the following dialogue takes place:

[1705] example:

[1706] User: "I want to go camping next weekend. Where can I find some recommended campgrounds?"

[1707] System: "The recommended campsites are as follows: 1. Mt. Fuji Campground 2. Mt. Mitake Campground"

[1708] User: "What should I wear when I go camping?"

[1709] System: "Here are some recommended outfits for this season: consider light layers, long-sleeve shirts, waterproof jackets, and hiking boots."

[1710] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1711] Program processing flow

[1712] Step 1:

[1713] A user puts on smart glasses and inputs a camping plan request through the application. A request is sent to the server. This input includes text data such as "What are some recommended campsites?"

[1714] Step 2:

[1715] The server receives the user's request. Using a natural language processing library (e.g., SpaCy), it analyzes the request to determine what the user is looking for. This analysis process involves tokenizing the input text and extracting keywords.

[1716] Step 3:

[1717] The server retrieves the user's location and past history from a database. It uses location services and a built-in history database (e.g., SQLite) to retrieve the user's current geographic location and previously visited campsites.

[1718] Step 4:

[1719] The server generates campsite recommendations based on the captured location information and past history, using an algorithm to list the best campsites based on geographic proximity and past user preferences.

[1720] Step 5:

[1721] The server returns the generated campsite recommendation information to the user's device. The information is displayed on the smart glasses. At this time, the recommended information (e.g., "Campsite at the foot of Mt. Fuji," "Campsite at Mt. Mitake," etc.) is displayed.

[1722] Step 6:

[1723] The user inputs the next request, for example, "What should I wear when I go camping?" and sends it to the server again. This request is again handled by the server.

[1724] Step 7:

[1725] The server obtains the current season and weather information. It uses a weather API to obtain current weather data and determines the season information from the internal clock.

[1726] Step 8:

[1727] The server generates appropriate clothing suggestions based on the acquired season and weather information, and selects and lists clothing items suitable for the weather conditions from a clothing database.

[1728] Step 9:

[1729] The server then sends the generated clothing suggestion information back to the user's device, and specific items such as "light layers, long-sleeved shirt, waterproof jacket, and hiking boots" are displayed on the smart glasses.

[1730] Specific processing operations

[1731] Input and Output:

[1732] Input: User voice or text input

[1733] Output: Generated camping plans and proposal information

[1734] Data processing and calculation:

[1735] Natural language processing: Analysis of input requests (tokenization, keyword extraction)

[1736] Data reference: Location information and past history database reference

[1737] Data generation: Generating optimal recommendations and proposals

[1738] Specific behavior:

[1739] Retrieving information from a database (e.g. SQLite)

[1740] Real-time external API requests (e.g. weather API)

[1741] Recommendation algorithms make optimal choices

[1742] This allows the user to efficiently prepare for camping and carry out activities on the day.

[1743] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1744] This invention relates to a system that personalizes camping plans and makes optimal suggestions based on the user's emotions. The system based on this invention combines an emotion engine that recognizes the user's emotions and adjusts camping plans and suggestions based on the user's emotion data. The main components and specific processing of this system are described below.

[1745] User Interface

[1746] This is the interface through which users input their camping planning requests and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information on spots along the way.

[1747] server

[1748] The server generates information in response to user requests and returns it to the device. Specifically, it implements databases and algorithms for generating campsite recommendations using an emotion engine, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on spots along the way.

[1749] Emotion Engine

[1750] The emotion engine is responsible for recognizing the user's emotions and adjusting camping plans and suggestions based on that emotional data. Emotion recognition is achieved using biometric sensors such as cameras and microphones, or natural language processing technology based on the user's text input.

[1751] Processing flow

[1752] Campsite selection

[1753] A user launches the app and enters a request to plan a camping trip.

[1754] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[1755] The server refers to the user's current location information and a database of past camping history, and selects the most suitable campsite candidate using an emotion engine, taking into account emotional data.

[1756] The server recommends "Mt. Fuji Campground" and "Mt. Mitake Campground" and sends them as a response to the terminal.

[1757] The terminal displays recommended campsite information to the user.

[1758] Clothes suggestions

[1759] The user asks about clothing.

[1760] User: "What should I wear when I go camping?"

[1761] The server generates appropriate clothing suggestions taking into consideration weather information, seasonal data, and emotion data from an emotion engine.

[1762] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[1763] The terminal displays clothing suggestion information to the user.

[1764] Tool Setup

[1765] A user asks about camping equipment.

[1766] User: "What equipment do I need for camping?"

[1767] The server refers to a list of basic camping equipment and generates a list that takes emotion data into consideration using an emotion engine.

[1768] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[1769] The terminal displays the tool setup information to the user.

[1770] Outdoor cooking recipe suggestions

[1771] A user asks about camping recipes.

[1772] User: "Tell me some easy camping recipes."

[1773] The server refers to a recipe database for camping cooking and generates an appropriate recipe by taking into consideration the emotional data using an emotion engine.

[1774] The server sends recipe information for "Foil-roasted vegetables, campfire burgers, and s'mores" to the device.

[1775] The terminal displays cooking recipe information to the user.

[1776] Activity suggestions

[1777] Ask about activities users can enjoy while camping.

[1778] User: "What activities can I enjoy while camping?"

[1779] The server refers to the activity suggestion database and generates appropriate activity information using an emotion engine, taking into account emotion data.

[1780] The server sends information such as "hiking, kayaking, fishing, stargazing around a campfire" to the device.

[1781] The terminal displays the activity information to the user.

[1782] Suggestions for information on scenic spots and hidden hot springs along the way

[1783] Ask about places users can stop along the way.

[1784] User: "Are there any scenic spots or hidden hot springs I can stop at on the way to the campsite?"

[1785] The server refers to a database of spots along the way and generates appropriate spot information using an emotion engine, taking into account emotion data.

[1786] The server sends information about Shiraito Falls and Gotemba Onsen to the terminal.

[1787] The device displays information about scenic spots and hidden hot springs along the way to the user.

[1788] Processing example

[1789] For example, if a user is anxious and planning a camping trip, the emotion engine will recognize that emotion. When the emotion engine detects "anxiety," the server will suggest relaxing campsites and easy activities accordingly. If a user asks, "Where should I go camping next weekend?", the server will recommend a campsite in a quiet plain as a "relaxing environment."

[1790] Similarly, clothing suggestions, tool setup, cooking recipe suggestions, activity selection, and information on spots along the way are also optimized based on the user's emotional data. This process enables personalized camping plans based on the user's emotional state, making the user's experience more comfortable and fulfilling.

[1791] Implementation Requirements

[1792] When implementing the system, the user interface must have an intuitive and easy-to-use design, and the server must have a fast and reliable database and algorithms. Furthermore, the emotion engine must integrate sensors capable of highly accurate emotion recognition and natural language processing technology. This system will enable users to consistently receive personalized information and enjoy the best camping experience.

[1793] The processing flow will be explained below.

[1794] Specific processing steps for camping planning (embedded emotion engine)

[1795] Campsite selection

[1796] Step 1:

[1797] The user launches the app and is presented with an interface for planning a camping trip.

[1798] Step 2:

[1799] A user types, "I want to go camping next weekend. What are some recommended campgrounds?"

[1800] Step 3:

[1801] The terminal receives the user's input information and sends a request for campsite recommendations to the server.

[1802] Step 4:

[1803] The device activates an emotion engine and acquires emotion data from the user's facial expressions and tone of voice.

[1804] Step 5:

[1805] The server refers to a campsite database to select the most suitable campsite based on the location information and emotion data of the arriving user.

[1806] Step 6:

[1807] The server takes into account the emotional data and recommends "Mt. Fuji Campground" and "Mt. Mitake Campground," and sends this as a response to the device.

[1808] Step 7:

[1809] The terminal displays recommended campsite information to the user.

[1810] Clothes suggestions

[1811] Step 1:

[1812] A user types, "What should I wear when I go camping?"

[1813] Step 2:

[1814] The terminal receives the user's input information and sends a request for clothing suggestions to the server.

[1815] Step 3:

[1816] The terminal starts an emotion engine and acquires the user's emotion data.

[1817] Step 4:

[1818] The server generates data to suggest appropriate clothing based on weather information, seasonal data, and emotional data.

[1819] Step 5:

[1820] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[1821] Step 6:

[1822] The terminal displays clothing suggestion information to the user.

[1823] Tool Setup

[1824] Step 1:

[1825] A user types, "What gear do I need for camping?"

[1826] Step 2:

[1827] The terminal receives the user's input information and sends a tool setup request to the server.

[1828] Step 3:

[1829] The terminal starts an emotion engine and acquires the user's emotion data.

[1830] Step 4:

[1831] The server refers to a list of basic camping equipment and generates equipment setup information that takes emotion data into consideration.

[1832] Step 5:

[1833] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[1834] Step 6:

[1835] The terminal displays the tool setup information to the user.

