KR102608368B1 - Point-to-Point delivery system and server supporting delivery route analysis and optimized vehicle allocation - Google Patents

Abstract

A P2P delivery system and server that supports delivery route analysis and optimized dispatch is provided. The server according to the embodiment includes a delivery reception module that receives delivery information provided from a user device, and includes the delivery information including origin information, destination information, and product information; a data collection module configured to collect high-speed traffic information of at least one middle mile and collect last mile dispatch information of at least one last mile; and a data analysis module including a delivery plan configuration unit that configures a delivery plan using middle mile based on the delivery information and the high-speed traffic information, wherein the delivery plan configuration unit analyzes the delivery information and provides corresponding high-speed traffic information. It includes a middle mile determination model for determining at least one middle mile and a delivery plan establishment model for establishing a delivery plan corresponding to the determined at least one middle mile, wherein the data analysis module includes the configured delivery plan and the Last mile dispatch for the first last mile delivery segment from the origin to the departure terminal of the middle mile and last mile dispatch for the second last mile delivery segment from the arrival terminal of the middle mile to the destination in response to the last mile dispatch information. It further includes a last mile dispatcher who performs at least one of the following.

Description

P2P delivery system and server supporting delivery route analysis and optimized vehicle allocation {Point-to-Point delivery system and server supporting delivery route analysis and optimized vehicle allocation}

The present invention relates to a point-to-point (P2P) delivery system and server that performs delivery using inter-regional high-speed transportation. Specifically, the present invention relates to a P2P delivery system and server that can provide improved P2P delivery by supporting delivery route analysis and optimized vehicle dispatch.

The content described in this section simply provides background information for this embodiment and does not constitute prior art.

With the Fourth Industrial Revolution, the logistics delivery market is actively being digitized and networked to provide efficient and rapid delivery services, and related technology development and research are being actively conducted. These technological developments related to logistics delivery are driving not only the quantitative growth of the logistics delivery market, but also qualitative growth in the delivery of general consumer goods rather than simple cargo delivery.

In particular, as the demand for online transactions and online activities has exploded since COVID-19, competition among various companies in the e-commerce market is intensifying, and the trend to dominate the market through differentiation in logistics delivery is intensifying. .

In particular, early morning delivery and same-day delivery are being provided for quick delivery in the e-commerce market, and companies that dominate the market in this way use self-built fulfillment centers or provide delivery through quick commerce. However, these methods are structured to incur high costs, and companies with insufficient capital or small-scale startups/small business owners cannot follow them, resulting in the problem of falling behind in the delivery service competition.

In addition, cargo delivery services using inter-regional high-speed transportation such as express buses and KTX have been provided in the past, but most of the work is carried out only by hand or simple digital reception. In other words, users who wanted to apply for cargo delivery had to visit the express terminal or train station in person to apply, and users who wanted to receive the delivered cargo had to visit the destination express terminal or train station in person to collect the delivered cargo, which was inconvenient.

In other words, even small-scale companies with insufficient capital, such as startups/small business owners, can provide same-day delivery using high-speed transportation at a low price, and general consumers can also receive same-day delivery using high-speed transportation with a simple operation using the user device. Systems and servers that can proceed are in demand.

The object of the present invention is to provide a P2P delivery system and server that can provide same-day P2P delivery at a low price using high-speed transportation as the middle mile.

In addition, the object of the present invention is to provide a system and server that allows general consumers to perform same-day delivery using high-speed transportation with a simple operation through a user device.

In addition, the object of the present invention is to provide a P2P delivery system and server that can support efficient high-speed transportation P2P delivery by analyzing the optimal delivery route and supporting optimized dispatch.

The objects of the present invention are not limited to the objects mentioned above, and other objects and advantages of the present invention that are not mentioned can be understood by the following description and will be more clearly understood by the examples of the present invention. Additionally, it will be readily apparent that the objects and advantages of the present invention can be realized by the means and combinations thereof indicated in the patent claims.

