System

Abstract

A system is provided.SOLUTION: A system comprising: means for managing a database; means for periodically registering transportation routes of vehicles that use expressways; means for allowing consignors to register cargoes; generation and AI means for analyzing optimal transportation routes and vehicles based on registered transportation routes and cargoes information; means for notifying transportation routes, unlock codes, and the like based on analysis results; means for managing deposit and receipt of cargoes during transportation and at destinations; and means for entrusting local taxi companies and ride-sharing companies with final delivery.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] The logistics industry is facing the 2024 problem, plagued by various issues such as labor shortages, an aging population, and restrictions on working hours. There is a particular need to secure efficient transportation methods, but expressways are not yet fully utilized compared to air routes and rail networks. Vehicles that regularly use expressways have a large amount of free space, but there is no way to utilize that space efficiently. The objective of this invention is to effectively utilize the free space of vehicles that regularly use expressways, thereby improving logistics efficiency and reducing transportation costs. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system that includes a database management means, a means for registering transport routes for vehicles that regularly use expressways, a means for shippers to register their cargo, a generation AI means for analyzing the optimal transport route and vehicle based on the registered transport route and cargo information, a means for notifying transport routes and unlock codes based on the analysis results, a means for managing the drop-off and pick-up of cargo en route and at the destination, and a means for entrusting final delivery to local taxi companies or ride-sharing companies. This system improves overall logistics efficiency by enabling quick and efficient drop-off and pick-up of cargo and promoting effective use of expressways.

[0006] A "database" is a system for systematically organizing and storing information and data, and for searching and manipulating them as needed.

[0007] A "vehicle that regularly uses an expressway" is a vehicle that travels a specific route via an expressway with a certain frequency.

[0008] The "transportation route" refers to route information such as the route from the departure point to the destination and rest stops along the way.

[0009] "Shipper" refers to an individual or corporation that wishes to send a package using logistics services.

[0010] "Cargo" means goods or merchandise transported from one place to another.

[0011] "Generative AI" is a technology that uses artificial intelligence to analyze data and make predictions, helping to select optimal transportation routes and vehicles.

[0012] "Notification" refers to the act or means of transmitting specific information to others in real time or at a specified timing.

[0013] An "unlock code" is a specific numeric or alphabetic code used to open or close a locked container.

[0014] "Local taxi and ride-sharing companies" refers to companies that provide passenger and cargo transportation services using vehicles in a specific area.

[0015] "Final delivery" refers to the final stage of transportation before a package reaches its destination.

[0016] A "system" is a broad concept that refers to multiple components that work together to provide specific functions or services. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

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

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

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

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention realizes efficient logistics through a system that combines a database, a transportation route registration means, a cargo registration means, a generation AI, a notification means, a management means, and a final delivery means. Specific embodiments for carrying out the present invention will be described below.

[0039] 1. The shipper registers the cargo information

[0040] User (shipper):

[0041] Shippers access the system using a dedicated device (such as a smartphone or tablet), enter information about the cargo they wish to leave (weight, dimensions, contents, etc.), and select service areas (SA) or parking areas (PA) at their departure and arrival points.

[0042] server:

[0043] The server provides a screen for accepting registration of cargo information and transportation routes. When the shipper completes the input and presses the send button, the server saves the data in a database.

[0044] 2. Registering transportation routes for regular users

[0045] User (regular user):

[0046] Drivers who regularly use expressways register information such as their route, departure and arrival times, and available spaces in the system.

[0047] server:

[0048] The server stores the information of regular users in a database so that it can be analyzed for use in the next package delivery.

[0049] 3. Generative AI selects optimal routes

[0050] server:

[0051] The generation AI installed on the server analyzes the optimal transport route and vehicle based on the departure and arrival points registered by the shipper and the route information of regular users. The analysis results are used to select the most efficient route and vehicle according to a pre-set algorithm.

[0052] 4. Notification of transportation route and unlock code

[0053] server:

[0054] Based on the analysis results, the server notifies the shipper of the location of the SA / PA where the package should be left and the unlock code. At the same time, it notifies the selected regular user of detailed package information and the designated SA / PA information.

[0055] 5. Baggage drop-off and collection management

[0056] User (shipper):

[0057] The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo.

[0058] server:

[0059] The server notifies the regular user in real time once the baggage has been checked in.

[0060] User (regular user):

[0061] Regular users will receive a notification and collect their luggage at the designated SA / PA, which will then be transported to the destination SA / PA along the route.

[0062] 6. Final Delivery Arrangements

[0063] User (regular user):

[0064] Regular passengers leave their luggage at the SA / PA at their destination and notify the server.

[0065] server:

[0066] The server notifies the local taxi company or ride-sharing company that the package has arrived at the destination service area or parking area. The final delivery person receives the notification and transports the package to its final destination.

[0067] Specific examples

[0068] As a specific example, suppose a shipper, "Mr. A," wants to deliver a product from Tokyo to Osaka. Mr. A enters product information on his terminal, selects an SA in Tokyo and an SA in Osaka, and sends the information to the server. Since information about regular user "Mr. B," who drives from Tokyo to Osaka every Monday, is already registered, the server uses generation AI to analyze Mr. B's route and notifies Mr. A based on the results. Mr. A leaves his luggage at the designated SA in Tokyo, and Mr. B picks it up and transports it to the SA in Osaka. Mr. B leaves his luggage at the SA in Osaka, and the server notifies the local taxi company, which then makes the final delivery. This series of steps results in efficient transportation and cost reductions.

[0069] The above is a specific embodiment for carrying out the present invention. Such a system will improve the efficiency of logistics and reduce costs, and will be an effective measure against the 2024 problem.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] The user (shipper) logs into the system using a dedicated terminal, enters the cargo information (weight, dimensions, contents, origin, destination) and clicks the send button.

[0073] Step 2:

[0074] The terminal transmits the input package information to the server.

[0075] Step 3:

[0076] The server receives the package information, stores it in the database, and returns a message to the user confirming that the information has been saved.

[0077] Step 4:

[0078] The user (regular user) inputs their route and available space information from a dedicated terminal and sends it.

[0079] Step 5:

[0080] The terminal transmits the regular user's route and available space information to the server.

[0081] Step 6:

[0082] The server receives the route information of regular users and stores it in a database.

[0083] Step 7:

[0084] The server begins analysis using generation AI based on cargo information from shippers and route information from regular users.

[0085] Step 8:

[0086] The generation AI selects the optimal transport route and corresponding vehicle.

[0087] Step 9:

[0088] Based on the analysis results, the server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code.

[0089] Step 10:

[0090] The server also notifies the selected regular users of the package information and the designated SA / PA information.

[0091] Step 11:

[0092] The user (shipper) brings the cargo to the designated SA / PA, unlocks the container using the unlock code provided by the server, and deposits the cargo.

[0093] Step 12:

[0094] The terminal reports the completion of baggage deposit to the server.

[0095] Step 13:

[0096] The server notifies the regular user in real time that the baggage has been confirmed.

[0097] Step 14:

[0098] The user (regular user) receives the notification and collects the package at the designated SA / PA.

[0099] Step 15:

[0100] The user (regular user) transports the luggage to the destination service area / parking area along the route.

[0101] Step 16:

[0102] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[0103] Step 17:

[0104] The server notifies local taxi companies and ride-sharing companies that the luggage has arrived at the arrival service area / parking area.

[0105] Step 18:

[0106] The user (a representative of a taxi company or ride-sharing company) receives a notification and goes to the SA / PA at the destination to pick up the luggage.

[0107] Step 19:

[0108] The user (a taxi company or ride-sharing company employee) transports the received package to its final destination and reports delivery completion to the server.

[0109] The above is the processing flow from depositing luggage to final delivery using the system of the present invention.

[0110] Example 1

[0111] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0112] In the logistics industry, selecting efficient transportation routes and ensuring smooth delivery of cargo both during transport and at the final destination are important issues. In particular, integrating information on multiple shippers and regular operators to select the optimal route is difficult, and arranging final delivery is also labor-intensive. Therefore, there is a need for a system that can efficiently manage the entire process, from cargo registration and transportation route selection to final delivery.

[0113] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0114] In this invention, the server includes a means for managing a database, a means for registering the routes of vehicles that operate regularly, a means for the shipper to register cargo, a generation AI means for analyzing the optimal transport route and vehicle based on the registered route and cargo information, a means for notifying the transport route and unlock code based on the analysis results, a means for managing the deposit and receipt of cargo at designated service areas or parking areas, and a means for coordinating with a local transportation service or shared driving service to entrust final delivery. This enables the selection of an efficient transport route, smooth delivery of cargo, and arrangement of final delivery.

[0115] The "means for managing the database" is a system for storing information on shippers and regular users, cargo information, and route information, and for retrieving and managing the information as needed.

[0116] "Means for registering the routes of vehicles that operate regularly" refers to methods or mechanisms for registering detailed information such as the routes, departure and arrival times, and available spaces of vehicles that operate regularly on expressways and public roads in the system.

[0117] "Means for a shipper to register a package" refers to a method or mechanism for a shipper to input and register information about the weight, dimensions, contents, origin, and destination of the package they wish to deposit into the system.

[0118] "Generative AI means" is an artificial intelligence technology that analyzes the optimal transport route and vehicle based on input cargo information and operation route information, and generates an efficient delivery plan.

[0119] "Means of notification" refers to a method or mechanism for providing information such as the transport route and unlock code to the shipper, and for notifying regular users of detailed information about their packages.

[0120] "Means for managing the deposit and receipt of packages at designated service or parking areas" means a system or method for managing and verifying the process by which shippers deposit packages and regular users collect packages at designated locations.

[0121] "Means of coordinating final delivery with a local transportation service or shared driving service" refers to a method or mechanism for coordinating with a local taxi company or ride-sharing company to arrange for the delivery of a package to its final destination.

[0122] The present invention is a logistics system that combines a database, a route registration means, a cargo registration means, a generation AI, a notification means, a management means, and a final delivery means. This enables efficient logistics. Specific embodiments for implementing the present invention will be described below.

[0123] 1. The shipper registers the cargo information

[0124] Users (shippers) access the system using a dedicated terminal (for example, a smartphone or tablet). The shipper enters information about the luggage they wish to store (weight, dimensions, contents, etc.) and selects the service area (SA) or parking area (PA) at their departure and arrival points. Specifically, the shipper operates their smartphone and enters their login ID and password to log into the system. They then enter detailed information about the luggage they wish to store and send it to the server.

[0125] The server provides a screen for accepting the registration of cargo information and operation routes, and stores the data sent from the shipper in a database. After the cargo information registration is complete, the server sends a confirmation email to the shipper to notify them that the cargo information has been successfully registered.

[0126] Example prompt:

[0127] "I would like to send a package from Tokyo to Osaka. The product information is as follows: weight 10kg, dimensions 50cm x 30cm x 20cm, contents: electronic product."

[0128] 2. Registering route information for regular users

[0129] Users (regular users) use dedicated terminals to register the route information of their vehicles that they operate regularly in the system. For example, a driver who regularly uses the expressway can enter detailed information such as their route, departure and arrival times, and available spaces.

[0130] The server stores the route information sent by the regular users in a database so that it can be used for the next package delivery. The server manages this information for use in analysis.

[0131] Example prompt:

[0132] "The bus runs from Tokyo to Osaka every Monday. It departs at 8:00 AM and arrives at 4:00 PM. There is space inside the bus for 50 kg of weight."

[0133] 3. Generative AI selects optimal routes

[0134] The server (generating AI) analyzes the optimal transport route and vehicle based on information registered by shippers and route information of regular users. The generating AI then selects the most efficient route based on an algorithm.

[0135] The server retrieves cargo information and route information from the database and analyzes it with the generation AI to create an optimal transportation plan. For example, the AI ​​analyzes how to optimally incorporate the shipper's cargo into the regular user's route.

[0136] Example prompt:

[0137] "Extract information about shippers and regular users from the database and use the AI ​​to select the optimal transport route and vehicle."

[0138] 4. Notification of transportation route and unlock code

[0139] Based on the analysis results, the server notifies the shipper of the location of the SA / PA where the package should be left and the unlock code. At the same time, it notifies the regular user of the package's detailed information and the designated SA / PA.

[0140] The server sends the shipper the location of the specified SA and the unlock code by email, and notifies the regular user of the package details and SA information.

[0141] Example prompt:

[0142] "Please inform the shipper of the SA to be deposited and the unlock code, and inform the regular user of the package details and SA information."

[0143] 5. Baggage drop-off and collection management

[0144] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code, and deposits the cargo.

[0145] The server confirms the baggage deposit and notifies the regular user of the information in real time.

[0146] The user (regular passenger) picks up the luggage at the designated SA / PA and transports it to the SA / PA at the destination along the route.

[0147] Example prompt:

[0148] "Instruct the shipper to use the unlock code to unlock the container and deposit the cargo. Notify the regular customer that the cargo will be deposited."

[0149] 6. Final Delivery Arrangements

[0150] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[0151] The server notifies the local transportation service or shared driving service that the package has arrived at the destination service area / parking area, and the final delivery person transports the package to the final destination.

[0152] Examples:

[0153] If Person A wants to send a product from Tokyo to Osaka, he or she uses a smartphone to enter the product information and send it to the server. Since the system is registered with information that Regular User B travels from Tokyo to Osaka every Monday, the server uses generation AI to analyze Person B's route and notifies Person A. Person A leaves the package at a designated service area in Tokyo, and Person B transports it to the service area in Osaka. The server then notifies the local transportation service, and the package is delivered to its final destination.

[0154] This series of steps and methods results in efficient transportation and cost reduction.

[0155] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0156] Step 1:

[0157] The user (shipper) registers the package information

[0158] Input: The shipper logs into the system using a terminal (smartphone or tablet) and enters the cargo information (weight, dimensions, contents, SA / PA of departure and arrival points).

[0159] The server stores the data

[0160] Output: The server receives the shipment information, stores it in a database, and sends a notification to the shipper confirming that the shipment information was successfully registered.

[0161] Specific operation: The shipper operates a smartphone, enters their login ID and password to log in to the system, then enters detailed information about the shipment and presses the send button. The server saves the data in a database and sends the shipper a confirmation email stating that the shipment information has been successfully registered.

[0162] Step 2:

[0163] The user (regular user) registers route information

[0164] Input: Regular passengers use the terminal to input details such as their route, departure and arrival times, and available spaces.

[0165] The server stores the data

[0166] Output: The server receives the route information and stores it in a database, ready for analysis so that it can be used for the next package delivery.

[0167] Specific operation: A regular user sets a route from Tokyo to Osaka every Monday, inputs the departure time as 8:00 AM, the arrival time as 4:00 PM, and the available space as 50 kg, and presses the send button. The server stores this information in the database.

[0168] Step 3:

[0169] Optimal route selection using generative AI

[0170] Input: The server retrieves package information and route information from the database.

[0171] The server (generative AI) analyzes the data

[0172] Output: The generation AI analyzes the optimal transport route and vehicle based on the input information and generates the results.

[0173] Specific operation: The server obtains the shipper's cargo information and the regular user's route information and passes it to the generation AI. The generation AI analyzes this information and selects the optimal transport route and vehicle based on an algorithm. As a result of the analysis, the most efficient route is generated.

[0174] Step 4:

[0175] Transport route and unlock code notification

[0176] Input: Analysis results of the generating AI

[0177] The server sends a notification

[0178] Output: The server notifies the shipper of the location and unlock code of the specified SA / PA, and notifies the subscriber of the package details.

[0179] Specific operation: Based on the analysis results of the generated AI, the server sends the shipper the location of a service area in Tokyo and the unlock code via email, and notifies regular user B of detailed information about the package and the information about the specified service area.

[0180] Step 5:

[0181] The shipper deposits the cargo at the designated SA / PA.

[0182] Input: Unlock code received by the shipper from the server

[0183] The server confirms the deposit

[0184] Output: The server confirms that the bag has been dropped off and notifies the subscriber in real time.

[0185] Specific operation: Shipper A arrives at the designated SA, enters the unlock code to unlock the container, and deposits his / her luggage. The server receives this information and sends a notification to regular user B that "the luggage has been deposited."

[0186] Step 6:

[0187] Regular passengers receive their packages

[0188] Input: Server notification

[0189] Regular users carry luggage

[0190] Output: Regular passengers collect their luggage at the designated service area and transport it to the destination service area / parking area along the route.

[0191] Specific operation: Regular user B picks up his luggage at a service area in Tokyo and transports it to a service area in Osaka Prefecture.

[0192] Step 7:

[0193] Final delivery arrangements

[0194] Input: Arrival notification from regular user

[0195] The server arranges final delivery

[0196] Output: The server notifies the local transportation service or shared driving service that the package has arrived at the destination SA and arranges for final delivery.

[0197] Specific operation: Regular user B arrives at a service area in Osaka Prefecture, deposits his / her luggage in the designated container, and notifies the server. The server then notifies the local transportation service of this information and arranges for delivery to the final destination.

[0198] The above is the specific flow of the system's program processing, which will enable efficient logistics.

[0199] (Application example 1)

[0200] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0201] Conventional logistics systems make it difficult to select efficient transportation routes and manage cargo, with a particular problem being the lack of coordination between shippers and transport personnel. Efficiency in final delivery of cargo and integrated management with local transportation service providers are also issues. For these reasons, a system that can improve the efficiency of the entire logistics system and deliver cargo quickly and reliably is needed.

[0202] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0203] In this invention, the server includes a database management unit, a unit for registering the transport routes of vehicles that regularly use expressways, and a unit for shippers to register their cargo. This allows the AI ​​to analyze the optimal transport route and vehicle based on cargo information from shippers and transport route information from regular users, and to provide appropriate notifications to shippers and transport personnel. Furthermore, notifications and cargo management can be achieved using smart devices, and final delivery arrangements with local transportation service providers can be smoothly made, thereby achieving overall logistics efficiency.

[0204] The "means of managing the database" is a system that centrally stores and manages information such as cargo information, transport route information, and user information.

[0205] "Means for registering transportation routes of vehicles that regularly use expressways" refers to an interface that allows drivers of vehicles that regularly travel the same route to input and save their own driving route information into the system.

[0206] "Means for shippers to register their cargo" refers to an interface that allows shippers to input cargo information (weight, dimensions, contents, departure point, arrival point, etc.) and send it to the system.

[0207] "Generative AI means" is an artificial intelligence technology that automatically analyzes and selects the optimal transport route and vehicle based on registered transport route and cargo information.

[0208] The "means of notification" is a system that notifies the shipper or transportation manager of information such as the transportation route and unlock code in a timely manner based on the analysis results.

[0209] "Means for managing the dropping off and picking up of luggage en route and at the destination" refers to a system that manages the procedures for dropping off and picking up luggage at designated service areas and parking areas.

[0210] "Means of entrusting final delivery to local mobility service providers" is a system that notifies and requests local taxi companies, ride-sharing companies, etc. to make final delivery at the destination.

[0211] "Means for registering luggage and displaying and notifying route analysis results using a smart device" refers to an application that provides functions such as luggage registration, displaying optimal routes, and notifying using a mobile device such as a smartphone or tablet.

[0212] The following describes the embodiments of the present invention. The system configuration described below is based on the technical elements described in the claims and includes specific implementation methods.

[0213] System Configuration

[0214] This system achieves efficient logistics by using a database, transportation route registration means, cargo registration means, generation AI, notification means, management means, final delivery means, and smart devices.

[0215] Databases and Servers

[0216] The database centrally manages information on cargo, transport routes, and regular users, and uses a relational database such as SQLite. The server is built using Flask (a Python web framework).

[0217] Shipper's registration of cargo information

[0218] Shippers use a smartphone or tablet to access a dedicated application and enter package information, including weight, dimensions, contents, origin, and destination, which is then sent to a server and stored in a database.

[0219] Registering transportation routes for regular users

[0220] Drivers who regularly use expressways input information such as their route, departure and arrival times, and available spaces into the application and send it to the server, where it is also stored in the database.

[0221] Optimal route selection using generative AI

[0222] The server uses the AI ​​to analyze the optimal transport route and vehicle based on the registered cargo information and route information of regular users. The AI ​​uses a pre-set algorithm to select the most efficient route and vehicle. The analysis results are stored on the server.

[0223] Notification of information by notification means

[0224] The server then notifies shippers and regular users of the necessary information based on the analysis results of the generative AI. The notification content includes the location of the designated service area (SA), parking area (PA), and unlock code. Notifications are sent in real time using a notification system such as Firebase Cloud Messaging (FCM).

[0225] Managing baggage drop-off and collection

[0226] The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo. Once the server confirms the deposit of the cargo, it notifies the regular user in real time. The regular user receives the notification and collects the cargo at the designated SA / PA. This information is recorded in the database.

[0227] Final delivery arrangements

[0228] A regular user leaves their luggage at the SA / PA at their destination and notifies the server. The server then notifies the local transportation service provider (e.g., a taxi company or ride-sharing company) that the luggage has arrived at the SA / PA. The final delivery person is notified and transports the luggage to its final destination. This information is also recorded in the database.

[0229] Specific examples

[0230] For example, if a shipper wants to deliver a product from Tokyo to Osaka, the shipper enters the product information on their terminal, selects a service area in Tokyo and another in Osaka, and sends it to the server. Since a regular user's driving information from Tokyo to Osaka every Monday is already registered, the server uses the generation AI to analyze the regular user's route and notifies the shipper based on the results. The shipper then leaves the package at the designated service area in Tokyo, where the regular user picks it up and transports it to the service area in Osaka. The server then notifies the local transportation service provider, and the final delivery is made.

[0231] Prompt Sentence Examples

[0232] Please register your luggage information. Enter the weight, dimensions, contents, departure and arrival points, and submit. We will then determine the best route for you and provide you with an unlock code. Follow the instructions to drop off or collect your luggage at the SA / PA.

[0233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0234] Step 1:

[0235] Registering luggage information

[0236] The user (shipper) accesses the application using a smartphone or tablet and enters cargo information such as weight, dimensions, contents, departure point, and arrival point. This input data is sent to the server and saved in a database. The server registers the cargo information in the database and verifies that the input information has been saved correctly.

[0237] Step 2:

[0238] Registering transport routes

[0239] Users (regular passengers) enter information such as their route, departure and arrival times, and available spaces into the application. This transport route information is sent to the server and stored in a database. The server then registers the regular passenger information in the database and analyzes it for use in the next package delivery.

[0240] Step 3:

[0241] Optimal route selection using generative AI

[0242] The server uses generative AI to analyze the optimal transport route and vehicle based on the cargo information and transport route information stored in the database. Here, the generative AI model inputs weight, dimensions, departure point, arrival point, and available vehicle route information, and outputs the most efficient route and vehicle. The server stores the generative AI's analysis results.

[0243] Step 4:

[0244] Notification Implementation

[0245] The server then sends information to shippers and regular users based on the analysis results of the AI. The notification includes the location of the specified SA / PA and the unlock code. The server sends the notification in real time using a notification system such as Firebase Cloud Messaging (FCM).

