Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device that enables drivers to efficiently acquire passengers. [Solution] An information processing device is provided, comprising: an acquisition unit that acquires instructions from a driver transmitted from a terminal and acquires real-time information from an external database; a processing unit that performs specific processing to acquire analysis results from a data generation model for optimizing the driver's business based on the instructions and the real-time information acquired by the acquisition unit; and an output unit that outputs information regarding the driver's business to the terminal based on the analysis results.

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method 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 in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the taxi industry and the ride-sharing industry, whether a driver can efficiently acquire passengers affects the success or failure of the business. However, there are problems that novice drivers and drivers unfamiliar with the local geography have difficulty in efficient business operations due to lack of experience and local knowledge. In addition, with the relaxation of ride-sharing regulations 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.

[0005] The present disclosure has been made in view of the above points, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program that enable a driver to efficiently acquire passengers. [Means for solving the problem]

[0006] An information processing device according to a first aspect of this disclosure includes: an acquisition unit that acquires instructions from a driver transmitted from a terminal and acquires real-time information from an external database; a processing unit that performs specific processing to acquire analysis results from a data generation model for optimizing the driver's business based on the instructions and the real-time information acquired by the acquisition unit; and an output unit that outputs information regarding the driver's business to the terminal based on the analysis results.

[0007] An information processing device according to a second aspect of this disclosure is an information processing device according to a first aspect, wherein the acquisition unit acquires event information, weather information, and traffic information as real-time information.

[0008] An information processing device according to a third aspect of this disclosure is an information processing device according to a second aspect, wherein the acquisition unit further acquires payment information from a restaurant from the external database.

[0009] An information processing device according to a fourth aspect of this disclosure is an information processing device according to any of the first to third aspects, wherein the acquisition unit further acquires unstructured information from the external database.

[0010] An information processing device according to a fifth aspect of this disclosure is an information processing device according to a fourth aspect, wherein the acquisition unit further acquires information posted to a social networking service as unstructured information from the external database.

[0011] The information processing device according to the sixth aspect of this disclosure is an information processing device according to any of the first to fifth aspects, wherein the processing device analyzes the emotional state of the driver and optimizes the driver's business operations based on the emotional state of the driver.

[0012] An information processing device according to a seventh aspect of this disclosure is an information processing device according to a sixth aspect, wherein the processing unit optimizes the driver's business by adjusting the route based on the driver's emotional state.

[0013] An information processing method relating to the eighth aspect of this disclosure includes a processor that acquires instructions from a driver transmitted from a terminal and real-time information from an external database, performs specific processing to acquire analysis results from a data generation model for optimizing the driver's business based on the instructions and the real-time information, and performs processing to output information relating to the driver's business to the terminal based on the analysis results.

[0014] An information processing program according to the ninth aspect of this disclosure causes a computer to perform specific processing to acquire instructions from a driver transmitted from a terminal and real-time information from an external database, to acquire analysis results from a data generation model for optimizing the driver's business based on the instructions and the real-time information, and to output information regarding the driver's business to the terminal based on the analysis results. [Effects of the Invention]

[0015] This disclosure provides an information processing device, an information processing method, and an information processing program that enable drivers to efficiently acquire passengers. [Brief explanation of the drawing]

[0016] [Figure 1] This figure shows an example of the configuration of a data processing system 10 according to an embodiment of the disclosed technology. [Figure 2] This figure shows an example of the essential functions of a data processing device and a smart device. [Figure 3] This figure shows an example of the functional configuration of a specific processing unit. [Figure 4] This figure shows an example of a screen output by a smart device to a display. [Figure 5]This is a diagram showing an example of the flow of a specific process executed by a data processing device. [Figure 6] This is a diagram showing an emotion map to which a plurality of emotions are mapped. [Figure 7] This is a diagram showing an emotion map to which a plurality of emotions are mapped.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the present disclosure will be described with reference to the drawings. In each of the drawings, the same or equivalent components and parts are denoted by the same reference numerals. Also, the dimensional ratios in the drawings are exaggerated for convenience of explanation and may be different from the actual ratios.

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the language used in the following description will be explained.

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0021] 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.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] 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).

[0024] 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."

[0025] Figure 1 shows an example of the configuration of a data processing system 10 according to an embodiment of this disclosure.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. The storage 32 stores a specific processing program 56. The specific processing program 56 is an example of an "information processing 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.

[0034] 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.

[0035] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), 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.

[0036] 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.

[0037] In this embodiment, the smart device 14 is installed in a vehicle such as a taxi or ride-sharing vehicle that operates a service to transport passengers to their destination.

[0038] 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 also be referred to as a "server," and the smart device 14 will also be referred to as a "terminal."