A server according to some embodiments of the present invention for solving the above problems is a delivery reception module that receives delivery information provided from a user device, and includes the delivery information including origin information, destination information, and product information. ; a data collection module configured to collect high-speed traffic information of at least one middle mile and collect last mile dispatch information of at least one last mile; and a data analysis module including a delivery plan configuration unit that configures a delivery plan using middle mile based on the delivery information and the high-speed traffic information, wherein the delivery plan configuration unit analyzes the delivery information and provides corresponding high-speed traffic information. It includes a middle mile determination model for determining at least one middle mile and a delivery plan establishment model for establishing a delivery plan corresponding to the determined at least one middle mile, wherein the data analysis module includes the configured delivery plan and the Last mile dispatch for the first last mile delivery segment from the origin to the departure terminal of the middle mile and last mile dispatch for the second last mile delivery segment from the arrival terminal of the middle mile to the destination in response to the last mile dispatch information. It further includes a last mile dispatcher who performs at least one of the following.

In addition, the last mile dispatch information includes location information of the corresponding last mile, the last mile dispatch unit sets a priority dispatch area for the last mile based on the location information of the last mile, and the last mile dispatch unit sets the priority dispatch area for the last mile. and perform dispatch for the first last mile delivery section in consideration of the priority dispatch area of the last mile, and perform dispatch for the second last mile delivery section in consideration of the arrival terminal and the priority dispatch area of the last mile. It can be done.

In addition, the data collection module collects location information of the middle mile moving according to the delivery plan, and the last mile dispatch model determines whether the location of the middle mile has passed a critical point, and the middle mile Last mile dispatch for the second last mile delivery section can be performed when arrival at the arrival terminal is predicted to pass the critical point.

In addition, the origin information includes departure location information and delivery reception time, the destination information includes arrival location information, the product information includes product quantity information, and the high-speed traffic information includes the corresponding middle mile It includes operation schedule information and transportation capacity information, and the middle mile judgment model has at least one operation schedule information and product transportation capacity information corresponding to the input origin location information, delivery reception time, destination location information, and product quantity information. It may be a classification model based on a machine learning model trained in advance to determine the middle mile of .

In addition, the delivery plan includes a travel route using middle mile, transportation cost, and transportation time, and further includes a cost payment module for the user to pay the transportation cost, and the cost payment module is configured to use a card or card for each user account. Supports registration of a simple password for account transfer to support payment of the transportation cost through the registered simple password, and the cost payment module configures a cyber money account for each user account to allow the user It may be possible to support payment of the transportation cost through cyber money charged to the cyber money account.

Additionally, the delivery reception module may further include a delivery information analysis model for analyzing the validity of the delivery information.

In addition, the delivery information analysis model is an artificial intelligence-based learning model that is pre-trained to determine the validity of the delivery information by comparing the delivery information and past delivery information, and the delivery reception module is an output result of the delivery information analysis model. If the delivery information is determined to be valid, the configuration of the delivery plan is requested from the data analysis module and the delivery information is stored in the database, and the delivery reception module performs the delivery information analysis model according to the output result of the delivery information analysis model. If the delivery information is determined to be invalid, the user device may be configured to request confirmation of the delivery information.

Additionally, the at least one middle mile may be a wide-area transportation means for moving between different regions based on a terminal, and the last mile may be a transportation means that can freely move within a specific region.

In addition, it further includes a cost settlement module for calculating the transport cost of the last mile and the transport cost of the middle mile, wherein the cost settlement module includes an operation scheduler that organizes the middle mile and last mile operated on a daily basis, The settlement amount is confirmed by verifying the settlement details on a daily basis according to the operation scheduler, and the cost settlement module configures a cyber money account for each middle mile or last mile, and transfers cyber money corresponding to the confirmed settlement amount to the corresponding account. It can be configured to deposit money in .