[1836] Outdoor cooking recipe suggestions

[1837] Step 1:

[1838] A user types, "Tell me some easy camping recipes."

[1839] Step 2:

[1840] The terminal receives the user's input information and sends a cooking recipe request to the server.

[1841] Step 3:

[1842] The terminal starts an emotion engine and acquires the user's emotion data.

[1843] Step 4:

[1844] The server refers to a recipe database for camping cooking and generates cooking recipe information that takes emotion data into consideration.

[1845] Step 5:

[1846] The server sends recipe information for "Foil-roasted vegetables, campfire burgers, and s'mores" to the device.

[1847] Step 6:

[1848] The terminal displays cooking recipe information to the user.

[1849] Activity suggestions

[1850] Step 1:

[1851] A user types, "What activities can I enjoy while camping?"

[1852] Step 2:

[1853] The terminal receives the user's input information and sends a request for activity suggestions to the server.

[1854] Step 3:

[1855] The terminal starts an emotion engine and acquires the user's emotion data.

[1856] Step 4:

[1857] The server refers to the activity proposal database and generates activity information that takes emotion data into consideration.

[1858] Step 5:

[1859] The server sends information such as "hiking, kayaking, fishing, stargazing around a campfire" to the device.

[1860] Step 6:

[1861] The terminal displays the activity information to the user.

[1862] Suggestions for information on scenic spots and hidden hot springs along the way

[1863] Step 1:

[1864] The user types in, "What are some great scenic spots and secret hot springs I can stop at on the way to the campsite?"

[1865] Step 2:

[1866] The terminal receives the user's input information and sends a request for information on scenic spots and secret hot springs to the server.

[1867] Step 3:

[1868] The terminal starts an emotion engine and acquires the user's emotion data.

[1869] Step 4:

[1870] The server refers to a database of road spots and generates road spot information taking emotion data into consideration.

[1871] Step 5:

[1872] The server sends information about Shiraito Falls and Gotemba Onsen to the terminal.

[1873] Step 6:

[1874] The device displays information about scenic spots and hidden hot springs to the user.

[1875] This makes it possible to provide personalized information according to the user's emotional state, allowing the user to enjoy a comfortable and fulfilling camping experience.

[1876] Example 2

[1877] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1878] Conventional camping planning support systems make suggestions without considering the user's emotional state, which often results in suggestions that are not optimal for the user's current emotional state. Furthermore, while optimal suggestions vary depending on the user's emotional state, there is a lack of a means to recognize emotions and provide personalized suggestions accordingly. This creates a demand for a system that allows users to plan appropriate camping trips without feeling anxious or stressed.

[1879] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a camping plan request from a user, means for requesting recommended campsite information from the server, means for generating the recommended campsite information based on the user's location information, past history, and emotion data, means for presenting the recommended information to the user, and means for recognizing the user's emotion using an emotion recognition engine. This makes it possible to recommend appropriate campsites, suggest clothing, and suggest tool setups that take into account the user's emotion data.

[1880] "User" refers to an individual who uses the system to make camping plans.

[1881] A "camping planning request" refers to a user's request for campsite recommendations and information about camping.

[1882] A "server" refers to a computer system that receives requests from users, processes the data, generates appropriate information, and returns it to the terminal.

[1883] "Campsite recommendation information" refers to information about suitable locations for camping, and is generated based on the user's location information, past camping history, and emotion data.

[1884] "Location information" refers to data about where a user is currently located or where a user has previously visited.

[1885] "Camping history" refers to records of campsites the user has visited in the past and the activities they performed there.

[1886] "Emotion data" is data that indicates the user's current emotional state and is generated by an emotion recognition engine.

[1887] An "emotion recognition engine" refers to a system that recognizes a user's emotions using a camera, microphone, or text analysis and generates that data.

[1888] "Clothing Information" refers to information about appropriate clothing for camping.

[1889] "Equipment Setup Information" refers to a list of equipment needed for camping and information on how to set it up.

[1890] The "means for generating recommendation information" refers to a process in which the server creates recommendation information about camping based on the user's location information, past history, and emotional data.

[1891] The "means for presenting recommendation information" refers to a process for displaying the generated recommendation information to the user through a user interface.

[1892] This invention relates to a system that personalizes camping plans and provides optimal suggestions based on the user's emotions. This system consists of three main components: a user interface, a server, and an emotion recognition engine.

[1893] User Interface

[1894] The user interface is where users input their camping planning requirements and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users can request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about spots along the way. This allows users to easily obtain information that meets their needs and desires.

[1895] server

[1896] The server generates information in response to user requests and returns it to the device. Specifically, the following databases and algorithms are implemented:

[1897] Database: MySQL and MongoDB are used to store user location information, past history, and information on various campsites.

[1898] Algorithm: A machine learning model using Python generates optimal recommendations based on user sentiment data and past history.

[1899] Emotion Recognition Engine

[1900] The emotion recognition engine is responsible for recognizing the user's emotions and adjusting camping plans and suggestions based on that emotion data. The following technologies are used for emotion recognition:

[1901] Biometric sensors: Use cameras and microphones to detect the user's facial expressions and voice sounds and recognize emotions (e.g., Amazon Rekognition, Microsoft Azure Emotion API).

[1902] Natural language processing: Analyzing user text input and recognizing sentiment (e.g., Google Cloud Natural Language API).

[1903] Specific examples of processing

[1904] Campsite selection

[1905] A user launches the app and enters a request: "I want to go camping next weekend. What are some recommended campgrounds?"

[1906] The server references the user's current location information and past camping history data, and selects the most suitable campsite candidate using an emotion recognition engine, taking into account the emotion data.

[1907] The server recommends "Mt. Fuji Campground" and "Mt. Mitake Campground" and sends them as a response to the terminal.

[1908] The terminal displays recommended campsite information to the user.

[1909] Clothes suggestions

[1910] A user asks, "What should I wear when I go camping?"

[1911] The server generates appropriate clothing suggestions taking into consideration weather information, seasonal data, and emotion data from an emotion recognition engine.

[1912] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[1913] The terminal displays clothing suggestion information to the user.

[1914] Tool Setup

[1915] A user asks, "What equipment do I need for camping?"

[1916] The server refers to a list of basic camping equipment and generates a list that also takes into account emotional data using an emotion recognition engine.

[1917] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[1918] The terminal displays the tool setup information to the user.

[1919] Prompt Sentence Examples

[1920] Describe how the system responds to the following user questions:

[1921] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[1922] The emotion engine detects anxiety. Please describe what campsites you recommend and how you tailor the information based on the user's emotions.

[1923] Through the above process, the system can take into account the user's emotional data and propose personalized camping plans, allowing the user to enjoy camping more comfortably and with peace of mind.

[1924] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1925] Step 1:

[1926] User Interface Input

[1927] A user launches a smartphone app or web application and inputs a camping plan request.

[1928] Input: User request (e.g., "I want to go camping next weekend. What campsites do you recommend?").

[1929] Output: The request data is sent to the server.

[1930] Specific operation: The user enters a question into the app's input form and presses the submit button.

[1931] Step 2:

[1932] Receiving and parsing the request

[1933] The server receives the request from the user interface and parses the content.

[1934] Input: The request data sent by the user.

[1935] Output: Parsed request information (e.g., a user's campsite recommendation request).

[1936] Specific operation: The server analyzes the received request data and performs a process to extract the necessary information.

[1937] Step 3:

[1938] Location information and history reference

[1939] The server references a location information database and a past camp history database.

[1940] Input: User's current location and past camping history.

[1941] Output: Referenced location information and camp history data.

[1942] Specific operation: The server sends a query to the database and collects the relevant location information and history data.

[1943] Step 4:

[1944] Emotion Recognition and Data Integration

[1945] An emotion recognition engine recognizes the user's emotion and generates emotion data.

[1946] Input: User biometric information and text input information.

[1947] Output: The generated emotion data.

[1948] How it works: The emotion recognition engine uses the camera, microphone, and text analysis to recognize the user's emotions in real time.

[1949] Step 5:

[1950] Data Processing and Information Generation

[1951] The server integrates location information, past history, and emotion data to generate optimal campsite recommendation information.

[1952] Input: location information, past history, emotional data.

[1953] Output: The generated campsite recommendations.

[1954] What it does: The server uses machine learning algorithms to select and aggregate the best campsite candidates.

[1955] Step 6:

[1956] Sending and Displaying Information

[1957] The server transmits the generated recommendation information to the terminal.

[1958] Input: Generated campsite recommendations.

[1959] Output: Recommendations sent to the device.

[1960] Specific operation: The server packages the recommendation information and sends the data to the terminal.

[1961] Step 7:

[1962] User interface display

[1963] The terminal displays the received recommendation information to the user.

[1964] Input: Recommendation information sent to the device.

[1965] Output: Recommendation information displayed on the user interface.

