system

Abstract

We provide the system. [Solution] An information processing device that provides drivers with real-time sales strategies, A means of obtaining event information, weather information, and traffic information from an external database, A means for performing analysis to optimize the driver's business using the acquired information, A means for proposing a sales area and route based on the aforementioned analysis, A means of notifying the driver of the proposed service area and route by voice using an audio output device, A means of receiving voice instructions from the driver and searching for additional information based on those instructions, A system that includes this.

Description

Technical Field

[0005]

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the rideshare industry, whether a driver can efficiently acquire passengers determines the success or failure of the business. However, there are problems that novice drivers or drivers unfamiliar with the local geography find it difficult to conduct efficient business due to lack of experience and local knowledge. In addition, with the liberalization of rideshare and the increase in foreign drivers, these problems have become even more prominent. Furthermore, even considering fully autonomous driving, the development of a system that supports efficient and safe operation is required. Therefore, means for solving these problems are necessary.

Means for Solving the Problems

[0005] This invention provides a system that uses generative artificial intelligence to analyze event information, weather information, and traffic information obtained from multiple external databases, and proposes business areas and routes to drivers in real time. Specifically, this system uses a voice output device to notify drivers of the proposals by voice, enabling hands-free operation. It also has a function to receive voice instructions from drivers and search for necessary additional information based on those instructions. Furthermore, by using business data collected from drivers to reinforce the system, it will be possible to realize advanced mobility support with a view to fully autonomous driving in the future.

[0006] An "information processing device" is a device that analyzes data acquired from external sources and provides drivers with the optimal sales strategy based on the results.

[0007] An "external database" is a database that stores event information, weather information, traffic information, etc., and plays the role of providing this information to the system.

[0008] "Generative artificial intelligence" is an artificial intelligence technology that predicts pedestrian traffic based on input information and presents sales strategies to drivers.

[0009] A "sales area" is a region where drivers can efficiently conduct sales activities, and it is identified based on real-time data analysis.

[0010] A "route" is a recommended path suggested by the system for drivers to travel efficiently within a designated service area.

[0011] A "voice output device" is a device that uses voice to transmit instructions and information to the driver in order to supplement visual information provided by the system.

[0012] "Voice commands" are verbal commands used by the driver to operate the system hands-free, and the system recognizes these commands and performs the necessary processing.

[0013] "Reinforcement learning" is a type of machine learning technique that improves a system's performance by using sales data obtained from drivers to enhance its capabilities. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Embodiments for Carrying out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the language used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] The system according to the present invention is an information processing device that supports drivers in efficiently carrying out their business activities. Its principle, configuration, and specific embodiments are described below.

[0036] Server operation

[0037] The server first retrieves real-time data such as event information, weather information, and traffic information from an external database. This data collection is performed regularly, and the retrieved data is analyzed within the server by generative artificial intelligence. In particular, it predicts pedestrian flow and determines which areas have a large number of potential passengers. Based on the results of this analysis, the server formulates the optimal service area and route.

[0038] Terminal operation

[0039] The terminal receives sales strategy information transmitted from the server. This information is then transmitted to the driver via speech synthesis technology, allowing the driver to obtain information hands-free. This enables the driver to acquire necessary information without distraction while driving, ensuring safe driving. Furthermore, the terminal accepts voice commands from the driver, supporting tasks such as obtaining new routes or confirming rest stops. Based on these requests, any additional information needed is retrieved from the server and provided to the driver.

[0040] User (driver) usage examples

[0041] Drivers can significantly improve their sales efficiency by using this system. For example, even in areas that would normally require experience and local knowledge, they can efficiently acquire passengers even in unfamiliar areas based on data provided by the server. If a user needs to change their sales area while driving due to local event information or sudden weather changes, they can instantly obtain the latest optimal strategy by entering voice instructions into the terminal.

[0042] This allows drivers to improve the accuracy and agility of their decision-making in business activities, contributing to efficient and safe driving. Therefore, the present invention provides drivers with an effective tool that dramatically improves their daily business activities.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The server retrieves event information, weather information, and traffic information from an external database. The data is regularly updated to ensure it remains up-to-date in real time.

[0046] Step 2:

[0047] The server inputs the acquired data into a generative artificial intelligence model for analysis. This analysis predicts pedestrian flow trends and calculates the concentration of passengers in specific areas and time periods.

[0048] Step 3:

[0049] Based on the analysis results, the server creates a strategy for the driver that determines the optimal sales area and route. This strategy includes recommended sales areas and the most efficient routes to reach them.

[0050] Step 4:

[0051] The server transmits the formulated sales strategy to the terminal. The terminal receives this information and prepares to accurately transmit it to the driver.

[0052] Step 5:

[0053] The terminal uses speech synthesis technology to notify the driver of the information it receives. Voice notifications allow drivers to understand the sales strategy without relying on visual cues, thus enabling safer driving.

[0054] Step 6:

[0055] The user (driver) begins operations in the designated area and route based on instructions from the terminal. If necessary, they can request additional information from the terminal via voice commands.

[0056] Step 7:

[0057] The terminal requests additional data from the server in response to voice commands from the driver. This data may include information that the driver needs to update in real time, such as traffic conditions and facility information for a specific area.

[0058] Step 8:

[0059] The server receives requests from terminals, analyzes the latest information, and sends it back to the terminals. Drivers can use this information to adjust their sales strategies as needed and maintain optimal performance.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] When drivers utilize external information to conduct sales activities efficiently, it is difficult for them to find the appropriate sales area and route in real time. Conventional systems lacked the support to integrate diverse information and take quick action, resulting in a heavy burden on drivers' decision-making.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for acquiring event information, weather information, and traffic information from external information sources; means for performing analysis to optimize transportation efficiency based on the acquired information; and means for formulating sales areas and routes based on the analysis. This enables drivers to find the optimal sales area and route in real time and conduct sales activities quickly and efficiently.

[0065] An "information processing system" is a device that collects and analyzes data and provides useful information based on the results.

[0066] "External information sources" refer to means of obtaining information from data providers or APIs that exist outside the system.

[0067] "Event information" refers to data about specific activities or events held in a region, which may influence people's movement patterns.

[0068] "Weather information" refers to real-time data about the weather, which directly impacts the planning of business activities.

[0069] "Traffic information" refers to data on current road conditions and congestion levels, which is important for selecting a driving route.

[0070] "Transportation efficiency" is an indicator that enables drivers to conduct business activities efficiently, and it is achieved by selecting appropriate routes and service areas.

[0071] "Generative artificial intelligence" refers to AI technology that can perform predictions and analyses based on large amounts of data, and specifically includes deep learning models.

[0072] A "speech synthesis device" is a device that has the technology to convert digital text information into speech, enabling drivers to obtain information by voice.

[0073] "Voice instructions" refer to instructions or commands that the driver inputs to the system using their voice.

[0074] This invention relates to an information processing system that enables drivers to obtain optimal service area and route information in real time. The entire system consists of three main components: a server, a terminal, and a user.

[0075] The server acquires event information, weather information, and traffic information from external sources. Specifically, it periodically collects this information using APIs and stores it in a database. Based on this information, the server performs data analysis using a generative AI model. A deep learning algorithm is used as the generative AI model. As a result of the analysis, the optimal sales area and route for a given time and location are calculated. The server compiles these analysis results and formulates the next required sales strategy.

[0076] The terminal uses speech synthesis technology to provide voice-based information about the service area and routes, enabling drivers to safely obtain this information without requiring any driver intervention. Existing speech synthesis software is used for this purpose. The terminal can also receive voice commands from the driver. For example, if the driver voice-commands, "Tell me the best route next," the terminal sends a request to the server, instantly retrieving and providing the necessary information.

[0077] Drivers, as users of the system, can improve the efficiency and accuracy of their sales activities. Even in unfamiliar areas, they can efficiently acquire passengers by utilizing specific sales routes provided by the server. Furthermore, they can have the flexibility to change their sales area in response to sudden weather changes or new event information while driving.

[0078] A concrete example of a prompt message is, "Based on real-time event information, weather information, and traffic information, please suggest the optimal sales area and route." By inputting this prompt message into the generating AI model, the model performs analysis and executes a process to formulate a sales strategy.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The server retrieves event information, weather information, and traffic information from external sources. In doing so, the server accesses each data provider using APIs to retrieve the latest information. The input is API endpoint information, and the output is the retrieved real-time data. As a result, the server's internal database stores the fundamental data necessary for developing sales strategies.

[0082] Step 2:

[0083] The server analyzes the acquired data using a generating AI model. This analysis supplies the AI ​​model with event information, weather information, and traffic information collected in step 1 as input. Using a prompt message, the model is instructed to "suggest the optimal sales area and route based on real-time information," and the AI ​​performs pedestrian flow prediction and regional analysis to generate output. The output provides information on the optimal sales area and route. This allows the server to obtain analysis results that form the basis of sales strategies provided to drivers.

[0084] Step 3:

[0085] The terminal receives sales strategy information from the server. The terminal takes sales area and route information received from the server as input. Based on this information, it uses speech synthesis technology to notify the driver of the information verbally. The output is an audible voice message for the driver. This allows the driver to receive the latest sales information hands-free and make decisions while safely driving the vehicle.

[0086] Step 4:

[0087] The terminal accepts voice commands from the driver. When the driver gives a new voice command, such as "I want to check different route information," the terminal recognizes that command as input. The terminal interprets the command using voice recognition technology and sends a new data request to the server. As output, the latest information that meets the driver's request is provided again via the terminal. This allows the driver to respond flexibly to external information that changes in real time.

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] In recent years, the transportation and food delivery industries have been increasingly required to utilize real-time traffic conditions and forecasts to ensure efficient and safe deliveries. However, many current systems fail to provide delivery personnel with sufficient information to efficiently select the optimal route, resulting in delivery delays and inefficient route selection.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes means for acquiring environmental information, traffic information, and weather information from an external database; means for performing analysis to optimize the driver's operations using the acquired diverse information; and means for analyzing the data and predicting pedestrian flow using generative artificial intelligence. This makes it possible to propose appropriate sales areas and travel routes to drivers in real time. Furthermore, it becomes possible to support drivers in performing deliveries safely and efficiently through voice instructions.

[0093] A "driver" is a person who operates a vehicle and is responsible for safely and efficiently transporting goods or people to their destination.

[0094] An "information processing device" is a device that collects and analyzes a wide variety of data and provides useful information to users.

[0095] An "external database" is a large-scale information repository that can be accessed from enterprise systems or the internet, and it stores a variety of information.

[0096] "Environmental information" refers to information that shows the real-time state of the area in which the system is operating, and this includes information on pedestrian traffic and local events.

[0097] "Traffic information" refers to information that shows the flow of traffic and congestion within a designated area.

[0098] "Weather information" refers to information about the weather conditions in a specific area.

[0099] "Acquisition method" refers to the method of receiving necessary data from an external source and storing it within the system.

[0100] "Analysis methods" refer to methods of performing analysis using acquired data to derive useful results or suggestions.

[0101] "Sales area" refers to the area in which delivery personnel operate, and it is the region that should be optimized for efficient sales activities.

[0102] A "travel route" is the path a driver should take to reach their destination, optimized to support efficient and safe travel.

[0103] A "voice output device" is a device that converts electronic data into voice information and transmits it to the user.

[0104] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to learn from large datasets and generate new information and predictions.

[0105] "Data analysis" is the act of analyzing vast amounts of information and deriving insights and proposals that are suitable for a specific purpose.

[0106] The system implementing this invention provides an information processing device that supports drivers in efficiently performing delivery tasks. The server, terminal, and user elements work together to realize this system.

[0107] The server acquires environmental, traffic, and weather information in real time from external databases. This data is collected using APIs (e.g., OpenWeatherMap and Google® Maps API). The server analyzes this data using generative artificial intelligence models (e.g., GPT-3®) to generate the optimal service area and travel routes to provide to drivers. It also predicts pedestrian flow and sets efficient delivery routes. To achieve this, the server integrates various data and provides the analysis results to drivers.

[0108] The driver's terminal receives instructions from the server and transmits the information to the driver via a voice output device. This voice output device can utilize technologies such as Google Cloud Text-to-Speech. This allows the driver to receive information hands-free, improving safety. Furthermore, the terminal recognizes voice instructions from the driver and analyzes them using Google Speech-to-Text. This voice recognition technology enables immediate responses to additional requests from the driver and allows for the retrieval of new data from the server.

[0109] As a concrete example, consider a scenario where many competitions are canceled due to rain. A server that obtains real-time weather information predicts changes in pedestrian traffic and suggests new routes to delivery personnel to avoid congestion. Thanks to this system, delivery personnel can avoid traffic jams and reach their destinations quickly.

[0110] A possible prompt for the generative AI model might be, "Analyze real-time traffic data and weather information to suggest the optimal route for delivery personnel to efficiently perform their delivery duties." This prompt provides crucial instructions for the generative AI model to derive the optimal sales strategy.

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] The server retrieves environmental information, traffic information, and weather information from an external database using an API. This input data includes real-time information about a specific region. The server integrates this data and stores it in a database for centralized management.

[0114] Step 2:

[0115] The server inputs the acquired data into a generating AI model (e.g., GPT-3). The server uses the model to analyze the data and identify the optimal service area and travel route for the driver. Here, efficient routes are generated by taking into account data correlations and time-series patterns.