A P2P delivery system according to some embodiments of the present invention for solving the above problems includes a first user device of a first user; a second user device of a second user to whom the first user delivers goods; a server supporting peer-to-peer delivery that delivers the product to the second user in response to a delivery request sent from the first user device; A middle mile management server that manages the middle mile responsible for middle mile delivery among the P2P delivery; and a last mile management server that manages the last mile responsible for last mile delivery during the P2P delivery, wherein the server is a delivery reception module that receives delivery information provided from the first user device, and converts the delivery information into origin information. , a delivery reception module containing destination information and product information; a data collection module configured to collect high-speed traffic information of at least one middle mile from the middle mile management server and collect last mile dispatch information of at least one last mile from the last mile management server; and a data analysis module including a delivery plan configuration unit that configures a delivery plan using middle mile based on the delivery information and the high-speed traffic information, wherein the delivery plan configuration unit analyzes the delivery information and provides corresponding high-speed traffic information. It includes a middle mile determination model for determining at least one middle mile and a delivery plan establishment model for establishing a delivery plan corresponding to the determined at least one middle mile, wherein the data analysis module includes the configured delivery plan and the Last mile dispatch for the first last mile delivery segment from the origin to the departure terminal of the middle mile and last mile dispatch for the second last mile delivery segment from the arrival terminal of the middle mile to the destination in response to the last mile dispatch information. It may further include a last mile dispatcher that performs at least one of the following.

The P2P delivery system and server according to some embodiments of the present invention can provide same-day P2P delivery at a low price by using high-speed transportation as the middle mile, and general consumers can also provide same-day delivery using high-speed transportation with a simple operation through a user device. We can support you in progress.

Additionally, the P2P delivery system and server according to some embodiments of the present invention can support efficient P2P delivery by analyzing the optimal delivery route and supporting optimized dispatch.

In addition, the P2P delivery system and server according to some embodiments of the present invention performs the dispatch of the last mile departing from the arrival terminal by considering the location of the middle mile, so the operation of the last mile can be performed more efficiently.

In addition, the P2P delivery system and server according to some embodiments of the present invention can provide a system environment that satisfies both users and deliverers by providing various payment methods and reasonable cost settlement methods.

In addition, the P2P delivery system and server according to some embodiments of the present invention may include an automatic reception system that receives delivery information in various ways from the user device and analyzes it, and may receive delivery information to minimize errors due to automatic reception. By determining the effectiveness of , it can support more accurate and efficient delivery reception.

In addition to the above-described content, specific effects of the present invention are described below while explaining specific details for carrying out the invention.

1 is a conceptual diagram illustrating a P2P delivery system according to some embodiments of the present invention.
Figure 2 is an example diagram to explain the progress of the P2P delivery service performed on the server of the present invention.
Figure 3 exemplarily illustrates a user environment provided through a first user's terminal.
Figure 4 is a block diagram showing an exemplary configuration of a server according to some embodiments of the present invention.
Figure 5 is a block diagram showing an exemplary configuration of a delivery reception module according to some embodiments of the present invention.
Figure 6 is an example diagram for explaining the operation of a delivery reception module according to some embodiments of the present invention.
Figure 7 is a block diagram showing an exemplary configuration of a data analysis module according to some embodiments of the present invention.
Figure 8 is an example diagram for explaining the operation of the delivery plan configuration unit according to some embodiments of the present invention.
Figure 9 is an example diagram for explaining the operation of the last mile dispatch unit according to some embodiments of the present invention.
Figure 10 is an example diagram to explain a process in which a dispatch process for a plurality of last miles is performed.
Figure 11 is a flow chart to explain the process in which dispatch to the last mile is performed based on the location information of the middle mile.
Figure 12 is a block diagram for explaining the configuration of a cost payment module according to an embodiment of the present invention.
Figure 13 is a block diagram for explaining the configuration of a cost settlement module according to an embodiment of the present invention.
Figure 14 is an example diagram for explaining the operation of a data collection module according to an embodiment of the present invention.

Terms or words used in this specification and patent claims should not be construed as limited to their general or dictionary meaning. According to the principle that the inventor can define terms or word concepts in order to explain his or her invention in the best way, it should be interpreted with a meaning and concept consistent with the technical idea of the present invention. In addition, the embodiments described in this specification and the configurations shown in the drawings are only one embodiment of the present invention and do not completely represent the technical idea of the present invention, so they cannot be replaced at the time of filing the present application. It should be understood that there may be various equivalents, variations, and applicable examples.