[1966] Specific operation: The terminal analyzes the received data and displays the information on the user interface.

[1967] (Application example 2)

[1968] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1969] Modern camping plans require more personalized suggestions based on the user's individual requests and emotional state. However, conventional systems struggle to recognize users' emotions and optimize suggestions based on that data. Even in brick-and-mortar stores, there is a lack of a way to provide optimal products and plans based on user emotions through dialogue. This leads to a decline in the quality of the user experience and a lack of fulfillment in the overall camping plan.

[1970] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving a camping plan request from a user; means for requesting recommended campsite information from the server; means for generating recommended campsite information based on the user's location information and past history; means for presenting the recommended information to the user; means for having an engine that recognizes the user's emotions and adjusting the campsite plan based on the emotion data; and means for using an interactive robot installed in a physical store to suggest optimal camping equipment and plans to the user. This makes it possible to suggest personalized camping plans based on the user's emotions, improving the customer experience in the physical store and increasing the overall quality of the user's campsite plans.

[1971] The "means for receiving a camping plan request from a user" refers to an interface that allows a user to input requests or questions about camping plans and a mechanism for receiving such requests.

[1972] The "means for requesting recommended campsite information from the server" is a communication means for requesting recommended campsite information from the server based on a user request.

[1973] "Means for generating recommended campsite information based on the user's location information and past history" is a function that utilizes the user's current location information and past behavioral history to select the most suitable campsite and generate recommended information.

[1974] The "means for presenting recommended information to the user" is a mechanism for displaying the generated recommended information for campsites on the user's device.

[1975] An "engine that recognizes user emotions" is software and hardware that analyzes and recognizes emotions from a user's facial expressions, tone of voice, text input, etc.

[1976] The "means for adjusting the camping plan based on emotion data" is a function for optimizing and adjusting the contents of the camping plan using the recognized emotion data of the user.

[1977] An "interactive robot installed in a physical store" is a robot that is placed in a physical store such as a camping equipment store and makes optimal suggestions based on emotions while directly interacting with the user.

[1978] The "means for suggesting camping equipment and plans" is a mechanism for suggesting appropriate camping equipment and plans of action based on the user's input and emotional data.

[1979] The system for implementing this invention mainly consists of a server, a user interface, an emotion engine, and an interactive robot installed in a physical store.

[1980] server

[1981] The server plays a central role in the system and performs the following processes:

[1982] 1. Receive a camping planning request from a user.

[1983] 2. Obtain the user's location information and past history data and generate campsite recommendation information.

[1984] 3. Use the emotion engine to adjust the camping plan based on the user's emotion data.

[1985] 4. Present recommendations to the user.

[1986] The server is equipped with a high-performance database and algorithms for fast and reliable data processing. The emotion engine works in conjunction with cameras and microphones for image recognition and voice analysis to recognize the user's emotions in real time.

[1987] User Interface

[1988] The user interface is the means by which users input their camping plan requests and interact with the system. It is implemented as a smartphone app or web application and allows the following operations:

[1989] Choosing a campsite

[1990] Clothing suggestions

[1991] Tool Setup

[1992] Outdoor Cooking Recipes

[1993] Activity suggestions

[1994] Request information on spots along the way

[1995] The interface has an intuitive and user-friendly design, allowing users to easily access the system.

[1996] Emotion Engine

[1997] The emotion engine is a key component that recognizes user emotions and makes suggestions based on that data. It uses biometric sensors and natural language processing technology to analyze emotion data from users' facial expressions, tone of voice, and text input.

[1998] For example, if a user is feeling anxious and asks, "I want to go camping next weekend. What campsites do you recommend?", the emotion engine will detect the anxiety and recommend a relaxing campsite.

[1999] Interactive robots in brick-and-mortar stores

[2000] The interactive robot, installed in a brick-and-mortar store, interacts with customers to recommend camping gear and plans. It operates as follows:

[2001] 1. The robot uses a camera and microphone to read the customer's emotions.

[2002] 2. Send the emotion data and your camping-related request to the server.

[2003] 3. Based on the recommendation information obtained from the server, suggestions are made via voice or display.

[2004] As a concrete example, here is an example of a conversation between a robot and a customer:

[2005] Robot: "Hello! What are your camping plans for today?"

[2006] Customer: "I'd like to go camping next weekend. Where can you recommend a campground?"

[2007] Robot: "Please wait a moment. We will find the best campsite for you based on the current weather and your preferences."

[2008] With the above system configuration, users can receive suggestions for optimal camping plans based on their emotional state, improving their in-store experience. Furthermore, the following prompt sentences can be used to facilitate information generation by the generative AI model:

[2009] Example prompt sentence:

[2010] I want to go camping next weekend. Where can I get some recommendations?

[2011] The system uses emotional data to personalize the user experience and provide a more comprehensive camping experience than ever before.

[2012] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2013] Step 1:

[2014] The user inputs a camping plan request. The user inputs a question or request about camping through a smartphone app or web application. For example, they input a prompt such as, "I want to go camping next weekend. Where is a recommended campsite?" Input data: Camping plan request. Output data: Request data from the user.

[2015] Step 2:

[2016] The user interface sends input data to the server. The terminal (smartphone or PC) receives the user's requested data and sends it to the server via the Internet. Input data: Data requested by the user. Output data: Requested data sent to the server.

[2017] Step 3:

[2018] The server obtains the user's location information and past history. The server obtains the user's current location information from GPS or IP address, and obtains related information by referring to a database of past camping history. Input data: User's request data, location information, and past history data. Output data: Complete request data including the user's location information and past history.

[2019] Step 4:

[2020] The emotion engine recognizes the user's emotions. The emotion engine analyzes the user's video and audio data acquired from the camera and microphone, or text input, and classifies the user's emotions. For example, it detects anxiety, excitement, joy, etc. Input data: User's video, audio, and text data. Output data: User's emotional data.

[2021] Step 5:

[2022] The server generates recommended campsite information. The server uses an algorithm to select the most suitable campsite based on the user's request data, location information, past history, and emotional data. A generative AI model is used to generate highly accurate recommendation information. Input data: User's request data, location information, past history, emotional data. Output data: Recommended campsite information.

[2023] Step 6:

[2024] The server sends the recommendation information to the terminal. The server returns the generated campsite recommendation information to the user interface again via the communication means. Input data: recommended campsite information. Output data: recommendation information sent to the terminal.

[2025] Step 7:

[2026] The terminal presents the recommendation information to the user. The terminal visually displays the received campsite recommendation information to the user. For example, detailed information and images of the campsite are displayed on the screen. Input data: recommendation information received from the server. Output data: campsite information presented to the user.

[2027] Step 8:

[2028] An interactive robot in a physical store makes suggestions to the user. The robot uses cameras and microphones inside the store to check the user's emotions again and sends the emotion data and the user's request to the server. It then makes suggestions for camping equipment and plans based on the latest recommendation information obtained from the server. Input data: The user's repeated request and emotion data. Output data: Suggestions for optimal camping equipment and plans.

[2029] As a result, users can receive suggestions for optimal camping plans and equipment based on their emotional state, enabling a personalized customer experience even in physical stores.

[2030] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2031] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2032] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2033] [Fourth embodiment]

[2034] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2035] 7, a 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.

[2036] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also 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).

[2037] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2038] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[2039] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[2040] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2041] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2042] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2043] The specific processing program 56 is an example of a "program" according to the technology of the present 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 in accordance with the specific processing program 56 executed on the RAM 30.

[2044] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2045] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2046] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2047] This invention relates to an interactive system that allows users to efficiently plan camping trips. The system according to this invention receives a camping trip plan request from a user, generates appropriate information in response to the request, and presents it to the user. This system is mainly implemented with the following configuration.

[2048] User Interface

[2049] This is the interface through which users enter details of their camping plans and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about spots along the way.

[2050] server

[2051] The server generates information in response to user requests and returns it to the device. Specifically, it implements databases and algorithms for generating campsite recommendations, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on road spots.

[2052] Processing flow

[2053] 1. Select a campsite

[2054] The user launches the app and requests to select a campsite.

[2055] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[2056] The server refers to the user's location information and past history and recommends the most suitable campsite.

[2057] The device will display recommended campsites. "The recommended campsites are as follows: 1. Mt. Fuji Campsite 2. Mt. Mitake Campsite."

[2058] 2. Clothing suggestions

[2059] The user asks about clothing.

[2060] User: "What should I wear when I go camping?"

[2061] The server will suggest appropriate clothing based on weather and seasonal data: "Consider light layers, long-sleeved shirts, waterproof jackets, and hiking boots."

[2062] The device will display clothing suggestions.

[2063] 3. Tool Setup

[2064] A user asks about camping equipment.

[2065] User: "What equipment do I need for camping?"

[2066] The server generates a list of basic camping equipment: "You'll need a tent, sleeping bag, cooking equipment, a lantern, and a first aid kit."