[0116] Step 3:

[0117] The generated data is pushed from the server to the driver's terminal. The terminal then informs the driver of this information audibly via an audio output device. This allows the driver to receive information about the suggested optimal route hands-free.

[0118] Step 4:

[0119] The user gives voice commands to the device. This voice is converted into text data on the device using speech recognition technology (e.g., Google Speech-to-Text). Input in this step may be requests for additional information or instructions for route changes from the user.

[0120] Step 5:

[0121] The terminal sends the instructions received from the user to the server. Based on this input, the server retrieves and analyzes new information if necessary and generates optimized additional information. This result is then sent back to the terminal and provided to the driver.

[0122] Step 6:

[0123] The server uses the overall data and driver feedback to reinforce the system through learning. This will improve future analytical accuracy and enable the proposal of more effective sales strategies. The output of Step 6 is the system's improved knowledge base.

[0124] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0125] This invention provides drivers with the most optimal sales strategies in real time, and further includes a function to recognize the driver's emotional state and provide corresponding feedback. In this system, the information processing unit, emotion engine, and terminal components work together in coordination.

[0126] Server operation

[0127] The server first retrieves event information, weather information, and traffic information from an external database and analyzes it using generative artificial intelligence. This analysis predicts pedestrian flow and identifies the optimal sales area and route for drivers. Based on this information, the server formulates a sales strategy and transmits it to the terminal. The server also provides additional information in response to the driver's voice commands.

[0128] Terminal operation

[0129] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. Voice instructions are used to ensure the driver can safely obtain information even while driving. Furthermore, the terminal is equipped with an emotion engine that analyzes the driver's emotional state based on their voice tone, facial recognition, and other biosensor information. This analysis information is sent to the server, where the sales strategy is adjusted according to the driver's emotional state.

[0130] User (driver) usage examples

[0131] Users receive instructions on their service area and routes from the server via their terminal. During normal work, the terminal's emotion engine detects the user's stress level and fatigue, and can suggest breaks or prompt route changes as needed. For example, if a user's fatigue level increases during a series of busy tasks, the system will provide voice advice to the driver to take a break.

[0132] This system allows drivers to improve efficiency through optimal sales strategies, enabling safe and comfortable sales activities. The use of the emotion engine is expected to improve driver health and reduce stress, ultimately leading to improved overall work performance. In this way, the present invention provides comprehensive sales support to drivers.

[0133] The following describes the processing flow.

[0134] Step 1:

[0135] The server retrieves event information, weather information, and traffic information from an external database. This information serves as foundational data for providing drivers with appropriate business strategies.

[0136] Step 2:

[0137] The server uses generative artificial intelligence to analyze the acquired information. This analysis predicts pedestrian traffic and identifies areas with a high concentration of potential passengers.

[0138] Step 3:

[0139] Based on the analysis results, the server formulates the optimal sales area and route for the driver. This sales strategy aims to maximize the efficiency of operational tasks.

[0140] Step 4:

[0141] The server transmits the formulated sales strategy and route information to the terminal. The terminal receives this information and prepares to present it appropriately to the driver.

[0142] Step 5:

[0143] The terminal uses speech synthesis technology to notify the driver of sales strategy information. This allows the driver to check the information hands-free while driving.

[0144] Step 6:

[0145] The device's emotion engine analyzes the driver's emotional state from their voice tone and facial expressions, and evaluates their stress levels and fatigue while driving.

[0146] Step 7:

[0147] The terminal sends the results of the emotion engine's analysis to the server and requests adjustments to the sales strategy that reflect the emotional state. This process enables route suggestions that take the driver's health and safety into consideration.

[0148] Step 8:

[0149] The user (driver) conducts sales activities according to the latest sales strategy provided by the terminal. If new information is needed or if the user's emotional state changes, the terminal retrieves additional information from the server accordingly and provides it to the user.

[0150] Step 9:

[0151] The server collects driver sales and emotional data and uses this data for reinforcement learning. This allows the system's performance to continuously improve, and in the future, it will be able to respond more flexibly to driver requests.

[0152] (Example 2)

[0153] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0154] Modern drivers need to adapt to a wealth of real-time information during their sales activities, but effectively processing this information and formulating optimal sales strategies is not easy. Furthermore, the lack of consideration for the driver's own emotions and health conditions leads to decreased efficiency and difficulties in ensuring safety. Therefore, there is a need for a system that optimizes sales strategies without burdening the driver.

[0155] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0156] In this invention, the server includes means for acquiring various information from an external database, means for analyzing information about the driver using the acquired information, and means for presenting recommended areas and routes based on the analysis results. This enables the formulation of optimal sales strategies in real time according to the situation, and safe and efficient driving support that takes into account the driver's emotional state.

[0157] An "external database" refers to a collection of information accessible via the internet or cloud services, including various event information, weather information, and traffic information.

[0158] "Means of analyzing information" refers to methods of processing acquired data to make decisions that are advantageous to the driver's business activities.

[0159] "Means for suggesting areas and routes" refers to the process of suggesting the optimal area and route for the driver based on the analysis results.

[0160] A "voice output device" refers to a device that notifies the driver of the analyzed results and suggestions via voice so that they can safely check them while driving.

[0161] "Means for receiving voice instructions and searching for related information" refers to the process of receiving voice instructions from the driver and obtaining corresponding additional information from the internet or databases.

[0162] "Means of analyzing emotional state" refers to technology that determines the driver's psychological and emotional state at a given time based on their voice, facial expressions, and other biometric information.

[0163] "Methods for adjusting sales strategies" refers to the process of optimizing existing sales plans in real time, taking into account the emotional state of drivers and changes in the external environment.

[0164] This invention is a system that provides drivers with the optimal sales strategy in real time, and further recognizes the driver's emotional state and provides feedback accordingly. The system mainly consists of a server, terminals, and users who utilize them.

[0165] First, the server collects necessary information from external databases. Specifically, it obtains event information, weather information, and traffic information via the internet. The APIs used include, for example, geographic information APIs used to obtain map data and weather information APIs used to obtain weather data. The server analyzes this information using a generative AI model to predict pedestrian flow and traffic conditions. In this analysis, prompts are input to the generative AI model. For example, a prompt might say, "Please provide a forecast of pedestrian flow in the Tokyo area during the morning."

[0166] Based on this analysis, the server determines the optimal sales area and route for the driver and sends it to the terminal. The sales strategy is communicated using the terminal's speech synthesis technology so that the driver can access the information hands-free. Specifically, a speech synthesis API is used to issue instructions such as, "Your next destination is Shinjuku."

[0167] On the other hand, the device constantly monitors the driver's emotional state. Through built-in sensors and microphones, it acquires the driver's voice tone and facial expression data, which is then analyzed by an emotion analysis engine. This information is transmitted to a server, and sales strategies are adjusted as needed.

[0168] Through the above process, the user (driver) can follow the suggested optimal sales route. As a result, safe and efficient driving becomes possible, and health management and stress reduction through emotion analysis can also be expected. In this way, the present invention provides comprehensive sales support to drivers.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] The server's role is to retrieve event information, weather information, and traffic information from an external database. This involves API calls via an internet connection. The retrieved data is returned to the server in JSON format, including metadata such as date, time, and location. This retrieved data serves as input for subsequent analysis.

[0172] Step 2:

[0173] The server's role is to input the acquired information into a generative AI model for analysis. Specifically, it inputs data as part of a prompt message, giving the command, "Output a traffic congestion forecast for the morning." Based on this command, the generative AI model quantifies pedestrian flow forecasts and congestion levels, generating the output necessary for optimizing sales areas and routes. This data forms the basis for developing optimized sales strategies.

[0174] Step 3:

[0175] The server determines the optimal sales area and route based on the analysis results and sends this information to the terminal. At this time, the generated data is constructed as a detailed plan that includes location information, recommended routes, and expected congestion times. Transmission to the terminal is done via a network protocol, and the server's output is used as input for the terminal's next processing.

[0176] Step 4:

[0177] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. Specifically, it uses a speech synthesis API to generate audio in the form of "The estimated time to your destination is 30 minutes." This audio output serves as a direct instruction to the driver. Through this entire process, the driver can obtain information without taking their hands off the wheel.

[0178] Step 5:

[0179] The device monitors the driver's condition in real time. This involves inputting voice tone and facial expressions into an emotion analysis engine for analysis. The acquired data is used to determine stress levels and fatigue levels, and the results are sent to the server. This provides detailed feedback on the driver's emotional state.

[0180] Step 6:

[0181] The server takes into account the driver's emotional state and fine-tunes the sales strategy as needed. For example, if a high stress level is detected, it may add rest stops or suggest a more comfortable route. The resulting strategic information is then sent back to the terminal for appropriate feedback.

[0182] Step 7:

[0183] The terminal then verbally re-notifies the driver of the adjusted sales strategy. This process is also carried out via a speech synthesis API. As a result, the driver receives optimal sales instructions based on the latest situation. Through the above series of steps, the driver can engage in sales activities with confidence and efficiency.

[0184] (Application Example 2)

[0185] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0186] Often, drivers or passengers are unable to obtain optimal business strategies or comfort during their ride, resulting in inefficient driving. Furthermore, the lack of consideration for the emotional state of drivers and passengers increases stress and discomfort, leading to a decline in the overall quality of the experience. These challenges need to be addressed.

[0187] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0188] In this invention, the server includes means for acquiring event information, weather information, and traffic information from an external database; means for analyzing the acquired information to determine the optimal sales strategy and propose a route; means for notifying the driver of the sales area and route by voice; and means for analyzing the emotional state of passengers and providing suggestions to improve their comfort. As a result, drivers can conduct sales efficiently while passengers can experience improved comfort.

[0189] An "information processing device" is a device that processes data obtained from an external source and provides appropriate information to the driver.

[0190] An "external database" is a data source used to collect information from external sources, including event information, weather information, and traffic information.

[0191] "Analysis" refers to the calculation process used to determine the optimal business strategy and route for drivers and passengers using the acquired data.

[0192] The "service area" is the region in which the driver is suggested to operate.

[0193] A "route" is the path chosen by the driver to travel.

[0194] A "voice output device" is a device used to convey analyzed information or suggestions in voice.

[0195] "Voice instructions" are instructions given by the driver to the system via voice.

[0196] "Emotional state" refers to the state in which passengers exhibit various emotional reactions.

[0197] "Comfort" refers to the level of comfort and satisfaction that passengers experience while riding.

[0198] To implement this invention, a system is constructed in which an information processing device, an emotion engine, a terminal equipped with a voice output device, and a server for analyzing various data work together.

[0199] The server retrieves event information, weather information, and traffic information from an external database and analyzes this information using generative artificial intelligence. Based on the analysis results, it identifies the optimal sales area and route for drivers and formulates a sales strategy. This information is then quickly transmitted to terminals.

[0200] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. A voice output device is installed within the vehicle, designed to allow for safe, real-time information acquisition even while driving. Furthermore, an emotion engine built into the terminal analyzes the emotional state of the driver and passengers from voice tone, facial expressions, and other biosensors. Based on the analyzed emotional state, the server adjusts the sales strategy and ride experience to improve comfort.

[0201] For example, if the emotional engine detects a stressed state while a passenger is in the vehicle, the server will suggest via the voice assistant, "Let's play some soothing music for a relaxing drive." Furthermore, it's possible to improve comfort by adjusting the interior temperature through the vehicle's environmental control system.

[0202] An example of a prompt message is, "Ride data suggests stress; suggest calming music and adjust climate." Based on this prompt, the server determines and implements specific actions to improve the rider's comfort during the ride.

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] The server retrieves event information, weather information, and traffic information from an external database. It then formats this data into the required format and prepares it for analysis. The input is raw data from the external database, and the output is formatted, analyzable data.

[0206] Step 2:

[0207] The server analyzes data acquired using generative artificial intelligence to identify the optimal sales area and route for drivers. Input data includes formatted event information, weather information, and traffic information, while output is the identified sales area and route. During the analysis process, the generative AI model predicts future pedestrian and traffic flow and creates an optimized sales strategy.

[0208] Step 3:

[0209] The server converts the identified service area and route into data for voice notification and sends it to the terminal. The input is the analyzed service area and route information, and the output is the data format for voice notification. After the information is sent, the terminal uses speech synthesis technology to notify the driver.

[0210] Step 4:

[0211] The terminal uses voice notification data received from the server to transmit information to the driver via a voice output device. The input is voice notification data, and the output is voice information conveyed to the driver. The driver then begins moving according to the proposed area and route.

[0212] Step 5:

[0213] The device's emotion engine analyzes voice tone and facial expressions to evaluate the emotional state of the driver and passengers. Input is voice and facial expression data acquired from the driver and passengers, and output is the analyzed emotional state information. Emotional changes are continuously monitored in real time.

[0214] Step 6:

[0215] The server adjusts sales strategies and ride experiences as needed based on emotional state information. In doing so, it generates prompts such as "Ride data suggests stress; suggest calming music and adjust climate," and sends them to the terminal. The input is the analyzed emotional state, and the output is the adjusted sales strategy and ride experience advice.

[0216] Step 7:

[0217] The terminal provides necessary voice assistance and environmental adjustments based on instructions from the server, and makes suggestions to the driver and passengers. The input is adjustment instructions from the server, and the output is specific suggestions and environmental settings for the driver and passengers. This allows drivers and passengers to have a more comfortable ride.