[0246] Step 5:

[0247] Checked baggage

[0248] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the luggage. The terminal inputs the unlock code to unlock the container and deposits the luggage. Once the server confirms the deposit of the luggage, it records it in the database and then notifies the regular user.

[0249] Step 6:

[0250] Picking up your luggage

[0251] The user (regular user) receives the notification and picks up the package at the designated SA / PA. After the server confirms that the regular user has picked up the package, it saves the data in the database. The regular user then transports the package to the destination SA / PA according to the route.

[0252] Step 7:

[0253] Final delivery arrangements

[0254] A regular user leaves their luggage at the SA / PA at their destination and notifies the server. The server records the arrival of the luggage at the SA / PA in the database and notifies the local mobility service provider. The final delivery person (mobility service provider) receives the notification and transports the luggage to its final destination.

[0255] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0256] The present invention realizes efficient logistics and an improved user experience through a system that combines a database, a transportation route registration means, a package registration means, a generation AI, a notification means, a management means, a final delivery means, and an emotion engine. Specific embodiments for carrying out the present invention will be described below.

[0257] 1. The shipper registers the cargo information

[0258] User (shipper):

[0259] Shippers access the system using a dedicated device (such as a smartphone or tablet), enter information about the cargo they wish to leave (weight, dimensions, contents, etc.), and select service areas (SA) or parking areas (PA) at their departure and arrival points.

[0260] server:

[0261] The server provides a screen for accepting registration of cargo information and transportation routes. When the shipper completes the input and presses the send button, the server saves the data in a database. In addition, the server sends video and audio data acquired from the terminal to the emotion engine to recognize the shipper's emotions.

[0262] 2. Registering transportation routes for regular users

[0263] User (regular user):

[0264] Drivers who regularly use expressways register information such as their route, departure and arrival times, and available spaces in the system.

[0265] server:

[0266] The server stores the information of regular users in a database, and at the same time, recognizes the emotions of regular users and records them in the database.

[0267] 3. Generative AI selects optimal routes

[0268] server:

[0269] The generation AI implemented on the server analyzes the optimal transport route and vehicle based on the departure and arrival points registered by the shipper and the route information of regular users.

[0270] Emotion Engine:

[0271] Based on the analysis results of the generation AI, the system also takes into account the emotional information of shippers and regular users to determine the optimal content and timing of notifications.

[0272] 4. Notification of transportation route and unlock code

[0273] server:

[0274] Based on the analysis results, the server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code. At this time, it uses an emotion engine to optimize the content of the notification and provides the information in a format that is easy for the shipper to understand. In addition, it notifies selected regular users of the cargo information and the designated SA / PA information.

[0275] 5. Baggage drop-off and collection management

[0276] User (shipper):

[0277] When the shipper arrives at the designated SA / PA, they unlock the container using the unlock code received from the server and deposit their cargo. At the same time, the emotion engine monitors the shipper's emotional state and provides support if there are any problems.

[0278] server:

[0279] Once the baggage has been checked in, the server notifies the regular user in real time, with the content of the notification also optimized by the emotion engine.

[0280] User (regular user):

[0281] Regular users will receive a notification and collect their luggage at the designated SA / PA, which will then be transported to the destination SA / PA along the route.

[0282] 6. Final Delivery Arrangements

[0283] User (regular user):

[0284] Regular passengers leave their luggage at the SA / PA at their destination and notify the server.

[0285] server:

[0286] The server notifies local taxi companies and ride-sharing companies that the package has arrived at the destination service area or parking area.The emotion engine also monitors the emotional state of the final delivery person, helping to ensure efficient delivery.

[0287] Specific examples

[0288] As a specific example, suppose shipper "Mr. A" wants to transport goods from Tokyo to Osaka. When Mr. A enters and sends the product information on his terminal, the emotion engine also analyzes Mr. A's situation. Based on the registration information of regular user "Mr. B," the generation AI analyzes the optimal route and notifies him. When Mr. A leaves the goods at the designated service area in Tokyo, the emotion engine also checks for any problems, and if it detects any signs of impatience or anxiety, it displays a support message. When regular user B delivers the goods to the service area in Osaka, the server notifies the local taxi company, and the taxi company, with the support of the emotion engine, delivers the goods to the final destination. In this way, by incorporating the emotion engine throughout the system, an improved user experience and efficient logistics are achieved.

[0289] The above is a detailed embodiment of the system of the present invention, from baggage deposit to final delivery. By combining it with an emotion engine, an even more user-friendly logistics system can be constructed.

[0290] The processing flow will be explained below.

[0291] Step 1:

[0292] The user (shipper) logs into the system using a dedicated terminal. They enter the cargo information (weight, dimensions, contents, departure point, arrival point) and click the send button. The terminal then sends the entered cargo information to the server.

[0293] Step 2:

[0294] The server receives the package information and stores it in a database. It also sends video and audio data acquired from the shipper's device to the emotion engine, which recognizes the shipper's emotions.

[0295] Step 3:

[0296] The emotion engine analyzes the shipper's emotional information and sends feedback to the server.

[0297] Step 4:

[0298] The user (regular user) inputs and transmits their own route and available space information from a dedicated terminal. The terminal then transmits the route and available space information of the regular user to the server.

[0299] Step 5:

[0300] The server receives the route information of regular users and stores it in a database. It also acquires the emotion information of regular users and sends it to the emotion engine.

[0301] Step 6:

[0302] The emotion engine analyzes the emotion information of regular users and sends feedback to the server.

[0303] Step 7:

[0304] The server uses the AI ​​to analyze the cargo information from the shipper and the route information from the regular users. The AI ​​then selects the optimal transport route and the corresponding vehicle.

[0305] Step 8:

[0306] The emotion engine determines the optimal notification content and timing based on the analysis results of the generation AI and emotional information.

[0307] Step 9:

[0308] The server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code. At this time, the notification content is optimized using an emotion engine. In addition, selected regular users are notified of the cargo information and the designated SA / PA information.

[0309] Step 10:

[0310] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code provided by the server, and deposits the cargo. At the same time, the emotion engine monitors the shipper's emotions, and displays a support message if there are any concerns or problems.

[0311] Step 11:

[0312] The terminal reports the completion of baggage deposit to the server.

[0313] Step 12:

[0314] The server notifies the regular user in real time that their luggage has been checked in. The content of the notification is also optimized by the emotion engine.

[0315] Step 13:

[0316] The user (regular user) receives the notification and picks up the luggage at the designated SA / PA. The luggage is then transported to the destination SA / PA along the route.

[0317] Step 14:

[0318] An emotion engine monitors the emotional state of subscribers and provides support when needed.

[0319] Step 15:

[0320] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[0321] Step 16:

[0322] The server notifies local taxi companies and ride-sharing companies that the package has arrived at the destination service area or parking area. The emotion engine also monitors the emotional state of the final delivery person and provides support to ensure efficient delivery.

[0323] Step 17:

[0324] The user (a representative of a taxi company or ride-sharing company) receives a notification and goes to the SA / PA at the destination to pick up the luggage.

[0325] Step 18:

[0326] The user (a taxi company or ride-sharing company employee) transports the received package to its final destination and reports delivery completion to the server.

[0327] Step 19:

[0328] The server notifies the sender that the package has been delivered and sends a thank-you message, which is also optimized by the emotion engine.

[0329] The above is a detailed processing flow from baggage deposit to final delivery using the system of the present invention. By incorporating an emotion engine, an improved user experience and efficient logistics can be achieved.

[0330] Example 2

[0331] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0332] In conventional logistics systems, selecting efficient transportation routes and arranging final deliveries takes a lot of time and effort. Furthermore, notification methods that do not take users' emotions into consideration can cause stress and reduce satisfaction. There is a need to solve these problems and achieve an improved user experience and efficient logistics.

[0333] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0334] In this invention, the server includes a database management unit, a registering unit for vehicle transport routes that regularly use expressways, a shipper's cargo registration unit, a generating AI unit that analyzes the optimal transport route and vehicle based on the registered transport route and cargo information, an emotion engine unit that analyzes emotion information and optimizes the content and timing of notifications, a unit that notifies the user of the transport route, unlock code, etc. based on the analysis results, a unit that monitors the user's emotional state and provides support messages as needed, a unit that manages the drop-off and receipt of cargo during transport and at the destination, and a unit that entrusts final delivery to a local transport service company. This enables efficient transport route selection and user-friendly notifications, improving the efficiency of the overall logistics process and user satisfaction.

[0335] "Means for managing a database" refers to software and hardware for efficiently storing, searching, and updating cargo information, transportation route information, etc.

[0336] "Means for registering transport routes of vehicles that regularly use expressways" refers to interfaces and tools for inputting and registering the operating routes and schedule information of vehicles that frequently use expressways into the system.

[0337] "Means for shippers to register their shipments" refers to the interfaces and tools that shippers use to enter detailed information about their shipments and register them in the system.

[0338] "Generative AI means" refers to artificial intelligence algorithms and systems that automatically analyze and select the optimal transport route and vehicle based on registered cargo information and transport route information.

[0339] "Emotion engine means" refers to software or hardware that analyzes the user's emotional state from facial expressions and voice data and optimizes the content and timing of notifications.

[0340] "Means for notifying transport routes, unlock codes, etc." refers to systems and services for notifying shippers and regular users of information on transport routes and unlock codes based on the analysis results.

[0341] "Means for monitoring the user's emotional state and providing a supportive message as needed" refers to the function of the system to monitor the user's emotional state in real time and display or send a supportive message when deemed necessary.

[0342] "Measures for managing the deposit and collection of baggage en route and at the destination" refers to the systems and protocols used to manage the smooth deposit and collection of baggage.

[0343] "Means of entrusting final delivery to a local transportation service company" refers to a system in which, in order to deliver cargo that has arrived at the destination, the company cooperates with a local transportation service company such as a taxi company or ride-sharing company and entrusts the work to that company.

[0344] The present invention is a system that realizes efficient logistics and an improved user experience by combining a database, a transportation route registration means, a parcel registration means, a generation AI, a notification means, a management means, a final delivery means, and an emotion engine. Specific embodiments for carrying out the present invention will be described below.

[0345] 1. The shipper registers the cargo information

[0346] User (shipper):

[0347] Shippers access the system by launching a dedicated app on their smartphones, tablets, or other devices. They then enter the weight, dimensions, and contents of the package into a form on the screen, as well as the service area (SA) or parking area (PA) of the departure and arrival points. For example, they might enter, "I want to deliver from a service area in Shibuya Ward, Tokyo to a parking area in Umeda, Osaka."

[0348] server:

[0349] The server receives the package information sent from the terminal and stores it in the corresponding database. At the same time, it sends the collected video and audio data to the emotion engine to analyze the sender's emotions. In this case, the specific hardware and software used are Amazon Web Services (AWS) and MySQL.

[0350] 2. Registering transportation routes for regular users

[0351] User (regular user):

[0352] Drivers who regularly use the expressway access the system using their smartphones or tablets. Drivers input information such as their route, departure and arrival times, and available space in the vehicle. They also input detailed schedules, such as "I'll drive from Tokyo to Osaka every Monday."

[0353] server:

[0354] The server receives route information sent from the terminal and stores it in a database. It also sends video and audio data to an emotion engine to analyze the emotions of regular passengers.

[0355] 3. Optimal route selection using generative AI

[0356] server:

[0357] The server retrieves information about shippers and regular users from the database and sends it to the generation AI. This generation AI analyzes the optimal transport route and vehicle based on the registered departure and arrival points and the regular user's route information. In this case, OpenAI's GPT-4 is used.

[0358] Emotion Engine:

[0359] The emotion engine analyzes the emotional information of shippers and regular users and integrates it with the analysis results of the generation AI. This determines the optimal notification timing and content, taking into account their emotional state. The emotion engine uses Affectiva Emotion AI and other technologies.

[0360] 4. Notification of transportation route and unlock code

[0361] server:

[0362] The server notifies shippers and regular users based on the analysis results of the generation AI and the emotion engine. Shippers are provided with the optimal transport route, the location of SA / PA, and the unlock code. Regular users are also notified of their cargo information and the designated SA / PA information.

[0363] 5. Baggage drop-off and collection management

[0364] User (shipper):

[0365] When the shipper arrives at the designated SA / PA, they unlock the container using the unlock code received from the server and deposit their cargo. At the same time, the emotion engine monitors the shipper's emotional state and displays a supportive message if it detects impatience or anxiety.

[0366] server:

[0367] Once the baggage has been checked in, the server notifies the regular user in real time, and the content of this notification is also optimized by the emotion engine.

[0368] User (regular user):

[0369] Regular users will receive a notification, collect their luggage at the designated SA / PA, and then follow the route to transport their luggage to the SA / PA at their destination.

[0370] 6. Final Delivery Arrangements

[0371] User (regular user):

[0372] The regular passenger arrives at the SA / PA at the destination and leaves his / her luggage. This information is notified to the server.

[0373] server:

[0374] The server confirms the arrival of the package and notifies the local taxi or ride-sharing company, which then picks up the package and delivers it to its final destination. During this process, the emotion engine monitors the emotional state of the final delivery person, helping to ensure efficient delivery.

[0375] Specific examples

[0376] A shipper, "Mr. A," uses a dedicated app to enter, "I want to transport goods from Tokyo to Osaka. I'm in a hurry, but I want it to be completed without any problems." The server receives and stores the package information and emotion data. A regular user, "Mr. B," registers a route from Tokyo to Osaka every Monday. The server stores this information in a database and analyzes the emotion data. The generative AI determines the optimal transport route and integrates it with the emotion engine. Mr. A is notified of the optimal transport route and unlock code, and Mr. B is also notified of information about picking up the package. Mr. A leaves his package at a designated service area in Tokyo, and if there are any problems, the emotion engine displays a support message. When Mr. B delivers his package to the service area in Osaka, the server notifies the taxi company, and with the support of the emotion engine, the package is delivered to its final destination.

[0377] This will enable efficient logistics and an improved user experience.

[0378] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0379] Step 1:

[0380] The shipper registers the cargo information

[0381] Input: The user (shipper) enters cargo information (weight, dimensions, contents, SA / PA at departure and arrival points) using a smartphone or tablet.

[0382] Specific operation: The sender launches the dedicated app and enters detailed information about the package into the form. For example, they might enter, "The product weighs 10 kg, its dimensions are 30 x 30 x 30 cm, its contents are electronic devices, its departure point is a service area in Shibuya Ward, Tokyo, and its arrival point is a parking area in Umeda, Osaka."

[0383] Output: The terminal sends the package information to the server and also prepares the video and audio data captured by the device's camera and microphone.

[0384] Data processing / calculation: The input data is first formatted in the terminal and then serialized for transmission to the server.

[0385] Step 2:

[0386] Receiving and storing information

[0387] Input: Parcel information and video / audio data sent from the terminal.

[0388] Specific operation: The server receives the package information sent from the terminal and stores it in the corresponding database. At the same time, it sends the video and audio data to the emotion engine to analyze the shipper's emotions.

[0389] Output: The package information is stored in the database, and the emotion analysis results are output to the emotion engine.

[0390] Data processing / calculation: Before being stored in the database, the data is checked for integrity, and the emotion engine performs sentiment analysis using machine learning models.

[0391] Step 3:

[0392] Registering transportation routes for regular users

[0393] Input: The user (regular user) inputs information about the route, departure time, arrival time, and available space on the terminal.

[0394] Specific operation: A regular user launches the dedicated app and enters route and schedule information into a form. For example, they enter information such as "Runs from Tokyo to Osaka every Monday, departing at 6:00 AM and arriving at 2:00 PM. Space availability is 50%."

[0395] Output: The device sends the registration information to the server, including face and voice data.

[0396] Data processing / computation: Information is formatted and serialized before being received by the server.

[0397] Step 4:

[0398] Receiving and storing information

[0399] Input: Route information and video / audio data of regular users.

[0400] Specific operation: The server receives route information sent from the terminal and stores it in a database. At the same time, it sends video and audio data to the emotion engine to analyze the emotions of regular passengers.

[0401] Output: The route information is stored in the database, and the emotion analysis results are output to the emotion engine.

[0402] Data processing / calculation: Data integrity checks are performed, and the emotion engine performs emotion analysis using machine learning models.

[0403] Step 5:

[0404] Optimal route selection using generative AI

[0405] Input: Package information and regular passenger information from the database.

[0406] Specific operation: The server retrieves information on shippers and regular users from the database and sends it to the generation AI. The generation AI analyzes the optimal transport route and vehicle based on the departure and arrival points and the regular user's route information.

[0407] Output: The analysis results of the optimal transport routes and vehicles are generated.

[0408] Data processing / calculation: Generative AI processes large amounts of data and algorithms calculate the optimal options.

[0409] Step 6:

[0410] Emotional information integration

[0411] Input: Analysis results of the emotion engine and the generative AI.

[0412] Specific operation: The emotion engine analyzes emotional information and integrates it with the analysis results of the generative AI, thereby optimizing the content and timing of notifications.

[0413] Output: Decision on optimal notification content and timing based on sentiment analysis.

[0414] Data processing / calculation: Complex data merging process is carried out to integrate emotional data and logistics data.

[0415] Step 7:

[0416] Transport route and unlock code notification

[0417] Input: Generated optimal transport route and unlock code.

[0418] Specific operation: Based on the analysis results, the server notifies the shipper and regular user. The shipper is provided with the optimal transport route, the location of the SA / PA, and the unlock code, while the regular user is notified of the cargo information and the specified SA / PA information.

[0419] Output: Shipper and subscriber are provided with delivery information and unlock codes.

[0420] Data processing / calculation: Notification content is optimized based on emotion data and formatted in a user-friendly format.

[0421] Step 8:

[0422] Checked baggage

[0423] Input: The unlock code received from the server when the shipper arrives at the specified SA / PA.

[0424] Specific operation: The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo. At the same time, the emotion engine monitors the shipper's emotional state and displays support messages as necessary.

[0425] Output: Notification from the shipper that the luggage has been deposited.

[0426] Data processing / calculation: Baggage deposit confirmation data is sent to the server in real time.

[0427] Step 9:

[0428] Real-time notifications

[0429] Input: Baggage drop-off information.

[0430] Specific operation: Once the baggage deposit is confirmed, the server notifies the regular user in real time. The content of this notification is also optimized by the emotion engine.

[0431] Output: Notify the regular user that they have received their package.

[0432] Data processing / calculation: Real-time data processing enables immediate notification.

[0433] Step 10:

[0434] Receiving and transporting luggage

[0435] Input: Regular passenger arrival and baggage claim information.

[0436] Specific operation: Regular passengers collect their luggage at the designated SA / PA and then transport it to the SA / PA at their destination along the route.

[0437] Output: Notification that regular user has received their luggage.

[0438] Data processing / calculation: The receipt confirmation data is sent to the server, and the next notification process is carried out.

[0439] Step 11:

[0440] Final delivery arrangements

[0441] Input: Regular passenger arrival and baggage drop-off information.

[0442] Specific operation: The regular passenger arrives at the SA / PA at the destination and leaves his / her luggage. This information is notified to the server.

[0443] Output: Final delivery notification to the taxi or ride-sharing company at the destination.

[0444] Data processing / calculation: Based on the arrival information and deposit information, contact processing for final delivery is carried out.

[0445] Step 12:

[0446] Executing the final delivery

[0447] Input: Final delivery person's receiving information.

[0448] How it works: The server confirms the arrival of the package and notifies local taxi or ride-sharing companies. These companies then pick up the package and deliver it to its final destination. The emotion engine also monitors the emotional state of the final delivery person to help ensure efficient delivery.

[0449] Output: Final delivery completion notification.

[0450] Data processing / calculation: Receipt confirmation data is sent to the server, and the entire system log is updated when delivery is complete.

[0451] (Application example 2)

[0452] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0453] Modern logistics and food delivery systems require efficient route selection and reliable package delivery, but at the same time, improving the user experience is also important. In particular, if delivery timing and notification methods do not meet user expectations, customer satisfaction may decline. Furthermore, there is a lack of mechanisms to improve overall system efficiency and user peace of mind, such as optimizing delivery personnel's routes and analyzing their emotional state. Therefore, providing efficient and user-friendly logistics and food delivery systems is a key challenge.

[0454] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0455] In this invention, the server includes means for managing a database, means for registering transportation routes for vehicles that regularly use expressways, means for shippers to register their cargo, generation AI means for analyzing optimal transportation routes and vehicles based on the registered transportation routes and cargo information, means for notifying the transport route, unlock code, etc. based on the analysis results, means for managing the drop-off and receipt of cargo during transportation and at the destination, means for entrusting final delivery to a local taxi company or ride-sharing company, means for analyzing user emotions using an emotion engine and optimizing the content and timing of notifications, and means for managing food delivery orders, food preparation, and delivery personnel routes. This makes it possible to provide an efficient logistics and food delivery system that improves the user experience.

[0456] 1. "Means for managing the database" refers to a system that centrally stores data such as transportation routes, cargo information, and user information, and adds, updates, and deletes data as needed.

[0457] 2. "Means for registering transport routes for vehicles that regularly use expressways" refers to a system that has the function of inputting and saving transport routes and operation schedule information used daily by vehicles that regularly use expressways.

[0458] 3. "Means for shippers to register their cargo" refers to a system that allows shippers to input and save information about the cargo they wish to transport (weight, dimensions, contents, origin, destination, etc.).

[0459] 4. "Generative AI means" is an artificial intelligence that automatically analyzes the optimal transport route and vehicle based on registered transport route and cargo information.

[0460] 5. "Means of notification" refers to a system that communicates important information to users, such as the optimal transportation route analyzed by the generating AI and the unlock code.

[0461] 6. "Means for managing the deposit and receipt of luggage" means a system that properly manages the deposit and receipt of luggage by shippers and regular users during transportation and at the destination.

[0462] 7. "Means of entrusting final delivery to a local taxi company or ride-sharing company" refers to a system in which a local taxi company or ride-sharing company is requested to make the final delivery at the destination of the package.

[0463] 8. The "Emotion Engine" is an artificial intelligence that analyzes the emotional state of users and delivery personnel and optimizes the content and timing of notifications based on the results.

[0464] 9. "Food delivery order management means" refers to a system that inputs and saves meal order information from users and manages the progress of orders from cooking to delivery.

[0465] 10. "Means for preparing food for food delivery" refers to a system in which restaurants input and save the food preparation status and completion time.

[0466] 11. "Means for managing delivery personnel's driving routes in food delivery" refers to a system that manages delivery personnel's driving routes, available time, and working conditions, and provides optimal delivery routes.

[0467] The food delivery system for realizing the invention consists of the following components: Each component plays a specific role and works together to ensure the smooth functioning of the entire system.

[0468] 1. Database Management Methods

[0469] A database is installed on the server, where transport route information, package information, user information, delivery person information, etc. are stored in a unified manner. A relational database management system (RDBMS) such as MySQL can be used as database management software. Data can be added, updated, and deleted efficiently through this database.

[0470] 2. Transportation route registration method

[0471] The terminal provides an interface for registering transportation routes for vehicles that regularly use the expressway. Users (drivers) input their own driving schedules and routes into the terminal, and the information is sent to the server and stored in a database.