[0039] In this embodiment, the specific processing unit 290 performs a specific processing step which involves determining the location to which the vehicle should head in order to pick up passengers, and then transmitting information about the determined location to the smart device 14.

[0040] First, the vehicle driver inputs instructions to the smart device 14 to inquire about the destination to pick up passengers. These instructions can be entered in text or by voice so that the driver can give instructions even while driving. The smart device 14 responds to the driver's inquiry and inquires with the data processing device 12 about the destination to pick up passengers. The data processing device 12 analyzes real-time information such as event information, weather information, traffic information, and payment information, and based on the analysis results, it formulates information related to the driver's business, such as the destination to pick up passengers. The data processing device 12 transmits the information regarding the destination to pick up passengers to the smart device 14.

[0041] The smart device 14 receives information transmitted from the data processing device 12 and presents the received information to the driver. In particular, in addition to textual information, the smart device 14 also transmits the received information to the driver by voice using speech synthesis technology. Because the information is transmitted by voice, the driver can obtain the information without using their hands. By obtaining information without using their hands, the driver can acquire the necessary information without being distracted while driving, and can continue driving safely. By using this system, the driver can significantly improve their sales efficiency. For example, even in areas where experience and local knowledge are usually required for sales, the driver can efficiently acquire passengers even in areas they are visiting for the first time, based on the data provided by the data processing device 12. Even if the driver needs to change their sales area while driving due to local event information or sudden changes in weather, they can input voice instructions into the smart device 14 and immediately obtain the latest and most optimal strategy from the data processing device 12.

[0042] A "driver" is a person who operates a vehicle and is responsible for safely and efficiently transporting goods or people to their destination.

[0043] An "external database" is a large-scale information repository accessible from enterprise systems or the internet, containing a variety of information. External databases include real-time information such as event information, weather information, traffic information, and payment information.

[0044] Figure 3 shows an example of the functional configuration of the specific processing unit 290. As shown in Figure 3, the specific processing unit 290 includes an input unit 292, a processing unit 294, and an output unit 296.

[0045] The acquisition unit 292 acquires user input received by the smart device 14. Specifically, it acquires at least one of the following data from the user received by the smart device 14: text, voice, and image. In this embodiment, the acquisition unit 292 acquires a user input received by the smart device 14 regarding the destination to which the driver should go to pick up passengers. Specifically, the acquisition unit 292 acquires user input from the driver such as "Please list some candidate areas to target next." The acquisition unit 292 also acquires real-time information such as event information, weather information, traffic information, and payment information from an external database. The data in the external database is updated periodically and is configured to always maintain the latest state in real time.

[0046] The processing unit 294 performs specific processing using the data generation model 58. Specifically, it inputs character, voice, and image data entered by the user into the data generation model 58 and obtains a generation result. In this embodiment, the processing unit 294 uses the data acquired by the acquisition unit 292 to obtain analysis results from the data generation model 58 for optimizing the driver's operations. Specifically, the processing unit 294 generates an instruction statement such as, "The vehicle's current location is near Hamamatsucho Station. Acquire information in real time from an external database, and based on the acquired information, list candidate areas for the driver to target next," and provides the generated instruction statement to the data generation model 58. The data generation model 58 outputs a response based on the instruction statement. For example, the data generation model 58 outputs responses such as, "The peak of customers leaving restaurants is occurring around Nishishinbashi 2-chome," or "The business show at Port City Takeshiba ends at 4 PM." Note that the vehicle's current location information may be obtained from a location information sensor such as a GPS (Global Positioning System) sensor installed in the vehicle.

[0047] The data generation model 58 may generate responses to instructions using unstructured information. Examples of unstructured information include posts on social networking services, weather information, and images of bus and taxi stands taken by network cameras. For example, if, at the time the instruction is received, there is an increase in posts on social networking services such as "There are no taxis at the taxi stand at Kokusai-Tenjijo Station," the data generation model 58 may output a response based on the instruction such as "It seems there are many people waiting for taxis at Kokusai-Tenjijo Station." Alternatively, if, at the time the instruction is received, there is an increase in posts such as "There has been a fatal accident on the Tokaido Line," the data generation model 58 may output a response based on the instruction such as "There has been a fatal accident on the Tokaido Line, so it seems that more people will be using taxis near Shinagawa Station."

[0048] For example, if, at the time the instruction is received, a network camera captures footage showing many people waiting for a bus at the bus stop in front of Toyosu Station, the data generation model 58 may output a response based on the instruction such as, "It appears there are many people waiting for a bus at the bus stop in front of Toyosu Station." For example, if, at the time the instruction is received, the weather radar indicates that it will start raining in central Tokyo in 15 minutes, the data generation model 58 may output a response based on the instruction such as, "It looks like it will start raining soon, so it seems like more people will be using taxis around Shimbashi Station."