[0218] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0219] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0220] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0221] [Second Embodiment]

[0222] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0223] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0224] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0225] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0226] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0227] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0228] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0229] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0230] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0231] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0232] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0233] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0234] The system according to the present invention is an information processing device that supports drivers in efficiently carrying out their business activities. Its principle, configuration, and specific embodiments are described below.

[0235] Server operation

[0236] The server first retrieves real-time data such as event information, weather information, and traffic information from an external database. This data collection is performed regularly, and the retrieved data is analyzed within the server by generative artificial intelligence. In particular, it predicts pedestrian flow and determines which areas have a large number of potential passengers. Based on the results of this analysis, the server formulates the optimal service area and route.

[0237] Terminal operation

[0238] The terminal receives sales strategy information transmitted from the server. This information is then transmitted to the driver via speech synthesis technology, allowing the driver to obtain information hands-free. This enables the driver to acquire necessary information without distraction while driving, ensuring safe driving. Furthermore, the terminal accepts voice commands from the driver, supporting tasks such as obtaining new routes or confirming rest stops. Based on these requests, any additional information needed is retrieved from the server and provided to the driver.

[0239] User (driver) usage examples

[0240] Drivers can significantly improve their sales efficiency by using this system. For example, even in areas that would normally require experience and local knowledge, they can efficiently acquire passengers even in unfamiliar areas based on data provided by the server. If a user needs to change their sales area while driving due to local event information or sudden weather changes, they can instantly obtain the latest optimal strategy by entering voice instructions into the terminal.

[0241] This allows drivers to improve the accuracy and agility of their decision-making in business activities, contributing to efficient and safe driving. Therefore, the present invention provides drivers with an effective tool that dramatically improves their daily business activities.

[0242] The following describes the processing flow.

[0243] Step 1:

[0244] The server retrieves event information, weather information, and traffic information from an external database. The data is regularly updated to ensure it remains up-to-date in real time.

[0245] Step 2:

[0246] The server inputs the acquired data into a generative artificial intelligence model for analysis. This analysis predicts pedestrian flow trends and calculates the concentration of passengers in specific areas and time periods.

[0247] Step 3:

[0248] Based on the analysis results, the server creates a strategy for the driver that determines the optimal sales area and route. This strategy includes recommended sales areas and the most efficient routes to reach them.

[0249] Step 4:

[0250] The server transmits the formulated sales strategy to the terminal. The terminal receives this information and prepares to accurately transmit it to the driver.

[0251] Step 5:

[0252] The terminal uses speech synthesis technology to notify the driver of the information it receives. Voice notifications allow drivers to understand the sales strategy without relying on visual cues, thus enabling safer driving.

[0253] Step 6:

[0254] The user (driver) begins operations in the designated area and route based on instructions from the terminal. If necessary, they can request additional information from the terminal via voice commands.

[0255] Step 7:

[0256] The terminal requests additional data from the server in response to voice commands from the driver. This data may include information that the driver needs to update in real time, such as traffic conditions and facility information for a specific area.

[0257] Step 8:

[0258] The server receives requests from terminals, analyzes the latest information, and sends it back to the terminals. Drivers can use this information to adjust their sales strategies as needed and maintain optimal performance.

[0259] (Example 1)

[0260] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0261] When drivers utilize external information to conduct sales activities efficiently, it is difficult for them to find the appropriate sales area and route in real time. Conventional systems lacked the support to integrate diverse information and take quick action, resulting in a heavy burden on drivers' decision-making.

[0262] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0263] In this invention, the server includes means for acquiring event information, weather information, and traffic information from external information sources; means for performing analysis to optimize transportation efficiency based on the acquired information; and means for formulating sales areas and routes based on the analysis. This enables drivers to find the optimal sales area and route in real time and conduct sales activities quickly and efficiently.

[0264] An "information processing system" is a device that collects and analyzes data and provides useful information based on the results.

[0265] "External information sources" refer to means of obtaining information from data providers or APIs that exist outside the system.

[0266] "Event information" refers to data about specific activities or events held in a region, which may influence people's movement patterns.

[0267] "Weather information" refers to real-time data about the weather, which directly impacts the planning of business activities.

[0268] "Traffic information" refers to data on current road conditions and congestion levels, which is important for selecting a driving route.

[0269] "Transportation efficiency" is an indicator that enables drivers to conduct business activities efficiently, and it is achieved by selecting appropriate routes and service areas.

[0270] "Generative artificial intelligence" refers to AI technology that can perform predictions and analyses based on large amounts of data, and specifically includes deep learning models.

[0271] A "speech synthesis device" is a device that has the technology to convert digital text information into speech, enabling drivers to obtain information by voice.

[0272] "Voice instructions" refer to instructions or commands that the driver inputs to the system using their voice.

[0273] This invention relates to an information processing system that enables drivers to obtain optimal service area and route information in real time. The entire system consists of three main components: a server, a terminal, and a user.

[0274] The server acquires event information, weather information, and traffic information from external sources. Specifically, it periodically collects this information using APIs and stores it in a database. Based on this information, the server performs data analysis using a generative AI model. A deep learning algorithm is used as the generative AI model. As a result of the analysis, the optimal sales area and route for a given time and location are calculated. The server compiles these analysis results and formulates the next required sales strategy.

[0275] The terminal uses speech synthesis technology to provide voice-based information about the service area and routes, enabling drivers to safely obtain this information without requiring any driver intervention. Existing speech synthesis software is used for this purpose. The terminal can also receive voice commands from the driver. For example, if the driver voice-commands, "Tell me the best route next," the terminal sends a request to the server, instantly retrieving and providing the necessary information.

[0276] Drivers, as users of the system, can improve the efficiency and accuracy of their sales activities. Even in unfamiliar areas, they can efficiently acquire passengers by utilizing specific sales routes provided by the server. Furthermore, they can have the flexibility to change their sales area in response to sudden weather changes or new event information while driving.

[0277] A concrete example of a prompt message is, "Based on real-time event information, weather information, and traffic information, please suggest the optimal sales area and route." By inputting this prompt message into the generating AI model, the model performs analysis and executes a process to formulate a sales strategy.

[0278] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0279] Step 1:

[0280] The server obtains event information, weather information, and traffic information from external information sources. At this time, the server accesses each data provider using an API to retrieve the latest information. The input is the endpoint information of the API, and the output is the acquired real-time data. As a result, basic data necessary for formulating business strategies is accumulated in the server's internal database.

[0281] Step 2:

[0282] The server analyzes the data obtained using a generative AI model. In this analysis, the event information, weather information, and traffic information collected in Step 1 are supplied to the AI model as input. Using a prompt sentence, "Please propose the optimal business area and route based on the information obtained in real-time" is input into the model, and the AI performs pedestrian flow prediction and regional analysis to generate an output. As the output, optimal business area and route information is obtained. As a result, the server obtains analysis results that serve as the basis for the business strategy provided to the driver.

[0283] Step 3:

[0284] The terminal receives business strategy information from the server. The terminal obtains the business area and route information received from the server as input. Based on this information, using voice synthesis technology, information is notified to the driver by voice. The output is a voice message that the driver can listen to. As a result, the driver can receive the latest business information hands-free and make decisions while driving the vehicle safely.

[0285] Step 4:

[0286] The terminal accepts voice instructions from the driver. When the driver gives a new instruction such as "I want to check different route information" by voice, the terminal recognizes the instruction as input. The terminal interprets the instruction using voice recognition technology and sends a new data request to the server. As the output, the latest information corresponding to the driver's request is provided again via the terminal. As a result, the driver can flexibly respond to the changing external information in real-time.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0289] In recent years, in the transportation industry, food delivery industry, etc., it has been required to utilize real-time traffic conditions and prediction information to perform deliveries efficiently and safely. However, many current systems cannot sufficiently provide the information necessary for delivery personnel to efficiently select an optimal route, and as a result, delivery delays and inefficient route selections may occur.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0291] In this invention, the server includes means for acquiring environmental information, mobile traffic information, and weather information from an external database, means for performing analysis for optimizing the operations of a driver using the acquired diverse information, and means for analyzing data and predicting the flow of people using generative artificial intelligence. Thereby, it becomes possible to propose an appropriate business area and a movement route to the driver in real time. Also, it becomes possible to support the driver to perform deliveries safely and efficiently through voice instructions.

[0292] A "driver" is a person who drives a vehicle and is responsible for transporting goods or people safely and efficiently to a destination.

[0293] An "information processing device" is a device that collects and analyzes various types of data and provides useful information to users.

[0294] An "external database" is a large-scale information aggregate that can be accessed from an enterprise system or the Internet and stores various types of information.

[0295] "Environmental information" refers to information that shows the real-time state of the area in which the system is operating, and this includes information on pedestrian traffic and local events.

[0296] "Traffic information" refers to information that shows the flow of traffic and congestion within a designated area.

[0297] "Weather information" refers to information about the weather conditions in a specific area.

[0298] "Acquisition method" refers to the method of receiving necessary data from an external source and storing it within the system.

[0299] "Analysis methods" refer to methods of performing analysis using acquired data to derive useful results or suggestions.

[0300] "Sales area" refers to the area in which delivery personnel operate, and it is the region that should be optimized for efficient sales activities.

[0301] A "travel route" is the path a driver should take to reach their destination, optimized to support efficient and safe travel.

[0302] A "voice output device" is a device that converts electronic data into voice information and transmits it to the user.

[0303] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to learn from large datasets and generate new information and predictions.

[0304] "Data analysis" is the act of analyzing vast amounts of information and deriving insights and proposals that are suitable for a specific purpose.

[0305] The system implementing this invention provides an information processing device that supports drivers in efficiently performing delivery tasks. The server, terminal, and user elements work together to realize this system.

[0306] The server retrieves environmental information, mobile traffic information, and weather information in real time from an external database. This data is collected using APIs (such as OpenWeatherMap and Google Maps API). The server uses a generative artificial intelligence model (such as GPT-3) to analyze this data and generate an optimal business area and travel route to be provided to the driver. In addition, it predicts the flow of people and sets an efficient delivery route. For this purpose, the server integrates various data and provides the analysis results to the driver.

[0307] The driver's terminal receives instructions from the server and transmits information to the driver through a voice output device. Technologies such as Google Cloud Text-to-Speech can be used for this voice output device. As a result, the driver can receive information hands-free, which is characterized by improved safety. Furthermore, the terminal recognizes voice instructions from the driver and analyzes them using Google Speech-to-Text. With this voice recognition technology, it becomes possible to immediately respond to additional requests submitted by the driver and obtain new data from the server.

[0308] As a specific example, consider a scenario where many competitions are cancelled during rainy days. The server that has obtained real-time weather information predicts changes in the flow of people and proposes a new route to the delivery staff to avoid congestion. Thanks to this system, the delivery staff can avoid traffic jams and reach the delivery destination quickly.

[0309] As a prompt sentence for the generative AI model, an input such as "Please analyze real-time traffic data and weather information and propose an optimal route for the delivery staff to efficiently perform their delivery operations" can be considered. This prompt gives an important instruction for the generative AI model to derive an optimal business strategy.

[0310] The flow of specific processing in Application Example 1 will be described using FIG.

[0311] Step 1:

[0312] The server retrieves environmental information, traffic information, and weather information from an external database using an API. This input data includes real-time information about a specific region. The server integrates this data and stores it in a database for centralized management.

[0313] Step 2:

[0314] The server inputs the acquired data into a generating AI model (e.g., GPT-3). The server uses the model to analyze the data and identify the optimal service area and travel route for the driver. Here, efficient routes are generated by taking into account data correlations and time-series patterns.

[0315] Step 3:

[0316] The generated data is pushed from the server to the driver's terminal. The terminal then informs the driver of this information audibly via an audio output device. This allows the driver to receive information about the suggested optimal route hands-free.

[0317] Step 4:

[0318] The user gives voice commands to the device. This voice is converted into text data on the device using speech recognition technology (e.g., Google Speech-to-Text). Input in this step may be requests for additional information or instructions for route changes from the user.

[0319] Step 5:

[0320] The terminal sends the instructions received from the user to the server. Based on this input, the server retrieves and analyzes new information if necessary and generates optimized additional information. This result is then sent back to the terminal and provided to the driver.

[0321] Step 6:

[0322] The server uses the overall data and driver feedback to reinforce the system through learning. This will improve future analytical accuracy and enable the proposal of more effective sales strategies. The output of Step 6 is the system's improved knowledge base.

[0323] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0324] This invention provides drivers with the most optimal sales strategies in real time, and further includes a function to recognize the driver's emotional state and provide corresponding feedback. In this system, the information processing unit, emotion engine, and terminal components work together in coordination.

[0325] Server operation

[0326] The server first retrieves event information, weather information, and traffic information from an external database and analyzes it using generative artificial intelligence. This analysis predicts pedestrian flow and identifies the optimal sales area and route for drivers. Based on this information, the server formulates a sales strategy and transmits it to the terminal. The server also provides additional information in response to the driver's voice commands.

[0327] Terminal operation

[0328] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. Voice instructions are used to ensure the driver can safely obtain information even while driving. Furthermore, the terminal is equipped with an emotion engine that analyzes the driver's emotional state based on their voice tone, facial recognition, and other biosensor information. This analysis information is sent to the server, where the sales strategy is adjusted according to the driver's emotional state.