[0472] 3. Baggage registration method

[0473] Using the terminal, the shipper inputs information about the cargo they wish to transport (weight, dimensions, contents, origin, destination, etc.), which is then stored in a database via the server.

[0474] 4. Generation AI means

[0475] The server is equipped with a generative AI that analyzes the optimal transport route and vehicle based on registered transport route and cargo information. TensorFlow and PyTorch can be used for the generative AI model. The AI ​​model analyzes large amounts of data and proposes efficient routes and vehicles.

[0476] 5. Means of notification

[0477] Based on the analysis results of the generating AI, the server notifies the user of important information such as transportation routes and unlock codes. Notification methods include push notifications, SMS, and email. In addition, an emotion engine analyzes the user's emotional state and optimizes the content and timing of notifications.

[0478] 6. Baggage drop-off and collection management methods

[0479] The server manages the drop-off and pick-up of luggage during transport and at destinations. Shippers and regular users drop off or pick up luggage at designated locations, allowing for real-time processing.

[0480] 7. Final delivery consignment method

[0481] At the destination, the server requests a local taxi company or ride-sharing company to make the final delivery, ensuring that the package reaches its final destination efficiently.

[0482] 8. Emotional Engine Means

[0483] The server is equipped with an emotion engine that analyzes the emotional state of the user and delivery person and optimizes the content and timing of notifications based on the results. This emotion engine can utilize emotion analysis services such as IBM Watson.

[0484] 9. Food delivery management measures

[0485] The terminal and server manage food delivery orders, food preparation, and delivery driver routes. Users input orders through the application, and restaurants input the food preparation status. Delivery driver routes are optimized using generative AI.

[0486] By integrating these methods, an efficient and user-friendly logistics and food delivery system can be realized. For example, when a user orders a pizza, the order information is stored in a database, and the optimal route from the restaurant to the delivery person is analyzed by a generative AI. The emotional state of the delivery person is analyzed by an emotion engine, and a notification is sent to the user.

[0487] An example of a prompt sentence is "Order ID: 1, Food: Pizza, Location: A, Status: Cooking, Delivery Person: ID2, Route: A to B, Emotion: Good."

[0488] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0489] Step 1:

[0490] The user registers package information on the terminal. At this time, the user inputs information such as the package's weight, dimensions, contents, departure point, and arrival point, and sends it from the terminal to the server. The server stores this information in a database. The specific input is package information, and the output is storage in the database.

[0491] Step 2:

[0492] Regular users register their own routes and schedules on their terminals. The driver inputs information such as route, departure and arrival times, and available spaces, and sends it from the terminal to the server. The server stores this information in a database. The specific input is route information, and the output is storage in the database.

[0493] Step 3:

[0494] The server uses a generative AI model to analyze registered cargo information and transport route information. The server retrieves this information from the database and inputs it into the generative AI. The generative AI calculates the optimal transport route and vehicle and generates the results. The specific inputs are cargo information and operating route information, and the output is a proposal for the optimal transport route and vehicle.

[0495] Step 4:

[0496] The server sends notifications to shippers and regular users based on the analysis results. Notification content includes the transport route, SA / PA locations, unlock codes, etc. Furthermore, an emotion engine is used to analyze the user's emotional state to determine the optimal notification timing and content. The specific inputs are the analysis results and emotional state, and the output is the optimized notification content.

[0497] Step 5:

[0498] The user (shipper) arrives at the notified SA / PA and deposits the luggage using a terminal. The server confirms the luggage deposit, records it in the database, and notifies regular users in real time. The specific input is the luggage deposit information, and the output is recording it in the database and notifying them.

[0499] Step 6:

[0500] The user (regular passenger) picks up their luggage at the designated SA / PA and transports it along the route. The server monitors this process in real time and notifies them as necessary. The specific input is the luggage receipt report, and the output is monitoring and notifying the transportation status.

[0501] Step 7:

[0502] The user (regular passenger) leaves their luggage at the SA / PA at their destination and notifies the server. The server confirms that the luggage has arrived at the destination and requests a local taxi company or ride-sharing company to make the final delivery. This completes the delivery procedure to the final destination. The specific input is an arrival report, and the output is a notification of final delivery arrangements.

[0503] Step 8:

[0504] In the case of food delivery, the server manages order information, food preparation status, and delivery routes. When users input orders and restaurants update food preparation status, this information is tracked in a database managed by the server. The generative AI calculates the optimal delivery route and notifies the user. The specific inputs are order information and cooking status, and the output is a notification of the optimal delivery route.

[0505] The above steps will result in an efficient and user-friendly logistics and food delivery system.

[0506] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0507] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0508] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0509] [Second embodiment]

[0510] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0511] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0512] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0513] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0514] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0515] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0516] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0517] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0518] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0519] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0520] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0521] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0522] The present invention realizes efficient logistics through a system that combines a database, a transportation route registration means, a cargo registration means, a generation AI, a notification means, a management means, and a final delivery means. Specific embodiments for carrying out the present invention will be described below.

[0523] 1. The shipper registers the cargo information

[0524] User (shipper):

[0525] Shippers access the system using a dedicated device (such as a smartphone or tablet), enter information about the cargo they wish to leave (weight, dimensions, contents, etc.), and select service areas (SA) or parking areas (PA) at their departure and arrival points.

[0526] server:

[0527] The server provides a screen for accepting registration of cargo information and transportation routes. When the shipper completes the input and presses the send button, the server saves the data in a database.

[0528] 2. Registering transportation routes for regular users

[0529] User (regular user):

[0530] Drivers who regularly use expressways register information such as their route, departure and arrival times, and available spaces in the system.

[0531] server:

[0532] The server stores the information of regular users in a database so that it can be analyzed for use in the next package delivery.

[0533] 3. Generative AI selects optimal routes

[0534] server:

[0535] The generation AI installed on the server analyzes the optimal transport route and vehicle based on the departure and arrival points registered by the shipper and the route information of regular users. The analysis results are used to select the most efficient route and vehicle according to a pre-set algorithm.

[0536] 4. Notification of transportation route and unlock code

[0537] server:

[0538] Based on the analysis results, the server notifies the shipper of the location of the SA / PA where the package should be left and the unlock code. At the same time, it notifies the selected regular user of detailed package information and the designated SA / PA information.

[0539] 5. Baggage drop-off and collection management

[0540] User (shipper):

[0541] The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo.

[0542] server:

[0543] The server notifies the regular user in real time once the baggage has been checked in.

[0544] User (regular user):

[0545] Regular users will receive a notification and collect their luggage at the designated SA / PA, which will then be transported to the destination SA / PA along the route.

[0546] 6. Final Delivery Arrangements

[0547] User (regular user):

[0548] Regular passengers leave their luggage at the SA / PA at their destination and notify the server.

[0549] server:

[0550] The server notifies the local taxi company or ride-sharing company that the package has arrived at the destination service area or parking area. The final delivery person receives the notification and transports the package to its final destination.

[0551] Specific examples

[0552] As a specific example, suppose a shipper, "Mr. A," wants to deliver a product from Tokyo to Osaka. Mr. A enters product information on his terminal, selects an SA in Tokyo and an SA in Osaka, and sends the information to the server. Since information about regular user "Mr. B," who drives from Tokyo to Osaka every Monday, is already registered, the server uses generation AI to analyze Mr. B's route and notifies Mr. A based on the results. Mr. A leaves his luggage at the designated SA in Tokyo, and Mr. B picks it up and transports it to the SA in Osaka. Mr. B leaves his luggage at the SA in Osaka, and the server notifies the local taxi company, which then makes the final delivery. This series of steps results in efficient transportation and cost reductions.

[0553] The above is a specific embodiment for carrying out the present invention. Such a system will improve the efficiency of logistics and reduce costs, and will be an effective measure against the 2024 problem.

[0554] The processing flow will be explained below.

[0555] Step 1:

[0556] The user (shipper) logs into the system using a dedicated terminal, enters the cargo information (weight, dimensions, contents, origin, destination) and clicks the send button.

[0557] Step 2:

[0558] The terminal transmits the input package information to the server.

[0559] Step 3:

[0560] The server receives the package information, stores it in the database, and returns a message to the user confirming that the information has been saved.

[0561] Step 4:

[0562] The user (regular user) inputs their route and available space information from a dedicated terminal and sends it.

[0563] Step 5:

[0564] The terminal transmits the regular user's route and available space information to the server.

[0565] Step 6:

[0566] The server receives the route information of regular users and stores it in a database.

[0567] Step 7:

[0568] The server begins analysis using generation AI based on cargo information from shippers and route information from regular users.

[0569] Step 8:

[0570] The generation AI selects the optimal transport route and corresponding vehicle.

[0571] Step 9:

[0572] Based on the analysis results, the server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code.

[0573] Step 10:

[0574] The server also notifies the selected regular users of the package information and the designated SA / PA information.

[0575] Step 11:

[0576] The user (shipper) brings the cargo to the designated SA / PA, unlocks the container using the unlock code provided by the server, and deposits the cargo.

[0577] Step 12:

[0578] The terminal reports the completion of baggage deposit to the server.

[0579] Step 13:

[0580] The server notifies the regular user in real time that the baggage has been confirmed.

[0581] Step 14:

[0582] The user (regular user) receives the notification and collects the package at the designated SA / PA.

[0583] Step 15:

[0584] The user (regular user) transports the luggage to the destination service area / parking area along the route.

[0585] Step 16:

[0586] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[0587] Step 17:

[0588] The server notifies local taxi companies and ride-sharing companies that the luggage has arrived at the arrival service area / parking area.

[0589] Step 18:

[0590] The user (a representative of a taxi company or ride-sharing company) receives a notification and goes to the SA / PA at the destination to pick up the luggage.

[0591] Step 19:

[0592] The user (a taxi company or ride-sharing company employee) transports the received package to its final destination and reports delivery completion to the server.

[0593] The above is the processing flow from depositing luggage to final delivery using the system of the present invention.

[0594] Example 1

[0595] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0596] In the logistics industry, selecting efficient transportation routes and ensuring smooth delivery of cargo both during transport and at the final destination are important issues. In particular, integrating information on multiple shippers and regular operators to select the optimal route is difficult, and arranging final delivery is also labor-intensive. Therefore, there is a need for a system that can efficiently manage the entire process, from cargo registration and transportation route selection to final delivery.

[0597] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0598] In this invention, the server includes a means for managing a database, a means for registering the routes of vehicles that operate regularly, a means for the shipper to register cargo, a generation AI means for analyzing the optimal transport route and vehicle based on the registered route and cargo information, a means for notifying the transport route and unlock code based on the analysis results, a means for managing the deposit and receipt of cargo at designated service areas or parking areas, and a means for coordinating with a local transportation service or shared driving service to entrust final delivery. This enables the selection of an efficient transport route, smooth delivery of cargo, and arrangement of final delivery.

[0599] The "means for managing the database" is a system for storing information on shippers and regular users, cargo information, and route information, and for retrieving and managing the information as needed.

[0600] "Means for registering the routes of vehicles that operate regularly" refers to methods or mechanisms for registering detailed information such as the routes, departure and arrival times, and available spaces of vehicles that operate regularly on expressways and public roads in the system.

[0601] "Means for a shipper to register a package" refers to a method or mechanism for a shipper to input and register information about the weight, dimensions, contents, origin, and destination of the package they wish to deposit into the system.

[0602] "Generative AI means" is an artificial intelligence technology that analyzes the optimal transport route and vehicle based on input cargo information and operation route information, and generates an efficient delivery plan.

[0603] "Means of notification" refers to a method or mechanism for providing information such as the transport route and unlock code to the shipper, and for notifying regular users of detailed information about their packages.

[0604] "Means for managing the deposit and receipt of packages at designated service or parking areas" means a system or method for managing and verifying the process by which shippers deposit packages and regular users collect packages at designated locations.

[0605] "Means of coordinating final delivery with a local transportation service or shared driving service" refers to a method or mechanism for coordinating with a local taxi company or ride-sharing company to arrange for the delivery of a package to its final destination.

[0606] The present invention is a logistics system that combines a database, a route registration means, a cargo registration means, a generation AI, a notification means, a management means, and a final delivery means. This enables efficient logistics. Specific embodiments for implementing the present invention will be described below.

[0607] 1. The shipper registers the cargo information

[0608] Users (shippers) access the system using a dedicated terminal (for example, a smartphone or tablet). The shipper enters information about the luggage they wish to store (weight, dimensions, contents, etc.) and selects the service area (SA) or parking area (PA) at their departure and arrival points. Specifically, the shipper operates their smartphone and enters their login ID and password to log into the system. They then enter detailed information about the luggage they wish to store and send it to the server.

[0609] The server provides a screen for accepting the registration of cargo information and operation routes, and stores the data sent from the shipper in a database. After the cargo information registration is complete, the server sends a confirmation email to the shipper to notify them that the cargo information has been successfully registered.

[0610] Example prompt:

[0611] "I would like to send a package from Tokyo to Osaka. The product information is as follows: weight 10kg, dimensions 50cm x 30cm x 20cm, contents: electronic product."

[0612] 2. Registering route information for regular users

[0613] Users (regular users) use dedicated terminals to register the route information of their vehicles that they operate regularly in the system. For example, a driver who regularly uses the expressway can enter detailed information such as their route, departure and arrival times, and available spaces.

[0614] The server stores the route information sent by the regular users in a database so that it can be used for the next package delivery. The server manages this information for use in analysis.

[0615] Example prompt:

[0616] "The bus runs from Tokyo to Osaka every Monday. It departs at 8:00 AM and arrives at 4:00 PM. There is space inside the bus for 50 kg of weight."

[0617] 3. Generative AI selects optimal routes

[0618] The server (generating AI) analyzes the optimal transport route and vehicle based on information registered by shippers and route information of regular users. The generating AI then selects the most efficient route based on an algorithm.

[0619] The server retrieves cargo information and route information from the database and analyzes it with the generation AI to create an optimal transportation plan. For example, the AI ​​analyzes how to optimally incorporate the shipper's cargo into the regular user's route.

[0620] Example prompt:

[0621] "Extract information about shippers and regular users from the database and use the AI ​​to select the optimal transport route and vehicle."

[0622] 4. Notification of transportation route and unlock code

[0623] Based on the analysis results, the server notifies the shipper of the location of the SA / PA where the package should be left and the unlock code. At the same time, it notifies the regular user of the package's detailed information and the designated SA / PA.

[0624] The server sends the shipper the location of the specified SA and the unlock code by email, and notifies the regular user of the package details and SA information.

[0625] Example prompt:

[0626] "Please inform the shipper of the SA to be deposited and the unlock code, and inform the regular user of the package details and SA information."

[0627] 5. Baggage drop-off and collection management

[0628] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code, and deposits the cargo.

[0629] The server confirms the baggage deposit and notifies the regular user of the information in real time.

[0630] The user (regular passenger) picks up the luggage at the designated SA / PA and transports it to the SA / PA at the destination along the route.

[0631] Example prompt:

[0632] "Instruct the shipper to use the unlock code to unlock the container and deposit the cargo. Notify the regular customer that the cargo will be deposited."

[0633] 6. Final Delivery Arrangements

[0634] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[0635] The server notifies the local transportation service or shared driving service that the package has arrived at the destination service area / parking area, and the final delivery person transports the package to the final destination.

[0636] Examples:

[0637] If Person A wants to send a product from Tokyo to Osaka, he or she uses a smartphone to enter the product information and send it to the server. Since the system is registered with information that Regular User B travels from Tokyo to Osaka every Monday, the server uses generation AI to analyze Person B's route and notifies Person A. Person A leaves the package at a designated service area in Tokyo, and Person B transports it to the service area in Osaka. The server then notifies the local transportation service, and the package is delivered to its final destination.

[0638] This series of steps and methods results in efficient transportation and cost reduction.

[0639] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0640] Step 1:

[0641] The user (shipper) registers the package information

[0642] Input: The shipper logs into the system using a terminal (smartphone or tablet) and enters the cargo information (weight, dimensions, contents, SA / PA of departure and arrival points).

[0643] The server stores the data

[0644] Output: The server receives the shipment information, stores it in a database, and sends a notification to the shipper confirming that the shipment information was successfully registered.

[0645] Specific operation: The shipper operates a smartphone, enters their login ID and password to log in to the system, then enters detailed information about the shipment and presses the send button. The server saves the data in a database and sends the shipper a confirmation email stating that the shipment information has been successfully registered.

[0646] Step 2:

[0647] The user (regular user) registers route information

[0648] Input: Regular passengers use the terminal to input details such as their route, departure and arrival times, and available spaces.

[0649] The server stores the data

[0650] Output: The server receives the route information and stores it in a database, ready for analysis so that it can be used for the next package delivery.

[0651] Specific operation: A regular user sets a route from Tokyo to Osaka every Monday, inputs the departure time as 8:00 AM, the arrival time as 4:00 PM, and the available space as 50 kg, and presses the send button. The server stores this information in the database.

[0652] Step 3:

[0653] Optimal route selection using generative AI

[0654] Input: The server retrieves package information and route information from the database.

[0655] The server (generative AI) analyzes the data

[0656] Output: The generation AI analyzes the optimal transport route and vehicle based on the input information and generates the results.

[0657] Specific operation: The server obtains the shipper's cargo information and the regular user's route information and passes it to the generation AI. The generation AI analyzes this information and selects the optimal transport route and vehicle based on an algorithm. As a result of the analysis, the most efficient route is generated.

[0658] Step 4:

[0659] Transport route and unlock code notification

[0660] Input: Analysis results of the generating AI

[0661] The server sends a notification

[0662] Output: The server notifies the shipper of the location and unlock code of the specified SA / PA, and notifies the subscriber of the package details.

[0663] Specific operation: Based on the analysis results of the generated AI, the server sends the shipper the location of a service area in Tokyo and the unlock code via email, and notifies regular user B of detailed information about the package and the information about the specified service area.

[0664] Step 5:

[0665] The shipper deposits the cargo at the designated SA / PA.

[0666] Input: Unlock code received by the shipper from the server

[0667] The server confirms the deposit

[0668] Output: The server confirms that the bag has been dropped off and notifies the subscriber in real time.

[0669] Specific operation: Shipper A arrives at the designated SA, enters the unlock code to unlock the container, and deposits his / her luggage. The server receives this information and sends a notification to regular user B that "the luggage has been deposited."

[0670] Step 6:

[0671] Regular passengers receive their packages

[0672] Input: Server notification

[0673] Regular users carry luggage

[0674] Output: Regular passengers collect their luggage at the designated service area and transport it to the destination service area / parking area along the route.

[0675] Specific operation: Regular user B picks up his luggage at a service area in Tokyo and transports it to a service area in Osaka Prefecture.

[0676] Step 7:

[0677] Final delivery arrangements

[0678] Input: Arrival notification from regular user

[0679] The server arranges final delivery

[0680] Output: The server notifies the local transportation service or shared driving service that the package has arrived at the destination SA and arranges for final delivery.

[0681] Specific operation: Regular user B arrives at a service area in Osaka Prefecture, deposits his / her luggage in the designated container, and notifies the server. The server then notifies the local transportation service of this information and arranges for delivery to the final destination.

[0682] The above is the specific flow of the system's program processing, which will enable efficient logistics.

[0683] (Application example 1)

[0684] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0685] Conventional logistics systems make it difficult to select efficient transportation routes and manage cargo, with a particular problem being the lack of coordination between shippers and transport personnel. Efficiency in final delivery of cargo and integrated management with local transportation service providers are also issues. For these reasons, a system that can improve the efficiency of the entire logistics system and deliver cargo quickly and reliably is needed.

[0686] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0687] In this invention, the server includes a database management unit, a unit for registering the transport routes of vehicles that regularly use expressways, and a unit for shippers to register their cargo. This allows the AI ​​to analyze the optimal transport route and vehicle based on cargo information from shippers and transport route information from regular users, and to provide appropriate notifications to shippers and transport personnel. Furthermore, notifications and cargo management can be achieved using smart devices, and final delivery arrangements with local transportation service providers can be smoothly made, thereby achieving overall logistics efficiency.

[0688] The "means of managing the database" is a system that centrally stores and manages information such as cargo information, transport route information, and user information.

[0689] "Means for registering transportation routes of vehicles that regularly use expressways" refers to an interface that allows drivers of vehicles that regularly travel the same route to input and save their own driving route information into the system.

[0690] "Means for shippers to register their cargo" refers to an interface that allows shippers to input cargo information (weight, dimensions, contents, departure point, arrival point, etc.) and send it to the system.

[0691] "Generative AI means" is an artificial intelligence technology that automatically analyzes and selects the optimal transport route and vehicle based on registered transport route and cargo information.

[0692] The "means of notification" is a system that notifies the shipper or transportation manager of information such as the transportation route and unlock code in a timely manner based on the analysis results.

[0693] "Means for managing the dropping off and picking up of luggage en route and at the destination" refers to a system that manages the procedures for dropping off and picking up luggage at designated service areas and parking areas.

[0694] "Means of entrusting final delivery to local mobility service providers" is a system that notifies and requests local taxi companies, ride-sharing companies, etc. to make final delivery at the destination.

[0695] "Means for registering luggage and displaying and notifying route analysis results using a smart device" refers to an application that provides functions such as luggage registration, displaying optimal routes, and notifying using a mobile device such as a smartphone or tablet.

[0696] The following describes the embodiments of the present invention. The system configuration described below is based on the technical elements described in the claims and includes specific implementation methods.

[0697] System Configuration

[0698] This system achieves efficient logistics by using a database, transportation route registration means, cargo registration means, generation AI, notification means, management means, final delivery means, and smart devices.

[0699] Databases and Servers

[0700] The database centrally manages information on cargo, transport routes, and regular users, and uses a relational database such as SQLite. The server is built using Flask (a Python web framework).

[0701] Shipper's registration of cargo information

[0702] Shippers use a smartphone or tablet to access a dedicated application and enter package information, including weight, dimensions, contents, origin, and destination, which is then sent to a server and stored in a database.

[0703] Registering transportation routes for regular users

[0704] Drivers who regularly use expressways input information such as their route, departure and arrival times, and available spaces into the application and send it to the server, where it is also stored in the database.

[0705] Optimal route selection using generative AI

[0706] The server uses the AI ​​to analyze the optimal transport route and vehicle based on the registered cargo information and route information of regular users. The AI ​​uses a pre-set algorithm to select the most efficient route and vehicle. The analysis results are stored on the server.

[0707] Notification of information by notification means

[0708] The server then notifies shippers and regular users of the necessary information based on the analysis results of the generative AI. The notification content includes the location of the designated service area (SA), parking area (PA), and unlock code. Notifications are sent in real time using a notification system such as Firebase Cloud Messaging (FCM).

[0709] Managing baggage drop-off and collection

[0710] The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo. Once the server confirms the deposit of the cargo, it notifies the regular user in real time. The regular user receives the notification and collects the cargo at the designated SA / PA. This information is recorded in the database.

[0711] Final delivery arrangements

[0712] A regular user leaves their luggage at the SA / PA at their destination and notifies the server. The server then notifies the local transportation service provider (e.g., a taxi company or ride-sharing company) that the luggage has arrived at the SA / PA. The final delivery person is notified and transports the luggage to its final destination. This information is also recorded in the database.