Terms such as first, second, A, and B used in the present specification and claims may be used to describe various components, but the components should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, a first component may be named a second component, and similarly, the second component may also be named a first component without departing from the scope of the present invention. The term 'and/or' includes any of a plurality of related stated items or a combination of a plurality of related stated items.

The terms used in the specification and claims are merely used to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as "include" or "have" should be understood as not precluding the existence or addition possibility of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification. .

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by a person of ordinary skill in the technical field to which the present invention pertains.

Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and unless clearly defined in the present application, should not be interpreted in an ideal or excessively formal sense. No.

In the present invention, an article may refer to an object that a user requests delivery in order to deliver it to another user. In the present invention, goods can be delivered through point-to-point delivery (P2P delivery) from a first point (origin) corresponding to a user to a second point (destination) corresponding to another user.

In the present invention, middle mile refers to a delivery method for delivering a user's goods, but may refer to a delivery method that performs delivery between intermediate points other than the origin or destination. In addition, in the present invention, middle mile may refer to a wide-area means of transportation that moves between different regions based on a middle mile point (terminal), and may be high-speed transportation to ensure same-day delivery or delivery within a short time. It can mean means.

In the present invention, the last mile refers to a delivery means for delivering a user's goods, and may refer to a delivery means that starts delivery at the origin or completes delivery at the destination. In other words, the last mile may refer to a delivery method that delivers from the origin to the middle mile departure terminal or a delivery method that delivers from the middle mile arrival terminal to the destination. Additionally, in the present invention, last mile may refer to a means of transportation that allows free movement within a specific area.

Additionally, each configuration, process, process, or method included in each embodiment of the present invention may be shared within the scope of not being technically contradictory to each other.

Hereinafter, with reference to FIGS. 1 to 14, a P2P delivery system according to some embodiments of the present invention will be described.

1 is a conceptual diagram illustrating a P2P delivery system according to some embodiments of the present invention.

Referring to FIG. 1, the P2P delivery system 10 includes a server 100, a first user device 110, a second user device 120, a middle mile management server 130, a last mile management server 140, It may include a traffic information server 150 and a weather information server 160.

The server 100 may provide a P2P delivery service to a plurality of users that supports P2P delivery between a plurality of users through middle mile and last mile.

The server 100 includes a first user device 110, a second user device 120, a middle mile management server 130, a last mile management server 140, a traffic information server 150, and a weather information server 160. It can be configured to exchange data through a network. Here, the network may include a network based on wired Internet technology, wireless Internet technology, and short-distance communication technology. Wired Internet technology may include, for example, at least one of a local area network (LAN) and a wide area network (WAN).

Wireless Internet technologies include, for example, Wireless LAN (WLAN), DLNA (Digital Living Network Alliance), Wibro (Wireless Broadband), Wimax (World Interoperability for Microwave Access: Wimax), and HSDPA (High Speed Downlink Packet). Access), HSUPA (High Speed Uplink Packet Access), IEEE 802.16, Long Term Evolution (LTE), LTE-A (Long Term Evolution-Advanced), Wireless Mobile Broadband Service (WMBS) and 5G NR (New Radio) technology. However, this embodiment is not limited to this.

Short-range communication technologies include, for example, Bluetooth, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra-Wideband (UWB), ZigBee, and Near Field Communication. At least one of NFC), Ultrasound Communication (USC), Visible Light Communication (VLC), Wi-Fi, Wi-Fi Direct, and 5G NR (New Radio) may include. However, this embodiment is not limited to this.

The first user device 110 is the user device of the first user corresponding to the starting point (origin point) for requesting delivery of goods. The second user device 120 corresponds to the user device of the second user corresponding to the end point (destination) where the product is delivered. The first user and the second user may be individual users, but are not limited thereto, and may also be corporate users.