[2067] The terminal displays the tool list to the user.

[2068] 4. Outdoor cooking recipe suggestions

[2069] A user asks about camping recipes.

[2070] User: "Tell me some easy camping recipes."

[2071] The server generates recipe information for simple camping meals. "You can easily make things like foil-roasted vegetables, campfire burgers, and s'mores."

[2072] The device displays the cooking recipe to the user.

[2073] 5. Activity suggestions

[2074] Ask about activities users can enjoy while camping.

[2075] User: "What activities can I enjoy while camping?"

[2076] The server generates the appropriate activity information: "Enjoy hiking, kayaking, fishing, stargazing around a campfire, and more."

[2077] The terminal displays the activity information to the user.

[2078] 6. Information on scenic spots and hidden hot springs along the way

[2079] Ask about places users can stop along the way.

[2080] User: "Are there any scenic spots or hidden hot springs I can stop at on the way to the campsite?"

[2081] The server generates information about scenic spots and hidden hot springs that can be visited along the way. "Shiraito Falls and Gotemba Onsen are popular."

[2082] The terminal displays this information to the user.

[2083] Processing example

[2084] For example, suppose a user launches an app to select a campsite for a weekend camping trip. In this case, if the user asks, "Which campsites are recommended?", the device sends this question to the server. The server identifies the best campsite based on location information and past history, and returns it to the device as recommended information. The device then displays this information to the user, allowing the user to choose from among the options.

[2085] Similarly, the selection of clothing, equipment setup, cooking recipe suggestions, activity selection, and provision of information on spots along the way are all done efficiently through collaboration between the user, device, and server. This series of processes allows users to easily create detailed and optimal camping plans.

[2086] Implementation Requirements

[2087] In terms of implementation, the user interface must have an intuitive and easy-to-use design, and the server must have a fast and reliable database and algorithms. Real-time data processing capabilities are also important, allowing for the immediate incorporation of local weather information and user history. This system will enable users to streamline their preparations and enjoy a quality camping experience.

[2088] The processing flow will be explained below.

[2089] Specific steps for planning a camp

[2090] Campsite selection

[2091] Step 1:

[2092] The user launches the app and is presented with an interface for planning a camping trip.

[2093] Step 2:

[2094] A user types, "I want to go camping next weekend. What are some recommended campgrounds?"

[2095] Step 3:

[2096] The terminal receives the user's input information and sends a request for campsite recommendations to the server.

[2097] Step 4:

[2098] The server refers to the user's current location information and a database of past camping history to select the most suitable campsite candidate.

[2099] Step 5:

[2100] The server generates recommended campsite information, such as "Mt. Fuji Campsite" and "Mt. Mitake Campsite," and sends it back to the terminal as a response.

[2101] Step 6:

[2102] The terminal displays the received campsite recommendation information to the user.

[2103] Clothes suggestions

[2104] Step 1:

[2105] A user types, "What should I wear when I go camping?"

[2106] Step 2:

[2107] The terminal receives the user's input information and sends a request for clothing suggestions to the server.

[2108] Step 3:

[2109] The server obtains weather forecasts and seasonal information in real time and generates appropriate clothing suggestions.

[2110] Step 4:

[2111] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[2112] Step 5:

[2113] The clothing suggestion information received by the terminal is displayed to the user.

[2114] Tool Setup

[2115] Step 1:

[2116] A user types, "What gear do I need for camping?"

[2117] Step 2:

[2118] The terminal receives the user's input information and sends a tool setup request to the server.

[2119] Step 3:

[2120] The server references a list of basic camping equipment and generates information on "tent, sleeping bag, cooking equipment, lantern, first aid kit."

[2121] Step 4:

[2122] The server sends the generated tool list to the terminal.

[2123] Step 5:

[2124] The terminal displays the received tool setup information to the user.

[2125] Outdoor cooking recipe suggestions

[2126] Step 1:

[2127] A user types, "Tell me some easy camping recipes."

[2128] Step 2:

[2129] The terminal receives the user's input information and sends a cooking recipe request to the server.

[2130] Step 3:

[2131] The server refers to a recipe database for camping dishes and generates recipe information for "Foil-baked vegetables, campfire burgers, and s'mores."

[2132] Step 4:

[2133] The server transmits the generated cooking recipe information to the terminal.

[2134] Step 5:

[2135] The terminal displays the received cooking recipe information to the user.

[2136] Activity suggestions

[2137] Step 1:

[2138] A user types, "What activities can I enjoy while camping?"

[2139] Step 2:

[2140] The terminal receives the user's input information and sends a request for activity suggestions to the server.

[2141] Step 3:

[2142] The server references a database of activity suggestions and generates information such as "hiking, kayaking, fishing, and stargazing around a campfire."

[2143] Step 4:

[2144] The activity information generated by the server is sent to the terminal.

[2145] Step 5:

[2146] The terminal displays the received activity information to the user.

[2147] Suggestions for information on scenic spots and hidden hot springs along the way

[2148] Step 1:

[2149] The user types in, "What are some great scenic spots and secret hot springs I can stop at on the way to the campsite?"

[2150] Step 2:

[2151] The terminal receives the user's input information and sends a request for information on scenic spots and secret hot springs to the server.

[2152] Step 3:

[2153] The server references a database of spots along the way and generates information on "Shiraito Falls" and "Gotemba Onsen."

[2154] Step 4:

[2155] The server transmits the generated route spot information to the terminal.

[2156] Step 5:

[2157] The device displays the information about scenic spots and secret hot springs received by the device to the user.

[2158] This allows users to efficiently obtain all the necessary information from planning to preparation and execution of their camping plans, enabling them to have a comfortable and fulfilling camping experience.

[2159] Example 1

[2160] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2161] When planning a camping trip, it is difficult for users to efficiently gather and prepare a wide range of information, such as selecting an appropriate campsite, necessary equipment, appropriate clothing, cooking recipes, activity selection, and information about spots along the way. A system that can resolve this difficulty is needed.

[2162] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2163] In this invention, the server includes means for generating recommended campsite information based on the user's location information and past history, means for generating appropriate clothing information based on weather and seasonal data, means for generating a list of camping equipment, means for generating simple cooking recipe information, means for generating information on activities that can be enjoyed while camping, and means for generating information on scenic spots and hidden hot springs along the way, thereby enabling the user to efficiently plan a series of camping trips.

[2164] "User" refers to a person who uses this system to plan a camping trip.

[2165] A "camping plan request" refers to a user requesting the system for information and suggestions necessary for carrying out a camping trip.

[2166] A "server" refers to a device that receives requests from users, generates the necessary information using a database or algorithm, and returns it.

[2167] "Recommended campsite information" refers to information about campsites recommended by the server based on the user's location information and past history.

[2168] "Clothing suggestions" refers to suggesting clothing and equipment suitable for camping based on weather and seasonal data.

[2169] "Equipment setup" refers to making a list of the equipment and tools needed for camping and preparing based on that.

[2170] "Cooking recipes" refers to information showing how to prepare meals that can be easily prepared while camping.

[2171] "Activity Information" refers to information about activities and events that can be enjoyed while camping.

[2172] "Information about spots along the way" refers to information about tourist spots such as famous places and hot springs that you can stop at on the way to the campsite.

[2173] "Request" refers to a request that a user sends to the system for specific information.

[2174] A "database" refers to a collection of digital information that stores various information about camping.

[2175] An "algorithm" refers to a procedure or computational method for solving a specific problem.

[2176] "Location information" refers to geographical information based on a user's current location and past behavioral history.

[2177] "Weather Data" means current and forecasted weather information for the proposed campsite.

[2178] "Seasonal data" refers to information about weather and environmental changes in a particular region or period.

[2179] This invention relates to an interactive system that allows users to efficiently plan camping trips. The system based on this invention receives a camping trip plan request from a user, generates appropriate information in response to the request, and presents it to the user. This system is generally implemented as a smartphone app or a web application.

[2180] User Interface

[2181] This is the interface through which users enter details of their camping plans and interact with the system, requesting campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about stops along the way.

[2182] server

[2183] The server generates information in response to user requests and returns it to the device. The server implements the following functions:

[2184] Recommendation information for campsites is generated based on the user's location information and past history.

[2185] Appropriate clothing information is generated based on weather and seasonal data.

[2186] Generate a list of camping gear.

[2187] To generate cooking recipe information that can be easily prepared.

[2188] Generate information about activities you can enjoy while camping.

[2189] Generates information on scenic spots and hidden hot springs along the way.

[2190] Processing flow

[2191] Campsite selection

[2192] When a user starts the app and asks, "I want to go camping next weekend. Where are some recommended campsites?", the device sends this question and the user's location information to the server. The server searches the database based on the location information and past history, generates recommendations for the best campsites, and sends them back to the device. The device then displays this information to the user.