[0329] User (driver) usage examples

[0330] Users receive instructions on their service area and routes from the server via their terminal. During normal work, the terminal's emotion engine detects the user's stress level and fatigue, and can suggest breaks or prompt route changes as needed. For example, if a user's fatigue level increases during a series of busy tasks, the system will provide voice advice to the driver to take a break.

[0331] This system allows drivers to improve efficiency through optimal sales strategies, enabling safe and comfortable sales activities. The use of the emotion engine is expected to improve driver health and reduce stress, ultimately leading to improved overall work performance. In this way, the present invention provides comprehensive sales support to drivers.

[0332] The following describes the processing flow.

[0333] Step 1:

[0334] The server retrieves event information, weather information, and traffic information from an external database. This information serves as foundational data for providing drivers with appropriate business strategies.

[0335] Step 2:

[0336] The server uses generative artificial intelligence to analyze the acquired information. This analysis predicts pedestrian traffic and identifies areas with a high concentration of potential passengers.

[0337] Step 3:

[0338] Based on the analysis results, the server formulates the optimal sales area and route for the driver. This sales strategy aims to maximize the efficiency of operational tasks.

[0339] Step 4:

[0340] The server transmits the formulated sales strategy and route information to the terminal. The terminal receives this information and prepares to present it appropriately to the driver.

[0341] Step 5:

[0342] The terminal uses speech synthesis technology to notify the driver of sales strategy information. This allows the driver to check the information hands-free while driving.

[0343] Step 6:

[0344] The device's emotion engine analyzes the driver's emotional state from their voice tone and facial expressions, and evaluates their stress levels and fatigue while driving.

[0345] Step 7:

[0346] The terminal sends the results of the emotion engine's analysis to the server and requests adjustments to the sales strategy that reflect the emotional state. This process enables route suggestions that take the driver's health and safety into consideration.

[0347] Step 8:

[0348] The user (driver) conducts sales activities according to the latest sales strategy provided by the terminal. If new information is needed or if the user's emotional state changes, the terminal retrieves additional information from the server accordingly and provides it to the user.

[0349] Step 9:

[0350] The server collects driver sales and emotional data and uses this data for reinforcement learning. This allows the system's performance to continuously improve, and in the future, it will be able to respond more flexibly to driver requests.

[0351] (Example 2)

[0352] Next, we will describe Example 2. 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".

[0353] Modern drivers need to adapt to a wealth of real-time information during their sales activities, but effectively processing this information and formulating optimal sales strategies is not easy. Furthermore, the lack of consideration for the driver's own emotions and health conditions leads to decreased efficiency and difficulties in ensuring safety. Therefore, there is a need for a system that optimizes sales strategies without burdening the driver.

[0354] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0355] In this invention, the server includes means for acquiring various information from an external database, means for analyzing information about the driver using the acquired information, and means for presenting recommended areas and routes based on the analysis results. This enables the formulation of optimal sales strategies in real time according to the situation, and safe and efficient driving support that takes into account the driver's emotional state.

[0356] An "external database" refers to a collection of information accessible via the internet or cloud services, including various event information, weather information, and traffic information.

[0357] "Means of analyzing information" refers to methods of processing acquired data to make decisions that are advantageous to the driver's business activities.

[0358] "Means for suggesting areas and routes" refers to the process of suggesting the optimal area and route for the driver based on the analysis results.

[0359] A "voice output device" refers to a device that notifies the driver of the analyzed results and suggestions via voice so that they can safely check them while driving.

[0360] "Means for receiving voice instructions and searching for related information" refers to the process of receiving voice instructions from the driver and obtaining corresponding additional information from the internet or databases.

[0361] "Means of analyzing emotional state" refers to technology that determines the driver's psychological and emotional state at a given time based on their voice, facial expressions, and other biometric information.

[0362] "Methods for adjusting sales strategies" refers to the process of optimizing existing sales plans in real time, taking into account the emotional state of drivers and changes in the external environment.

[0363] This invention is a system that provides drivers with the optimal sales strategy in real time, and further recognizes the driver's emotional state and provides feedback accordingly. The system mainly consists of a server, terminals, and users who utilize them.

[0364] First, the server collects necessary information from external databases. Specifically, it obtains event information, weather information, and traffic information via the internet. The APIs used include, for example, geographic information APIs used to obtain map data and weather information APIs used to obtain weather data. The server analyzes this information using a generative AI model to predict pedestrian flow and traffic conditions. In this analysis, prompts are input to the generative AI model. For example, a prompt might say, "Please provide a forecast of pedestrian flow in the Tokyo area during the morning."

[0365] Based on this analysis, the server determines the optimal sales area and route for the driver and sends it to the terminal. The sales strategy is communicated using the terminal's speech synthesis technology so that the driver can access the information hands-free. Specifically, a speech synthesis API is used to issue instructions such as, "Your next destination is Shinjuku."

[0366] On the other hand, the device constantly monitors the driver's emotional state. Through built-in sensors and microphones, it acquires the driver's voice tone and facial expression data, which is then analyzed by an emotion analysis engine. This information is transmitted to a server, and sales strategies are adjusted as needed.

[0367] Through the above process, the user (driver) can follow the suggested optimal sales route. As a result, safe and efficient driving becomes possible, and health management and stress reduction through emotion analysis can also be expected. In this way, the present invention provides comprehensive sales support to drivers.

[0368] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0369] Step 1:

[0370] The server's role is to retrieve event information, weather information, and traffic information from an external database. This involves API calls via an internet connection. The retrieved data is returned to the server in JSON format, including metadata such as date, time, and location. This retrieved data serves as input for subsequent analysis.

[0371] Step 2:

[0372] The server's role is to input the acquired information into a generative AI model for analysis. Specifically, it inputs data as part of a prompt message, giving the command, "Output a traffic congestion forecast for the morning." Based on this command, the generative AI model quantifies pedestrian flow forecasts and congestion levels, generating the output necessary for optimizing sales areas and routes. This data forms the basis for developing optimized sales strategies.

[0373] Step 3:

[0374] The server determines the optimal sales area and route based on the analysis results and sends this information to the terminal. At this time, the generated data is constructed as a detailed plan that includes location information, recommended routes, and expected congestion times. Transmission to the terminal is done via a network protocol, and the server's output is used as input for the terminal's next processing.

[0375] Step 4:

[0376] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. Specifically, it uses a speech synthesis API to generate audio in the form of "The estimated time to your destination is 30 minutes." This audio output serves as a direct instruction to the driver. Through this entire process, the driver can obtain information without taking their hands off the wheel.

[0377] Step 5:

[0378] The device monitors the driver's condition in real time. This involves inputting voice tone and facial expressions into an emotion analysis engine for analysis. The acquired data is used to determine stress levels and fatigue levels, and the results are sent to the server. This provides detailed feedback on the driver's emotional state.

[0379] Step 6:

[0380] The server takes into account the driver's emotional state and fine-tunes the sales strategy as needed. For example, if a high stress level is detected, it may add rest stops or suggest a more comfortable route. The resulting strategic information is then sent back to the terminal for appropriate feedback.

[0381] Step 7:

[0382] The terminal then verbally re-notifies the driver of the adjusted sales strategy. This process is also carried out via a speech synthesis API. As a result, the driver receives optimal sales instructions based on the latest situation. Through the above series of steps, the driver can engage in sales activities with confidence and efficiency.

[0383] (Application Example 2)

[0384] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0385] Often, drivers or passengers are unable to obtain optimal business strategies or comfort during their ride, resulting in inefficient driving. Furthermore, the lack of consideration for the emotional state of drivers and passengers increases stress and discomfort, leading to a decline in the overall quality of the experience. These challenges need to be addressed.

[0386] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0387] In this invention, the server includes means for acquiring event information, weather information, and traffic information from an external database; means for analyzing the acquired information to determine the optimal sales strategy and propose a route; means for notifying the driver of the sales area and route by voice; and means for analyzing the emotional state of passengers and providing suggestions to improve their comfort. As a result, drivers can conduct sales efficiently while passengers can experience improved comfort.

[0388] An "information processing device" is a device that processes data obtained from an external source and provides appropriate information to the driver.

[0389] An "external database" is a data source used to collect information from external sources, including event information, weather information, and traffic information.

[0390] "Analysis" refers to the calculation process used to determine the optimal business strategy and route for drivers and passengers using the acquired data.

[0391] The "service area" is the region in which the driver is suggested to operate.

[0392] A "route" is the path chosen by the driver to travel.

[0393] A "voice output device" is a device used to convey analyzed information or suggestions in voice.

[0394] "Voice instructions" are instructions given by the driver to the system via voice.

[0395] "Emotional state" refers to the state in which passengers exhibit various emotional reactions.

[0396] "Comfort" refers to the level of comfort and satisfaction that passengers experience while riding.

[0397] To implement this invention, a system is constructed in which an information processing device, an emotion engine, a terminal equipped with a voice output device, and a server for analyzing various data work together.

[0398] The server retrieves event information, weather information, and traffic information from an external database and analyzes this information using generative artificial intelligence. Based on the analysis results, it identifies the optimal sales area and route for drivers and formulates a sales strategy. This information is then quickly transmitted to terminals.

[0399] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. A voice output device is installed within the vehicle, designed to allow for safe, real-time information acquisition even while driving. Furthermore, an emotion engine built into the terminal analyzes the emotional state of the driver and passengers from voice tone, facial expressions, and other biosensors. Based on the analyzed emotional state, the server adjusts the sales strategy and ride experience to improve comfort.

[0400] For example, if the emotional engine detects a stressed state while a passenger is in the vehicle, the server will suggest via the voice assistant, "Let's play some soothing music for a relaxing drive." Furthermore, it's possible to improve comfort by adjusting the interior temperature through the vehicle's environmental control system.

[0401] An example of a prompt message is, "Ride data suggests stress; suggest calming music and adjust climate." Based on this prompt, the server determines and implements specific actions to improve the rider's comfort during the ride.

[0402] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0403] Step 1:

[0404] The server retrieves event information, weather information, and traffic information from an external database. It then formats this data into the required format and prepares it for analysis. The input is raw data from the external database, and the output is formatted, analyzable data.

[0405] Step 2:

[0406] The server analyzes data acquired using generative artificial intelligence to identify the optimal sales area and route for drivers. Input data includes formatted event information, weather information, and traffic information, while output is the identified sales area and route. During the analysis process, the generative AI model predicts future pedestrian and traffic flow and creates an optimized sales strategy.

[0407] Step 3:

[0408] The server converts the identified service area and route into data for voice notification and sends it to the terminal. The input is the analyzed service area and route information, and the output is the data format for voice notification. After the information is sent, the terminal uses speech synthesis technology to notify the driver.

[0409] Step 4:

[0410] The terminal uses voice notification data received from the server to transmit information to the driver via a voice output device. The input is voice notification data, and the output is voice information conveyed to the driver. The driver then begins moving according to the proposed area and route.

[0411] Step 5:

[0412] The device's emotion engine analyzes voice tone and facial expressions to evaluate the emotional state of the driver and passengers. Input is voice and facial expression data acquired from the driver and passengers, and output is the analyzed emotional state information. Emotional changes are continuously monitored in real time.

[0413] Step 6:

[0414] The server adjusts sales strategies and ride experiences as needed based on emotional state information. In doing so, it generates prompts such as "Ride data suggests stress; suggest calming music and adjust climate," and sends them to the terminal. The input is the analyzed emotional state, and the output is the adjusted sales strategy and ride experience advice.

[0415] Step 7:

[0416] The terminal provides necessary voice assistance and environmental adjustments based on instructions from the server, and makes suggestions to the driver and passengers. The input is adjustment instructions from the server, and the output is specific suggestions and environmental settings for the driver and passengers. This allows drivers and passengers to have a more comfortable ride.

[0417] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0418] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0419] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0420] [Third Embodiment]

[0421] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0422] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0423] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0424] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0425] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0426] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0427] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0428] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0429] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0430] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0431] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0432] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0433] The system according to the present invention is an information processing device that supports drivers in efficiently carrying out their business activities. Its principle, configuration, and specific embodiments are described below.

[0434] Server operation

[0435] The server first retrieves real-time data such as event information, weather information, and traffic information from an external database. This data collection is performed regularly, and the retrieved data is analyzed within the server by generative artificial intelligence. In particular, it predicts pedestrian flow and determines which areas have a large number of potential passengers. Based on the results of this analysis, the server formulates the optimal service area and route.

[0436] Terminal operation

[0437] The terminal receives sales strategy information transmitted from the server. This information is then transmitted to the driver via speech synthesis technology, allowing the driver to obtain information hands-free. This enables the driver to acquire necessary information without distraction while driving, ensuring safe driving. Furthermore, the terminal accepts voice commands from the driver, supporting tasks such as obtaining new routes or confirming rest stops. Based on these requests, any additional information needed is retrieved from the server and provided to the driver.

[0438] User (driver) usage examples

[0439] Drivers can significantly improve their sales efficiency by using this system. For example, even in areas that would normally require experience and local knowledge, they can efficiently acquire passengers even in unfamiliar areas based on data provided by the server. If a user needs to change their sales area while driving due to local event information or sudden weather changes, they can instantly obtain the latest optimal strategy by entering voice instructions into the terminal.

[0440] This allows drivers to improve the accuracy and agility of their decision-making in business activities, contributing to efficient and safe driving. Therefore, the present invention provides drivers with an effective tool that dramatically improves their daily business activities.