The server 100 may provide a user environment in which the P2P delivery service can be used through the first user device 110 and the second user device 120. The server 100 may provide a service environment to the user through a service application installed on each of the first user device 110 and the second user device 120. Here, the service application may be a dedicated application for providing a service environment, or a web browsing application for providing through a web page. The first user device 110 and the second user device 120 may be electronic devices that can provide a user environment. Illustratively, the first user device 110 and the second user device 120 may be a smart phone, a type of portable terminal, but the present invention is not limited thereto. The first user device 110 and the second user device 120 use various types of electronic devices such as personal computers (PCs), laptops, tablets, mobile phones, smartphones, and wearable devices (e.g., watch-type terminals). It can be included. Additionally, in some embodiments, the first user device 110 and the second user device 120 may be an electronic device that supports receiving a shipment installed at a terminal in which middle mile is operated, or an electronic device that supports collecting a delivered item. It may be an electronic device, and a P2P delivery service may be available through the provided user environment.

However, the embodiments of the present invention are not limited thereto. The first user and the second user transmit text, voice, or images to the server 100 through a communication means (messenger application, text, or phone, etc.) other than the dedicated application that provides the service environment, and the server 100 You can also use the P2P service provided.

The server 100 is capable of collecting data for the main operation of the P2P service, processing and storing the collected data, and configures a user environment for users to conveniently use the delivery service, so that the first and second user devices It can be provided as (110, 120).

The first user may input delivery information through the first user device 110, and the delivery information may be transmitted to the server 100. Here, delivery information may include origin information, destination information, and product information.

The server 100 may configure a delivery plan using middle mile based on delivery information. Here, middle mile may refer to a delivery method that performs delivery between intermediate points other than the origin or destination. In addition, the middle mile may refer to a wide-area transportation method that moves between different regions based on the middle mile point (terminal). The first user and the second user may be located in different areas, and the delivery requested by the first user may be a wide-area delivery that requires moving to another area. The server 100 can establish a wide-area delivery plan using the middle mile and support the first user to process wide-area delivery on the same day or within a short time. In other words, the server 100 can support wide-area delivery on the same day or within a short period of time even if the first user does not have logistics infrastructure.

Middle mile corresponds to high-speed transportation that moves passengers from the departure terminal to the arrival terminal. Additionally, the middle mile may be configured to further include transportation space for transporting goods in addition to passengers.

The middle mile management server 130 may include first to nth middle mile management servers 130_1 to 130_n that manage different types of middle miles. The first to nth middle mile management servers 130_1 to 130_n may manage the operation of the corresponding middle mile. Exemplarily, the first middle mile management server 130_1 manages the operation of the plurality of first middle miles, the second middle mile management server 130_2 manages the operation of the plurality of second middle miles, and the third The middle mile management server 130_3 may manage the operation of a plurality of third middle miles. The first middle mile, second middle mile, and third middle mile may be different types of high-speed, wide-area transportation. By way of example, the first middle mile may be an express bus, the second middle mile may be a high-speed rail (KTX), and the third middle mile may be an airplane, but are not limited thereto.

As an example, the first middle mile management server 130_1 may manage operation schedule information for a plurality of middle miles (express buses) and manage product transport capacity information for each of the plurality of middle miles. The operation schedule information may include departure time information for each middle mile planned based on the departure terminal, arrival time information for each middle mile to arrive at the arrival terminal, and transportation cost information accordingly. Additionally, the product transportation capacity information may be information indicating the remaining capacity available for transportation based on information on products scheduled and reserved to be transported by each middle mile.

The server 100 can collect middle mile operation schedule information and product transportation capacity information from the middle mile management server 130, and use the collected information to establish a delivery plan using the middle mile. Here, the server 100 can collect operation schedule information and product transportation capacity information from each of the first to nth middle mile management servers 130_1 to 130_n, and provide integrated schedule information and integrated transportation capacity that integrates the collected information. Information can be generated.

Here, the middle mile corresponds to a means of transportation that moves between the departure terminal and the arrival terminal. Accordingly, a last mile may be required to move goods from a starting point to a departure terminal or from an arrival terminal to a destination point. The server 100 may support the movement of goods through the last mile.

Last mile can refer to a means of transportation that allows free movement within a specific area. The last mile may constitute a transportation space for transporting goods. Last mile may be a means of transportation for directly delivering goods from a specific point to another point, but is not limited to this. In addition, the last mile may be a means of transportation that allows not only the transportation of goods but also the boarding of passengers, but is not limited to this.