[2193] Clothes suggestions

[2194] When a user asks, "What should I wear when I go camping?", the device sends the request and location information to the server. The server retrieves weather and seasonal data, generates information suggesting appropriate clothing, and sends it back to the device. The device then displays this information to the user.

[2195] Tool Setup

[2196] When a user asks, "What equipment do I need for camping?", the device sends the request to the server. The server generates a list of camping equipment and sends it back to the device. The device displays this information to the user.

[2197] Outdoor cooking recipe suggestions

[2198] When a user asks, "Tell me some easy camping recipes," the device sends the request to the server. The server generates simple cooking recipe information and returns it to the device. The device then displays this information to the user.

[2199] Activity suggestions

[2200] When a user asks, "Tell me about activities I can enjoy while camping," the device sends the request to the server, which generates appropriate activity information and sends it back to the device, which then displays it to the user.

[2201] Suggestions for information on scenic spots and hidden hot springs along the way

[2202] When a user asks, "What are some scenic spots and hidden hot springs I can stop at on the way to the campsite?", the device sends the request to the server. The server generates information about spots that can be stopped at along the way and sends it back to the device. The device then displays this information to the user.

[2203] Specific examples

[2204] For example, if a user launches an app to plan a weekend camping trip and asks, "Where are some recommended campsites?", the device will send this question to the server. The server will identify the best campsites based on location information and past history, and return it to the device as recommended information. The device will then display this information to the user, who can then choose from it. Similarly, the selection of clothing, equipment setup, cooking recipe suggestions, activity selection, and provision of information on spots along the way are all done efficiently through collaboration between the user, device, and server. This series of processes enables users to easily create detailed and optimal camping plans.

[2205] This system allows users to streamline the entire preparation process and enjoy a high-quality camping experience.

[2206] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2207] Campsite selection

[2208] Processing Steps

[2209] Step 1:

[2210] A user launches a smartphone app or web application.

[2211] Input: None

[2212] Output: The app is launched.

[2213] Step 2:

[2214] The user types into the interface, "I want to go camping next weekend. What are some recommended campgrounds?"

[2215] Input: User question

[2216] Output: Question typed into terminal

[2217] Step 3:

[2218] The device acquires the user's location information and sends it to the server along with the question.

[2219] Input: User question, location information

[2220] Output: The location and question are sent to the server.

[2221] Step 4:

[2222] The server searches a database based on the location information received and past history to identify the best campsite.

[2223] Input: Location information, past history

[2224] Output: Campsite recommendation information

[2225] Step 5:

[2226] The server returns the generated campsite recommendation information to the terminal.

[2227] Input: Campsite recommendation information

[2228] Output: Recommendation information is sent to the device

[2229] Step 6:

[2230] The terminal analyzes the campsite recommendation information received from the server and displays it to the user.

[2231] Input: Campsite recommendation information

[2232] Output: User is shown the recommendation

[2233] Clothes suggestions

[2234] Processing Steps

[2235] Step 1:

[2236] The user types into the interface, "What should I wear when I go camping?"

[2237] Input: User question

[2238] Output: Question typed into terminal

[2239] Step 2:

[2240] The device acquires the user's location information and sends it to the server along with the question.

[2241] Input: User question, location information

[2242] Output: The location and question are sent to the server.

[2243] Step 3:

[2244] The server retrieves current weather and season data and identifies appropriate clothing.

[2245] Input: Weather data, seasonal data, location information

[2246] Output: Clothes suggestion information

[2247] Step 4:

[2248] The server returns the generated clothing suggestion information to the terminal.

[2249] Input: Clothing suggestion information

[2250] Output: Suggestion information is sent to the device

[2251] Step 5:

[2252] The terminal analyzes the clothing suggestion information received from the server and displays it to the user.

[2253] Input: Clothing suggestion information

[2254] Output: The user is presented with the suggested information

[2255] Tool Setup

[2256] Processing Steps

[2257] Step 1:

[2258] The user types into the interface, "What equipment do I need for camping?"

[2259] Input: User question

[2260] Output: Question typed into terminal

[2261] Step 2:

[2262] The terminal sends a question to the server.

[2263] Input: User question

[2264] Output: The question is sent to the server

[2265] Step 3:

[2266] The server generates a basic camping equipment list from a database.

[2267] Input: None

[2268] Output: Tool list

[2269] Step 4:

[2270] The server returns the generated tool list to the terminal.

[2271] Input: Tool list

[2272] Output: The list is sent to the terminal.

[2273] Step 5:

[2274] The terminal analyzes the tool list received from the server and displays it to the user.

[2275] Input: Tool list

[2276] Output: The list is displayed to the user

[2277] Outdoor cooking recipe suggestions

[2278] Processing Steps

[2279] Step 1:

[2280] A user types into the interface, "Can you give me some easy camping recipes?"

[2281] Input: User question

[2282] Output: Question typed into terminal

[2283] Step 2:

[2284] The terminal sends a question to the server.

[2285] Input: User question

[2286] Output: The question is sent to the server

[2287] Step 3:

[2288] The server generates easy-to-make cooking recipe information from the database.

[2289] Input: None

[2290] Output: Cooking recipe information

[2291] Step 4:

[2292] The server returns the generated cooking recipe information to the terminal.

[2293] Input: Cooking recipe information

[2294] Output: Recipe information is sent to the device

[2295] Step 5:

[2296] The terminal analyzes the cooking recipe information received from the server and displays it to the user.

[2297] Input: Cooking recipe information

[2298] Output: The recipe information is displayed to the user.

[2299] Activity suggestions

[2300] Processing Steps

[2301] Step 1:

[2302] The user types into the interface, "Tell me some fun activities to do while camping."

[2303] Input: User question

[2304] Output: Question typed into terminal

[2305] Step 2:

[2306] The terminal sends a question to the server.

[2307] Input: User question

[2308] Output: The question is sent to the server

[2309] Step 3:

[2310] The server generates the appropriate activity information from the database.

[2311] Input: None

[2312] Output: Activity information

[2313] Step 4:

[2314] The server returns the generated activity information to the terminal.

[2315] Input: Activity information

[2316] Output: Activity information is sent to the device

[2317] Step 5:

[2318] The terminal analyzes the activity information received from the server and displays it to the user.

[2319] Input: Activity information

[2320] Output: User is shown activity information

[2321] Suggestions for information on scenic spots and hidden hot springs along the way

[2322] Processing Steps

[2323] Step 1:

[2324] The user types into the interface, "What are some great scenic spots and hidden hot springs I can stop at on the way to the campsite?"

[2325] Input: User question

[2326] Output: Question typed into terminal

[2327] Step 2:

[2328] The terminal sends a question to the server.

[2329] Input: User question

[2330] Output: The question is sent to the server

[2331] Step 3:

[2332] The server generates information on scenic spots and hidden hot springs from the database.

[2333] Input: None

[2334] Output: Spot information

[2335] Step 4:

[2336] The server returns the generated spot information to the terminal.

[2337] Input: Spot information

[2338] Output: Spot information is sent to the device

[2339] Step 5:

[2340] The device analyzes the spot information received from the server and displays it to the user.

[2341] Input: Spot information

[2342] Output: The spot information is displayed to the user

[2343] (Application example 1)

[2344] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2345] Conventional camping planning systems typically require users to obtain information through an interface, but there is a demand for a more interactive and intuitive shopping experience, such as a brick-and-mortar store. Furthermore, they lack the real-time and appropriate information required for on-site use, making it difficult for users to make optimal decisions on-site. This often leads to inefficient on-site preparation and execution, resulting in a poor camping experience.

[2346] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2347] In this invention, the server includes means for receiving a camping plan request from a user, means for requesting recommended campsite information from the server, means for generating the recommended campsite information based on the user's location information and past history, means for presenting the recommended information to the user, and means for cooperating with an in-store guidance device to present the user with optimal camping equipment and information, thereby enabling consistent support from in-store guidance to on-site preparations.

[2348] A "camping plan request" is information or a request regarding detailed plans for a user to go camping.

[2349] A "server" is a data processing device that generates information based on a request from a user and returns it to the terminal.

[2350] "Campsite recommendation information" is data for suggesting suitable campsites based on the user's wishes and conditions.

[2351] "User location information" is information that indicates the geographical location where the user is currently located.

[2352] "Past history" refers to data relating to camping trips and campsites selected by the user in the past.

[2353] The "means for presenting recommendation information" refers to an interface or device for displaying the generated recommendation information to the user.

[2354] An "in-store guidance device" is a device that provides information and guidance to users within a physical store.

[2355] "Camping equipment" refers to the tools and equipment necessary for camping.

[2356] "Appropriate clothing information" is suggestions and data about clothing suitable for camping.

[2357] "Equipment Setup Information" means specific guides and instructions for preparing and setting up camping equipment.