[0441] The following describes the processing flow.

[0442] Step 1:

[0443] The server retrieves event information, weather information, and traffic information from an external database. The data is regularly updated to ensure it remains up-to-date in real time.

[0444] Step 2:

[0445] The server inputs the acquired data into a generative artificial intelligence model for analysis. This analysis predicts pedestrian flow trends and calculates the concentration of passengers in specific areas and time periods.

[0446] Step 3:

[0447] Based on the analysis results, the server creates a strategy for the driver that determines the optimal sales area and route. This strategy includes recommended sales areas and the most efficient routes to reach them.

[0448] Step 4:

[0449] The server transmits the formulated sales strategy to the terminal. The terminal receives this information and prepares to accurately transmit it to the driver.

[0450] Step 5:

[0451] The terminal uses speech synthesis technology to notify the driver of the information it receives. Voice notifications allow drivers to understand the sales strategy without relying on visual cues, thus enabling safer driving.

[0452] Step 6:

[0453] The user (driver) begins operations in the designated area and route based on instructions from the terminal. If necessary, they can request additional information from the terminal via voice commands.

[0454] Step 7:

[0455] The terminal requests additional data from the server in response to voice commands from the driver. This data may include information that the driver needs to update in real time, such as traffic conditions and facility information for a specific area.

[0456] Step 8:

[0457] The server receives requests from terminals, analyzes the latest information, and sends it back to the terminals. Drivers can use this information to adjust their sales strategies as needed and maintain optimal performance.

[0458] (Example 1)

[0459] Next, we will describe Example 1. 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."

[0460] When drivers utilize external information to conduct sales activities efficiently, it is difficult for them to find the appropriate sales area and route in real time. Conventional systems lacked the support to integrate diverse information and take quick action, resulting in a heavy burden on drivers' decision-making.

[0461] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0462] In this invention, the server includes means for acquiring event information, weather information, and traffic information from external information sources; means for performing analysis to optimize transportation efficiency based on the acquired information; and means for formulating sales areas and routes based on the analysis. This enables drivers to find the optimal sales area and route in real time and conduct sales activities quickly and efficiently.

[0463] An "information processing system" is a device that collects and analyzes data and provides useful information based on the results.

[0464] "External information sources" refer to means of obtaining information from data providers or APIs that exist outside the system.

[0465] "Event information" refers to data about specific activities or events held in a region, which may influence people's movement patterns.

[0466] "Weather information" refers to real-time data about the weather, which directly impacts the planning of business activities.

[0467] "Traffic information" refers to data on current road conditions and congestion levels, which is important for selecting a driving route.

[0468] "Transportation efficiency" is an indicator that enables drivers to conduct business activities efficiently, and it is achieved by selecting appropriate routes and service areas.

[0469] "Generative artificial intelligence" refers to AI technology that can perform predictions and analyses based on large amounts of data, and specifically includes deep learning models.

[0470] A "speech synthesis device" is a device that has the technology to convert digital text information into speech, enabling drivers to obtain information by voice.

[0471] "Voice instructions" refer to instructions or commands that the driver inputs to the system using their voice.

[0472] This invention relates to an information processing system that enables drivers to obtain optimal service area and route information in real time. The entire system consists of three main components: a server, a terminal, and a user.

[0473] The server acquires event information, weather information, and traffic information from external sources. Specifically, it periodically collects this information using APIs and stores it in a database. Based on this information, the server performs data analysis using a generative AI model. A deep learning algorithm is used as the generative AI model. As a result of the analysis, the optimal sales area and route for a given time and location are calculated. The server compiles these analysis results and formulates the next required sales strategy.

[0474] The terminal uses speech synthesis technology to provide voice-based information about the service area and routes, enabling drivers to safely obtain this information without requiring any driver intervention. Existing speech synthesis software is used for this purpose. The terminal can also receive voice commands from the driver. For example, if the driver voice-commands, "Tell me the best route next," the terminal sends a request to the server, instantly retrieving and providing the necessary information.

[0475] Drivers, as users of the system, can improve the efficiency and accuracy of their sales activities. Even in unfamiliar areas, they can efficiently acquire passengers by utilizing specific sales routes provided by the server. Furthermore, they can have the flexibility to change their sales area in response to sudden weather changes or new event information while driving.

[0476] A concrete example of a prompt message is, "Based on real-time event information, weather information, and traffic information, please suggest the optimal sales area and route." By inputting this prompt message into the generating AI model, the model performs analysis and executes a process to formulate a sales strategy.

[0477] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0478] Step 1:

[0479] The server retrieves event information, weather information, and traffic information from external sources. In doing so, the server accesses each data provider using APIs to retrieve the latest information. The input is API endpoint information, and the output is the retrieved real-time data. As a result, the server's internal database stores the fundamental data necessary for developing sales strategies.

[0480] Step 2:

[0481] The server analyzes the acquired data using a generating AI model. This analysis supplies the AI ​​model with event information, weather information, and traffic information collected in step 1 as input. Using a prompt message, the model is instructed to "suggest the optimal sales area and route based on real-time information," and the AI ​​performs pedestrian flow prediction and regional analysis to generate output. The output provides information on the optimal sales area and route. This allows the server to obtain analysis results that form the basis of sales strategies provided to drivers.

[0482] Step 3:

[0483] The terminal receives sales strategy information from the server. The terminal takes sales area and route information received from the server as input. Based on this information, it uses speech synthesis technology to notify the driver of the information verbally. The output is an audible voice message for the driver. This allows the driver to receive the latest sales information hands-free and make decisions while safely driving the vehicle.

[0484] Step 4:

[0485] The terminal accepts voice commands from the driver. When the driver gives a new voice command, such as "I want to check different route information," the terminal recognizes that command as input. The terminal interprets the command using voice recognition technology and sends a new data request to the server. As output, the latest information that meets the driver's request is provided again via the terminal. This allows the driver to respond flexibly to external information that changes in real time.

[0486] (Application Example 1)

[0487] Next, we will explain Application Example 1. In the following explanation, 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."

[0488] In recent years, the transportation and food delivery industries have been increasingly required to utilize real-time traffic conditions and forecasts to ensure efficient and safe deliveries. However, many current systems fail to provide delivery personnel with sufficient information to efficiently select the optimal route, resulting in delivery delays and inefficient route selection.

[0489] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0490] In this invention, the server includes means for acquiring environmental information, traffic information, and weather information from an external database; means for performing analysis to optimize the driver's operations using the acquired diverse information; and means for analyzing the data and predicting pedestrian flow using generative artificial intelligence. This makes it possible to propose appropriate sales areas and travel routes to drivers in real time. Furthermore, it becomes possible to support drivers in performing deliveries safely and efficiently through voice instructions.

[0491] A "driver" is a person who operates a vehicle and is responsible for safely and efficiently transporting goods or people to their destination.

[0492] An "information processing device" is a device that collects and analyzes a wide variety of data and provides useful information to users.

[0493] An "external database" is a large-scale information repository that can be accessed from enterprise systems or the internet, and it stores a variety of information.

[0494] "Environmental information" refers to information that shows the real-time state of the area in which the system is operating, and this includes information on pedestrian traffic and local events.

[0495] "Traffic information" refers to information that shows the flow of traffic and congestion within a designated area.

[0496] "Weather information" refers to information about the weather conditions in a specific area.

[0497] "Acquisition method" refers to the method of receiving necessary data from an external source and storing it within the system.

[0498] "Analysis methods" refer to methods of performing analysis using acquired data to derive useful results or suggestions.

[0499] "Sales area" refers to the area in which delivery personnel operate, and it is the region that should be optimized for efficient sales activities.

[0500] A "travel route" is the path a driver should take to reach their destination, optimized to support efficient and safe travel.

[0501] A "voice output device" is a device that converts electronic data into voice information and transmits it to the user.

[0502] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to learn from large datasets and generate new information and predictions.

[0503] "Data analysis" is the act of analyzing vast amounts of information and deriving insights and proposals that are suitable for a specific purpose.

[0504] The system implementing this invention provides an information processing device that supports drivers in efficiently performing delivery tasks. The server, terminal, and user elements work together to realize this system.

[0505] The server retrieves environmental, traffic, and weather information in real time from external databases. This data is collected using APIs (e.g., OpenWeatherMap and Google Maps API). The server analyzes this data using generative artificial intelligence models (e.g., GPT-3) to generate the optimal service area and travel routes to provide to drivers. It also predicts pedestrian flow and sets efficient delivery routes. To achieve this, the server integrates various data and provides the analysis results to drivers.

[0506] The driver's terminal receives instructions from the server and transmits the information to the driver via a voice output device. This voice output device can utilize technologies such as Google Cloud Text-to-Speech. This allows the driver to receive information hands-free, improving safety. Furthermore, the terminal recognizes voice instructions from the driver and analyzes them using Google Speech-to-Text. This voice recognition technology enables immediate responses to additional requests from the driver and allows for the retrieval of new data from the server.

[0507] As a concrete example, consider a scenario where many competitions are canceled due to rain. A server that obtains real-time weather information predicts changes in pedestrian traffic and suggests new routes to delivery personnel to avoid congestion. Thanks to this system, delivery personnel can avoid traffic jams and reach their destinations quickly.

[0508] A possible prompt for the generative AI model might be, "Analyze real-time traffic data and weather information to suggest the optimal route for delivery personnel to efficiently perform their delivery duties." This prompt provides crucial instructions for the generative AI model to derive the optimal sales strategy.

[0509] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0510] Step 1:

[0511] The server retrieves environmental information, traffic information, and weather information from an external database using an API. This input data includes real-time information about a specific region. The server integrates this data and stores it in a database for centralized management.

[0512] Step 2:

[0513] The server inputs the acquired data into a generating AI model (e.g., GPT-3). The server uses the model to analyze the data and identify the optimal service area and travel route for the driver. Here, efficient routes are generated by taking into account data correlations and time-series patterns.

[0514] Step 3:

[0515] The generated data is pushed from the server to the driver's terminal. The terminal then informs the driver of this information audibly via an audio output device. This allows the driver to receive information about the suggested optimal route hands-free.

[0516] Step 4:

[0517] The user gives voice commands to the device. This voice is converted into text data on the device using speech recognition technology (e.g., Google Speech-to-Text). Input in this step may be requests for additional information or instructions for route changes from the user.

[0518] Step 5:

[0519] The terminal sends the instructions received from the user to the server. Based on this input, the server retrieves and analyzes new information if necessary and generates optimized additional information. This result is then sent back to the terminal and provided to the driver.

[0520] Step 6:

[0521] The server uses the overall data and driver feedback to reinforce the system through learning. This will improve future analytical accuracy and enable the proposal of more effective sales strategies. The output of Step 6 is the system's improved knowledge base.

[0522] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0523] This invention provides drivers with the most optimal sales strategies in real time, and further includes a function to recognize the driver's emotional state and provide corresponding feedback. In this system, the information processing unit, emotion engine, and terminal components work together in coordination.

[0524] Server operation

[0525] The server first retrieves event information, weather information, and traffic information from an external database and analyzes it using generative artificial intelligence. This analysis predicts pedestrian flow and identifies the optimal sales area and route for drivers. Based on this information, the server formulates a sales strategy and transmits it to the terminal. The server also provides additional information in response to the driver's voice commands.

[0526] Terminal operation

[0527] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. Voice instructions are used to ensure the driver can safely obtain information even while driving. Furthermore, the terminal is equipped with an emotion engine that analyzes the driver's emotional state based on their voice tone, facial recognition, and other biosensor information. This analysis information is sent to the server, where the sales strategy is adjusted according to the driver's emotional state.

[0528] User (driver) usage examples

[0529] Users receive instructions on their service area and routes from the server via their terminal. During normal work, the terminal's emotion engine detects the user's stress level and fatigue, and can suggest breaks or prompt route changes as needed. For example, if a user's fatigue level increases during a series of busy tasks, the system will provide voice advice to the driver to take a break.

[0530] This system allows drivers to improve efficiency through optimal sales strategies, enabling safe and comfortable sales activities. The use of the emotion engine is expected to improve driver health and reduce stress, ultimately leading to improved overall work performance. In this way, the present invention provides comprehensive sales support to drivers.

[0531] The following describes the processing flow.

[0532] Step 1:

[0533] The server retrieves event information, weather information, and traffic information from an external database. This information serves as foundational data for providing drivers with appropriate business strategies.

[0534] Step 2:

[0535] The server uses generative artificial intelligence to analyze the acquired information. This analysis predicts pedestrian traffic and identifies areas with a high concentration of potential passengers.

[0536] Step 3:

[0537] Based on the analysis results, the server formulates the optimal sales area and route for the driver. This sales strategy aims to maximize the efficiency of operational tasks.

[0538] Step 4:

[0539] The server transmits the formulated sales strategy and route information to the terminal. The terminal receives this information and prepares to present it appropriately to the driver.

[0540] Step 5:

[0541] The terminal uses speech synthesis technology to notify the driver of sales strategy information. This allows the driver to check the information hands-free while driving.

[0542] Step 6:

[0543] The device's emotion engine analyzes the driver's emotional state from their voice tone and facial expressions, and evaluates their stress levels and fatigue while driving.

[0544] Step 7:

[0545] The terminal sends the results of the emotion engine's analysis to the server and requests adjustments to the sales strategy that reflect the emotional state. This process enables route suggestions that take the driver's health and safety into consideration.