[0049] It goes without saying that the data generation model 58 may output answers based on multiple sources of information, not just a single source.

[0050] The output unit 296 transmits the result of the specific processing to the smart device 14. In this embodiment, the output unit 296 transmits the response obtained by the processing unit 294 from the data generation model 58 to the smart device 14. On 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 then transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12.

[0051] Figure 4 shows an example of the screen output by the smart device 14 to the display 40A. When the driver asks the smart device 14 by voice, "Tell me the candidate areas to target next," the smart device 14 converts the content of the driver's voice inquiry into text and displays it on the display 40A. The smart device 14 then displays the information of candidate areas to target next, transmitted from the data processing device 12, on the display 40A. In the example in Figure 4, the area around Nishishinbashi 2-chome and Port City Takeshiba are displayed on the display 40A as candidate areas to target next.

[0052] After the data processing device 12 has suggested candidate areas to target and these are displayed on the display 40A, and before the data processing device 12 suggests candidate areas to target, the driver may want to confirm whether a particular area is appropriate as a candidate area to target. The data processing device 12 may respond to the driver's inquiry about whether a particular area is appropriate as a candidate area to target by indicating whether that area is appropriate as a candidate area to target.

[0053] For example, if a driver asks the smart device 14, "What about Yaesu Exit at Tokyo Station?", the smart device 14 sends the received user input to the data processing device 12. The data processing device 12 has a processing unit 294 that generates an instruction statement for the data generation model 58, for example, "The vehicle's current location is near Hamamatsucho Station. Obtain information in real time from an external database, and based on the obtained information, determine whether Yaesu Exit at Tokyo Station is a suitable area for the driver to target next," and provides the generated instruction statement to the data generation model 58. Here, if the information obtained from the external database indicates that there are already many taxis at Yaesu Exit at Tokyo Station or that there are not many customers at the taxi stand, the data generation model 58 may output an answer such as, "Yaesu Exit at Tokyo Station is currently oversupplied, so we do not recommend it."

[0054] Furthermore, suppose that the information obtainable from the external database includes the reservation status of Shinkansen reserved seats, and that reserved seats on Shinkansen arriving at Tokyo Station remain fully booked for a certain period of time. In such a case, the data generation model 58 may output a response such as, "Tokyo Station Yaesu Exit is currently oversaturated and not recommended. Reserved seats on Shinkansen arriving at Tokyo Station after 8 PM are almost fully booked, so we recommend reconsidering after 8 PM."

[0055] In the above description, the driver is a taxi or rideshare vehicle driver, and the data processing device 12 suggests information about the driver's business, specifically the destination to pick up passengers. However, this disclosure is not limited to such examples. The driver may also be a driver who collects or delivers packages. In this case, the data processing device 12 may suggest a route suitable for collection or delivery as information about the driver's business. For example, suppose the driver asks the smart device 14, "Tell me a route that will allow me to deliver the package effectively." The data processing device 12, through its processing unit 294, generates an instruction statement for the data generation model 58, for example, "The vehicle's current location is near Meguro Station. Obtain information from an external database in real time, and based on the obtained information, suggest a route that will allow the driver to deliver the package effectively," and provides the generated instruction statement to the data generation model 58. The data processing device 12 then transmits the response generated by the data generation model 58 to the smart device 14 as a route that will allow the package to be delivered effectively.

[0056] 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.

[0057] Next, the operation of the data processing system 10 will be explained.

[0058] An example of the flow of a specific process executed by the data processing device 12 will be explained with reference to Figure 5. Note that the flow of a specific process shown in Figure 5 is an example of an "information processing method" related to the technology of this disclosure.

[0059] In step S300, the processing unit 294 determines whether a predetermined trigger condition is met. The predetermined trigger condition is that user input received by the smart device 14 has been acquired.

[0060] If the trigger condition is met in step S300 (step S300; Yes), the data processing system 10 proceeds to step S301. On the other hand, if the trigger condition is not met in step S300 (step S300; No), the data processing system 10 terminates the specific processing.

[0061] In step S301, the processing unit 294 uses the user input entered on the smart device 14 to add instructions for obtaining the result of a specific process and generates a prompt. Specifically, the processing unit 294 generates a prompt that says, "The vehicle's current location is ○○. Obtain information in real time from the external database and, based on the obtained information, list the candidate areas the driver should target next."