[0713] Specific examples

[0714] For example, if a shipper wants to deliver a product from Tokyo to Osaka, the shipper enters the product information on their terminal, selects a service area in Tokyo and another in Osaka, and sends it to the server. Since a regular user's driving information from Tokyo to Osaka every Monday is already registered, the server uses the generation AI to analyze the regular user's route and notifies the shipper based on the results. The shipper then leaves the package at the designated service area in Tokyo, where the regular user picks it up and transports it to the service area in Osaka. The server then notifies the local transportation service provider, and the final delivery is made.

[0715] Prompt Sentence Examples

[0716] Please register your luggage information. Enter the weight, dimensions, contents, departure and arrival points, and submit. We will then determine the best route for you and provide you with an unlock code. Follow the instructions to drop off or collect your luggage at the SA / PA.

[0717] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0718] Step 1:

[0719] Registering luggage information

[0720] The user (shipper) accesses the application using a smartphone or tablet and enters cargo information such as weight, dimensions, contents, departure point, and arrival point. This input data is sent to the server and saved in a database. The server registers the cargo information in the database and verifies that the input information has been saved correctly.

[0721] Step 2:

[0722] Registering transport routes

[0723] Users (regular passengers) enter information such as their route, departure and arrival times, and available spaces into the application. This transport route information is sent to the server and stored in a database. The server then registers the regular passenger information in the database and analyzes it for use in the next package delivery.

[0724] Step 3:

[0725] Optimal route selection using generative AI

[0726] The server uses generative AI to analyze the optimal transport route and vehicle based on the cargo information and transport route information stored in the database. Here, the generative AI model inputs weight, dimensions, departure point, arrival point, and available vehicle route information, and outputs the most efficient route and vehicle. The server stores the generative AI's analysis results.

[0727] Step 4:

[0728] Notification Implementation

[0729] The server then sends information to shippers and regular users based on the analysis results of the AI. The notification includes the location of the specified SA / PA and the unlock code. The server sends the notification in real time using a notification system such as Firebase Cloud Messaging (FCM).

[0730] Step 5:

[0731] Checked baggage

[0732] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the luggage. The terminal inputs the unlock code to unlock the container and deposits the luggage. Once the server confirms the deposit of the luggage, it records it in the database and then notifies the regular user.

[0733] Step 6:

[0734] Picking up your luggage

[0735] The user (regular user) receives the notification and picks up the package at the designated SA / PA. After the server confirms that the regular user has picked up the package, it saves the data in the database. The regular user then transports the package to the destination SA / PA according to the route.

[0736] Step 7:

[0737] Final delivery arrangements

[0738] A regular user leaves their luggage at the SA / PA at their destination and notifies the server. The server records the arrival of the luggage at the SA / PA in the database and notifies the local mobility service provider. The final delivery person (mobility service provider) receives the notification and transports the luggage to its final destination.

[0739] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0740] The present invention realizes efficient logistics and an improved user experience through a system that combines a database, a transportation route registration means, a package registration means, a generation AI, a notification means, a management means, a final delivery means, and an emotion engine. Specific embodiments for carrying out the present invention will be described below.

[0741] 1. The shipper registers the cargo information

[0742] User (shipper):

[0743] Shippers access the system using a dedicated device (such as a smartphone or tablet), enter information about the cargo they wish to leave (weight, dimensions, contents, etc.), and select service areas (SA) or parking areas (PA) at their departure and arrival points.

[0744] server:

[0745] The server provides a screen for accepting registration of cargo information and transportation routes. When the shipper completes the input and presses the send button, the server saves the data in a database. In addition, the server sends video and audio data acquired from the terminal to the emotion engine to recognize the shipper's emotions.

[0746] 2. Registering transportation routes for regular users

[0747] User (regular user):

[0748] Drivers who regularly use expressways register information such as their route, departure and arrival times, and available spaces in the system.

[0749] server:

[0750] The server stores the information of regular users in a database, and at the same time, recognizes the emotions of regular users and records them in the database.

[0751] 3. Generative AI selects optimal routes

[0752] server:

[0753] The generation AI implemented on the server analyzes the optimal transport route and vehicle based on the departure and arrival points registered by the shipper and the route information of regular users.

[0754] Emotion Engine:

[0755] Based on the analysis results of the generation AI, the system also takes into account the emotional information of shippers and regular users to determine the optimal content and timing of notifications.

[0756] 4. Notification of transportation route and unlock code

[0757] server:

[0758] Based on the analysis results, the server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code. At this time, it uses an emotion engine to optimize the content of the notification and provides the information in a format that is easy for the shipper to understand. In addition, it notifies selected regular users of the cargo information and the designated SA / PA information.

[0759] 5. Baggage drop-off and collection management

[0760] User (shipper):

[0761] When the shipper arrives at the designated SA / PA, they unlock the container using the unlock code received from the server and deposit their cargo. At the same time, the emotion engine monitors the shipper's emotional state and provides support if there are any problems.

[0762] server:

[0763] Once the baggage has been checked in, the server notifies the regular user in real time, with the content of the notification also optimized by the emotion engine.

[0764] User (regular user):

[0765] Regular users will receive a notification and collect their luggage at the designated SA / PA, which will then be transported to the destination SA / PA along the route.

[0766] 6. Final Delivery Arrangements

[0767] User (regular user):

[0768] Regular passengers leave their luggage at the SA / PA at their destination and notify the server.

[0769] server:

[0770] The server notifies local taxi companies and ride-sharing companies that the package has arrived at the destination service area or parking area.The emotion engine also monitors the emotional state of the final delivery person, helping to ensure efficient delivery.

[0771] Specific examples

[0772] As a specific example, suppose shipper "Mr. A" wants to transport goods from Tokyo to Osaka. When Mr. A enters and sends the product information on his terminal, the emotion engine also analyzes Mr. A's situation. Based on the registration information of regular user "Mr. B," the generation AI analyzes the optimal route and notifies him. When Mr. A leaves the goods at the designated service area in Tokyo, the emotion engine also checks for any problems, and if it detects any signs of impatience or anxiety, it displays a support message. When regular user B delivers the goods to the service area in Osaka, the server notifies the local taxi company, and the taxi company, with the support of the emotion engine, delivers the goods to the final destination. In this way, by incorporating the emotion engine throughout the system, an improved user experience and efficient logistics are achieved.

[0773] The above is a detailed embodiment of the system of the present invention, from baggage deposit to final delivery. By combining it with an emotion engine, an even more user-friendly logistics system can be constructed.

[0774] The processing flow will be explained below.

[0775] Step 1:

[0776] The user (shipper) logs into the system using a dedicated terminal. They enter the cargo information (weight, dimensions, contents, departure point, arrival point) and click the send button. The terminal then sends the entered cargo information to the server.

[0777] Step 2:

[0778] The server receives the package information and stores it in a database. It also sends video and audio data acquired from the shipper's device to the emotion engine, which recognizes the shipper's emotions.

[0779] Step 3:

[0780] The emotion engine analyzes the shipper's emotional information and sends feedback to the server.

[0781] Step 4:

[0782] The user (regular user) inputs and transmits their own route and available space information from a dedicated terminal. The terminal then transmits the route and available space information of the regular user to the server.

[0783] Step 5:

[0784] The server receives the route information of regular users and stores it in a database. It also acquires the emotion information of regular users and sends it to the emotion engine.

[0785] Step 6:

[0786] The emotion engine analyzes the emotion information of regular users and sends feedback to the server.

[0787] Step 7:

[0788] The server uses the AI ​​to analyze the cargo information from the shipper and the route information from the regular users. The AI ​​then selects the optimal transport route and the corresponding vehicle.

[0789] Step 8:

[0790] The emotion engine determines the optimal notification content and timing based on the analysis results of the generation AI and emotional information.

[0791] Step 9:

[0792] The server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code. At this time, the notification content is optimized using an emotion engine. In addition, selected regular users are notified of the cargo information and the designated SA / PA information.

[0793] Step 10:

[0794] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code provided by the server, and deposits the cargo. At the same time, the emotion engine monitors the shipper's emotions, and displays a support message if there are any concerns or problems.

[0795] Step 11:

[0796] The terminal reports the completion of baggage deposit to the server.

[0797] Step 12:

[0798] The server notifies the regular user in real time that their luggage has been checked in. The content of the notification is also optimized by the emotion engine.

[0799] Step 13:

[0800] The user (regular user) receives the notification and picks up the luggage at the designated SA / PA. The luggage is then transported to the destination SA / PA along the route.

[0801] Step 14:

[0802] An emotion engine monitors the emotional state of subscribers and provides support when needed.

[0803] Step 15:

[0804] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[0805] Step 16:

[0806] The server notifies local taxi companies and ride-sharing companies that the package has arrived at the destination service area or parking area. The emotion engine also monitors the emotional state of the final delivery person and provides support to ensure efficient delivery.

[0807] Step 17:

[0808] The user (a representative of a taxi company or ride-sharing company) receives a notification and goes to the SA / PA at the destination to pick up the luggage.

[0809] Step 18:

[0810] The user (a taxi company or ride-sharing company employee) transports the received package to its final destination and reports delivery completion to the server.

[0811] Step 19:

[0812] The server notifies the sender that the package has been delivered and sends a thank-you message, which is also optimized by the emotion engine.

[0813] The above is a detailed processing flow from baggage deposit to final delivery using the system of the present invention. By incorporating an emotion engine, an improved user experience and efficient logistics can be achieved.

[0814] Example 2

[0815] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0816] In conventional logistics systems, selecting efficient transportation routes and arranging final deliveries takes a lot of time and effort. Furthermore, notification methods that do not take users' emotions into consideration can cause stress and reduce satisfaction. There is a need to solve these problems and achieve an improved user experience and efficient logistics.

[0817] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0818] In this invention, the server includes a database management unit, a registering unit for vehicle transport routes that regularly use expressways, a shipper's cargo registration unit, a generating AI unit that analyzes the optimal transport route and vehicle based on the registered transport route and cargo information, an emotion engine unit that analyzes emotion information and optimizes the content and timing of notifications, a unit that notifies the user of the transport route, unlock code, etc. based on the analysis results, a unit that monitors the user's emotional state and provides support messages as needed, a unit that manages the drop-off and receipt of cargo during transport and at the destination, and a unit that entrusts final delivery to a local transport service company. This enables efficient transport route selection and user-friendly notifications, improving the efficiency of the overall logistics process and user satisfaction.

[0819] "Means for managing a database" refers to software and hardware for efficiently storing, searching, and updating cargo information, transportation route information, etc.

[0820] "Means for registering transport routes of vehicles that regularly use expressways" refers to interfaces and tools for inputting and registering the operating routes and schedule information of vehicles that frequently use expressways into the system.

[0821] "Means for shippers to register their shipments" refers to the interfaces and tools that shippers use to enter detailed information about their shipments and register them in the system.

[0822] "Generative AI means" refers to artificial intelligence algorithms and systems that automatically analyze and select the optimal transport route and vehicle based on registered cargo information and transport route information.

[0823] "Emotion engine means" refers to software or hardware that analyzes the user's emotional state from facial expressions and voice data and optimizes the content and timing of notifications.

[0824] "Means for notifying transport routes, unlock codes, etc." refers to systems and services for notifying shippers and regular users of information on transport routes and unlock codes based on the analysis results.

[0825] "Means for monitoring the user's emotional state and providing a supportive message as needed" refers to the function of the system to monitor the user's emotional state in real time and display or send a supportive message when deemed necessary.

[0826] "Measures for managing the deposit and collection of baggage en route and at the destination" refers to the systems and protocols used to manage the smooth deposit and collection of baggage.

[0827] "Means of entrusting final delivery to a local transportation service company" refers to a system in which, in order to deliver cargo that has arrived at the destination, the company cooperates with a local transportation service company such as a taxi company or ride-sharing company and entrusts the work to that company.

[0828] The present invention is a system that realizes efficient logistics and an improved user experience by combining a database, a transportation route registration means, a parcel registration means, a generation AI, a notification means, a management means, a final delivery means, and an emotion engine. Specific embodiments for carrying out the present invention will be described below.

[0829] 1. The shipper registers the cargo information

[0830] User (shipper):

[0831] Shippers access the system by launching a dedicated app on their smartphones, tablets, or other devices. They then enter the weight, dimensions, and contents of the package into a form on the screen, as well as the service area (SA) or parking area (PA) of the departure and arrival points. For example, they might enter, "I want to deliver from a service area in Shibuya Ward, Tokyo to a parking area in Umeda, Osaka."

[0832] server:

[0833] The server receives the package information sent from the terminal and stores it in the corresponding database. At the same time, it sends the collected video and audio data to the emotion engine to analyze the sender's emotions. In this case, the specific hardware and software used are Amazon Web Services (AWS) and MySQL.

[0834] 2. Registering transportation routes for regular users

[0835] User (regular user):

[0836] Drivers who regularly use the expressway access the system using their smartphones or tablets. Drivers input information such as their route, departure and arrival times, and available space in the vehicle. They also input detailed schedules, such as "I'll drive from Tokyo to Osaka every Monday."

[0837] server:

[0838] The server receives route information sent from the terminal and stores it in a database. It also sends video and audio data to an emotion engine to analyze the emotions of regular passengers.

[0839] 3. Optimal route selection using generative AI

[0840] server:

[0841] The server retrieves information about shippers and regular users from the database and sends it to the generation AI. This generation AI analyzes the optimal transport route and vehicle based on the registered departure and arrival points and the regular user's route information. In this case, OpenAI's GPT-4 is used.

[0842] Emotion Engine:

[0843] The emotion engine analyzes the emotional information of shippers and regular users and integrates it with the analysis results of the generation AI. This determines the optimal notification timing and content, taking into account their emotional state. The emotion engine uses Affectiva Emotion AI and other technologies.

[0844] 4. Notification of transportation route and unlock code

[0845] server:

[0846] The server notifies shippers and regular users based on the analysis results of the generation AI and the emotion engine. Shippers are provided with the optimal transport route, the location of SA / PA, and the unlock code. Regular users are also notified of their cargo information and the designated SA / PA information.

[0847] 5. Baggage drop-off and collection management

[0848] User (shipper):

[0849] When the shipper arrives at the designated SA / PA, they unlock the container using the unlock code received from the server and deposit their cargo. At the same time, the emotion engine monitors the shipper's emotional state and displays a supportive message if it detects impatience or anxiety.

[0850] server:

[0851] Once the baggage has been checked in, the server notifies the regular user in real time, and the content of this notification is also optimized by the emotion engine.

[0852] User (regular user):

[0853] Regular users will receive a notification, collect their luggage at the designated SA / PA, and then follow the route to transport their luggage to the SA / PA at their destination.

[0854] 6. Final Delivery Arrangements

[0855] User (regular user):

[0856] The regular passenger arrives at the SA / PA at the destination and leaves his / her luggage. This information is notified to the server.

[0857] server:

[0858] The server confirms the arrival of the package and notifies the local taxi or ride-sharing company, which then picks up the package and delivers it to its final destination. During this process, the emotion engine monitors the emotional state of the final delivery person, helping to ensure efficient delivery.

[0859] Specific examples

[0860] A shipper, "Mr. A," uses a dedicated app to enter, "I want to transport goods from Tokyo to Osaka. I'm in a hurry, but I want it to be completed without any problems." The server receives and stores the package information and emotion data. A regular user, "Mr. B," registers a route from Tokyo to Osaka every Monday. The server stores this information in a database and analyzes the emotion data. The generative AI determines the optimal transport route and integrates it with the emotion engine. Mr. A is notified of the optimal transport route and unlock code, and Mr. B is also notified of information about picking up the package. Mr. A leaves his package at a designated service area in Tokyo, and if there are any problems, the emotion engine displays a support message. When Mr. B delivers his package to the service area in Osaka, the server notifies the taxi company, and with the support of the emotion engine, the package is delivered to its final destination.

[0861] This will enable efficient logistics and an improved user experience.

[0862] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0863] Step 1:

[0864] The shipper registers the cargo information

[0865] Input: The user (shipper) enters cargo information (weight, dimensions, contents, SA / PA at departure and arrival points) using a smartphone or tablet.

[0866] Specific operation: The sender launches the dedicated app and enters detailed information about the package into the form. For example, they might enter, "The product weighs 10 kg, its dimensions are 30 x 30 x 30 cm, its contents are electronic devices, its departure point is a service area in Shibuya Ward, Tokyo, and its arrival point is a parking area in Umeda, Osaka."

[0867] Output: The terminal sends the package information to the server and also prepares the video and audio data captured by the device's camera and microphone.

[0868] Data processing / calculation: The input data is first formatted in the terminal and then serialized for transmission to the server.

[0869] Step 2:

[0870] Receiving and storing information

[0871] Input: Parcel information and video / audio data sent from the terminal.

[0872] Specific operation: The server receives the package information sent from the terminal and stores it in the corresponding database. At the same time, it sends the video and audio data to the emotion engine to analyze the shipper's emotions.

[0873] Output: The package information is stored in the database, and the emotion analysis results are output to the emotion engine.

[0874] Data processing / calculation: Before being stored in the database, the data is checked for integrity, and the emotion engine performs sentiment analysis using machine learning models.

[0875] Step 3:

[0876] Registering transportation routes for regular users

[0877] Input: The user (regular user) inputs information about the route, departure time, arrival time, and available space on the terminal.

[0878] Specific operation: A regular user launches the dedicated app and enters route and schedule information into a form. For example, they enter information such as "Runs from Tokyo to Osaka every Monday, departing at 6:00 AM and arriving at 2:00 PM. Space availability is 50%."

[0879] Output: The device sends the registration information to the server, including face and voice data.

[0880] Data processing / computation: Information is formatted and serialized before being received by the server.

[0881] Step 4:

[0882] Receiving and storing information

[0883] Input: Route information and video / audio data of regular users.

[0884] Specific operation: The server receives route information sent from the terminal and stores it in a database. At the same time, it sends video and audio data to the emotion engine to analyze the emotions of regular passengers.

[0885] Output: The route information is stored in the database, and the emotion analysis results are output to the emotion engine.

[0886] Data processing / calculation: Data integrity checks are performed, and the emotion engine performs emotion analysis using machine learning models.

[0887] Step 5:

[0888] Optimal route selection using generative AI

[0889] Input: Package information and regular passenger information from the database.

[0890] Specific operation: The server retrieves information on shippers and regular users from the database and sends it to the generation AI. The generation AI analyzes the optimal transport route and vehicle based on the departure and arrival points and the regular user's route information.

[0891] Output: The analysis results of the optimal transport routes and vehicles are generated.

[0892] Data processing / calculation: Generative AI processes large amounts of data and algorithms calculate the optimal options.

[0893] Step 6:

[0894] Emotional information integration

[0895] Input: Analysis results of the emotion engine and the generative AI.

[0896] Specific operation: The emotion engine analyzes emotional information and integrates it with the analysis results of the generative AI, thereby optimizing the content and timing of notifications.

[0897] Output: Decision on optimal notification content and timing based on sentiment analysis.

[0898] Data processing / calculation: Complex data merging process is carried out to integrate emotional data and logistics data.

[0899] Step 7:

[0900] Transport route and unlock code notification

[0901] Input: Generated optimal transport route and unlock code.

[0902] Specific operation: Based on the analysis results, the server notifies the shipper and regular user. The shipper is provided with the optimal transport route, the location of the SA / PA, and the unlock code, while the regular user is notified of the cargo information and the specified SA / PA information.

[0903] Output: Shipper and subscriber are provided with delivery information and unlock codes.

[0904] Data processing / calculation: Notification content is optimized based on emotion data and formatted in a user-friendly format.

[0905] Step 8:

[0906] Checked baggage

[0907] Input: The unlock code received from the server when the shipper arrives at the specified SA / PA.

[0908] Specific operation: The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo. At the same time, the emotion engine monitors the shipper's emotional state and displays support messages as necessary.

[0909] Output: Notification from the shipper that the luggage has been deposited.

[0910] Data processing / calculation: Baggage deposit confirmation data is sent to the server in real time.

[0911] Step 9:

[0912] Real-time notifications

[0913] Input: Baggage drop-off information.

[0914] Specific operation: Once the baggage deposit is confirmed, the server notifies the regular user in real time. The content of this notification is also optimized by the emotion engine.

[0915] Output: Notify the regular user that they have received their package.

[0916] Data processing / calculation: Real-time data processing enables immediate notification.

[0917] Step 10:

[0918] Receiving and transporting luggage

[0919] Input: Regular passenger arrival and baggage claim information.

[0920] Specific operation: Regular passengers collect their luggage at the designated SA / PA and then transport it to the SA / PA at their destination along the route.

[0921] Output: Notification that regular user has received their luggage.

[0922] Data processing / calculation: The receipt confirmation data is sent to the server, and the next notification process is carried out.

[0923] Step 11:

[0924] Final delivery arrangements

[0925] Input: Regular passenger arrival and baggage drop-off information.

[0926] Specific operation: The regular passenger arrives at the SA / PA at the destination and leaves his / her luggage. This information is notified to the server.

[0927] Output: Final delivery notification to the taxi or ride-sharing company at the destination.

[0928] Data processing / calculation: Based on the arrival information and deposit information, contact processing for final delivery is carried out.

[0929] Step 12:

[0930] Executing the final delivery

[0931] Input: Final delivery person's receiving information.

[0932] How it works: The server confirms the arrival of the package and notifies local taxi or ride-sharing companies. These companies then pick up the package and deliver it to its final destination. The emotion engine also monitors the emotional state of the final delivery person to help ensure efficient delivery.

[0933] Output: Final delivery completion notification.

[0934] Data processing / calculation: Receipt confirmation data is sent to the server, and the entire system log is updated when delivery is complete.

[0935] (Application example 2)

[0936] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0937] Modern logistics and food delivery systems require efficient route selection and reliable package delivery, but at the same time, improving the user experience is also important. In particular, if delivery timing and notification methods do not meet user expectations, customer satisfaction may decline. Furthermore, there is a lack of mechanisms to improve overall system efficiency and user peace of mind, such as optimizing delivery personnel's routes and analyzing their emotional state. Therefore, providing efficient and user-friendly logistics and food delivery systems is a key challenge.

[0938] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0939] In this invention, the server includes means for managing a database, means for registering transportation routes for vehicles that regularly use expressways, means for shippers to register their cargo, generation AI means for analyzing optimal transportation routes and vehicles based on the registered transportation routes and cargo information, means for notifying the transport route, unlock code, etc. based on the analysis results, means for managing the drop-off and receipt of cargo during transportation and at the destination, means for entrusting final delivery to a local taxi company or ride-sharing company, means for analyzing user emotions using an emotion engine and optimizing the content and timing of notifications, and means for managing food delivery orders, food preparation, and delivery personnel routes. This makes it possible to provide an efficient logistics and food delivery system that improves the user experience.

[0940] 1. "Means for managing the database" refers to a system that centrally stores data such as transportation routes, cargo information, and user information, and adds, updates, and deletes data as needed.