[0546] Step 8:

[0547] The user (driver) conducts sales activities according to the latest sales strategy provided by the terminal. If new information is needed or if the user's emotional state changes, the terminal retrieves additional information from the server accordingly and provides it to the user.

[0548] Step 9:

[0549] The server collects driver sales and emotional data and uses this data for reinforcement learning. This allows the system's performance to continuously improve, and in the future, it will be able to respond more flexibly to driver requests.

[0550] (Example 2)

[0551] Next, we will describe Example 2. 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."

[0552] Modern drivers need to adapt to a wealth of real-time information during their sales activities, but effectively processing this information and formulating optimal sales strategies is not easy. Furthermore, the lack of consideration for the driver's own emotions and health conditions leads to decreased efficiency and difficulties in ensuring safety. Therefore, there is a need for a system that optimizes sales strategies without burdening the driver.

[0553] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0554] In this invention, the server includes means for acquiring various information from an external database, means for analyzing information about the driver using the acquired information, and means for presenting recommended areas and routes based on the analysis results. This enables the formulation of optimal sales strategies in real time according to the situation, and safe and efficient driving support that takes into account the driver's emotional state.

[0555] An "external database" refers to a collection of information accessible via the internet or cloud services, including various event information, weather information, and traffic information.

[0556] "Means of analyzing information" refers to methods of processing acquired data to make decisions that are advantageous to the driver's business activities.

[0557] "Means for suggesting areas and routes" refers to the process of suggesting the optimal area and route for the driver based on the analysis results.

[0558] A "voice output device" refers to a device that notifies the driver of the analyzed results and suggestions via voice so that they can safely check them while driving.

[0559] "Means for receiving voice instructions and searching for related information" refers to the process of receiving voice instructions from the driver and obtaining corresponding additional information from the internet or databases.

[0560] "Means of analyzing emotional state" refers to technology that determines the driver's psychological and emotional state at a given time based on their voice, facial expressions, and other biometric information.

[0561] "Methods for adjusting sales strategies" refers to the process of optimizing existing sales plans in real time, taking into account the emotional state of drivers and changes in the external environment.

[0562] This invention is a system that provides drivers with the optimal sales strategy in real time, and further recognizes the driver's emotional state and provides feedback accordingly. The system mainly consists of a server, terminals, and users who utilize them.

[0563] First, the server collects necessary information from external databases. Specifically, it obtains event information, weather information, and traffic information via the internet. The APIs used include, for example, geographic information APIs used to obtain map data and weather information APIs used to obtain weather data. The server analyzes this information using a generative AI model to predict pedestrian flow and traffic conditions. In this analysis, prompts are input to the generative AI model. For example, a prompt might say, "Please provide a forecast of pedestrian flow in the Tokyo area during the morning."

[0564] Based on this analysis, the server determines the optimal sales area and route for the driver and sends it to the terminal. The sales strategy is communicated using the terminal's speech synthesis technology so that the driver can access the information hands-free. Specifically, a speech synthesis API is used to issue instructions such as, "Your next destination is Shinjuku."

[0565] On the other hand, the device constantly monitors the driver's emotional state. Through built-in sensors and microphones, it acquires the driver's voice tone and facial expression data, which is then analyzed by an emotion analysis engine. This information is transmitted to a server, and sales strategies are adjusted as needed.

[0566] Through the above process, the user (driver) can follow the suggested optimal sales route. As a result, safe and efficient driving becomes possible, and health management and stress reduction through emotion analysis can also be expected. In this way, the present invention provides comprehensive sales support to drivers.

[0567] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0568] Step 1:

[0569] The server's role is to retrieve event information, weather information, and traffic information from an external database. This involves API calls via an internet connection. The retrieved data is returned to the server in JSON format, including metadata such as date, time, and location. This retrieved data serves as input for subsequent analysis.

[0570] Step 2:

[0571] The server's role is to input the acquired information into a generative AI model for analysis. Specifically, it inputs data as part of a prompt message, giving the command, "Output a traffic congestion forecast for the morning." Based on this command, the generative AI model quantifies pedestrian flow forecasts and congestion levels, generating the output necessary for optimizing sales areas and routes. This data forms the basis for developing optimized sales strategies.

[0572] Step 3:

[0573] The server determines the optimal sales area and route based on the analysis results and sends this information to the terminal. At this time, the generated data is constructed as a detailed plan that includes location information, recommended routes, and expected congestion times. Transmission to the terminal is done via a network protocol, and the server's output is used as input for the terminal's next processing.

[0574] Step 4:

[0575] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. Specifically, it uses a speech synthesis API to generate audio in the form of "The estimated time to your destination is 30 minutes." This audio output serves as a direct instruction to the driver. Through this entire process, the driver can obtain information without taking their hands off the wheel.

[0576] Step 5:

[0577] The device monitors the driver's condition in real time. This involves inputting voice tone and facial expressions into an emotion analysis engine for analysis. The acquired data is used to determine stress levels and fatigue levels, and the results are sent to the server. This provides detailed feedback on the driver's emotional state.

[0578] Step 6:

[0579] The server takes into account the driver's emotional state and fine-tunes the sales strategy as needed. For example, if a high stress level is detected, it may add rest stops or suggest a more comfortable route. The resulting strategic information is then sent back to the terminal for appropriate feedback.

[0580] Step 7:

[0581] The terminal then verbally re-notifies the driver of the adjusted sales strategy. This process is also carried out via a speech synthesis API. As a result, the driver receives optimal sales instructions based on the latest situation. Through the above series of steps, the driver can engage in sales activities with confidence and efficiency.

[0582] (Application Example 2)

[0583] Next, we will explain application example 2. In the following explanation, 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."

[0584] Often, drivers or passengers are unable to obtain optimal business strategies or comfort during their ride, resulting in inefficient driving. Furthermore, the lack of consideration for the emotional state of drivers and passengers increases stress and discomfort, leading to a decline in the overall quality of the experience. These challenges need to be addressed.

[0585] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0586] In this invention, the server includes means for acquiring event information, weather information, and traffic information from an external database; means for analyzing the acquired information to determine the optimal sales strategy and propose a route; means for notifying the driver of the sales area and route by voice; and means for analyzing the emotional state of passengers and providing suggestions to improve their comfort. As a result, drivers can conduct sales efficiently while passengers can experience improved comfort.

[0587] An "information processing device" is a device that processes data obtained from an external source and provides appropriate information to the driver.

[0588] An "external database" is a data source used to collect information from external sources, including event information, weather information, and traffic information.

[0589] "Analysis" refers to the calculation process used to determine the optimal business strategy and route for drivers and passengers using the acquired data.

[0590] The "service area" is the region in which the driver is suggested to operate.

[0591] A "route" is the path chosen by the driver to travel.

[0592] A "voice output device" is a device used to convey analyzed information or suggestions in voice.

[0593] "Voice instructions" are instructions given by the driver to the system via voice.

[0594] "Emotional state" refers to the state in which passengers exhibit various emotional reactions.

[0595] "Comfort" refers to the level of comfort and satisfaction that passengers experience while riding.

[0596] To implement this invention, a system is constructed in which an information processing device, an emotion engine, a terminal equipped with a voice output device, and a server for analyzing various data work together.

[0597] The server retrieves event information, weather information, and traffic information from an external database and analyzes this information using generative artificial intelligence. Based on the analysis results, it identifies the optimal sales area and route for drivers and formulates a sales strategy. This information is then quickly transmitted to terminals.

[0598] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. A voice output device is installed within the vehicle, designed to allow for safe, real-time information acquisition even while driving. Furthermore, an emotion engine built into the terminal analyzes the emotional state of the driver and passengers from voice tone, facial expressions, and other biosensors. Based on the analyzed emotional state, the server adjusts the sales strategy and ride experience to improve comfort.

[0599] For example, if the emotional engine detects a stressed state while a passenger is in the vehicle, the server will suggest via the voice assistant, "Let's play some soothing music for a relaxing drive." Furthermore, it's possible to improve comfort by adjusting the interior temperature through the vehicle's environmental control system.

[0600] An example of a prompt message is, "Ride data suggests stress; suggest calming music and adjust climate." Based on this prompt, the server determines and implements specific actions to improve the rider's comfort during the ride.

[0601] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0602] Step 1:

[0603] The server retrieves event information, weather information, and traffic information from an external database. It then formats this data into the required format and prepares it for analysis. The input is raw data from the external database, and the output is formatted, analyzable data.

[0604] Step 2:

[0605] The server analyzes data acquired using generative artificial intelligence to identify the optimal sales area and route for drivers. Input data includes formatted event information, weather information, and traffic information, while output is the identified sales area and route. During the analysis process, the generative AI model predicts future pedestrian and traffic flow and creates an optimized sales strategy.

[0606] Step 3:

[0607] The server converts the identified service area and route into data for voice notification and sends it to the terminal. The input is the analyzed service area and route information, and the output is the data format for voice notification. After the information is sent, the terminal uses speech synthesis technology to notify the driver.

[0608] Step 4:

[0609] The terminal uses voice notification data received from the server to transmit information to the driver via a voice output device. The input is voice notification data, and the output is voice information conveyed to the driver. The driver then begins moving according to the proposed area and route.

[0610] Step 5:

[0611] The device's emotion engine analyzes voice tone and facial expressions to evaluate the emotional state of the driver and passengers. Input is voice and facial expression data acquired from the driver and passengers, and output is the analyzed emotional state information. Emotional changes are continuously monitored in real time.

[0612] Step 6:

[0613] The server adjusts sales strategies and ride experiences as needed based on emotional state information. In doing so, it generates prompts such as "Ride data suggests stress; suggest calming music and adjust climate," and sends them to the terminal. The input is the analyzed emotional state, and the output is the adjusted sales strategy and ride experience advice.

[0614] Step 7:

[0615] The terminal provides necessary voice assistance and environmental adjustments based on instructions from the server, and makes suggestions to the driver and passengers. The input is adjustment instructions from the server, and the output is specific suggestions and environmental settings for the driver and passengers. This allows drivers and passengers to have a more comfortable ride.

[0616] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0617] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0618] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0619] [Fourth Embodiment]

[0620] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0621] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0622] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0623] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0624] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0625] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0626] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0627] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0628] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0629] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0630] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0631] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0632] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0633] The system according to the present invention is an information processing device that supports drivers in efficiently carrying out their business activities. Its principle, configuration, and specific embodiments are described below.

[0634] Server operation

[0635] The server first retrieves real-time data such as event information, weather information, and traffic information from an external database. This data collection is performed regularly, and the retrieved data is analyzed within the server by generative artificial intelligence. In particular, it predicts pedestrian flow and determines which areas have a large number of potential passengers. Based on the results of this analysis, the server formulates the optimal service area and route.

[0636] Terminal operation

[0637] The terminal receives sales strategy information transmitted from the server. This information is then transmitted to the driver via speech synthesis technology, allowing the driver to obtain information hands-free. This enables the driver to acquire necessary information without distraction while driving, ensuring safe driving. Furthermore, the terminal accepts voice commands from the driver, supporting tasks such as obtaining new routes or confirming rest stops. Based on these requests, any additional information needed is retrieved from the server and provided to the driver.

[0638] User (driver) usage examples

[0639] Drivers can significantly improve their sales efficiency by using this system. For example, even in areas that would normally require experience and local knowledge, they can efficiently acquire passengers even in unfamiliar areas based on data provided by the server. If a user needs to change their sales area while driving due to local event information or sudden weather changes, they can instantly obtain the latest optimal strategy by entering voice instructions into the terminal.

[0640] This allows drivers to improve the accuracy and agility of their decision-making in business activities, contributing to efficient and safe driving. Therefore, the present invention provides drivers with an effective tool that dramatically improves their daily business activities.

[0641] The following describes the processing flow.

[0642] Step 1:

[0643] The server retrieves event information, weather information, and traffic information from an external database. The data is regularly updated to ensure it remains up-to-date in real time.

[0644] Step 2:

[0645] The server inputs the acquired data into a generative artificial intelligence model for analysis. This analysis predicts pedestrian flow trends and calculates the concentration of passengers in specific areas and time periods.

[0646] Step 3:

[0647] Based on the analysis results, the server creates a strategy for the driver that determines the optimal sales area and route. This strategy includes recommended sales areas and the most efficient routes to reach them.

[0648] Step 4:

[0649] The server transmits the formulated sales strategy to the terminal. The terminal receives this information and prepares to accurately transmit it to the driver.

[0650] Step 5:

[0651] The terminal uses speech synthesis technology to notify the driver of the information it receives. Voice notifications allow drivers to understand the sales strategy without relying on visual cues, thus enabling safer driving.

[0652] Step 6:

[0653] The user (driver) begins operations in the designated area and route based on instructions from the terminal. If necessary, they can request additional information from the terminal via voice commands.

[0654] Step 7:

[0655] The terminal requests additional data from the server in response to voice commands from the driver. This data may include information that the driver needs to update in real time, such as traffic conditions and facility information for a specific area.

[0656] Step 8:

[0657] The server receives requests from terminals, analyzes the latest information, and sends it back to the terminals. Drivers can use this information to adjust their sales strategies as needed and maintain optimal performance.