[0062] In step S303, the processing unit 294 inputs the generated prompt to the data generation model 58 and obtains the result of a specific process based on the output of the data generation model 58. In this embodiment, the processing unit 294 performs a process to propose information about the next area the driver should target as the specific process.

[0063] In step S304, the output unit 296 outputs the result of the specific processing to the smart device 14 and terminates the specific processing. As a result of the specific processing, the output unit 296 outputs information about the next area the driver will target to the smart device 14.

[0064] The data processing device 12 may determine the driver's emotions and, based on the determined emotions, suggest information about the next area the driver should target.

[0065] 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 6).

[0066] Figure 6 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.

[0067] 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.

[0068] 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.

[0069] 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.

[0070] 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."

[0071] 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 placed close together have similar values, as shown in the emotion map 900 in Figure 7. Figure 7 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0072] 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.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] 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.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] The following is further disclosed regarding the embodiments described above. (Note 1) An acquisition unit that acquires instructions from the driver transmitted from the terminal and acquires real-time information from an external database, A processing unit that performs specific processing to obtain analysis results from a data generation model for optimizing the driver's business based on the voice instructions and the real-time information acquired by the acquisition unit, An output unit that outputs information regarding the driver's business operations to the terminal based on the analysis results, An information processing device equipped with the following features. (Note 2) The acquisition unit is an information processing device as described in Appendix 1, which acquires event information, weather information, and traffic information as real-time information. (Note 3) The acquisition unit further acquires payment information from restaurants from the external database, as described in Appendix 2. (Note 4) The acquisition unit further acquires unstructured information from the external database, as described in any of Appendix 1 to Appendix 3. (Note 5) The information processing device described in Appendix 4 further acquires information posted to a social networking service as unstructured information from the external database. (Note 6) The processing unit is an information processing device according to any one of the appendices 1 to 5, which analyzes the driver's emotional state and optimizes the driver's business operations based on the driver's emotional state. (Note 7) The processing unit is an information processing device as described in Appendix 6, which optimizes the driver's work by adjusting the route based on the driver's emotional state. (Note 8) The processor, The system acquires instructions from the driver transmitted from the terminal and also retrieves real-time information from an external database. A specific process is performed to obtain analysis results from a data generation model for optimizing the driver's work based on the aforementioned voice instructions and the aforementioned real-time information. Based on the analysis results, the terminal outputs information regarding the driver's business activities. An information processing method that executes a process. (Note 9) On the computer, The system acquires instructions from the driver transmitted from the terminal and also retrieves real-time information from an external database. A specific process is performed to obtain analysis results from a data generation model for optimizing the driver's work based on the aforementioned voice instructions and the aforementioned real-time information. Based on the analysis results, the terminal outputs information regarding the driver's business activities. An information processing program that executes a process. [Explanation of symbols]

[0084] 10 Data Processing Systems 12 Data Processing Devices 14 Smart Devices< / url:>

Claims

1. An acquisition unit that acquires instructions from the driver transmitted from the terminal and acquires real-time information from an external database, A processing unit that performs specific processing to obtain analysis results from a data generation model for optimizing the driver's business based on the instructions and the real-time information acquired by the acquisition unit, An output unit that outputs information regarding the driver's business operations to the terminal based on the analysis results, An information processing device equipped with the following features.

2. The information processing apparatus according to claim 1, wherein the acquisition unit acquires event information, weather information, and traffic information as real-time information.

3. The information processing apparatus according to claim 2, wherein the acquisition unit further acquires payment information for restaurants from the external database.

4. The information processing apparatus according to claim 1, wherein the acquisition unit further acquires unstructured information from the external database.

5. The information processing apparatus according to claim 4, wherein the acquisition unit further acquires information posted to a social networking service as unstructured information from the external database.

6. The information processing apparatus according to claim 1, wherein the processing unit analyzes the driver's emotional state and optimizes the driver's business operations based on the driver's emotional state.

7. The information processing apparatus according to claim 6, wherein the processing unit optimizes the driver's business by adjusting the route based on the driver's emotional state.

8. The processor, The system acquires instructions from the driver transmitted from the terminal and also retrieves real-time information from an external database. A specific process is performed to obtain analysis results from a data generation model to optimize the driver's business operations based on the aforementioned instructions and the real-time information. Based on the analysis results, the terminal outputs information regarding the driver's business activities. An information processing method that executes a process.

9. On the computer, The system acquires instructions from the driver transmitted from the terminal and also retrieves real-time information from an external database. A specific process is performed to obtain analysis results from a data generation model to optimize the driver's business operations based on the aforementioned instructions and the real-time information. Based on the analysis results, the terminal outputs information regarding the driver's business activities. An information processing program that executes a process.

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