[0941] 2. "Means for registering transport routes for vehicles that regularly use expressways" refers to a system that has the function of inputting and saving transport routes and operation schedule information used daily by vehicles that regularly use expressways.

[0942] 3. "Means for shippers to register their cargo" refers to a system that allows shippers to input and save information about the cargo they wish to transport (weight, dimensions, contents, origin, destination, etc.).

[0943] 4. "Generative AI means" is an artificial intelligence that automatically analyzes the optimal transport route and vehicle based on registered transport route and cargo information.

[0944] 5. "Means of notification" refers to a system that communicates important information to users, such as the optimal transportation route analyzed by the generating AI and the unlock code.

[0945] 6. "Means for managing the deposit and receipt of luggage" means a system that properly manages the deposit and receipt of luggage by shippers and regular users during transportation and at the destination.

[0946] 7. "Means of entrusting final delivery to a local taxi company or ride-sharing company" refers to a system in which a local taxi company or ride-sharing company is requested to make the final delivery at the destination of the package.

[0947] 8. The "Emotion Engine" is an artificial intelligence that analyzes the emotional state of users and delivery personnel and optimizes the content and timing of notifications based on the results.

[0948] 9. "Food delivery order management means" refers to a system that inputs and saves meal order information from users and manages the progress of orders from cooking to delivery.

[0949] 10. "Means for preparing food for food delivery" refers to a system in which restaurants input and save the food preparation status and completion time.

[0950] 11. "Means for managing delivery personnel's driving routes in food delivery" refers to a system that manages delivery personnel's driving routes, available time, and working conditions, and provides optimal delivery routes.

[0951] The food delivery system for realizing the invention consists of the following components: Each component plays a specific role and works together to ensure the smooth functioning of the entire system.

[0952] 1. Database Management Methods

[0953] A database is installed on the server, where transport route information, package information, user information, delivery person information, etc. are stored in a unified manner. A relational database management system (RDBMS) such as MySQL can be used as database management software. Data can be added, updated, and deleted efficiently through this database.

[0954] 2. Transportation route registration method

[0955] The terminal provides an interface for registering transportation routes for vehicles that regularly use the expressway. Users (drivers) input their own driving schedules and routes into the terminal, and the information is sent to the server and stored in a database.

[0956] 3. Baggage registration method

[0957] Using the terminal, the shipper inputs information about the cargo they wish to transport (weight, dimensions, contents, origin, destination, etc.), which is then stored in a database via the server.

[0958] 4. Generation AI means

[0959] The server is equipped with a generative AI that analyzes the optimal transport route and vehicle based on registered transport route and cargo information. TensorFlow and PyTorch can be used for the generative AI model. The AI ​​model analyzes large amounts of data and proposes efficient routes and vehicles.

[0960] 5. Means of notification

[0961] Based on the analysis results of the generating AI, the server notifies the user of important information such as transportation routes and unlock codes. Notification methods include push notifications, SMS, and email. In addition, an emotion engine analyzes the user's emotional state and optimizes the content and timing of notifications.

[0962] 6. Baggage drop-off and collection management methods

[0963] The server manages the drop-off and pick-up of luggage during transport and at destinations. Shippers and regular users drop off or pick up luggage at designated locations, allowing for real-time processing.

[0964] 7. Final delivery consignment method

[0965] At the destination, the server requests a local taxi company or ride-sharing company to make the final delivery, ensuring that the package reaches its final destination efficiently.

[0966] 8. Emotional Engine Means

[0967] The server is equipped with an emotion engine that analyzes the emotional state of the user and delivery person and optimizes the content and timing of notifications based on the results. This emotion engine can utilize emotion analysis services such as IBM Watson.

[0968] 9. Food delivery management measures

[0969] The terminal and server manage food delivery orders, food preparation, and delivery driver routes. Users input orders through the application, and restaurants input the food preparation status. Delivery driver routes are optimized using generative AI.

[0970] By integrating these methods, an efficient and user-friendly logistics and food delivery system can be realized. For example, when a user orders a pizza, the order information is stored in a database, and the optimal route from the restaurant to the delivery person is analyzed by a generative AI. The emotional state of the delivery person is analyzed by an emotion engine, and a notification is sent to the user.

[0971] An example of a prompt sentence is "Order ID: 1, Food: Pizza, Location: A, Status: Cooking, Delivery Person: ID2, Route: A to B, Emotion: Good."

[0972] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0973] Step 1:

[0974] The user registers package information on the terminal. At this time, the user inputs information such as the package's weight, dimensions, contents, departure point, and arrival point, and sends it from the terminal to the server. The server stores this information in a database. The specific input is package information, and the output is storage in the database.

[0975] Step 2:

[0976] Regular users register their own routes and schedules on their terminals. The driver inputs information such as route, departure and arrival times, and available spaces, and sends it from the terminal to the server. The server stores this information in a database. The specific input is route information, and the output is storage in the database.

[0977] Step 3:

[0978] The server uses a generative AI model to analyze registered cargo information and transport route information. The server retrieves this information from the database and inputs it into the generative AI. The generative AI calculates the optimal transport route and vehicle and generates the results. The specific inputs are cargo information and operating route information, and the output is a proposal for the optimal transport route and vehicle.

[0979] Step 4:

[0980] The server sends notifications to shippers and regular users based on the analysis results. Notification content includes the transport route, SA / PA locations, unlock codes, etc. Furthermore, an emotion engine is used to analyze the user's emotional state to determine the optimal notification timing and content. The specific inputs are the analysis results and emotional state, and the output is the optimized notification content.

[0981] Step 5:

[0982] The user (shipper) arrives at the notified SA / PA and deposits the luggage using a terminal. The server confirms the luggage deposit, records it in the database, and notifies regular users in real time. The specific input is the luggage deposit information, and the output is recording it in the database and notifying them.

[0983] Step 6:

[0984] The user (regular passenger) picks up their luggage at the designated SA / PA and transports it along the route. The server monitors this process in real time and notifies them as necessary. The specific input is the luggage receipt report, and the output is monitoring and notifying the transportation status.

[0985] Step 7:

[0986] The user (regular passenger) leaves their luggage at the SA / PA at their destination and notifies the server. The server confirms that the luggage has arrived at the destination and requests a local taxi company or ride-sharing company to make the final delivery. This completes the delivery procedure to the final destination. The specific input is an arrival report, and the output is a notification of final delivery arrangements.

[0987] Step 8:

[0988] In the case of food delivery, the server manages order information, food preparation status, and delivery routes. When users input orders and restaurants update food preparation status, this information is tracked in a database managed by the server. The generative AI calculates the optimal delivery route and notifies the user. The specific inputs are order information and cooking status, and the output is a notification of the optimal delivery route.

[0989] The above steps will result in an efficient and user-friendly logistics and food delivery system.

[0990] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0991] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0992] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0993] [Third embodiment]

[0994] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0995] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0996] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0997] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0998] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0999] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1000] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1001] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1002] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1003] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1004] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1005] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1006] The present invention realizes efficient logistics through a system that combines a database, a transportation route registration means, a cargo registration means, a generation AI, a notification means, a management means, and a final delivery means. Specific embodiments for carrying out the present invention will be described below.

[1007] 1. The shipper registers the cargo information

[1008] User (shipper):

[1009] Shippers access the system using a dedicated device (such as a smartphone or tablet), enter information about the cargo they wish to leave (weight, dimensions, contents, etc.), and select service areas (SA) or parking areas (PA) at their departure and arrival points.

[1010] server:

[1011] The server provides a screen for accepting registration of cargo information and transportation routes. When the shipper completes the input and presses the send button, the server saves the data in a database.

[1012] 2. Registering transportation routes for regular users

[1013] User (regular user):

[1014] Drivers who regularly use expressways register information such as their route, departure and arrival times, and available spaces in the system.

[1015] server:

[1016] The server stores the information of regular users in a database so that it can be analyzed for use in the next package delivery.

[1017] 3. Generative AI selects optimal routes

[1018] server:

[1019] The generation AI installed on the server analyzes the optimal transport route and vehicle based on the departure and arrival points registered by the shipper and the route information of regular users. The analysis results are used to select the most efficient route and vehicle according to a pre-set algorithm.

[1020] 4. Notification of transportation route and unlock code

[1021] server:

[1022] Based on the analysis results, the server notifies the shipper of the location of the SA / PA where the package should be left and the unlock code. At the same time, it notifies the selected regular user of detailed package information and the designated SA / PA information.

[1023] 5. Baggage drop-off and collection management

[1024] User (shipper):

[1025] The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo.

[1026] server:

[1027] The server notifies the regular user in real time once the baggage has been checked in.

[1028] User (regular user):

[1029] Regular users will receive a notification and collect their luggage at the designated SA / PA, which will then be transported to the destination SA / PA along the route.

[1030] 6. Final Delivery Arrangements

[1031] User (regular user):

[1032] Regular passengers leave their luggage at the SA / PA at their destination and notify the server.

[1033] server:

[1034] The server notifies the local taxi company or ride-sharing company that the package has arrived at the destination service area or parking area. The final delivery person receives the notification and transports the package to its final destination.

[1035] Specific examples

[1036] As a specific example, suppose a shipper, "Mr. A," wants to deliver a product from Tokyo to Osaka. Mr. A enters product information on his terminal, selects an SA in Tokyo and an SA in Osaka, and sends the information to the server. Since information about regular user "Mr. B," who drives from Tokyo to Osaka every Monday, is already registered, the server uses generation AI to analyze Mr. B's route and notifies Mr. A based on the results. Mr. A leaves his luggage at the designated SA in Tokyo, and Mr. B picks it up and transports it to the SA in Osaka. Mr. B leaves his luggage at the SA in Osaka, and the server notifies the local taxi company, which then makes the final delivery. This series of steps results in efficient transportation and cost reductions.

[1037] The above is a specific embodiment for carrying out the present invention. Such a system will improve the efficiency of logistics and reduce costs, and will be an effective measure against the 2024 problem.

[1038] The processing flow will be explained below.

[1039] Step 1:

[1040] The user (shipper) logs into the system using a dedicated terminal, enters the cargo information (weight, dimensions, contents, origin, destination) and clicks the send button.

[1041] Step 2:

[1042] The terminal transmits the input package information to the server.

[1043] Step 3:

[1044] The server receives the package information, stores it in the database, and returns a message to the user confirming that the information has been saved.

[1045] Step 4:

[1046] The user (regular user) inputs their route and available space information from a dedicated terminal and sends it.

[1047] Step 5:

[1048] The terminal transmits the regular user's route and available space information to the server.

[1049] Step 6:

[1050] The server receives the route information of regular users and stores it in a database.

[1051] Step 7:

[1052] The server begins analysis using generation AI based on cargo information from shippers and route information from regular users.

[1053] Step 8:

[1054] The generation AI selects the optimal transport route and corresponding vehicle.

[1055] Step 9:

[1056] Based on the analysis results, the server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code.

[1057] Step 10:

[1058] The server also notifies the selected regular users of the package information and the designated SA / PA information.

[1059] Step 11:

[1060] The user (shipper) brings the cargo to the designated SA / PA, unlocks the container using the unlock code provided by the server, and deposits the cargo.

[1061] Step 12:

[1062] The terminal reports the completion of baggage deposit to the server.

[1063] Step 13:

[1064] The server notifies the regular user in real time that the baggage has been confirmed.

[1065] Step 14:

[1066] The user (regular user) receives the notification and collects the package at the designated SA / PA.

[1067] Step 15:

[1068] The user (regular user) transports the luggage to the destination service area / parking area along the route.

[1069] Step 16:

[1070] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[1071] Step 17:

[1072] The server notifies local taxi companies and ride-sharing companies that the luggage has arrived at the arrival service area / parking area.

[1073] Step 18:

[1074] The user (a representative of a taxi company or ride-sharing company) receives a notification and goes to the SA / PA at the destination to pick up the luggage.

[1075] Step 19:

[1076] The user (a taxi company or ride-sharing company employee) transports the received package to its final destination and reports delivery completion to the server.

[1077] The above is the processing flow from depositing luggage to final delivery using the system of the present invention.

[1078] Example 1

[1079] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1080] In the logistics industry, selecting efficient transportation routes and ensuring smooth delivery of cargo both during transport and at the final destination are important issues. In particular, integrating information on multiple shippers and regular operators to select the optimal route is difficult, and arranging final delivery is also labor-intensive. Therefore, there is a need for a system that can efficiently manage the entire process, from cargo registration and transportation route selection to final delivery.

[1081] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1082] In this invention, the server includes a means for managing a database, a means for registering the routes of vehicles that operate regularly, a means for the shipper to register cargo, a generation AI means for analyzing the optimal transport route and vehicle based on the registered route and cargo information, a means for notifying the transport route and unlock code based on the analysis results, a means for managing the deposit and receipt of cargo at designated service areas or parking areas, and a means for coordinating with a local transportation service or shared driving service to entrust final delivery. This enables the selection of an efficient transport route, smooth delivery of cargo, and arrangement of final delivery.

[1083] The "means for managing the database" is a system for storing information on shippers and regular users, cargo information, and route information, and for retrieving and managing the information as needed.

[1084] "Means for registering the routes of vehicles that operate regularly" refers to methods or mechanisms for registering detailed information such as the routes, departure and arrival times, and available spaces of vehicles that operate regularly on expressways and public roads in the system.

[1085] "Means for a shipper to register a package" refers to a method or mechanism for a shipper to input and register information about the weight, dimensions, contents, origin, and destination of the package they wish to deposit into the system.

[1086] "Generative AI means" is an artificial intelligence technology that analyzes the optimal transport route and vehicle based on input cargo information and operation route information, and generates an efficient delivery plan.

[1087] "Means of notification" refers to a method or mechanism for providing information such as the transport route and unlock code to the shipper, and for notifying regular users of detailed information about their packages.

[1088] "Means for managing the deposit and receipt of packages at designated service or parking areas" means a system or method for managing and verifying the process by which shippers deposit packages and regular users collect packages at designated locations.

[1089] "Means of coordinating final delivery with a local transportation service or shared driving service" refers to a method or mechanism for coordinating with a local taxi company or ride-sharing company to arrange for the delivery of a package to its final destination.

[1090] The present invention is a logistics system that combines a database, a route registration means, a cargo registration means, a generation AI, a notification means, a management means, and a final delivery means. This enables efficient logistics. Specific embodiments for implementing the present invention will be described below.

[1091] 1. The shipper registers the cargo information

[1092] Users (shippers) access the system using a dedicated terminal (for example, a smartphone or tablet). The shipper enters information about the luggage they wish to store (weight, dimensions, contents, etc.) and selects the service area (SA) or parking area (PA) at their departure and arrival points. Specifically, the shipper operates their smartphone and enters their login ID and password to log into the system. They then enter detailed information about the luggage they wish to store and send it to the server.

[1093] The server provides a screen for accepting the registration of cargo information and operation routes, and stores the data sent from the shipper in a database. After the cargo information registration is complete, the server sends a confirmation email to the shipper to notify them that the cargo information has been successfully registered.

[1094] Example prompt:

[1095] "I would like to send a package from Tokyo to Osaka. The product information is as follows: weight 10kg, dimensions 50cm x 30cm x 20cm, contents: electronic product."

[1096] 2. Registering route information for regular users

[1097] Users (regular users) use dedicated terminals to register the route information of their vehicles that they operate regularly in the system. For example, a driver who regularly uses the expressway can enter detailed information such as their route, departure and arrival times, and available spaces.

[1098] The server stores the route information sent by the regular users in a database so that it can be used for the next package delivery. The server manages this information for use in analysis.

[1099] Example prompt:

[1100] "The bus runs from Tokyo to Osaka every Monday. It departs at 8:00 AM and arrives at 4:00 PM. There is space inside the bus for 50 kg of weight."

[1101] 3. Generative AI selects optimal routes

[1102] The server (generating AI) analyzes the optimal transport route and vehicle based on information registered by shippers and route information of regular users. The generating AI then selects the most efficient route based on an algorithm.

[1103] The server retrieves cargo information and route information from the database and analyzes it with the generation AI to create an optimal transportation plan. For example, the AI ​​analyzes how to optimally incorporate the shipper's cargo into the regular user's route.

[1104] Example prompt:

[1105] "Extract information about shippers and regular users from the database and use the AI ​​to select the optimal transport route and vehicle."

[1106] 4. Notification of transportation route and unlock code

[1107] Based on the analysis results, the server notifies the shipper of the location of the SA / PA where the package should be left and the unlock code. At the same time, it notifies the regular user of the package's detailed information and the designated SA / PA.

[1108] The server sends the shipper the location of the specified SA and the unlock code by email, and notifies the regular user of the package details and SA information.

[1109] Example prompt:

[1110] "Please inform the shipper of the SA to be deposited and the unlock code, and inform the regular user of the package details and SA information."

[1111] 5. Baggage drop-off and collection management

[1112] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code, and deposits the cargo.

[1113] The server confirms the baggage deposit and notifies the regular user of the information in real time.

[1114] The user (regular passenger) picks up the luggage at the designated SA / PA and transports it to the SA / PA at the destination along the route.

[1115] Example prompt:

[1116] "Instruct the shipper to use the unlock code to unlock the container and deposit the cargo. Notify the regular customer that the cargo will be deposited."

[1117] 6. Final Delivery Arrangements

[1118] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[1119] The server notifies the local transportation service or shared driving service that the package has arrived at the destination service area / parking area, and the final delivery person transports the package to the final destination.

[1120] Examples:

[1121] If Person A wants to send a product from Tokyo to Osaka, he or she uses a smartphone to enter the product information and send it to the server. Since the system is registered with information that Regular User B travels from Tokyo to Osaka every Monday, the server uses generation AI to analyze Person B's route and notifies Person A. Person A leaves the package at a designated service area in Tokyo, and Person B transports it to the service area in Osaka. The server then notifies the local transportation service, and the package is delivered to its final destination.

[1122] This series of steps and methods results in efficient transportation and cost reduction.

[1123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1124] Step 1:

[1125] The user (shipper) registers the package information

[1126] Input: The shipper logs into the system using a terminal (smartphone or tablet) and enters the cargo information (weight, dimensions, contents, SA / PA of departure and arrival points).

[1127] The server stores the data

[1128] Output: The server receives the shipment information, stores it in a database, and sends a notification to the shipper confirming that the shipment information was successfully registered.

[1129] Specific operation: The shipper operates a smartphone, enters their login ID and password to log in to the system, then enters detailed information about the shipment and presses the send button. The server saves the data in a database and sends the shipper a confirmation email stating that the shipment information has been successfully registered.

[1130] Step 2:

[1131] The user (regular user) registers route information

[1132] Input: Regular passengers use the terminal to input details such as their route, departure and arrival times, and available spaces.

[1133] The server stores the data

[1134] Output: The server receives the route information and stores it in a database, ready for analysis so that it can be used for the next package delivery.

[1135] Specific operation: A regular user sets a route from Tokyo to Osaka every Monday, inputs the departure time as 8:00 AM, the arrival time as 4:00 PM, and the available space as 50 kg, and presses the send button. The server stores this information in the database.

[1136] Step 3:

[1137] Optimal route selection using generative AI

[1138] Input: The server retrieves package information and route information from the database.

[1139] The server (generative AI) analyzes the data

[1140] Output: The generation AI analyzes the optimal transport route and vehicle based on the input information and generates the results.

[1141] Specific operation: The server obtains the shipper's cargo information and the regular user's route information and passes it to the generation AI. The generation AI analyzes this information and selects the optimal transport route and vehicle based on an algorithm. As a result of the analysis, the most efficient route is generated.

[1142] Step 4:

[1143] Transport route and unlock code notification

[1144] Input: Analysis results of the generating AI

[1145] The server sends a notification

[1146] Output: The server notifies the shipper of the location and unlock code of the specified SA / PA, and notifies the subscriber of the package details.

[1147] Specific operation: Based on the analysis results of the generated AI, the server sends the shipper the location of a service area in Tokyo and the unlock code via email, and notifies regular user B of detailed information about the package and the information about the specified service area.

[1148] Step 5:

[1149] The shipper deposits the cargo at the designated SA / PA.

[1150] Input: Unlock code received by the shipper from the server

[1151] The server confirms the deposit

[1152] Output: The server confirms that the bag has been dropped off and notifies the subscriber in real time.

[1153] Specific operation: Shipper A arrives at the designated SA, enters the unlock code to unlock the container, and deposits his / her luggage. The server receives this information and sends a notification to regular user B that "the luggage has been deposited."

[1154] Step 6:

[1155] Regular passengers receive their packages

[1156] Input: Server notification

[1157] Regular users carry luggage

[1158] Output: Regular passengers collect their luggage at the designated service area and transport it to the destination service area / parking area along the route.

[1159] Specific operation: Regular user B picks up his luggage at a service area in Tokyo and transports it to a service area in Osaka Prefecture.

[1160] Step 7:

[1161] Final delivery arrangements

[1162] Input: Arrival notification from regular user

[1163] The server arranges final delivery

[1164] Output: The server notifies the local transportation service or shared driving service that the package has arrived at the destination SA and arranges for final delivery.

[1165] Specific operation: Regular user B arrives at a service area in Osaka Prefecture, deposits his / her luggage in the designated container, and notifies the server. The server then notifies the local transportation service of this information and arranges for delivery to the final destination.

[1166] The above is the specific flow of the system's program processing, which will enable efficient logistics.

[1167] (Application example 1)

[1168] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1169] Conventional logistics systems make it difficult to select efficient transportation routes and manage cargo, with a particular problem being the lack of coordination between shippers and transport personnel. Efficiency in final delivery of cargo and integrated management with local transportation service providers are also issues. For these reasons, a system that can improve the efficiency of the entire logistics system and deliver cargo quickly and reliably is needed.

[1170] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1171] In this invention, the server includes a database management unit, a unit for registering the transport routes of vehicles that regularly use expressways, and a unit for shippers to register their cargo. This allows the AI ​​to analyze the optimal transport route and vehicle based on cargo information from shippers and transport route information from regular users, and to provide appropriate notifications to shippers and transport personnel. Furthermore, notifications and cargo management can be achieved using smart devices, and final delivery arrangements with local transportation service providers can be smoothly made, thereby achieving overall logistics efficiency.

[1172] The "means of managing the database" is a system that centrally stores and manages information such as cargo information, transport route information, and user information.

[1173] "Means for registering transportation routes of vehicles that regularly use expressways" refers to an interface that allows drivers of vehicles that regularly travel the same route to input and save their own driving route information into the system.

[1174] "Means for shippers to register their cargo" refers to an interface that allows shippers to input cargo information (weight, dimensions, contents, departure point, arrival point, etc.) and send it to the system.

[1175] "Generative AI means" is an artificial intelligence technology that automatically analyzes and selects the optimal transport route and vehicle based on registered transport route and cargo information.

[1176] The "means of notification" is a system that notifies the shipper or transportation manager of information such as the transportation route and unlock code in a timely manner based on the analysis results.

[1177] "Means for managing the dropping off and picking up of luggage en route and at the destination" refers to a system that manages the procedures for dropping off and picking up luggage at designated service areas and parking areas.