[2358] This invention is an interactive system for efficiently planning camping trips, and can be implemented as a user assistant in a physical store. This system is mainly composed of a user interface, a server, and a guide device in the store.

[2359] System configuration

[2360] 1. User Interface

[2361] The user interface allows users to input details of their camping plans and interact with the system. Implemented as smart glasses or a smartphone app, the user can request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about stops along the way.

[2362] 2. Server

[2363] The server generates information in response to user requests and returns it to the device. This server is equipped with a fast and reliable database and algorithms. Specifically, it includes databases and algorithms for generating campsite recommendations, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on road spots.

[2364] 3. Guidance devices in stores

[2365] The in-store guidance device provides users with information and guidance on camping equipment. When a user wearing smart glasses visits a physical store, the system provides the necessary information in real time.

[2366] Processing flow

[2367] The server receives a camping plan request from the user and generates information based on the request. For example, if a user requests, "Where are some recommended campsites?", the server automatically references the user's location information and past history to generate recommendations for the best campsites. The generated information is then displayed on the user's smart glasses.

[2368] Hardware and software used

[2369] Hardware: smart glasses (e.g., Google Glass), smartphones

[2370] Software: Python programs, natural language processing libraries (e.g., SpaCy), databases (e.g., SQLite)

[2371] Data processing and calculation

[2372] The server references the database based on the user's request and generates information appropriate for the user. At this time, it uses natural language processing to analyze the user's input and extract appropriate information. It also generates customized recommendation information based on location information and past history.

[2373] Specific examples

[2374] When a user wears the smart glasses in a physical store and requests "outfit suggestions" through the app, the system will provide optimal outfit suggestions based on the current season and weather information. Specifically, the following dialogue takes place:

[2375] example:

[2376] User: "I want to go camping next weekend. Where can I find some recommended campgrounds?"

[2377] System: "The recommended campsites are as follows: 1. Mt. Fuji Campground 2. Mt. Mitake Campground"

[2378] User: "What should I wear when I go camping?"

[2379] System: "Here are some recommended outfits for this season: consider light layers, long-sleeve shirts, waterproof jackets, and hiking boots."

[2380] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2381] Program processing flow

[2382] Step 1:

[2383] A user puts on smart glasses and inputs a camping plan request through the application. A request is sent to the server. This input includes text data such as "What are some recommended campsites?"

[2384] Step 2:

[2385] The server receives the user's request. Using a natural language processing library (e.g., SpaCy), it analyzes the request to determine what the user is looking for. This analysis process involves tokenizing the input text and extracting keywords.

[2386] Step 3:

[2387] The server retrieves the user's location and past history from a database. It uses location services and a built-in history database (e.g., SQLite) to retrieve the user's current geographic location and previously visited campsites.

[2388] Step 4:

[2389] The server generates campsite recommendations based on the captured location information and past history, using an algorithm to list the best campsites based on geographic proximity and past user preferences.

[2390] Step 5:

[2391] The server returns the generated campsite recommendation information to the user's device. The information is displayed on the smart glasses. At this time, the recommended information (e.g., "Campsite at the foot of Mt. Fuji," "Campsite at Mt. Mitake," etc.) is displayed.

[2392] Step 6:

[2393] The user inputs the next request, for example, "What should I wear when I go camping?" and sends it to the server again. This request is again handled by the server.

[2394] Step 7:

[2395] The server obtains the current season and weather information. It uses a weather API to obtain current weather data and determines the season information from the internal clock.

[2396] Step 8:

[2397] The server generates appropriate clothing suggestions based on the acquired season and weather information, and selects and lists clothing items suitable for the weather conditions from a clothing database.

[2398] Step 9:

[2399] The server then sends the generated clothing suggestion information back to the user's device, and specific items such as "light layers, long-sleeved shirt, waterproof jacket, and hiking boots" are displayed on the smart glasses.

[2400] Specific processing operations

[2401] Input and Output:

[2402] Input: User voice or text input

[2403] Output: Generated camping plans and proposal information

[2404] Data processing and calculation:

[2405] Natural language processing: Analysis of input requests (tokenization, keyword extraction)

[2406] Data reference: Location information and past history database reference

[2407] Data generation: Generating optimal recommendations and proposals

[2408] Specific behavior:

[2409] Retrieving information from a database (e.g. SQLite)

[2410] Real-time external API requests (e.g. weather API)

[2411] Recommendation algorithms make optimal choices

[2412] This allows the user to efficiently prepare for camping and carry out activities on the day.

[2413] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2414] This invention relates to a system that personalizes camping plans and makes optimal suggestions based on the user's emotions. The system based on this invention combines an emotion engine that recognizes the user's emotions and adjusts camping plans and suggestions based on the user's emotion data. The main components and specific processing of this system are described below.

[2415] User Interface

[2416] This is the interface through which users input their camping planning requests and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information on spots along the way.

[2417] server

[2418] The server generates information in response to user requests and returns it to the device. Specifically, it implements databases and algorithms for generating campsite recommendations using an emotion engine, clothing suggestions, equipment setup information, outdoor cooking recipes, activity suggestions, and information on spots along the way.

[2419] Emotion Engine

[2420] The emotion engine is responsible for recognizing the user's emotions and adjusting camping plans and suggestions based on that emotional data. Emotion recognition is achieved using biometric sensors such as cameras and microphones, or natural language processing technology based on the user's text input.

[2421] Processing flow

[2422] Campsite selection

[2423] A user launches the app and enters a request to plan a camping trip.

[2424] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[2425] The server refers to the user's current location information and a database of past camping history, and selects the most suitable campsite candidate using an emotion engine, taking into account emotional data.

[2426] The server recommends "Mt. Fuji Campground" and "Mt. Mitake Campground" and sends them as a response to the terminal.

[2427] The terminal displays recommended campsite information to the user.

[2428] Clothes suggestions

[2429] The user asks about clothing.

[2430] User: "What should I wear when I go camping?"

[2431] The server generates appropriate clothing suggestions taking into consideration weather information, seasonal data, and emotion data from an emotion engine.

[2432] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[2433] The terminal displays clothing suggestion information to the user.

[2434] Tool Setup

[2435] A user asks about camping equipment.

[2436] User: "What equipment do I need for camping?"

[2437] The server refers to a list of basic camping equipment and generates a list that takes emotion data into consideration using an emotion engine.

[2438] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[2439] The terminal displays the tool setup information to the user.

[2440] Outdoor cooking recipe suggestions

[2441] A user asks about camping recipes.

[2442] User: "Tell me some easy camping recipes."

[2443] The server refers to a recipe database for camping cooking and generates an appropriate recipe by taking into consideration the emotional data using an emotion engine.

[2444] The server sends recipe information for "Foil-roasted vegetables, campfire burgers, and s'mores" to the device.

[2445] The terminal displays cooking recipe information to the user.

[2446] Activity suggestions

[2447] Ask about activities users can enjoy while camping.

[2448] User: "What activities can I enjoy while camping?"

[2449] The server refers to the activity suggestion database and generates appropriate activity information using an emotion engine, taking into account emotion data.

[2450] The server sends information such as "hiking, kayaking, fishing, stargazing around a campfire" to the device.

[2451] The terminal displays the activity information to the user.

[2452] Suggestions for information on scenic spots and hidden hot springs along the way

[2453] Ask about places users can stop along the way.

[2454] User: "Are there any scenic spots or hidden hot springs I can stop at on the way to the campsite?"

[2455] The server refers to a database of spots along the way and generates appropriate spot information using an emotion engine, taking into account emotion data.

[2456] The server sends information about Shiraito Falls and Gotemba Onsen to the terminal.

[2457] The device displays information about scenic spots and hidden hot springs along the way to the user.

[2458] Processing example

[2459] For example, if a user is anxious and planning a camping trip, the emotion engine will recognize that emotion. When the emotion engine detects "anxiety," the server will suggest relaxing campsites and easy activities accordingly. If a user asks, "Where should I go camping next weekend?", the server will recommend a campsite in a quiet plain as a "relaxing environment."

[2460] Similarly, clothing suggestions, tool setup, cooking recipe suggestions, activity selection, and information on spots along the way are also optimized based on the user's emotional data. This process enables personalized camping plans based on the user's emotional state, making the user's experience more comfortable and fulfilling.

[2461] Implementation Requirements

[2462] When implementing the system, the user interface must have an intuitive and easy-to-use design, and the server must have a fast and reliable database and algorithms. Furthermore, the emotion engine must integrate sensors capable of highly accurate emotion recognition and natural language processing technology. This system will enable users to consistently receive personalized information and enjoy the best camping experience.

[2463] The processing flow will be explained below.

[2464] Specific processing steps for camping planning (embedded emotion engine)

[2465] Campsite selection

[2466] Step 1:

[2467] The user launches the app and is presented with an interface for planning a camping trip.

[2468] Step 2:

[2469] A user types, "I want to go camping next weekend. What are some recommended campgrounds?"