[0658] (Example 1)

[0659] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0660] When drivers utilize external information to conduct sales activities efficiently, it is difficult for them to find the appropriate sales area and route in real time. Conventional systems lacked the support to integrate diverse information and take quick action, resulting in a heavy burden on drivers' decision-making.

[0661] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0662] In this invention, the server includes means for acquiring event information, weather information, and traffic information from external information sources; means for performing analysis to optimize transportation efficiency based on the acquired information; and means for formulating sales areas and routes based on the analysis. This enables drivers to find the optimal sales area and route in real time and conduct sales activities quickly and efficiently.

[0663] An "information processing system" is a device that collects and analyzes data and provides useful information based on the results.

[0664] "External information sources" refer to means of obtaining information from data providers or APIs that exist outside the system.

[0665] "Event information" refers to data about specific activities or events held in a region, which may influence people's movement patterns.

[0666] "Weather information" refers to real-time data about the weather, which directly impacts the planning of business activities.

[0667] "Traffic information" refers to data on current road conditions and congestion levels, which is important for selecting a driving route.

[0668] "Transportation efficiency" is an indicator that enables drivers to conduct business activities efficiently, and it is achieved by selecting appropriate routes and service areas.

[0669] "Generative artificial intelligence" refers to AI technology that can perform predictions and analyses based on large amounts of data, and specifically includes deep learning models.

[0670] A "speech synthesis device" is a device that has the technology to convert digital text information into speech, enabling drivers to obtain information by voice.

[0671] "Voice instructions" refer to instructions or commands that the driver inputs to the system using their voice.

[0672] This invention relates to an information processing system that enables drivers to obtain optimal service area and route information in real time. The entire system consists of three main components: a server, a terminal, and a user.

[0673] The server acquires event information, weather information, and traffic information from external sources. Specifically, it periodically collects this information using APIs and stores it in a database. Based on this information, the server performs data analysis using a generative AI model. A deep learning algorithm is used as the generative AI model. As a result of the analysis, the optimal sales area and route for a given time and location are calculated. The server compiles these analysis results and formulates the next required sales strategy.

[0674] The terminal uses speech synthesis technology to provide voice-based information about the service area and routes, enabling drivers to safely obtain this information without requiring any driver intervention. Existing speech synthesis software is used for this purpose. The terminal can also receive voice commands from the driver. For example, if the driver voice-commands, "Tell me the best route next," the terminal sends a request to the server, instantly retrieving and providing the necessary information.

[0675] Drivers, as users of the system, can improve the efficiency and accuracy of their sales activities. Even in unfamiliar areas, they can efficiently acquire passengers by utilizing specific sales routes provided by the server. Furthermore, they can have the flexibility to change their sales area in response to sudden weather changes or new event information while driving.

[0676] A concrete example of a prompt message is, "Based on real-time event information, weather information, and traffic information, please suggest the optimal sales area and route." By inputting this prompt message into the generating AI model, the model performs analysis and executes a process to formulate a sales strategy.

[0677] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0678] Step 1:

[0679] The server retrieves event information, weather information, and traffic information from external sources. In doing so, the server accesses each data provider using APIs to retrieve the latest information. The input is API endpoint information, and the output is the retrieved real-time data. As a result, the server's internal database stores the fundamental data necessary for developing sales strategies.

[0680] Step 2:

[0681] The server analyzes the acquired data using a generating AI model. This analysis supplies the AI ​​model with event information, weather information, and traffic information collected in step 1 as input. Using a prompt message, the model is instructed to "suggest the optimal sales area and route based on real-time information," and the AI ​​performs pedestrian flow prediction and regional analysis to generate output. The output provides information on the optimal sales area and route. This allows the server to obtain analysis results that form the basis of sales strategies provided to drivers.

[0682] Step 3:

[0683] The terminal receives sales strategy information from the server. The terminal takes sales area and route information received from the server as input. Based on this information, it uses speech synthesis technology to notify the driver of the information verbally. The output is an audible voice message for the driver. This allows the driver to receive the latest sales information hands-free and make decisions while safely driving the vehicle.

[0684] Step 4:

[0685] The terminal accepts voice commands from the driver. When the driver gives a new voice command, such as "I want to check different route information," the terminal recognizes that command as input. The terminal interprets the command using voice recognition technology and sends a new data request to the server. As output, the latest information that meets the driver's request is provided again via the terminal. This allows the driver to respond flexibly to external information that changes in real time.

[0686] (Application Example 1)

[0687] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0688] In recent years, the transportation and food delivery industries have been increasingly required to utilize real-time traffic conditions and forecasts to ensure efficient and safe deliveries. However, many current systems fail to provide delivery personnel with sufficient information to efficiently select the optimal route, resulting in delivery delays and inefficient route selection.

[0689] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0690] In this invention, the server includes means for acquiring environmental information, traffic information, and weather information from an external database; means for performing analysis to optimize the driver's operations using the acquired diverse information; and means for analyzing the data and predicting pedestrian flow using generative artificial intelligence. This makes it possible to propose appropriate sales areas and travel routes to drivers in real time. Furthermore, it becomes possible to support drivers in performing deliveries safely and efficiently through voice instructions.

[0691] A "driver" is a person who operates a vehicle and is responsible for safely and efficiently transporting goods or people to their destination.

[0692] An "information processing device" is a device that collects and analyzes a wide variety of data and provides useful information to users.

[0693] An "external database" is a large-scale information repository that can be accessed from enterprise systems or the internet, and it stores a variety of information.

[0694] "Environmental information" refers to information that shows the real-time state of the area in which the system is operating, and this includes information on pedestrian traffic and local events.

[0695] "Traffic information" refers to information that shows the flow of traffic and congestion within a designated area.

[0696] "Weather information" refers to information about the weather conditions in a specific area.

[0697] "Acquisition method" refers to the method of receiving necessary data from an external source and storing it within the system.

[0698] "Analysis methods" refer to methods of performing analysis using acquired data to derive useful results or suggestions.

[0699] "Sales area" refers to the area in which delivery personnel operate, and it is the region that should be optimized for efficient sales activities.

[0700] A "travel route" is the path a driver should take to reach their destination, optimized to support efficient and safe travel.

[0701] A "voice output device" is a device that converts electronic data into voice information and transmits it to the user.

[0702] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to learn from large datasets and generate new information and predictions.

[0703] "Data analysis" is the act of analyzing vast amounts of information and deriving insights and proposals that are suitable for a specific purpose.

[0704] The system implementing this invention provides an information processing device that supports drivers in efficiently performing delivery tasks. The server, terminal, and user elements work together to realize this system.

[0705] The server retrieves environmental, traffic, and weather information in real time from external databases. This data is collected using APIs (e.g., OpenWeatherMap and Google Maps API). The server analyzes this data using generative artificial intelligence models (e.g., GPT-3) to generate the optimal service area and travel routes to provide to drivers. It also predicts pedestrian flow and sets efficient delivery routes. To achieve this, the server integrates various data and provides the analysis results to drivers.

[0706] The driver's terminal receives instructions from the server and transmits the information to the driver via a voice output device. This voice output device can utilize technologies such as Google Cloud Text-to-Speech. This allows the driver to receive information hands-free, improving safety. Furthermore, the terminal recognizes voice instructions from the driver and analyzes them using Google Speech-to-Text. This voice recognition technology enables immediate responses to additional requests from the driver and allows for the retrieval of new data from the server.

[0707] As a concrete example, consider a scenario where many competitions are canceled due to rain. A server that obtains real-time weather information predicts changes in pedestrian traffic and suggests new routes to delivery personnel to avoid congestion. Thanks to this system, delivery personnel can avoid traffic jams and reach their destinations quickly.

[0708] A possible prompt for the generative AI model might be, "Analyze real-time traffic data and weather information to suggest the optimal route for delivery personnel to efficiently perform their delivery duties." This prompt provides crucial instructions for the generative AI model to derive the optimal sales strategy.

[0709] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0710] Step 1:

[0711] The server retrieves environmental information, traffic information, and weather information from an external database using an API. This input data includes real-time information about a specific region. The server integrates this data and stores it in a database for centralized management.

[0712] Step 2:

[0713] The server inputs the acquired data into a generating AI model (e.g., GPT-3). The server uses the model to analyze the data and identify the optimal service area and travel route for the driver. Here, efficient routes are generated by taking into account data correlations and time-series patterns.

[0714] Step 3:

[0715] The generated data is pushed from the server to the driver's terminal. The terminal then informs the driver of this information audibly via an audio output device. This allows the driver to receive information about the suggested optimal route hands-free.

[0716] Step 4:

[0717] The user gives voice commands to the device. This voice is converted into text data on the device using speech recognition technology (e.g., Google Speech-to-Text). Input in this step may be requests for additional information or instructions for route changes from the user.

[0718] Step 5:

[0719] The terminal sends the instructions received from the user to the server. Based on this input, the server retrieves and analyzes new information if necessary and generates optimized additional information. This result is then sent back to the terminal and provided to the driver.

[0720] Step 6:

[0721] The server uses the overall data and driver feedback to reinforce the system through learning. This will improve future analytical accuracy and enable the proposal of more effective sales strategies. The output of Step 6 is the system's improved knowledge base.

[0722] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0723] This invention provides drivers with the most optimal sales strategies in real time, and further includes a function to recognize the driver's emotional state and provide corresponding feedback. In this system, the information processing unit, emotion engine, and terminal components work together in coordination.

[0724] Server operation

[0725] The server first retrieves event information, weather information, and traffic information from an external database and analyzes it using generative artificial intelligence. This analysis predicts pedestrian flow and identifies the optimal sales area and route for drivers. Based on this information, the server formulates a sales strategy and transmits it to the terminal. The server also provides additional information in response to the driver's voice commands.

[0726] Terminal operation

[0727] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. Voice instructions are used to ensure the driver can safely obtain information even while driving. Furthermore, the terminal is equipped with an emotion engine that analyzes the driver's emotional state based on their voice tone, facial recognition, and other biosensor information. This analysis information is sent to the server, where the sales strategy is adjusted according to the driver's emotional state.

[0728] User (driver) usage examples

[0729] Users receive instructions on their service area and routes from the server via their terminal. During normal work, the terminal's emotion engine detects the user's stress level and fatigue, and can suggest breaks or prompt route changes as needed. For example, if a user's fatigue level increases during a series of busy tasks, the system will provide voice advice to the driver to take a break.

[0730] This system allows drivers to improve efficiency through optimal sales strategies, enabling safe and comfortable sales activities. The use of the emotion engine is expected to improve driver health and reduce stress, ultimately leading to improved overall work performance. In this way, the present invention provides comprehensive sales support to drivers.

[0731] The following describes the processing flow.

[0732] Step 1:

[0733] The server retrieves event information, weather information, and traffic information from an external database. This information serves as foundational data for providing drivers with appropriate business strategies.

[0734] Step 2:

[0735] The server uses generative artificial intelligence to analyze the acquired information. This analysis predicts pedestrian traffic and identifies areas with a high concentration of potential passengers.

[0736] Step 3:

[0737] Based on the analysis results, the server formulates the optimal sales area and route for the driver. This sales strategy aims to maximize the efficiency of operational tasks.

[0738] Step 4:

[0739] The server transmits the formulated sales strategy and route information to the terminal. The terminal receives this information and prepares to present it appropriately to the driver.

[0740] Step 5:

[0741] The terminal uses speech synthesis technology to notify the driver of sales strategy information. This allows the driver to check the information hands-free while driving.

[0742] Step 6:

[0743] The device's emotion engine analyzes the driver's emotional state from their voice tone and facial expressions, and evaluates their stress levels and fatigue while driving.

[0744] Step 7:

[0745] The terminal sends the results of the emotion engine's analysis to the server and requests adjustments to the sales strategy that reflect the emotional state. This process enables route suggestions that take the driver's health and safety into consideration.

[0746] Step 8:

[0747] The user (driver) conducts sales activities according to the latest sales strategy provided by the terminal. If new information is needed or if the user's emotional state changes, the terminal retrieves additional information from the server accordingly and provides it to the user.

[0748] Step 9:

[0749] The server collects driver sales and emotional data and uses this data for reinforcement learning. This allows the system's performance to continuously improve, and in the future, it will be able to respond more flexibly to driver requests.

[0750] (Example 2)

[0751] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0752] Modern drivers need to adapt to a wealth of real-time information during their sales activities, but effectively processing this information and formulating optimal sales strategies is not easy. Furthermore, the lack of consideration for the driver's own emotions and health conditions leads to decreased efficiency and difficulties in ensuring safety. Therefore, there is a need for a system that optimizes sales strategies without burdening the driver.

[0753] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0754] In this invention, the server includes means for acquiring various information from an external database, means for analyzing information about the driver using the acquired information, and means for presenting recommended areas and routes based on the analysis results. This enables the formulation of optimal sales strategies in real time according to the situation, and safe and efficient driving support that takes into account the driver's emotional state.

[0755] An "external database" refers to a collection of information accessible via the internet or cloud services, including various event information, weather information, and traffic information.

[0756] "Means of analyzing information" refers to methods of processing acquired data to make decisions that are advantageous to the driver's business activities.

[0757] "Means for suggesting areas and routes" refers to the process of suggesting the optimal area and route for the driver based on the analysis results.

[0758] A "voice output device" refers to a device that notifies the driver of the analyzed results and suggestions via voice so that they can safely check them while driving.