[1178] "Means of entrusting final delivery to local mobility service providers" is a system that notifies and requests local taxi companies, ride-sharing companies, etc. to make final delivery at the destination.

[1179] "Means for registering luggage and displaying and notifying route analysis results using a smart device" refers to an application that provides functions such as luggage registration, displaying optimal routes, and notifying using a mobile device such as a smartphone or tablet.

[1180] The following describes the embodiments of the present invention. The system configuration described below is based on the technical elements described in the claims and includes specific implementation methods.

[1181] System Configuration

[1182] This system achieves efficient logistics by using a database, transportation route registration means, cargo registration means, generation AI, notification means, management means, final delivery means, and smart devices.

[1183] Databases and Servers

[1184] The database centrally manages information on cargo, transport routes, and regular users, and uses a relational database such as SQLite. The server is built using Flask (a Python web framework).

[1185] Shipper's registration of cargo information

[1186] Shippers use a smartphone or tablet to access a dedicated application and enter package information, including weight, dimensions, contents, origin, and destination, which is then sent to a server and stored in a database.

[1187] Registering transportation routes for regular users

[1188] Drivers who regularly use expressways input information such as their route, departure and arrival times, and available spaces into the application and send it to the server, where it is also stored in the database.

[1189] Optimal route selection using generative AI

[1190] The server uses the AI ​​to analyze the optimal transport route and vehicle based on the registered cargo information and route information of regular users. The AI ​​uses a pre-set algorithm to select the most efficient route and vehicle. The analysis results are stored on the server.

[1191] Notification of information by notification means

[1192] The server then notifies shippers and regular users of the necessary information based on the analysis results of the generative AI. The notification content includes the location of the designated service area (SA), parking area (PA), and unlock code. Notifications are sent in real time using a notification system such as Firebase Cloud Messaging (FCM).

[1193] Managing baggage drop-off and collection

[1194] The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo. Once the server confirms the deposit of the cargo, it notifies the regular user in real time. The regular user receives the notification and collects the cargo at the designated SA / PA. This information is recorded in the database.

[1195] Final delivery arrangements

[1196] A regular user leaves their luggage at the SA / PA at their destination and notifies the server. The server then notifies the local transportation service provider (e.g., a taxi company or ride-sharing company) that the luggage has arrived at the SA / PA. The final delivery person is notified and transports the luggage to its final destination. This information is also recorded in the database.

[1197] Specific examples

[1198] For example, if a shipper wants to deliver a product from Tokyo to Osaka, the shipper enters the product information on their terminal, selects a service area in Tokyo and another in Osaka, and sends it to the server. Since a regular user's driving information from Tokyo to Osaka every Monday is already registered, the server uses the generation AI to analyze the regular user's route and notifies the shipper based on the results. The shipper then leaves the package at the designated service area in Tokyo, where the regular user picks it up and transports it to the service area in Osaka. The server then notifies the local transportation service provider, and the final delivery is made.

[1199] Prompt Sentence Examples

[1200] Please register your luggage information. Enter the weight, dimensions, contents, departure and arrival points, and submit. We will then determine the best route for you and provide you with an unlock code. Follow the instructions to drop off or collect your luggage at the SA / PA.

[1201] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1202] Step 1:

[1203] Registering luggage information

[1204] The user (shipper) accesses the application using a smartphone or tablet and enters cargo information such as weight, dimensions, contents, departure point, and arrival point. This input data is sent to the server and saved in a database. The server registers the cargo information in the database and verifies that the input information has been saved correctly.

[1205] Step 2:

[1206] Registering transport routes

[1207] Users (regular passengers) enter information such as their route, departure and arrival times, and available spaces into the application. This transport route information is sent to the server and stored in a database. The server then registers the regular passenger information in the database and analyzes it for use in the next package delivery.

[1208] Step 3:

[1209] Optimal route selection using generative AI

[1210] The server uses generative AI to analyze the optimal transport route and vehicle based on the cargo information and transport route information stored in the database. Here, the generative AI model inputs weight, dimensions, departure point, arrival point, and available vehicle route information, and outputs the most efficient route and vehicle. The server stores the generative AI's analysis results.

[1211] Step 4:

[1212] Notification Implementation

[1213] The server then sends information to shippers and regular users based on the analysis results of the AI. The notification includes the location of the specified SA / PA and the unlock code. The server sends the notification in real time using a notification system such as Firebase Cloud Messaging (FCM).

[1214] Step 5:

[1215] Checked baggage

[1216] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the luggage. The terminal inputs the unlock code to unlock the container and deposits the luggage. Once the server confirms the deposit of the luggage, it records it in the database and then notifies the regular user.

[1217] Step 6:

[1218] Picking up your luggage

[1219] The user (regular user) receives the notification and picks up the package at the designated SA / PA. After the server confirms that the regular user has picked up the package, it saves the data in the database. The regular user then transports the package to the destination SA / PA according to the route.

[1220] Step 7:

[1221] Final delivery arrangements

[1222] A regular user leaves their luggage at the SA / PA at their destination and notifies the server. The server records the arrival of the luggage at the SA / PA in the database and notifies the local mobility service provider. The final delivery person (mobility service provider) receives the notification and transports the luggage to its final destination.

[1223] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1224] The present invention realizes efficient logistics and an improved user experience through a system that combines a database, a transportation route registration means, a package registration means, a generation AI, a notification means, a management means, a final delivery means, and an emotion engine. Specific embodiments for carrying out the present invention will be described below.

[1225] 1. The shipper registers the cargo information

[1226] User (shipper):

[1227] Shippers access the system using a dedicated device (such as a smartphone or tablet), enter information about the cargo they wish to leave (weight, dimensions, contents, etc.), and select service areas (SA) or parking areas (PA) at their departure and arrival points.

[1228] server:

[1229] The server provides a screen for accepting registration of cargo information and transportation routes. When the shipper completes the input and presses the send button, the server saves the data in a database. In addition, the server sends video and audio data acquired from the terminal to the emotion engine to recognize the shipper's emotions.

[1230] 2. Registering transportation routes for regular users

[1231] User (regular user):

[1232] Drivers who regularly use expressways register information such as their route, departure and arrival times, and available spaces in the system.

[1233] server:

[1234] The server stores the information of regular users in a database, and at the same time, recognizes the emotions of regular users and records them in the database.

[1235] 3. Generative AI selects optimal routes

[1236] server:

[1237] The generation AI implemented on the server analyzes the optimal transport route and vehicle based on the departure and arrival points registered by the shipper and the route information of regular users.

[1238] Emotion Engine:

[1239] Based on the analysis results of the generation AI, the system also takes into account the emotional information of shippers and regular users to determine the optimal content and timing of notifications.

[1240] 4. Notification of transportation route and unlock code

[1241] server:

[1242] Based on the analysis results, the server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code. At this time, it uses an emotion engine to optimize the content of the notification and provides the information in a format that is easy for the shipper to understand. In addition, it notifies selected regular users of the cargo information and the designated SA / PA information.

[1243] 5. Baggage drop-off and collection management

[1244] User (shipper):

[1245] When the shipper arrives at the designated SA / PA, they unlock the container using the unlock code received from the server and deposit their cargo. At the same time, the emotion engine monitors the shipper's emotional state and provides support if there are any problems.

[1246] server:

[1247] Once the baggage has been checked in, the server notifies the regular user in real time, with the content of the notification also optimized by the emotion engine.

[1248] User (regular user):

[1249] Regular users will receive a notification and collect their luggage at the designated SA / PA, which will then be transported to the destination SA / PA along the route.

[1250] 6. Final Delivery Arrangements

[1251] User (regular user):

[1252] Regular passengers leave their luggage at the SA / PA at their destination and notify the server.

[1253] server:

[1254] The server notifies local taxi companies and ride-sharing companies that the package has arrived at the destination service area or parking area.The emotion engine also monitors the emotional state of the final delivery person, helping to ensure efficient delivery.

[1255] Specific examples

[1256] As a specific example, suppose shipper "Mr. A" wants to transport goods from Tokyo to Osaka. When Mr. A enters and sends the product information on his terminal, the emotion engine also analyzes Mr. A's situation. Based on the registration information of regular user "Mr. B," the generation AI analyzes the optimal route and notifies him. When Mr. A leaves the goods at the designated service area in Tokyo, the emotion engine also checks for any problems, and if it detects any signs of impatience or anxiety, it displays a support message. When regular user B delivers the goods to the service area in Osaka, the server notifies the local taxi company, and the taxi company, with the support of the emotion engine, delivers the goods to the final destination. In this way, by incorporating the emotion engine throughout the system, an improved user experience and efficient logistics are achieved.

[1257] The above is a detailed embodiment of the system of the present invention, from baggage deposit to final delivery. By combining it with an emotion engine, an even more user-friendly logistics system can be constructed.

[1258] The processing flow will be explained below.

[1259] Step 1:

[1260] The user (shipper) logs into the system using a dedicated terminal. They enter the cargo information (weight, dimensions, contents, departure point, arrival point) and click the send button. The terminal then sends the entered cargo information to the server.

[1261] Step 2:

[1262] The server receives the package information and stores it in a database. It also sends video and audio data acquired from the shipper's device to the emotion engine, which recognizes the shipper's emotions.

[1263] Step 3:

[1264] The emotion engine analyzes the shipper's emotional information and sends feedback to the server.

[1265] Step 4:

[1266] The user (regular user) inputs and transmits their own route and available space information from a dedicated terminal. The terminal then transmits the route and available space information of the regular user to the server.

[1267] Step 5:

[1268] The server receives the route information of regular users and stores it in a database. It also acquires the emotion information of regular users and sends it to the emotion engine.

[1269] Step 6:

[1270] The emotion engine analyzes the emotion information of regular users and sends feedback to the server.

[1271] Step 7:

[1272] The server uses the AI ​​to analyze the cargo information from the shipper and the route information from the regular users. The AI ​​then selects the optimal transport route and the corresponding vehicle.

[1273] Step 8:

[1274] The emotion engine determines the optimal notification content and timing based on the analysis results of the generation AI and emotional information.

[1275] Step 9:

[1276] The server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code. At this time, the notification content is optimized using an emotion engine. In addition, selected regular users are notified of the cargo information and the designated SA / PA information.

[1277] Step 10:

[1278] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code provided by the server, and deposits the cargo. At the same time, the emotion engine monitors the shipper's emotions, and displays a support message if there are any concerns or problems.

[1279] Step 11:

[1280] The terminal reports the completion of baggage deposit to the server.

[1281] Step 12:

[1282] The server notifies the regular user in real time that their luggage has been checked in. The content of the notification is also optimized by the emotion engine.

[1283] Step 13:

[1284] The user (regular user) receives the notification and picks up the luggage at the designated SA / PA. The luggage is then transported to the destination SA / PA along the route.

[1285] Step 14:

[1286] An emotion engine monitors the emotional state of subscribers and provides support when needed.

[1287] Step 15:

[1288] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[1289] Step 16:

[1290] The server notifies local taxi companies and ride-sharing companies that the package has arrived at the destination service area or parking area. The emotion engine also monitors the emotional state of the final delivery person and provides support to ensure efficient delivery.

[1291] Step 17:

[1292] The user (a representative of a taxi company or ride-sharing company) receives a notification and goes to the SA / PA at the destination to pick up the luggage.

[1293] Step 18:

[1294] The user (a taxi company or ride-sharing company employee) transports the received package to its final destination and reports delivery completion to the server.

[1295] Step 19:

[1296] The server notifies the sender that the package has been delivered and sends a thank-you message, which is also optimized by the emotion engine.

[1297] The above is a detailed processing flow from baggage deposit to final delivery using the system of the present invention. By incorporating an emotion engine, an improved user experience and efficient logistics can be achieved.

[1298] Example 2

[1299] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1300] In conventional logistics systems, selecting efficient transportation routes and arranging final deliveries takes a lot of time and effort. Furthermore, notification methods that do not take users' emotions into consideration can cause stress and reduce satisfaction. There is a need to solve these problems and achieve an improved user experience and efficient logistics.

[1301] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1302] In this invention, the server includes a database management unit, a registering unit for vehicle transport routes that regularly use expressways, a shipper's cargo registration unit, a generating AI unit that analyzes the optimal transport route and vehicle based on the registered transport route and cargo information, an emotion engine unit that analyzes emotion information and optimizes the content and timing of notifications, a unit that notifies the user of the transport route, unlock code, etc. based on the analysis results, a unit that monitors the user's emotional state and provides support messages as needed, a unit that manages the drop-off and receipt of cargo during transport and at the destination, and a unit that entrusts final delivery to a local transport service company. This enables efficient transport route selection and user-friendly notifications, improving the efficiency of the overall logistics process and user satisfaction.

[1303] "Means for managing a database" refers to software and hardware for efficiently storing, searching, and updating cargo information, transportation route information, etc.

[1304] "Means for registering transport routes of vehicles that regularly use expressways" refers to interfaces and tools for inputting and registering the operating routes and schedule information of vehicles that frequently use expressways into the system.

[1305] "Means for shippers to register their shipments" refers to the interfaces and tools that shippers use to enter detailed information about their shipments and register them in the system.

[1306] "Generative AI means" refers to artificial intelligence algorithms and systems that automatically analyze and select the optimal transport route and vehicle based on registered cargo information and transport route information.

[1307] "Emotion engine means" refers to software or hardware that analyzes the user's emotional state from facial expressions and voice data and optimizes the content and timing of notifications.

[1308] "Means for notifying transport routes, unlock codes, etc." refers to systems and services for notifying shippers and regular users of information on transport routes and unlock codes based on the analysis results.

[1309] "Means for monitoring the user's emotional state and providing a supportive message as needed" refers to the function of the system to monitor the user's emotional state in real time and display or send a supportive message when deemed necessary.

[1310] "Measures for managing the deposit and collection of baggage en route and at the destination" refers to the systems and protocols used to manage the smooth deposit and collection of baggage.

[1311] "Means of entrusting final delivery to a local transportation service company" refers to a system in which, in order to deliver cargo that has arrived at the destination, the company cooperates with a local transportation service company such as a taxi company or ride-sharing company and entrusts the work to that company.

[1312] The present invention is a system that realizes efficient logistics and an improved user experience by combining a database, a transportation route registration means, a parcel registration means, a generation AI, a notification means, a management means, a final delivery means, and an emotion engine. Specific embodiments for carrying out the present invention will be described below.

[1313] 1. The shipper registers the cargo information

[1314] User (shipper):

[1315] Shippers access the system by launching a dedicated app on their smartphones, tablets, or other devices. They then enter the weight, dimensions, and contents of the package into a form on the screen, as well as the service area (SA) or parking area (PA) of the departure and arrival points. For example, they might enter, "I want to deliver from a service area in Shibuya Ward, Tokyo to a parking area in Umeda, Osaka."

[1316] server:

[1317] The server receives the package information sent from the terminal and stores it in the corresponding database. At the same time, it sends the collected video and audio data to the emotion engine to analyze the sender's emotions. In this case, the specific hardware and software used are Amazon Web Services (AWS) and MySQL.

[1318] 2. Registering transportation routes for regular users

[1319] User (regular user):

[1320] Drivers who regularly use the expressway access the system using their smartphones or tablets. Drivers input information such as their route, departure and arrival times, and available space in the vehicle. They also input detailed schedules, such as "I'll drive from Tokyo to Osaka every Monday."

[1321] server:

[1322] The server receives route information sent from the terminal and stores it in a database. It also sends video and audio data to an emotion engine to analyze the emotions of regular passengers.

[1323] 3. Optimal route selection using generative AI

[1324] server:

[1325] The server retrieves information about shippers and regular users from the database and sends it to the generation AI. This generation AI analyzes the optimal transport route and vehicle based on the registered departure and arrival points and the regular user's route information. In this case, OpenAI's GPT-4 is used.

[1326] Emotion Engine:

[1327] The emotion engine analyzes the emotional information of shippers and regular users and integrates it with the analysis results of the generation AI. This determines the optimal notification timing and content, taking into account their emotional state. The emotion engine uses Affectiva Emotion AI and other technologies.

[1328] 4. Notification of transportation route and unlock code

[1329] server:

[1330] The server notifies shippers and regular users based on the analysis results of the generation AI and the emotion engine. Shippers are provided with the optimal transport route, the location of SA / PA, and the unlock code. Regular users are also notified of their cargo information and the designated SA / PA information.

[1331] 5. Baggage drop-off and collection management

[1332] User (shipper):

[1333] When the shipper arrives at the designated SA / PA, they unlock the container using the unlock code received from the server and deposit their cargo. At the same time, the emotion engine monitors the shipper's emotional state and displays a supportive message if it detects impatience or anxiety.

[1334] server:

[1335] Once the baggage has been checked in, the server notifies the regular user in real time, and the content of this notification is also optimized by the emotion engine.

[1336] User (regular user):

[1337] Regular users will receive a notification, collect their luggage at the designated SA / PA, and then follow the route to transport their luggage to the SA / PA at their destination.

[1338] 6. Final Delivery Arrangements

[1339] User (regular user):

[1340] The regular passenger arrives at the SA / PA at the destination and leaves his / her luggage. This information is notified to the server.

[1341] server:

[1342] The server confirms the arrival of the package and notifies the local taxi or ride-sharing company, which then picks up the package and delivers it to its final destination. During this process, the emotion engine monitors the emotional state of the final delivery person, helping to ensure efficient delivery.

[1343] Specific examples

[1344] A shipper, "Mr. A," uses a dedicated app to enter, "I want to transport goods from Tokyo to Osaka. I'm in a hurry, but I want it to be completed without any problems." The server receives and stores the package information and emotion data. A regular user, "Mr. B," registers a route from Tokyo to Osaka every Monday. The server stores this information in a database and analyzes the emotion data. The generative AI determines the optimal transport route and integrates it with the emotion engine. Mr. A is notified of the optimal transport route and unlock code, and Mr. B is also notified of information about picking up the package. Mr. A leaves his package at a designated service area in Tokyo, and if there are any problems, the emotion engine displays a support message. When Mr. B delivers his package to the service area in Osaka, the server notifies the taxi company, and with the support of the emotion engine, the package is delivered to its final destination.

[1345] This will enable efficient logistics and an improved user experience.

[1346] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1347] Step 1:

[1348] The shipper registers the cargo information

[1349] Input: The user (shipper) enters cargo information (weight, dimensions, contents, SA / PA at departure and arrival points) using a smartphone or tablet.

[1350] Specific operation: The sender launches the dedicated app and enters detailed information about the package into the form. For example, they might enter, "The product weighs 10 kg, its dimensions are 30 x 30 x 30 cm, its contents are electronic devices, its departure point is a service area in Shibuya Ward, Tokyo, and its arrival point is a parking area in Umeda, Osaka."

[1351] Output: The terminal sends the package information to the server and also prepares the video and audio data captured by the device's camera and microphone.

[1352] Data processing / calculation: The input data is first formatted in the terminal and then serialized for transmission to the server.

[1353] Step 2:

[1354] Receiving and storing information

[1355] Input: Parcel information and video / audio data sent from the terminal.

[1356] Specific operation: The server receives the package information sent from the terminal and stores it in the corresponding database. At the same time, it sends the video and audio data to the emotion engine to analyze the shipper's emotions.

[1357] Output: The package information is stored in the database, and the emotion analysis results are output to the emotion engine.

[1358] Data processing / calculation: Before being stored in the database, the data is checked for integrity, and the emotion engine performs sentiment analysis using machine learning models.

[1359] Step 3:

[1360] Registering transportation routes for regular users

[1361] Input: The user (regular user) inputs information about the route, departure time, arrival time, and available space on the terminal.

[1362] Specific operation: A regular user launches the dedicated app and enters route and schedule information into a form. For example, they enter information such as "Runs from Tokyo to Osaka every Monday, departing at 6:00 AM and arriving at 2:00 PM. Space availability is 50%."

[1363] Output: The device sends the registration information to the server, including face and voice data.

[1364] Data processing / computation: Information is formatted and serialized before being received by the server.

[1365] Step 4:

[1366] Receiving and storing information

[1367] Input: Route information and video / audio data of regular users.

[1368] Specific operation: The server receives route information sent from the terminal and stores it in a database. At the same time, it sends video and audio data to the emotion engine to analyze the emotions of regular passengers.

[1369] Output: The route information is stored in the database, and the emotion analysis results are output to the emotion engine.

[1370] Data processing / calculation: Data integrity checks are performed, and the emotion engine performs emotion analysis using machine learning models.

[1371] Step 5:

[1372] Optimal route selection using generative AI

[1373] Input: Package information and regular passenger information from the database.

[1374] Specific operation: The server retrieves information on shippers and regular users from the database and sends it to the generation AI. The generation AI analyzes the optimal transport route and vehicle based on the departure and arrival points and the regular user's route information.

[1375] Output: The analysis results of the optimal transport routes and vehicles are generated.

[1376] Data processing / calculation: Generative AI processes large amounts of data and algorithms calculate the optimal options.

[1377] Step 6:

[1378] Emotional information integration

[1379] Input: Analysis results of the emotion engine and the generative AI.

[1380] Specific operation: The emotion engine analyzes emotional information and integrates it with the analysis results of the generative AI, thereby optimizing the content and timing of notifications.

[1381] Output: Decision on optimal notification content and timing based on sentiment analysis.

[1382] Data processing / calculation: Complex data merging process is carried out to integrate emotional data and logistics data.

[1383] Step 7:

[1384] Transport route and unlock code notification

[1385] Input: Generated optimal transport route and unlock code.

[1386] Specific operation: Based on the analysis results, the server notifies the shipper and regular user. The shipper is provided with the optimal transport route, the location of the SA / PA, and the unlock code, while the regular user is notified of the cargo information and the specified SA / PA information.

[1387] Output: Shipper and subscriber are provided with delivery information and unlock codes.

[1388] Data processing / calculation: Notification content is optimized based on emotion data and formatted in a user-friendly format.

[1389] Step 8:

[1390] Checked baggage

[1391] Input: The unlock code received from the server when the shipper arrives at the specified SA / PA.

[1392] Specific operation: The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo. At the same time, the emotion engine monitors the shipper's emotional state and displays support messages as necessary.

[1393] Output: Notification from the shipper that the luggage has been deposited.

[1394] Data processing / calculation: Baggage deposit confirmation data is sent to the server in real time.

[1395] Step 9:

[1396] Real-time notifications

[1397] Input: Baggage drop-off information.

[1398] Specific operation: Once the baggage deposit is confirmed, the server notifies the regular user in real time. The content of this notification is also optimized by the emotion engine.

[1399] Output: Notify the regular user that they have received their package.

[1400] Data processing / calculation: Real-time data processing enables immediate notification.

[1401] Step 10:

[1402] Receiving and transporting luggage

[1403] Input: Regular passenger arrival and baggage claim information.

[1404] Specific operation: Regular passengers collect their luggage at the designated SA / PA and then transport it to the SA / PA at their destination along the route.

[1405] Output: Notification that regular user has received their luggage.

[1406] Data processing / calculation: The receipt confirmation data is sent to the server, and the next notification process is carried out.