[2470] Step 3:

[2471] The terminal receives the user's input information and sends a request for campsite recommendations to the server.

[2472] Step 4:

[2473] The device activates an emotion engine and acquires emotion data from the user's facial expressions and tone of voice.

[2474] Step 5:

[2475] The server refers to a campsite database to select the most suitable campsite based on the location information and emotion data of the arriving user.

[2476] Step 6:

[2477] The server takes into account the emotional data and recommends "Mt. Fuji Campground" and "Mt. Mitake Campground," and sends this as a response to the device.

[2478] Step 7:

[2479] The terminal displays recommended campsite information to the user.

[2480] Clothes suggestions

[2481] Step 1:

[2482] A user types, "What should I wear when I go camping?"

[2483] Step 2:

[2484] The terminal receives the user's input information and sends a request for clothing suggestions to the server.

[2485] Step 3:

[2486] The terminal starts an emotion engine and acquires the user's emotion data.

[2487] Step 4:

[2488] The server generates data to suggest appropriate clothing based on weather information, seasonal data, and emotional data.

[2489] Step 5:

[2490] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[2491] Step 6:

[2492] The terminal displays clothing suggestion information to the user.

[2493] Tool Setup

[2494] Step 1:

[2495] A user types, "What gear do I need for camping?"

[2496] Step 2:

[2497] The terminal receives the user's input information and sends a tool setup request to the server.

[2498] Step 3:

[2499] The terminal starts an emotion engine and acquires the user's emotion data.

[2500] Step 4:

[2501] The server refers to a list of basic camping equipment and generates equipment setup information that takes emotion data into consideration.

[2502] Step 5:

[2503] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[2504] Step 6:

[2505] The terminal displays the tool setup information to the user.

[2506] Outdoor cooking recipe suggestions

[2507] Step 1:

[2508] A user types, "Tell me some easy camping recipes."

[2509] Step 2:

[2510] The terminal receives the user's input information and sends a cooking recipe request to the server.

[2511] Step 3:

[2512] The terminal starts an emotion engine and acquires the user's emotion data.

[2513] Step 4:

[2514] The server refers to a recipe database for camping cooking and generates cooking recipe information that takes emotion data into consideration.

[2515] Step 5:

[2516] The server sends recipe information for "Foil-roasted vegetables, campfire burgers, and s'mores" to the device.

[2517] Step 6:

[2518] The terminal displays cooking recipe information to the user.

[2519] Activity suggestions

[2520] Step 1:

[2521] A user types, "What activities can I enjoy while camping?"

[2522] Step 2:

[2523] The terminal receives the user's input information and sends a request for activity suggestions to the server.

[2524] Step 3:

[2525] The terminal starts an emotion engine and acquires the user's emotion data.

[2526] Step 4:

[2527] The server refers to the activity proposal database and generates activity information that takes emotion data into consideration.

[2528] Step 5:

[2529] The server sends information such as "hiking, kayaking, fishing, stargazing around a campfire" to the device.

[2530] Step 6:

[2531] The terminal displays the activity information to the user.

[2532] Suggestions for information on scenic spots and hidden hot springs along the way

[2533] Step 1:

[2534] The user types in, "What are some great scenic spots and secret hot springs I can stop at on the way to the campsite?"

[2535] Step 2:

[2536] The terminal receives the user's input information and sends a request for information on scenic spots and secret hot springs to the server.

[2537] Step 3:

[2538] The terminal starts an emotion engine and acquires the user's emotion data.

[2539] Step 4:

[2540] The server refers to a database of road spots and generates road spot information taking emotion data into consideration.

[2541] Step 5:

[2542] The server sends information about Shiraito Falls and Gotemba Onsen to the terminal.

[2543] Step 6:

[2544] The device displays information about scenic spots and hidden hot springs to the user.

[2545] This makes it possible to provide personalized information according to the user's emotional state, allowing the user to enjoy a comfortable and fulfilling camping experience.

[2546] Example 2

[2547] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2548] Conventional camping planning support systems make suggestions without considering the user's emotional state, which often results in suggestions that are not optimal for the user's current emotional state. Furthermore, while optimal suggestions vary depending on the user's emotional state, there is a lack of a means to recognize emotions and provide personalized suggestions accordingly. This creates a demand for a system that allows users to plan appropriate camping trips without feeling anxious or stressed.

[2549] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a camping plan request from a user, means for requesting recommended campsite information from the server, means for generating the recommended campsite information based on the user's location information, past history, and emotion data, means for presenting the recommended information to the user, and means for recognizing the user's emotion using an emotion recognition engine. This makes it possible to recommend appropriate campsites, suggest clothing, and suggest tool setups that take into account the user's emotion data.

[2550] "User" refers to an individual who uses the system to make camping plans.

[2551] A "camping planning request" refers to a user's request for campsite recommendations and information about camping.

[2552] A "server" refers to a computer system that receives requests from users, processes the data, generates appropriate information, and returns it to the terminal.

[2553] "Campsite recommendation information" refers to information about suitable locations for camping, and is generated based on the user's location information, past camping history, and emotion data.

[2554] "Location information" refers to data about where a user is currently located or where a user has previously visited.

[2555] "Camping history" refers to records of campsites the user has visited in the past and the activities they performed there.

[2556] "Emotion data" is data that indicates the user's current emotional state and is generated by an emotion recognition engine.

[2557] An "emotion recognition engine" refers to a system that recognizes a user's emotions using a camera, microphone, or text analysis and generates that data.

[2558] "Clothing Information" refers to information about appropriate clothing for camping.

[2559] "Equipment Setup Information" refers to a list of equipment needed for camping and information on how to set it up.

[2560] The "means for generating recommendation information" refers to a process in which the server creates recommendation information about camping based on the user's location information, past history, and emotional data.

[2561] The "means for presenting recommendation information" refers to a process for displaying the generated recommendation information to the user through a user interface.

[2562] This invention relates to a system that personalizes camping plans and provides optimal suggestions based on the user's emotions. This system consists of three main components: a user interface, a server, and an emotion recognition engine.

[2563] User Interface

[2564] The user interface is where users input their camping planning requirements and interact with the system. It is typically implemented as a smartphone app or web application. Through this interface, users can request campsite selection, clothing suggestions, equipment setup, outdoor cooking recipes, activity suggestions, and information about spots along the way. This allows users to easily obtain information that meets their needs and desires.

[2565] server

[2566] The server generates information in response to user requests and returns it to the device. Specifically, the following databases and algorithms are implemented:

[2567] Database: MySQL and MongoDB are used to store user location information, past history, and information on various campsites.

[2568] Algorithm: A machine learning model using Python generates optimal recommendations based on user sentiment data and past history.

[2569] Emotion Recognition Engine

[2570] The emotion recognition engine is responsible for recognizing the user's emotions and adjusting camping plans and suggestions based on that emotion data. The following technologies are used for emotion recognition:

[2571] Biometric sensors: Use cameras and microphones to detect the user's facial expressions and voice sounds and recognize emotions (e.g., Amazon Rekognition, Microsoft Azure Emotion API).

[2572] Natural language processing: Analyzing user text input and recognizing sentiment (e.g., Google Cloud Natural Language API).

[2573] Specific examples of processing

[2574] Campsite selection

[2575] A user launches the app and enters a request: "I want to go camping next weekend. What are some recommended campgrounds?"

[2576] The server references the user's current location information and past camping history data, and selects the most suitable campsite candidate using an emotion recognition engine, taking into account the emotion data.

[2577] The server recommends "Mt. Fuji Campground" and "Mt. Mitake Campground" and sends them as a response to the terminal.

[2578] The terminal displays recommended campsite information to the user.

[2579] Clothes suggestions

[2580] A user asks, "What should I wear when I go camping?"

[2581] The server generates appropriate clothing suggestions taking into consideration weather information, seasonal data, and emotion data from an emotion recognition engine.

[2582] The server sends information to the terminal saying, "Light layers, long-sleeved shirts, waterproof jackets, hiking boots, etc. are appropriate."

[2583] The terminal displays clothing suggestion information to the user.

[2584] Tool Setup

[2585] A user asks, "What equipment do I need for camping?"

[2586] The server refers to a list of basic camping equipment and generates a list that also takes into account emotional data using an emotion recognition engine.

[2587] The server sends information about "tents, sleeping bags, cooking equipment, lanterns, and first aid kits" to the terminal.

[2588] The terminal displays the tool setup information to the user.

[2589] Prompt Sentence Examples

[2590] Describe how the system responds to the following user questions:

[2591] User: "I want to go camping next weekend. What are some recommended campgrounds?"

[2592] The emotion engine detects anxiety. Please describe what campsites you recommend and how you tailor the information based on the user's emotions.

[2593] Through the above process, the system can take into account the user's emotional data and propose personalized camping plans, allowing the user to enjoy camping more comfortably and with peace of mind.