[0759] "Means for receiving voice instructions and searching for related information" refers to the process of receiving voice instructions from the driver and obtaining corresponding additional information from the internet or databases.

[0760] "Means of analyzing emotional state" refers to technology that determines the driver's psychological and emotional state at a given time based on their voice, facial expressions, and other biometric information.

[0761] "Methods for adjusting sales strategies" refers to the process of optimizing existing sales plans in real time, taking into account the emotional state of drivers and changes in the external environment.

[0762] This invention is a system that provides drivers with the optimal sales strategy in real time, and further recognizes the driver's emotional state and provides feedback accordingly. The system mainly consists of a server, terminals, and users who utilize them.

[0763] First, the server collects necessary information from external databases. Specifically, it obtains event information, weather information, and traffic information via the internet. The APIs used include, for example, geographic information APIs used to obtain map data and weather information APIs used to obtain weather data. The server analyzes this information using a generative AI model to predict pedestrian flow and traffic conditions. In this analysis, prompts are input to the generative AI model. For example, a prompt might say, "Please provide a forecast of pedestrian flow in the Tokyo area during the morning."

[0764] Based on this analysis, the server determines the optimal sales area and route for the driver and sends it to the terminal. The sales strategy is communicated using the terminal's speech synthesis technology so that the driver can access the information hands-free. Specifically, a speech synthesis API is used to issue instructions such as, "Your next destination is Shinjuku."

[0765] On the other hand, the device constantly monitors the driver's emotional state. Through built-in sensors and microphones, it acquires the driver's voice tone and facial expression data, which is then analyzed by an emotion analysis engine. This information is transmitted to a server, and sales strategies are adjusted as needed.

[0766] Through the above process, the user (driver) can follow the suggested optimal sales route. As a result, safe and efficient driving becomes possible, and health management and stress reduction through emotion analysis can also be expected. In this way, the present invention provides comprehensive sales support to drivers.

[0767] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0768] Step 1:

[0769] The server's role is to retrieve event information, weather information, and traffic information from an external database. This involves API calls via an internet connection. The retrieved data is returned to the server in JSON format, including metadata such as date, time, and location. This retrieved data serves as input for subsequent analysis.

[0770] Step 2:

[0771] The server's role is to input the acquired information into a generative AI model for analysis. Specifically, it inputs data as part of a prompt message, giving the command, "Output a traffic congestion forecast for the morning." Based on this command, the generative AI model quantifies pedestrian flow forecasts and congestion levels, generating the output necessary for optimizing sales areas and routes. This data forms the basis for developing optimized sales strategies.

[0772] Step 3:

[0773] The server determines the optimal sales area and route based on the analysis results and sends this information to the terminal. At this time, the generated data is constructed as a detailed plan that includes location information, recommended routes, and expected congestion times. Transmission to the terminal is done via a network protocol, and the server's output is used as input for the terminal's next processing.

[0774] Step 4:

[0775] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. Specifically, it uses a speech synthesis API to generate audio in the form of "The estimated time to your destination is 30 minutes." This audio output serves as a direct instruction to the driver. Through this entire process, the driver can obtain information without taking their hands off the wheel.

[0776] Step 5:

[0777] The device monitors the driver's condition in real time. This involves inputting voice tone and facial expressions into an emotion analysis engine for analysis. The acquired data is used to determine stress levels and fatigue levels, and the results are sent to the server. This provides detailed feedback on the driver's emotional state.

[0778] Step 6:

[0779] The server takes into account the driver's emotional state and fine-tunes the sales strategy as needed. For example, if a high stress level is detected, it may add rest stops or suggest a more comfortable route. The resulting strategic information is then sent back to the terminal for appropriate feedback.

[0780] Step 7:

[0781] The terminal then verbally re-notifies the driver of the adjusted sales strategy. This process is also carried out via a speech synthesis API. As a result, the driver receives optimal sales instructions based on the latest situation. Through the above series of steps, the driver can engage in sales activities with confidence and efficiency.

[0782] (Application Example 2)

[0783] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0784] Often, drivers or passengers are unable to obtain optimal business strategies or comfort during their ride, resulting in inefficient driving. Furthermore, the lack of consideration for the emotional state of drivers and passengers increases stress and discomfort, leading to a decline in the overall quality of the experience. These challenges need to be addressed.

[0785] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0786] In this invention, the server includes means for acquiring event information, weather information, and traffic information from an external database; means for analyzing the acquired information to determine the optimal sales strategy and propose a route; means for notifying the driver of the sales area and route by voice; and means for analyzing the emotional state of passengers and providing suggestions to improve their comfort. As a result, drivers can conduct sales efficiently while passengers can experience improved comfort.

[0787] An "information processing device" is a device that processes data obtained from an external source and provides appropriate information to the driver.

[0788] An "external database" is a data source used to collect information from external sources, including event information, weather information, and traffic information.

[0789] "Analysis" refers to the calculation process used to determine the optimal business strategy and route for drivers and passengers using the acquired data.

[0790] The "service area" is the region in which the driver is suggested to operate.

[0791] A "route" is the path chosen by the driver to travel.

[0792] A "voice output device" is a device used to convey analyzed information or suggestions in voice.

[0793] "Voice instructions" are instructions given by the driver to the system via voice.

[0794] "Emotional state" refers to the state in which passengers exhibit various emotional reactions.

[0795] "Comfort" refers to the level of comfort and satisfaction that passengers experience while riding.

[0796] To implement this invention, a system is constructed in which an information processing device, an emotion engine, a terminal equipped with a voice output device, and a server for analyzing various data work together.

[0797] The server retrieves event information, weather information, and traffic information from an external database and analyzes this information using generative artificial intelligence. Based on the analysis results, it identifies the optimal sales area and route for drivers and formulates a sales strategy. This information is then quickly transmitted to terminals.

[0798] The terminal uses speech synthesis technology to notify the driver of sales strategies received from the server. A voice output device is installed within the vehicle, designed to allow for safe, real-time information acquisition even while driving. Furthermore, an emotion engine built into the terminal analyzes the emotional state of the driver and passengers from voice tone, facial expressions, and other biosensors. Based on the analyzed emotional state, the server adjusts the sales strategy and ride experience to improve comfort.

[0799] For example, if the emotional engine detects a stressed state while a passenger is in the vehicle, the server will suggest via the voice assistant, "Let's play some soothing music for a relaxing drive." Furthermore, it's possible to improve comfort by adjusting the interior temperature through the vehicle's environmental control system.

[0800] An example of a prompt message is, "Ride data suggests stress; suggest calming music and adjust climate." Based on this prompt, the server determines and implements specific actions to improve the rider's comfort during the ride.

[0801] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0802] Step 1:

[0803] The server retrieves event information, weather information, and traffic information from an external database. It then formats this data into the required format and prepares it for analysis. The input is raw data from the external database, and the output is formatted, analyzable data.

[0804] Step 2:

[0805] The server analyzes data acquired using generative artificial intelligence to identify the optimal sales area and route for drivers. Input data includes formatted event information, weather information, and traffic information, while output is the identified sales area and route. During the analysis process, the generative AI model predicts future pedestrian and traffic flow and creates an optimized sales strategy.

[0806] Step 3:

[0807] The server converts the identified service area and route into data for voice notification and sends it to the terminal. The input is the analyzed service area and route information, and the output is the data format for voice notification. After the information is sent, the terminal uses speech synthesis technology to notify the driver.

[0808] Step 4:

[0809] The terminal uses voice notification data received from the server to transmit information to the driver via a voice output device. The input is voice notification data, and the output is voice information conveyed to the driver. The driver then begins moving according to the proposed area and route.

[0810] Step 5:

[0811] The device's emotion engine analyzes voice tone and facial expressions to evaluate the emotional state of the driver and passengers. Input is voice and facial expression data acquired from the driver and passengers, and output is the analyzed emotional state information. Emotional changes are continuously monitored in real time.

[0812] Step 6:

[0813] The server adjusts sales strategies and ride experiences as needed based on emotional state information. In doing so, it generates prompts such as "Ride data suggests stress; suggest calming music and adjust climate," and sends them to the terminal. The input is the analyzed emotional state, and the output is the adjusted sales strategy and ride experience advice.

[0814] Step 7:

[0815] The terminal provides necessary voice assistance and environmental adjustments based on instructions from the server, and makes suggestions to the driver and passengers. The input is adjustment instructions from the server, and the output is specific suggestions and environmental settings for the driver and passengers. This allows drivers and passengers to have a more comfortable ride.

[0816] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0817] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0818] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0819] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0820] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0821] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0822] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0823] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0824] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0825] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0826] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0827] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0828] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0829] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0830] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0831] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0832] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0833] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0834] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0835] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0836] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0837] The following is further disclosed regarding the embodiments described above.

[0838] (Claim 1)

[0839] An information processing device that provides drivers with real-time sales strategies,

[0840] A means of obtaining event information, weather information, and traffic information from an external database,

[0841] A means for performing analysis to optimize the driver's business using the acquired information,

[0842] A means for proposing a sales area and route based on the aforementioned analysis,

[0843] A means of notifying the driver of the proposed service area and route by voice using an audio output device,

[0844] A means of receiving voice instructions from the driver and searching for additional information based on those instructions,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, further comprising means for collecting sales data from drivers and using that data to reinforce the system.

[0848] (Claim 3)

[0849] The system according to claim 1, comprising means for analyzing acquired information using generative artificial intelligence and proposing sales areas and routes.

[0850] "Example 1"

[0851] (Claim 1)

[0852] An information processing system that provides drivers with real-time business plans,

[0853] Means for obtaining event information, weather information, and traffic information from external sources,

[0854] A means for performing analysis to optimize transportation efficiency based on the acquired information,

[0855] A means for formulating sales areas and routes based on the aforementioned analysis,

[0856] A means of communicating the designated service area and route to the driver by voice using a speech synthesis device,

[0857] A means for receiving voice instructions from the driver and obtaining supplementary information based on those instructions,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, further comprising means for collecting management data from drivers and using that data to reinforce the system.

[0861] (Claim 3)

[0862] The system according to claim 1, comprising means for analyzing acquired information using generative artificial intelligence and formulating sales areas and routes.

[0863] "Application Example 1"

[0864] (Claim 1)

[0865] An information processing device that provides drivers with real-time sales strategies,

[0866] A means of obtaining environmental information, traffic information, and weather information from an external database,

[0867] A means of performing analysis to optimize the driver's business using the diverse information acquired,

[0868] A means of proposing sales areas and travel routes based on analysis,

[0869] A means for notifying the driver of the proposed service area and travel route by voice using an audio output device,

[0870] A means for receiving voice instructions from the driver and retrieving and providing additional information based on those instructions,

[0871] A method for analyzing data and predicting pedestrian flow using generative artificial intelligence,

[0872] A means for calculating the optimal route for a delivery area and transmitting the information to the terminal of the person in charge of transportation,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, further comprising means for collecting sales data from drivers and using that data to reinforce the system.

[0876] (Claim 3)

[0877] The system according to claim 1, comprising means for analyzing acquired information using generative artificial intelligence and proposing business areas and travel routes.

[0878] "Example 2 of combining an emotion engine"

[0879] (Claim 1)

[0880] Means of obtaining various information from external databases,

[0881] A means of analyzing information about the driver using the acquired information,

[0882] A means for presenting recommended areas and routes based on the analysis results,

[0883] A means of informing the driver of the presented area and route by voice using an audio output device,

[0884] A means for receiving voice instructions from the driver and searching for relevant information based on those instructions,

[0885] A means of analyzing the driver's emotional state,

[0886] A means of adjusting sales strategies based on emotional states,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, further comprising means for suggesting a break or re-selecting a route based on the driver's emotional state.

[0890] (Claim 3)

[0891] The system according to claim 1, comprising means for analyzing acquired information using generative artificial intelligence and proposing areas and routes.

[0892] "Application example 2 when combining with an emotional engine"

[0893] (Claim 1)

[0894] An information processing device that provides drivers with real-time sales strategies,

[0895] A means of obtaining event information, weather information, and traffic information from an external database,

[0896] A means for performing analysis to optimize the driver's business using the acquired information,

[0897] A means for proposing a sales area and route based on the aforementioned analysis,

[0898] A means of notifying the driver of the proposed service area and route by voice using an audio output device,

[0899] A means of receiving voice instructions from the driver and searching for additional information based on those instructions,

[0900] A means of analyzing the emotional state of passengers and providing suggestions to improve their comfort,

[0901] A system that includes this.

[0902] (Claim 2)

[0903] The system according to claim 1, further comprising means for collecting sales data from drivers and using that data to reinforce the system.

[0904] (Claim 3)

[0905] The system according to claim 1, comprising means for analyzing acquired information using generative artificial intelligence and proposing sales areas and routes. [Explanation of symbols]

[0906] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An information processing device that provides drivers with real-time sales strategies, A means of obtaining event information, weather information, and traffic information from an external database, A means for performing analysis to optimize the driver's business using the acquired information, A means for proposing a sales area and route based on the aforementioned analysis, A means of notifying the driver of the proposed service area and route by voice using an audio output device, A means of receiving voice instructions from the driver and searching for additional information based on those instructions, A system that includes this.

2. The system according to claim 1, further comprising means for collecting sales data from drivers and using that data to reinforce the system.

3. The system according to claim 1, comprising means for analyzing acquired information using generative artificial intelligence and proposing sales areas and routes.

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