[1407] Step 11:

[1408] Final delivery arrangements

[1409] Input: Regular passenger arrival and baggage drop-off information.

[1410] Specific operation: The regular passenger arrives at the SA / PA at the destination and leaves his / her luggage. This information is notified to the server.

[1411] Output: Final delivery notification to the taxi or ride-sharing company at the destination.

[1412] Data processing / calculation: Based on the arrival information and deposit information, contact processing for final delivery is carried out.

[1413] Step 12:

[1414] Executing the final delivery

[1415] Input: Final delivery person's receiving information.

[1416] How it works: The server confirms the arrival of the package and notifies local taxi or ride-sharing companies. These companies then pick up the package and deliver it to its final destination. The emotion engine also monitors the emotional state of the final delivery person to help ensure efficient delivery.

[1417] Output: Final delivery completion notification.

[1418] Data processing / calculation: Receipt confirmation data is sent to the server, and the entire system log is updated when delivery is complete.

[1419] (Application example 2)

[1420] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1421] Modern logistics and food delivery systems require efficient route selection and reliable package delivery, but at the same time, improving the user experience is also important. In particular, if delivery timing and notification methods do not meet user expectations, customer satisfaction may decline. Furthermore, there is a lack of mechanisms to improve overall system efficiency and user peace of mind, such as optimizing delivery personnel's routes and analyzing their emotional state. Therefore, providing efficient and user-friendly logistics and food delivery systems is a key challenge.

[1422] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1423] In this invention, the server includes means for managing a database, means for registering transportation routes for vehicles that regularly use expressways, means for shippers to register their cargo, generation AI means for analyzing optimal transportation routes and vehicles based on the registered transportation routes and cargo information, means for notifying the transport route, unlock code, etc. based on the analysis results, means for managing the drop-off and receipt of cargo during transportation and at the destination, means for entrusting final delivery to a local taxi company or ride-sharing company, means for analyzing user emotions using an emotion engine and optimizing the content and timing of notifications, and means for managing food delivery orders, food preparation, and delivery personnel routes. This makes it possible to provide an efficient logistics and food delivery system that improves the user experience.

[1424] 1. "Means for managing the database" refers to a system that centrally stores data such as transportation routes, cargo information, and user information, and adds, updates, and deletes data as needed.

[1425] 2. "Means for registering transport routes for vehicles that regularly use expressways" refers to a system that has the function of inputting and saving transport routes and operation schedule information used daily by vehicles that regularly use expressways.

[1426] 3. "Means for shippers to register their cargo" refers to a system that allows shippers to input and save information about the cargo they wish to transport (weight, dimensions, contents, origin, destination, etc.).

[1427] 4. "Generative AI means" is an artificial intelligence that automatically analyzes the optimal transport route and vehicle based on registered transport route and cargo information.

[1428] 5. "Means of notification" refers to a system that communicates important information to users, such as the optimal transportation route analyzed by the generating AI and the unlock code.

[1429] 6. "Means for managing the deposit and receipt of luggage" means a system that properly manages the deposit and receipt of luggage by shippers and regular users during transportation and at the destination.

[1430] 7. "Means of entrusting final delivery to a local taxi company or ride-sharing company" refers to a system in which a local taxi company or ride-sharing company is requested to make the final delivery at the destination of the package.

[1431] 8. The "Emotion Engine" is an artificial intelligence that analyzes the emotional state of users and delivery personnel and optimizes the content and timing of notifications based on the results.

[1432] 9. "Food delivery order management means" refers to a system that inputs and saves meal order information from users and manages the progress of orders from cooking to delivery.

[1433] 10. "Means for preparing food for food delivery" refers to a system in which restaurants input and save the food preparation status and completion time.

[1434] 11. "Means for managing delivery personnel's driving routes in food delivery" refers to a system that manages delivery personnel's driving routes, available time, and working conditions, and provides optimal delivery routes.

[1435] The food delivery system for realizing the invention consists of the following components: Each component plays a specific role and works together to ensure the smooth functioning of the entire system.

[1436] 1. Database Management Methods

[1437] A database is installed on the server, where transport route information, package information, user information, delivery person information, etc. are stored in a unified manner. A relational database management system (RDBMS) such as MySQL can be used as database management software. Data can be added, updated, and deleted efficiently through this database.

[1438] 2. Transportation route registration method

[1439] The terminal provides an interface for registering transportation routes for vehicles that regularly use the expressway. Users (drivers) input their own driving schedules and routes into the terminal, and the information is sent to the server and stored in a database.

[1440] 3. Baggage registration method

[1441] Using the terminal, the shipper inputs information about the cargo they wish to transport (weight, dimensions, contents, origin, destination, etc.), which is then stored in a database via the server.

[1442] 4. Generation AI means

[1443] The server is equipped with a generative AI that analyzes the optimal transport route and vehicle based on registered transport route and cargo information. TensorFlow and PyTorch can be used for the generative AI model. The AI ​​model analyzes large amounts of data and proposes efficient routes and vehicles.

[1444] 5. Means of notification

[1445] Based on the analysis results of the generating AI, the server notifies the user of important information such as transportation routes and unlock codes. Notification methods include push notifications, SMS, and email. In addition, an emotion engine analyzes the user's emotional state and optimizes the content and timing of notifications.

[1446] 6. Baggage drop-off and collection management methods

[1447] The server manages the drop-off and pick-up of luggage during transport and at destinations. Shippers and regular users drop off or pick up luggage at designated locations, allowing for real-time processing.

[1448] 7. Final delivery consignment method

[1449] At the destination, the server requests a local taxi company or ride-sharing company to make the final delivery, ensuring that the package reaches its final destination efficiently.

[1450] 8. Emotional Engine Means

[1451] The server is equipped with an emotion engine that analyzes the emotional state of the user and delivery person and optimizes the content and timing of notifications based on the results. This emotion engine can utilize emotion analysis services such as IBM Watson.

[1452] 9. Food delivery management measures

[1453] The terminal and server manage food delivery orders, food preparation, and delivery driver routes. Users input orders through the application, and restaurants input the food preparation status. Delivery driver routes are optimized using generative AI.

[1454] By integrating these methods, an efficient and user-friendly logistics and food delivery system can be realized. For example, when a user orders a pizza, the order information is stored in a database, and the optimal route from the restaurant to the delivery person is analyzed by a generative AI. The emotional state of the delivery person is analyzed by an emotion engine, and a notification is sent to the user.

[1455] An example of a prompt sentence is "Order ID: 1, Food: Pizza, Location: A, Status: Cooking, Delivery Person: ID2, Route: A to B, Emotion: Good."

[1456] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1457] Step 1:

[1458] The user registers package information on the terminal. At this time, the user inputs information such as the package's weight, dimensions, contents, departure point, and arrival point, and sends it from the terminal to the server. The server stores this information in a database. The specific input is package information, and the output is storage in the database.

[1459] Step 2:

[1460] Regular users register their own routes and schedules on their terminals. The driver inputs information such as route, departure and arrival times, and available spaces, and sends it from the terminal to the server. The server stores this information in a database. The specific input is route information, and the output is storage in the database.

[1461] Step 3:

[1462] The server uses a generative AI model to analyze registered cargo information and transport route information. The server retrieves this information from the database and inputs it into the generative AI. The generative AI calculates the optimal transport route and vehicle and generates the results. The specific inputs are cargo information and operating route information, and the output is a proposal for the optimal transport route and vehicle.

[1463] Step 4:

[1464] The server sends notifications to shippers and regular users based on the analysis results. Notification content includes the transport route, SA / PA locations, unlock codes, etc. Furthermore, an emotion engine is used to analyze the user's emotional state to determine the optimal notification timing and content. The specific inputs are the analysis results and emotional state, and the output is the optimized notification content.

[1465] Step 5:

[1466] The user (shipper) arrives at the notified SA / PA and deposits the luggage using a terminal. The server confirms the luggage deposit, records it in the database, and notifies regular users in real time. The specific input is the luggage deposit information, and the output is recording it in the database and notifying them.

[1467] Step 6:

[1468] The user (regular passenger) picks up their luggage at the designated SA / PA and transports it along the route. The server monitors this process in real time and notifies them as necessary. The specific input is the luggage receipt report, and the output is monitoring and notifying the transportation status.

[1469] Step 7:

[1470] The user (regular passenger) leaves their luggage at the SA / PA at their destination and notifies the server. The server confirms that the luggage has arrived at the destination and requests a local taxi company or ride-sharing company to make the final delivery. This completes the delivery procedure to the final destination. The specific input is an arrival report, and the output is a notification of final delivery arrangements.

[1471] Step 8:

[1472] In the case of food delivery, the server manages order information, food preparation status, and delivery routes. When users input orders and restaurants update food preparation status, this information is tracked in a database managed by the server. The generative AI calculates the optimal delivery route and notifies the user. The specific inputs are order information and cooking status, and the output is a notification of the optimal delivery route.

[1473] The above steps will result in an efficient and user-friendly logistics and food delivery system.

[1474] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1475] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1476] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1477] [Fourth embodiment]

[1478] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1479] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1480] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1481] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1482] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1483] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1484] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1485] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1486] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1487] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1488] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1489] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1490] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1491] The present invention realizes efficient logistics through a system that combines a database, a transportation route registration means, a cargo registration means, a generation AI, a notification means, a management means, and a final delivery means. Specific embodiments for carrying out the present invention will be described below.

[1492] 1. The shipper registers the cargo information

[1493] User (shipper):

[1494] Shippers access the system using a dedicated device (such as a smartphone or tablet), enter information about the cargo they wish to leave (weight, dimensions, contents, etc.), and select service areas (SA) or parking areas (PA) at their departure and arrival points.

[1495] server:

[1496] The server provides a screen for accepting registration of cargo information and transportation routes. When the shipper completes the input and presses the send button, the server saves the data in a database.

[1497] 2. Registering transportation routes for regular users

[1498] User (regular user):

[1499] Drivers who regularly use expressways register information such as their route, departure and arrival times, and available spaces in the system.

[1500] server:

[1501] The server stores the information of regular users in a database so that it can be analyzed for use in the next package delivery.

[1502] 3. Generative AI selects optimal routes

[1503] server:

[1504] The generation AI installed on the server analyzes the optimal transport route and vehicle based on the departure and arrival points registered by the shipper and the route information of regular users. The analysis results are used to select the most efficient route and vehicle according to a pre-set algorithm.

[1505] 4. Notification of transportation route and unlock code

[1506] server:

[1507] Based on the analysis results, the server notifies the shipper of the location of the SA / PA where the package should be left and the unlock code. At the same time, it notifies the selected regular user of detailed package information and the designated SA / PA information.

[1508] 5. Baggage drop-off and collection management

[1509] User (shipper):

[1510] The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo.

[1511] server:

[1512] The server notifies the regular user in real time once the baggage has been checked in.

[1513] User (regular user):

[1514] Regular users will receive a notification and collect their luggage at the designated SA / PA, which will then be transported to the destination SA / PA along the route.

[1515] 6. Final Delivery Arrangements

[1516] User (regular user):

[1517] Regular passengers leave their luggage at the SA / PA at their destination and notify the server.

[1518] server:

[1519] The server notifies the local taxi company or ride-sharing company that the package has arrived at the destination service area or parking area. The final delivery person receives the notification and transports the package to its final destination.

[1520] Specific examples

[1521] As a specific example, suppose a shipper, "Mr. A," wants to deliver a product from Tokyo to Osaka. Mr. A enters product information on his terminal, selects an SA in Tokyo and an SA in Osaka, and sends the information to the server. Since information about regular user "Mr. B," who drives from Tokyo to Osaka every Monday, is already registered, the server uses generation AI to analyze Mr. B's route and notifies Mr. A based on the results. Mr. A leaves his luggage at the designated SA in Tokyo, and Mr. B picks it up and transports it to the SA in Osaka. Mr. B leaves his luggage at the SA in Osaka, and the server notifies the local taxi company, which then makes the final delivery. This series of steps results in efficient transportation and cost reductions.

[1522] The above is a specific embodiment for carrying out the present invention. Such a system will improve the efficiency of logistics and reduce costs, and will be an effective measure against the 2024 problem.

[1523] The processing flow will be explained below.

[1524] Step 1:

[1525] The user (shipper) logs into the system using a dedicated terminal, enters the cargo information (weight, dimensions, contents, origin, destination) and clicks the send button.

[1526] Step 2:

[1527] The terminal transmits the input package information to the server.

[1528] Step 3:

[1529] The server receives the package information, stores it in the database, and returns a message to the user confirming that the information has been saved.

[1530] Step 4:

[1531] The user (regular user) inputs their route and available space information from a dedicated terminal and sends it.

[1532] Step 5:

[1533] The terminal transmits the regular user's route and available space information to the server.

[1534] Step 6:

[1535] The server receives the route information of regular users and stores it in a database.

[1536] Step 7:

[1537] The server begins analysis using generation AI based on cargo information from shippers and route information from regular users.

[1538] Step 8:

[1539] The generation AI selects the optimal transport route and corresponding vehicle.

[1540] Step 9:

[1541] Based on the analysis results, the server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code.

[1542] Step 10:

[1543] The server also notifies the selected regular users of the package information and the designated SA / PA information.

[1544] Step 11:

[1545] The user (shipper) brings the cargo to the designated SA / PA, unlocks the container using the unlock code provided by the server, and deposits the cargo.

[1546] Step 12:

[1547] The terminal reports the completion of baggage deposit to the server.

[1548] Step 13:

[1549] The server notifies the regular user in real time that the baggage has been confirmed.

[1550] Step 14:

[1551] The user (regular user) receives the notification and collects the package at the designated SA / PA.

[1552] Step 15:

[1553] The user (regular user) transports the luggage to the destination service area / parking area along the route.

[1554] Step 16:

[1555] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[1556] Step 17:

[1557] The server notifies local taxi companies and ride-sharing companies that the luggage has arrived at the arrival service area / parking area.

[1558] Step 18:

[1559] The user (a representative of a taxi company or ride-sharing company) receives a notification and goes to the SA / PA at the destination to pick up the luggage.

[1560] Step 19:

[1561] The user (a taxi company or ride-sharing company employee) transports the received package to its final destination and reports delivery completion to the server.

[1562] The above is the processing flow from depositing luggage to final delivery using the system of the present invention.

[1563] Example 1

[1564] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1565] In the logistics industry, selecting efficient transportation routes and ensuring smooth delivery of cargo both during transport and at the final destination are important issues. In particular, integrating information on multiple shippers and regular operators to select the optimal route is difficult, and arranging final delivery is also labor-intensive. Therefore, there is a need for a system that can efficiently manage the entire process, from cargo registration and transportation route selection to final delivery.

[1566] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1567] In this invention, the server includes a means for managing a database, a means for registering the routes of vehicles that operate regularly, a means for the shipper to register cargo, a generation AI means for analyzing the optimal transport route and vehicle based on the registered route and cargo information, a means for notifying the transport route and unlock code based on the analysis results, a means for managing the deposit and receipt of cargo at designated service areas or parking areas, and a means for coordinating with a local transportation service or shared driving service to entrust final delivery. This enables the selection of an efficient transport route, smooth delivery of cargo, and arrangement of final delivery.

[1568] The "means for managing the database" is a system for storing information on shippers and regular users, cargo information, and route information, and for retrieving and managing the information as needed.

[1569] "Means for registering the routes of vehicles that operate regularly" refers to methods or mechanisms for registering detailed information such as the routes, departure and arrival times, and available spaces of vehicles that operate regularly on expressways and public roads in the system.

[1570] "Means for a shipper to register a package" refers to a method or mechanism for a shipper to input and register information about the weight, dimensions, contents, origin, and destination of the package they wish to deposit into the system.

[1571] "Generative AI means" is an artificial intelligence technology that analyzes the optimal transport route and vehicle based on input cargo information and operation route information, and generates an efficient delivery plan.

[1572] "Means of notification" refers to a method or mechanism for providing information such as the transport route and unlock code to the shipper, and for notifying regular users of detailed information about their packages.

[1573] "Means for managing the deposit and receipt of packages at designated service or parking areas" means a system or method for managing and verifying the process by which shippers deposit packages and regular users collect packages at designated locations.

[1574] "Means of coordinating final delivery with a local transportation service or shared driving service" refers to a method or mechanism for coordinating with a local taxi company or ride-sharing company to arrange for the delivery of a package to its final destination.

[1575] The present invention is a logistics system that combines a database, a route registration means, a cargo registration means, a generation AI, a notification means, a management means, and a final delivery means. This enables efficient logistics. Specific embodiments for implementing the present invention will be described below.

[1576] 1. The shipper registers the cargo information

[1577] Users (shippers) access the system using a dedicated terminal (for example, a smartphone or tablet). The shipper enters information about the luggage they wish to store (weight, dimensions, contents, etc.) and selects the service area (SA) or parking area (PA) at their departure and arrival points. Specifically, the shipper operates their smartphone and enters their login ID and password to log into the system. They then enter detailed information about the luggage they wish to store and send it to the server.

[1578] The server provides a screen for accepting the registration of cargo information and operation routes, and stores the data sent from the shipper in a database. After the cargo information registration is complete, the server sends a confirmation email to the shipper to notify them that the cargo information has been successfully registered.

[1579] Example prompt:

[1580] "I would like to send a package from Tokyo to Osaka. The product information is as follows: weight 10kg, dimensions 50cm x 30cm x 20cm, contents: electronic product."

[1581] 2. Registering route information for regular users

[1582] Users (regular users) use dedicated terminals to register the route information of their vehicles that they operate regularly in the system. For example, a driver who regularly uses the expressway can enter detailed information such as their route, departure and arrival times, and available spaces.

[1583] The server stores the route information sent by the regular users in a database so that it can be used for the next package delivery. The server manages this information for use in analysis.

[1584] Example prompt:

[1585] "The bus runs from Tokyo to Osaka every Monday. It departs at 8:00 AM and arrives at 4:00 PM. There is space inside the bus for 50 kg of weight."

[1586] 3. Generative AI selects optimal routes

[1587] The server (generating AI) analyzes the optimal transport route and vehicle based on information registered by shippers and route information of regular users. The generating AI then selects the most efficient route based on an algorithm.

[1588] The server retrieves cargo information and route information from the database and analyzes it with the generation AI to create an optimal transportation plan. For example, the AI ​​analyzes how to optimally incorporate the shipper's cargo into the regular user's route.

[1589] Example prompt:

[1590] "Extract information about shippers and regular users from the database and use the AI ​​to select the optimal transport route and vehicle."

[1591] 4. Notification of transportation route and unlock code

[1592] Based on the analysis results, the server notifies the shipper of the location of the SA / PA where the package should be left and the unlock code. At the same time, it notifies the regular user of the package's detailed information and the designated SA / PA.

[1593] The server sends the shipper the location of the specified SA and the unlock code by email, and notifies the regular user of the package details and SA information.

[1594] Example prompt:

[1595] "Please inform the shipper of the SA to be deposited and the unlock code, and inform the regular user of the package details and SA information."

[1596] 5. Baggage drop-off and collection management

[1597] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code, and deposits the cargo.

[1598] The server confirms the baggage deposit and notifies the regular user of the information in real time.

[1599] The user (regular passenger) picks up the luggage at the designated SA / PA and transports it to the SA / PA at the destination along the route.

[1600] Example prompt:

[1601] "Instruct the shipper to use the unlock code to unlock the container and deposit the cargo. Notify the regular customer that the cargo will be deposited."

[1602] 6. Final Delivery Arrangements

[1603] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[1604] The server notifies the local transportation service or shared driving service that the package has arrived at the destination service area / parking area, and the final delivery person transports the package to the final destination.

[1605] Examples:

[1606] If Person A wants to send a product from Tokyo to Osaka, he or she uses a smartphone to enter the product information and send it to the server. Since the system is registered with information that Regular User B travels from Tokyo to Osaka every Monday, the server uses generation AI to analyze Person B's route and notifies Person A. Person A leaves the package at a designated service area in Tokyo, and Person B transports it to the service area in Osaka. The server then notifies the local transportation service, and the package is delivered to its final destination.

[1607] This series of steps and methods results in efficient transportation and cost reduction.

[1608] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1609] Step 1:

[1610] The user (shipper) registers the package information

[1611] Input: The shipper logs into the system using a terminal (smartphone or tablet) and enters the cargo information (weight, dimensions, contents, SA / PA of departure and arrival points).

[1612] The server stores the data

[1613] Output: The server receives the shipment information, stores it in a database, and sends a notification to the shipper confirming that the shipment information was successfully registered.

[1614] Specific operation: The shipper operates a smartphone, enters their login ID and password to log in to the system, then enters detailed information about the shipment and presses the send button. The server saves the data in a database and sends the shipper a confirmation email stating that the shipment information has been successfully registered.

[1615] Step 2:

[1616] The user (regular user) registers route information

[1617] Input: Regular passengers use the terminal to input details such as their route, departure and arrival times, and available spaces.

[1618] The server stores the data

[1619] Output: The server receives the route information and stores it in a database, ready for analysis so that it can be used for the next package delivery.

[1620] Specific operation: A regular user sets a route from Tokyo to Osaka every Monday, inputs the departure time as 8:00 AM, the arrival time as 4:00 PM, and the available space as 50 kg, and presses the send button. The server stores this information in the database.

[1621] Step 3:

[1622] Optimal route selection using generative AI

[1623] Input: The server retrieves package information and route information from the database.

[1624] The server (generative AI) analyzes the data

[1625] Output: The generation AI analyzes the optimal transport route and vehicle based on the input information and generates the results.

[1626] Specific operation: The server obtains the shipper's cargo information and the regular user's route information and passes it to the generation AI. The generation AI analyzes this information and selects the optimal transport route and vehicle based on an algorithm. As a result of the analysis, the most efficient route is generated.

[1627] Step 4:

[1628] Transport route and unlock code notification

[1629] Input: Analysis results of the generating AI

[1630] The server sends a notification

[1631] Output: The server notifies the shipper of the location and unlock code of the specified SA / PA, and notifies the subscriber of the package details.

[1632] Specific operation: Based on the analysis results of the generated AI, the server sends the shipper the location of a service area in Tokyo and the unlock code via email, and notifies regular user B of detailed information about the package and the information about the specified service area.

[1633] Step 5:

[1634] The shipper deposits the cargo at the designated SA / PA.

[1635] Input: Unlock code received by the shipper from the server

[1636] The server confirms the deposit

[1637] Output: The server confirms that the bag has been dropped off and notifies the subscriber in real time.

[1638] Specific operation: Shipper A arrives at the designated SA, enters the unlock code to unlock the container, and deposits his / her luggage. The server receives this information and sends a notification to regular user B that "the luggage has been deposited."

[1639] Step 6:

[1640] Regular passengers receive their packages

[1641] Input: Server notification

[1642] Regular users carry luggage

[1643] Output: Regular passengers collect their luggage at the designated service area and transport it to the destination service area / parking area along the route.

[1644] Specific operation: Regular user B picks up his luggage at a service area in Tokyo and transports it to a service area in Osaka Prefecture.