[2594] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2595] Step 1:

[2596] User Interface Input

[2597] A user launches a smartphone app or web application and inputs a camping plan request.

[2598] Input: User request (e.g., "I want to go camping next weekend. What campsites do you recommend?").

[2599] Output: The request data is sent to the server.

[2600] Specific operation: The user enters a question into the app's input form and presses the submit button.

[2601] Step 2:

[2602] Receiving and parsing the request

[2603] The server receives the request from the user interface and parses the content.

[2604] Input: The request data sent by the user.

[2605] Output: Parsed request information (e.g., a user's campsite recommendation request).

[2606] Specific operation: The server analyzes the received request data and performs a process to extract the necessary information.

[2607] Step 3:

[2608] Location information and history reference

[2609] The server references a location information database and a past camp history database.

[2610] Input: User's current location and past camping history.

[2611] Output: Referenced location information and camp history data.

[2612] Specific operation: The server sends a query to the database and collects the relevant location information and history data.

[2613] Step 4:

[2614] Emotion Recognition and Data Integration

[2615] An emotion recognition engine recognizes the user's emotion and generates emotion data.

[2616] Input: User biometric information and text input information.

[2617] Output: The generated emotion data.

[2618] How it works: The emotion recognition engine uses the camera, microphone, and text analysis to recognize the user's emotions in real time.

[2619] Step 5:

[2620] Data Processing and Information Generation

[2621] The server integrates location information, past history, and emotion data to generate optimal campsite recommendation information.

[2622] Input: location information, past history, emotional data.

[2623] Output: The generated campsite recommendations.

[2624] What it does: The server uses machine learning algorithms to select and aggregate the best campsite candidates.

[2625] Step 6:

[2626] Sending and Displaying Information

[2627] The server transmits the generated recommendation information to the terminal.

[2628] Input: Generated campsite recommendations.

[2629] Output: Recommendations sent to the device.

[2630] Specific operation: The server packages the recommendation information and sends the data to the terminal.

[2631] Step 7:

[2632] User interface display

[2633] The terminal displays the received recommendation information to the user.

[2634] Input: Recommendation information sent to the device.

[2635] Output: Recommendation information displayed on the user interface.

[2636] Specific operation: The terminal analyzes the received data and displays the information on the user interface.

[2637] (Application example 2)

[2638] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2639] Modern camping plans require more personalized suggestions based on the user's individual requests and emotional state. However, conventional systems struggle to recognize users' emotions and optimize suggestions based on that data. Even in brick-and-mortar stores, there is a lack of a way to provide optimal products and plans based on user emotions through dialogue. This leads to a decline in the quality of the user experience and a lack of fulfillment in the overall camping plan.

[2640] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving a camping plan request from a user; means for requesting recommended campsite information from the server; means for generating recommended campsite information based on the user's location information and past history; means for presenting the recommended information to the user; means for having an engine that recognizes the user's emotions and adjusting the campsite plan based on the emotion data; and means for using an interactive robot installed in a physical store to suggest optimal camping equipment and plans to the user. This makes it possible to suggest personalized camping plans based on the user's emotions, improving the customer experience in the physical store and increasing the overall quality of the user's campsite plans.

[2641] The "means for receiving a camping plan request from a user" refers to an interface that allows a user to input requests or questions about camping plans and a mechanism for receiving such requests.

[2642] The "means for requesting recommended campsite information from the server" is a communication means for requesting recommended campsite information from the server based on a user request.

[2643] "Means for generating recommended campsite information based on the user's location information and past history" is a function that utilizes the user's current location information and past behavioral history to select the most suitable campsite and generate recommended information.

[2644] The "means for presenting recommended information to the user" is a mechanism for displaying the generated recommended information for campsites on the user's device.

[2645] An "engine that recognizes user emotions" is software and hardware that analyzes and recognizes emotions from a user's facial expressions, tone of voice, text input, etc.

[2646] The "means for adjusting the camping plan based on emotion data" is a function for optimizing and adjusting the contents of the camping plan using the recognized emotion data of the user.

[2647] An "interactive robot installed in a physical store" is a robot that is placed in a physical store such as a camping equipment store and makes optimal suggestions based on emotions while directly interacting with the user.

[2648] The "means for suggesting camping equipment and plans" is a mechanism for suggesting appropriate camping equipment and plans of action based on the user's input and emotional data.

[2649] The system for implementing this invention mainly consists of a server, a user interface, an emotion engine, and an interactive robot installed in a physical store.

[2650] server

[2651] The server plays a central role in the system and performs the following processes:

[2652] 1. Receive a camping planning request from a user.

[2653] 2. Obtain the user's location information and past history data and generate campsite recommendation information.

[2654] 3. Use the emotion engine to adjust the camping plan based on the user's emotion data.

[2655] 4. Present recommendations to the user.

[2656] The server is equipped with a high-performance database and algorithms for fast and reliable data processing. The emotion engine works in conjunction with cameras and microphones for image recognition and voice analysis to recognize the user's emotions in real time.

[2657] User Interface

[2658] The user interface is the means by which users input their camping plan requests and interact with the system. It is implemented as a smartphone app or web application and allows the following operations:

[2659] Choosing a campsite

[2660] Clothing suggestions

[2661] Tool Setup

[2662] Outdoor Cooking Recipes

[2663] Activity suggestions

[2664] Request information on spots along the way

[2665] The interface has an intuitive and user-friendly design, allowing users to easily access the system.

[2666] Emotion Engine

[2667] The emotion engine is a key component that recognizes user emotions and makes suggestions based on that data. It uses biometric sensors and natural language processing technology to analyze emotion data from users' facial expressions, tone of voice, and text input.

[2668] For example, if a user is feeling anxious and asks, "I want to go camping next weekend. What campsites do you recommend?", the emotion engine will detect the anxiety and recommend a relaxing campsite.

[2669] Interactive robots in brick-and-mortar stores

[2670] The interactive robot, installed in a brick-and-mortar store, interacts with customers to recommend camping gear and plans. It operates as follows:

[2671] 1. The robot uses a camera and microphone to read the customer's emotions.

[2672] 2. Send the emotion data and your camping-related request to the server.

[2673] 3. Based on the recommendation information obtained from the server, suggestions are made via voice or display.

[2674] As a concrete example, here is an example of a conversation between a robot and a customer:

[2675] Robot: "Hello! What are your camping plans for today?"

[2676] Customer: "I'd like to go camping next weekend. Where can you recommend a campground?"

[2677] Robot: "Please wait a moment. We will find the best campsite for you based on the current weather and your preferences."

[2678] With the above system configuration, users can receive suggestions for optimal camping plans based on their emotional state, improving their in-store experience. Furthermore, the following prompt sentences can be used to facilitate information generation by the generative AI model:

[2679] Example prompt sentence:

[2680] I want to go camping next weekend. Where can I get some recommendations?

[2681] The system uses emotional data to personalize the user experience and provide a more comprehensive camping experience than ever before.

[2682] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2683] Step 1:

[2684] The user inputs a camping plan request. The user inputs a question or request about camping through a smartphone app or web application. For example, they input a prompt such as, "I want to go camping next weekend. Where is a recommended campsite?" Input data: Camping plan request. Output data: Request data from the user.

[2685] Step 2:

[2686] The user interface sends input data to the server. The terminal (smartphone or PC) receives the user's requested data and sends it to the server via the Internet. Input data: Data requested by the user. Output data: Requested data sent to the server.

[2687] Step 3:

[2688] The server obtains the user's location information and past history. The server obtains the user's current location information from GPS or IP address, and obtains related information by referring to a database of past camping history. Input data: User's request data, location information, and past history data. Output data: Complete request data including the user's location information and past history.

[2689] Step 4:

[2690] The emotion engine recognizes the user's emotions. The emotion engine analyzes the user's video and audio data acquired from the camera and microphone, or text input, and classifies the user's emotions. For example, it detects anxiety, excitement, joy, etc. Input data: User's video, audio, and text data. Output data: User's emotional data. ...

Claims

1. means for receiving a camping plan request from a user; a means for requesting campsite recommendation information from a server; A means for generating campsite recommendation information based on the user's location information and past history; means for presenting recommendation information to a user; A system including:

2. The system according to claim 1 , further comprising means for receiving from the user a suggestion of clothing suitable for camping, generating appropriate clothing information based on the suggestion, and presenting the information to the user.

3. 2. The system according to claim 1, further comprising means for receiving from a user a list of equipment required for camping, generating equipment setup information based on the list, and presenting the information to the user.

4. The system according to claim 1 , further comprising means for receiving from the user suggestions for activities to be performed during camp, generating appropriate activity information based on the suggestions, and presenting the information to the user.

5. 2. The system according to claim 1, further comprising means for receiving information from the user about scenic spots and hidden hot springs that can be visited along the way, generating route spot information based on the information, and presenting the information to the user.

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