The last mile management server 140 may include first to kth last mile management servers 140_1 to 140_k that manage different types of last miles. The first to kth last mile management servers (140_1 to 140_n) may manage the operation of the corresponding last mile. Exemplarily, the first last mile management server 140_1 manages the operation of the plurality of first last miles, the second last mile management server 140_2 manages the operation of the plurality of second last miles, and the third The last mile management server 140_3 may manage the operation of a plurality of third last miles. The first last mile, second last mile, and third last mile may be different types of intra-regional transportation. Additionally, transportation costs for the first to third last miles may vary depending on either the distance or time for transporting the product. In other words, as either the distance or time for transporting goods increases, the transport cost may increase proportionally. By way of example, the first last mile may be a quick delivery motorcycle, the second last mile may be a shared vehicle, and the third last mile may be a cargo truck, but are not limited thereto.

As an example, the first last mile management server 140_1 may manage operation information of a plurality of last miles (quick delivery motorcycles) and may manage location information of each of the plurality of last miles. Operation information may be information indicating whether the last mile is currently being delivered or whether delivery is reserved at a specific point in time. It may be possible to identify available last miles through driving information. The location information may be current location information for each last mile. Location information can be used as basic information for dispatching last miles.

The traffic information server 150 may be a public server that identifies and provides traffic conditions and traffic flows from the origin to the destination of product delivery. The traffic information server 150 can predict traffic status information at a future point in time based on current traffic data and past traffic data. Traffic status information on a specific route can be predicted at a specific time on a specific day. By way of example, traffic status information may be information that predicts traffic flow, such as smooth, normal, or congested. The server 100 can receive traffic status information from the traffic information server 150 and use it to establish a delivery plan based on the traffic status information.

Additionally, the weather information server 160 may be a public server that determines and delivers weather conditions and abnormal weather events from the point of origin to the destination of product delivery. The weather information server 160 can predict weather condition information at a future point in time based on weather conditions, current weather conditions of abnormal weather conditions, and past weather conditions. In other words, weather condition information on a specific route can be predicted at a specific time on a specific day. By way of example, the weather condition information may be information predicting the occurrence of predicted temperature, predicted humidity, predicted precipitation, predicted snowfall, or other abnormal weather events. The server 100 can receive weather condition information from the weather information server 160 and use it to establish a delivery plan based on the weather condition information.

Figure 2 is an example diagram to explain the progress of the P2P delivery service performed on the server of the present invention. Figure 3 exemplarily illustrates a user environment provided through a first user's terminal.

Referring to FIG. 2, analysis and confirmation of the first user's delivery receipt may be performed in the server 100 through an automated process. Referring to (a) of FIG. 3, the first user can input origin information and destination information through the user environment, and also input product information. The server 100 can verify the validity of the received delivery request and perform analysis on the validated delivery request. The server 100 may predict a route and route for delivering goods in response to the first user's delivery request, configure a delivery plan using the prediction, and provide the delivery plan to the user. Referring to (b) of FIG. 3, it can be seen that a delivery plan using express buses and KTX is provided to the first user. The first user can select a plurality of delivery plans provided through the user environment.

If the first user requests to proceed with the selected delivery plan, or if the delivery plan satisfies the conditions requested in advance by the user, the application may be completed. Guidance on completion of delivery reception, as shown in (c) of FIG. 3, may be provided through the user environment. Additionally, the server 100 may provide functions such as simple payment or regular payment to facilitate the first user's payment for the delivery plan. After the first user completes the payment, the product is delivered. Here, delivery from the departure point to the departure terminal and from the arrival terminal to the destination is performed by the last mile, and movement between the departure terminal and the arrival terminal is carried out through the determined middle mile. The server 100 can provide an optimized dispatch process so that last mile delivery can also be performed appropriately. Additionally, the server 100 can monitor the entire process of sequentially delivering goods to the last mile, middle mile, and last mile, and support optimized delivery.

Hereinafter, with reference to FIGS. 4 to 14, the main components of the server 100 and the features provided by the components will be described in more detail.