[1645] Step 7:

[1646] Final delivery arrangements

[1647] Input: Arrival notification from regular user

[1648] The server arranges final delivery

[1649] Output: The server notifies the local transportation service or shared driving service that the package has arrived at the destination SA and arranges for final delivery.

[1650] Specific operation: Regular user B arrives at a service area in Osaka Prefecture, deposits his / her luggage in the designated container, and notifies the server. The server then notifies the local transportation service of this information and arranges for delivery to the final destination.

[1651] The above is the specific flow of the system's program processing, which will enable efficient logistics.

[1652] (Application example 1)

[1653] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1654] Conventional logistics systems make it difficult to select efficient transportation routes and manage cargo, with a particular problem being the lack of coordination between shippers and transport personnel. Efficiency in final delivery of cargo and integrated management with local transportation service providers are also issues. For these reasons, a system that can improve the efficiency of the entire logistics system and deliver cargo quickly and reliably is needed.

[1655] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1656] In this invention, the server includes a database management unit, a unit for registering the transport routes of vehicles that regularly use expressways, and a unit for shippers to register their cargo. This allows the AI ​​to analyze the optimal transport route and vehicle based on cargo information from shippers and transport route information from regular users, and to provide appropriate notifications to shippers and transport personnel. Furthermore, notifications and cargo management can be achieved using smart devices, and final delivery arrangements with local transportation service providers can be smoothly made, thereby achieving overall logistics efficiency.

[1657] The "means of managing the database" is a system that centrally stores and manages information such as cargo information, transport route information, and user information.

[1658] "Means for registering transportation routes of vehicles that regularly use expressways" refers to an interface that allows drivers of vehicles that regularly travel the same route to input and save their own driving route information into the system.

[1659] "Means for shippers to register their cargo" refers to an interface that allows shippers to input cargo information (weight, dimensions, contents, departure point, arrival point, etc.) and send it to the system.

[1660] "Generative AI means" is an artificial intelligence technology that automatically analyzes and selects the optimal transport route and vehicle based on registered transport route and cargo information.

[1661] The "means of notification" is a system that notifies the shipper or transportation manager of information such as the transportation route and unlock code in a timely manner based on the analysis results.

[1662] "Means for managing the dropping off and picking up of luggage en route and at the destination" refers to a system that manages the procedures for dropping off and picking up luggage at designated service areas and parking areas.

[1663] "Means of entrusting final delivery to local mobility service providers" is a system that notifies and requests local taxi companies, ride-sharing companies, etc. to make final delivery at the destination.

[1664] "Means for registering luggage and displaying and notifying route analysis results using a smart device" refers to an application that provides functions such as luggage registration, displaying optimal routes, and notifying using a mobile device such as a smartphone or tablet.

[1665] The following describes the embodiments of the present invention. The system configuration described below is based on the technical elements described in the claims and includes specific implementation methods.

[1666] System Configuration

[1667] This system achieves efficient logistics by using a database, transportation route registration means, cargo registration means, generation AI, notification means, management means, final delivery means, and smart devices.

[1668] Databases and Servers

[1669] The database centrally manages information on cargo, transport routes, and regular users, and uses a relational database such as SQLite. The server is built using Flask (a Python web framework).

[1670] Shipper's registration of cargo information

[1671] Shippers use a smartphone or tablet to access a dedicated application and enter package information, including weight, dimensions, contents, origin, and destination, which is then sent to a server and stored in a database.

[1672] Registering transportation routes for regular users

[1673] Drivers who regularly use expressways input information such as their route, departure and arrival times, and available spaces into the application and send it to the server, where it is also stored in the database.

[1674] Optimal route selection using generative AI

[1675] The server uses the AI ​​to analyze the optimal transport route and vehicle based on the registered cargo information and route information of regular users. The AI ​​uses a pre-set algorithm to select the most efficient route and vehicle. The analysis results are stored on the server.

[1676] Notification of information by notification means

[1677] The server then notifies shippers and regular users of the necessary information based on the analysis results of the generative AI. The notification content includes the location of the designated service area (SA), parking area (PA), and unlock code. Notifications are sent in real time using a notification system such as Firebase Cloud Messaging (FCM).

[1678] Managing baggage drop-off and collection

[1679] The shipper arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the cargo. Once the server confirms the deposit of the cargo, it notifies the regular user in real time. The regular user receives the notification and collects the cargo at the designated SA / PA. This information is recorded in the database.

[1680] Final delivery arrangements

[1681] A regular user leaves their luggage at the SA / PA at their destination and notifies the server. The server then notifies the local transportation service provider (e.g., a taxi company or ride-sharing company) that the luggage has arrived at the SA / PA. The final delivery person is notified and transports the luggage to its final destination. This information is also recorded in the database.

[1682] Specific examples

[1683] For example, if a shipper wants to deliver a product from Tokyo to Osaka, the shipper enters the product information on their terminal, selects a service area in Tokyo and another in Osaka, and sends it to the server. Since a regular user's driving information from Tokyo to Osaka every Monday is already registered, the server uses the generation AI to analyze the regular user's route and notifies the shipper based on the results. The shipper then leaves the package at the designated service area in Tokyo, where the regular user picks it up and transports it to the service area in Osaka. The server then notifies the local transportation service provider, and the final delivery is made.

[1684] Prompt Sentence Examples

[1685] Please register your luggage information. Enter the weight, dimensions, contents, departure and arrival points, and submit. We will then determine the best route for you and provide you with an unlock code. Follow the instructions to drop off or collect your luggage at the SA / PA.

[1686] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1687] Step 1:

[1688] Registering luggage information

[1689] The user (shipper) accesses the application using a smartphone or tablet and enters cargo information such as weight, dimensions, contents, departure point, and arrival point. This input data is sent to the server and saved in a database. The server registers the cargo information in the database and verifies that the input information has been saved correctly.

[1690] Step 2:

[1691] Registering transport routes

[1692] Users (regular passengers) enter information such as their route, departure and arrival times, and available spaces into the application. This transport route information is sent to the server and stored in a database. The server then registers the regular passenger information in the database and analyzes it for use in the next package delivery.

[1693] Step 3:

[1694] Optimal route selection using generative AI

[1695] The server uses generative AI to analyze the optimal transport route and vehicle based on the cargo information and transport route information stored in the database. Here, the generative AI model inputs weight, dimensions, departure point, arrival point, and available vehicle route information, and outputs the most efficient route and vehicle. The server stores the generative AI's analysis results.

[1696] Step 4:

[1697] Notification Implementation

[1698] The server then sends information to shippers and regular users based on the analysis results of the AI. The notification includes the location of the specified SA / PA and the unlock code. The server sends the notification in real time using a notification system such as Firebase Cloud Messaging (FCM).

[1699] Step 5:

[1700] Checked baggage

[1701] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code received from the server, and deposits the luggage. The terminal inputs the unlock code to unlock the container and deposits the luggage. Once the server confirms the deposit of the luggage, it records it in the database and then notifies the regular user.

[1702] Step 6:

[1703] Picking up your luggage

[1704] The user (regular user) receives the notification and picks up the package at the designated SA / PA. After the server confirms that the regular user has picked up the package, it saves the data in the database. The regular user then transports the package to the destination SA / PA according to the route.

[1705] Step 7:

[1706] Final delivery arrangements

[1707] A regular user leaves their luggage at the SA / PA at their destination and notifies the server. The server records the arrival of the luggage at the SA / PA in the database and notifies the local mobility service provider. The final delivery person (mobility service provider) receives the notification and transports the luggage to its final destination.

[1708] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1709] The present invention realizes efficient logistics and an improved user experience through a system that combines a database, a transportation route registration means, a package registration means, a generation AI, a notification means, a management means, a final delivery means, and an emotion engine. Specific embodiments for carrying out the present invention will be described below.

[1710] 1. The shipper registers the cargo information

[1711] User (shipper):

[1712] Shippers access the system using a dedicated device (such as a smartphone or tablet), enter information about the cargo they wish to leave (weight, dimensions, contents, etc.), and select service areas (SA) or parking areas (PA) at their departure and arrival points.

[1713] server:

[1714] The server provides a screen for accepting registration of cargo information and transportation routes. When the shipper completes the input and presses the send button, the server saves the data in a database. In addition, the server sends video and audio data acquired from the terminal to the emotion engine to recognize the shipper's emotions.

[1715] 2. Registering transportation routes for regular users

[1716] User (regular user):

[1717] Drivers who regularly use expressways register information such as their route, departure and arrival times, and available spaces in the system.

[1718] server:

[1719] The server stores the information of regular users in a database, and at the same time, recognizes the emotions of regular users and records them in the database.

[1720] 3. Generative AI selects optimal routes

[1721] server:

[1722] The generation AI implemented on the server analyzes the optimal transport route and vehicle based on the departure and arrival points registered by the shipper and the route information of regular users.

[1723] Emotion Engine:

[1724] Based on the analysis results of the generation AI, the system also takes into account the emotional information of shippers and regular users to determine the optimal content and timing of notifications.

[1725] 4. Notification of transportation route and unlock code

[1726] server:

[1727] Based on the analysis results, the server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code. At this time, it uses an emotion engine to optimize the content of the notification and provides the information in a format that is easy for the shipper to understand. In addition, it notifies selected regular users of the cargo information and the designated SA / PA information.

[1728] 5. Baggage drop-off and collection management

[1729] User (shipper):

[1730] When the shipper arrives at the designated SA / PA, they unlock the container using the unlock code received from the server and deposit their cargo. At the same time, the emotion engine monitors the shipper's emotional state and provides support if there are any problems.

[1731] server:

[1732] Once the baggage has been checked in, the server notifies the regular user in real time, with the content of the notification also optimized by the emotion engine.

[1733] User (regular user):

[1734] Regular users will receive a notification and collect their luggage at the designated SA / PA, which will then be transported to the destination SA / PA along the route.

[1735] 6. Final Delivery Arrangements

[1736] User (regular user):

[1737] Regular passengers leave their luggage at the SA / PA at their destination and notify the server.

[1738] server:

[1739] The server notifies local taxi companies and ride-sharing companies that the package has arrived at the destination service area or parking area.The emotion engine also monitors the emotional state of the final delivery person, helping to ensure efficient delivery.

[1740] Specific examples

[1741] As a specific example, suppose shipper "Mr. A" wants to transport goods from Tokyo to Osaka. When Mr. A enters and sends the product information on his terminal, the emotion engine also analyzes Mr. A's situation. Based on the registration information of regular user "Mr. B," the generation AI analyzes the optimal route and notifies him. When Mr. A leaves the goods at the designated service area in Tokyo, the emotion engine also checks for any problems, and if it detects any signs of impatience or anxiety, it displays a support message. When regular user B delivers the goods to the service area in Osaka, the server notifies the local taxi company, and the taxi company, with the support of the emotion engine, delivers the goods to the final destination. In this way, by incorporating the emotion engine throughout the system, an improved user experience and efficient logistics are achieved.

[1742] The above is a detailed embodiment of the system of the present invention, from baggage deposit to final delivery. By combining it with an emotion engine, an even more user-friendly logistics system can be constructed.

[1743] The processing flow will be explained below.

[1744] Step 1:

[1745] The user (shipper) logs into the system using a dedicated terminal. They enter the cargo information (weight, dimensions, contents, departure point, arrival point) and click the send button. The terminal then sends the entered cargo information to the server.

[1746] Step 2:

[1747] The server receives the package information and stores it in a database. It also sends video and audio data acquired from the shipper's device to the emotion engine, which recognizes the shipper's emotions.

[1748] Step 3:

[1749] The emotion engine analyzes the shipper's emotional information and sends feedback to the server.

[1750] Step 4:

[1751] The user (regular user) inputs and transmits their own route and available space information from a dedicated terminal. The terminal then transmits the route and available space information of the regular user to the server.

[1752] Step 5:

[1753] The server receives the route information of regular users and stores it in a database. It also acquires the emotion information of regular users and sends it to the emotion engine.

[1754] Step 6:

[1755] The emotion engine analyzes the emotion information of regular users and sends feedback to the server.

[1756] Step 7:

[1757] The server uses the AI ​​to analyze the cargo information from the shipper and the route information from the regular users. The AI ​​then selects the optimal transport route and the corresponding vehicle.

[1758] Step 8:

[1759] The emotion engine determines the optimal notification content and timing based on the analysis results of the generation AI and emotional information.

[1760] Step 9:

[1761] The server notifies the shipper of the optimal transport route, the location of SA / PA, and the unlock code. At this time, the notification content is optimized using an emotion engine. In addition, selected regular users are notified of the cargo information and the designated SA / PA information.

[1762] Step 10:

[1763] The user (shipper) arrives at the designated SA / PA, unlocks the container using the unlock code provided by the server, and deposits the cargo. At the same time, the emotion engine monitors the shipper's emotions, and displays a support message if there are any concerns or problems.

[1764] Step 11:

[1765] The terminal reports the completion of baggage deposit to the server.

[1766] Step 12:

[1767] The server notifies the regular user in real time that their luggage has been checked in. The content of the notification is also optimized by the emotion engine.

[1768] Step 13:

[1769] The user (regular user) receives the notification and picks up the luggage at the designated SA / PA. The luggage is then transported to the destination SA / PA along the route.

[1770] Step 14:

[1771] An emotion engine monitors the emotional state of subscribers and provides support when needed.

[1772] Step 15:

[1773] The user (regular passenger) leaves his / her luggage at the SA / PA at the destination and notifies the server.

[1774] Step 16:

[1775] The server notifies local taxi companies and ride-sharing companies that the package has arrived at the destination service area or parking area. The emotion engine also monitors the emotional state of the final delivery person and provides support to ensure efficient delivery.

[1776] Step 17:

[1777] The user (a representative of a taxi company or ride-sharing company) receives a notification and goes to the SA / PA at the destination to pick up the luggage.

[1778] Step 18:

[1779] The user (a taxi company or ride-sharing company employee) transports the received package to its final destination and reports delivery completion to the server.

[1780] Step 19:

[1781] The server notifies the sender that the package has been delivered and sends a thank-you message, which is also optimized by the emotion engine.

[1782] The above is a detailed processing flow from baggage deposit to final delivery using the system of the present invention. By incorporating an emotion engine, an improved user experience and efficient logistics can be achieved.

[1783] Example 2

[1784] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1785] In conventional logistics systems, selecting efficient transportation routes and arranging final deliveries takes a lot of time and effort. Furthermore, notification methods that do not take users' emotions into consideration can cause stress and reduce satisfaction. There is a need to solve these problems and achieve an improved user experience and efficient logistics.

[1786] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1787] In this invention, the server includes a database management unit, a registering unit for vehicle transport routes that regularly use expressways, a shipper's cargo registration unit, a generating AI unit that analyzes the optimal transport route and vehicle based on the registered transport route and cargo information, an emotion engine unit that analyzes emotion information and optimizes the content and timing of notifications, a unit that notifies the user of the transport route, unlock code, etc. based on the analysis results, a unit that monitors the user's emotional state and provides support messages as needed, a unit that manages the drop-off and receipt of cargo during transport and at the destination, and a unit that entrusts final delivery to a local transport service company. This enables efficient transport route selection and user-friendly notifications, improving the efficiency of the overall logistics process and user satisfaction.

[1788] "Means for managing a database" refers to software and hardware for efficiently storing, searching, and updating cargo information, transportation route information, etc.

[1789] "Means for registering transport routes of vehicles that regularly use expressways" refers to interfaces and tools for inputting and registering the operating routes and schedule information of vehicles that frequently use expressways into the system.

[1790] "Means for shippers to register their shipments" refers to the interfaces and tools that shippers use to enter detailed information about their shipments and register them in the system.

[1791] "Generative AI means" refers to artificial intelligence algorithms and systems that automatically analyze and select the optimal transport route and vehicle based on registered cargo information and transport route information.

[1792] "Emotion engine means" refers to software or hardware that analyzes the user's emotional state from facial expressions and voice data and optimizes the content and timing of notifications.

[1793] "Means for notifying transport routes, unlock codes, etc." refers to systems and services for notifying shippers and regular users of information on transport routes and unlock codes based on the analysis results.

[1794] "Means for monitoring the user's emotional state and providing a supportive message as needed" refers to the function of the system to monitor the user's emotional state in real time and display or send a supportive message when deemed necessary.

[1795] "Measures for managing the deposit and collection of baggage en route and at the destination" refers to the systems and protocols used to manage the smooth deposit and collection of baggage.

[1796] "Means of entrusting final delivery to a local transportation service company" refers to a system in which, in order to deliver cargo that has arrived at the destination, the company cooperates with a local transportation service company such as a taxi company or ride-sharing company and entrusts the work to that company.

[1797] The present invention is a system that realizes efficient logistics and an improved user experience by combining a database, a transportation route registration means, a parcel registration means, a generation AI, a notification means, a management means, a final delivery means, and an emotion engine. Specific embodiments for carrying out the present invention will be described below.

[1798] 1. The shipper registers the cargo information

[1799] User (shipper):

[1800] Shippers access the system by launching a dedicated app on their smartphones, tablets, or other devices. They then enter the weight, dimensions, and contents of the package into a form on the screen, as well as the service area (SA) or parking area (PA) of the departure and arrival points. For example, they might enter, "I want to deliver from a service area in Shibuya Ward, Tokyo to a parking area in Umeda, Osaka."

[1801] server:

[1802] The server receives the package information sent from the terminal and stores it in the corresponding database. At the same time, it sends the collected video and audio data to the emotion engine to analyze the sender's emotions. In this case, the specific hardware and software used are Amazon Web Services (AWS) and MySQL.

[1803] 2. Registering transportation routes for regular users

[1804] User (regular user):

[1805] Drivers who regularly use the expressway access the system using their smartphones or tablets. Drivers input information such as their route, departure and arrival times, and available space in the vehicle. They also input detailed schedules, such as "I'll drive from Tokyo to Osaka every Monday."

[1806] server:

[1807] The server receives route information sent from the terminal and stores it in a database. It also sends video and audio data to an emotion engine to analyze the emotions of regular passengers.

[1808] 3. Optimal route selection using generative AI

[1809] server:

[1810] The server retrieves information about shippers and regular users from the database and sends it to the generation AI. This generation AI analyzes the optimal transport route and vehicle based on the registered departure and arrival points and the regular user's route information. In this case, OpenAI's GPT-4 is used.

[1811] Emotion Engine:

[1812] The emotion engine analyzes the emotional information of shippers and regular users and integrates it with the analysis results of the generation AI. This determines the optimal notification timing and content, taking into account their emotional state. The emotion engine uses Affectiva Emotion AI and other technologies.

[1813] 4. Notification of transportation route and unlock code

[1814] server:

[1815] The server notifies shippers and regular users based on the analysis results of the generation AI and the emotion engine. Shippers are provided with the optimal transport route, the location of SA / PA, and the unlock code. Regular users are also notified of their cargo information and the designated SA / PA information.

[1816] 5. Baggage drop-off and collection management

[1817] User (shipper):

[1818] When the shipper arrives at the designated SA / PA, they unlock the container using the unlock code received from the server and deposit their cargo. At the same time, the emotion engine monitors the shipper's emotional state and displays a supportive message if it detects impatience or anxiety.

[1819] server:

[1820] Once the baggage has been checked in, the server notifies the regular user in real time, and the content of this notification is also optimized by the emotion engine.

[1821] User (regular user):

[1822] Regular users will receive a notification, collect their luggage at the designated SA / PA, and then follow the route to transport their luggage to the SA / PA at their destination.

[1823] 6. Final Delivery Arrangements

[1824] User (regular user):

[1825] The regular passenger arrives at the SA / PA at the destination and leaves his / her luggage. This information is notified to the server.

[1826] server:

[1827] The server confirms the arrival of the package and notifies the local taxi or ride-sharing company, which then picks up the package and delivers it to its final destination. During this process, the emotion engine monitors the emotional state of the final delivery person, helping to ensure efficient delivery.

[1828] Specific examples

[1829] A shipper, "Mr. A," uses a dedicated app to enter, "I want to transport goods from Tokyo to Osaka. I'm in a hurry, but I want it to be completed without any problems." The server receives and stores the package information and emotion data. A regular user, "Mr. B," registers a route from Tokyo to Osaka every Monday. The server stores this information in a database and analyzes the emotion data. The generative AI determines the optimal transport route and integrates it with the emotion engine. Mr. A is notified of the optimal transport route and unlock code, and Mr. B is also notified of information about picking up the package. Mr. A leaves his package at a designated service area in Tokyo, and if there are any problems, the emotion engine displays a support message. When Mr. B delivers his package to the service area in Osaka, the server notifies the taxi company, and with the support of the emotion engine, the package is delivered to its final destination.

[1830] This will enable efficient logistics and an improved user experience.

[1831] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1832] Step 1:

[1833] The shipper registers the cargo information

[1834] Input: The user (shipper) enters cargo information (weight, dimensions, contents, SA / PA at departure and arrival points) using a smartphone or tablet.

[1835] Specific operation: The sender launches the dedicated app and enters detailed information about the package into the form. For example, they might enter, "The product weighs 10 kg, its dimensions are 30 x 30 x 30 cm, its contents are electronic devices, its departure point is a service area in Shibuya Ward, Tokyo, and its arrival point is a parking area in Umeda, Osaka."

[1836] Output: The terminal sends the package information to the server and also prepares the video and audio data captured by the device's camera and microphone.

[1837] Data processing / calculation: The input data is first formatted in the terminal and then serialized for transmission to the server.

[1838] Step 2:

[1839] Receiving and storing information

[1840] Input: Parcel information and video / audio data sent from the terminal.

[1841] Specific operation: The server receives the package information sent from the terminal and stores it in the corresponding database. At the same time, it sends the video and audio data to the emotion engine to analyze the shipper's emotions.

[1842] Output: The package information is stored in the database, and the emotion analysis results are output to the emotion engine.

[1843] Data processing / calculation: Before being stored in the database, the data is checked for integrity, and the emotion engine performs sentiment analysis using machine learning models.

[1844] Step 3:

[1845] Registering transportation routes for regular users

[1846] Input: The user (regular user) inputs information about the route, departure time, arrival time, and available space on the terminal.

[1847] Specific operation: A regular user launches the dedicated app and enters route and schedule information into a form. For example, they enter information such as "Runs from Tokyo to Osaka every Monday, departing at 6:00 AM and arriving at 2:00 PM. Space availability is 50%."

[1848] Ou...

Claims

1. a means for managing the database; a means for registering the transport routes of vehicles that regularly use the expressway; A means by which shippers register their shipments; A generation AI method that analyzes the optimal transport route and vehicle based on registered transport route and cargo information, Based on the analysis results, a means of notifying the user of transport routes, unlock codes, etc. A means of managing the deposit and collection of luggage en route and at destination; A means of outsourcing final delivery to local taxi companies or ride-sharing companies, A system including:

2. The system of claim 1, wherein an unlock code is generated based on an analysis of the package information and the transport route, and the unlock code is notified to the shipper.

3. The system of claim 1, wherein final delivery of the package is performed through collaboration with local taxi companies or ride-sharing companies.

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