Figure 4 is a block diagram showing an exemplary configuration of a server according to some embodiments of the present invention. Figure 5 is a block diagram showing an exemplary configuration of a delivery reception module according to some embodiments of the present invention. Figure 6 is an example diagram for explaining the operation of a delivery reception module according to some embodiments of the present invention. Figure 7 is a block diagram showing an exemplary configuration of a data analysis module according to some embodiments of the present invention. Figure 8 is an example diagram for explaining the operation of the delivery plan configuration unit according to some embodiments of the present invention. Figure 9 is an example diagram for explaining the operation of the last mile dispatch unit according to some embodiments of the present invention. Figure 10 is an example diagram to explain a process in which a dispatch process for a plurality of last miles is performed. Figure 11 is a flow chart to explain the process in which dispatch to the last mile is performed based on the location information of the middle mile. Figure 12 is a block diagram for explaining the configuration of a cost payment module according to an embodiment of the present invention. Figure 13 is a block diagram for explaining the configuration of a cost settlement module according to an embodiment of the present invention. Figure 14 is an example diagram for explaining the operation of a data collection module according to an embodiment of the present invention.

Referring to Figure 4, the server 100 includes a delivery reception module 101, a data collection module 102, a data analysis module 103, a delivery management module 104, a cost payment module 105, and a cost settlement module ( 106) and database 107.

The delivery reception module 101 may receive delivery information input by the first user through the first user device 110. The data analysis module 103 can analyze delivery information and establish a delivery plan based on the delivery information. The data collection module 102 may collect data necessary for the data analysis module 103 to establish a delivery plan through data exchange with other servers. The delivery management module 104 can manage the delivery status of goods according to the delivery plan. The cost payment module 105 may support the first user to pay the delivery cost included in the delivery plan. The cost settlement module 106 may support settlement of transportation costs for each middle mile and last mile that performs delivery according to the delivery plan. The database 107 can temporarily or permanently store data required for the operation and processing of the above-described configuration and data generated according to the operation and processing. Additionally, the operations of the main components of the server 100 described above may be partially or fully controlled and managed through an administrator environment implemented in the server 100. Here, the manager environment of the server 100 is partially or fully linked with other components that exchange data (e.g., first and second user devices, middle mile management server, last mile management server) through API. It can be.

The delivery reception module 101 can analyze delivery information entered by the user and verify the validity of the analyzed delivery information.

Referring to Figure 5, the delivery reception module 101 includes a first delivery reception unit (101A), a second delivery reception unit (101B), a third delivery reception unit (101C), a fourth delivery reception unit (101D), and a delivery information verification unit ( 101E).

The first delivery reception unit 101A can receive delivery information entered by the user through an API-linked user environment and a dedicated application, and can configure and receive delivery information through this. The second delivery reception unit 101B to the fourth delivery reception unit 101D may analyze the means provided by the user through other communication means to configure and receive delivery information. In some embodiments, the second delivery reception unit 101B configures delivery information by analyzing the user's text information, the third delivery reception unit 101C configures delivery information by analyzing the user's voice information, and the fourth delivery reception unit 101C configures delivery information by analyzing the user's voice information. The reception unit 101D may configure delivery information by analyzing the user's image information.

Referring to FIG. 6, delivery information provided through a user device on which a dedicated application is implemented may further include API interworking information. The first delivery reception unit 101A analyzes the API linkage information included in the delivery information to check authority, and if it is confirmed that the user is authorized, it receives the delivery information.

The second delivery reception unit 101B can receive the user's text information. The user's text information may be transmitted from the user device to the server 100 through a messenger application or text message other than a dedicated application. The text information may be text data containing key information related to requesting delivery of a specific item from the origin to the destination. The second delivery reception unit 101B may include a text analysis model, and may analyze text information and configure delivery information through the text analysis model.

The text analysis model consists of a text recognizer that recognizes text from text information, a text dimension reducer that reduces the dimensionality of the recognized text, a value extractor that extracts values corresponding to preset keys from the dimensionally reduced text, and It may include a delivery information configurator that configures delivery information based on the delivery information. Text dimensionality reducers reduce data throughput by reducing the dimensionality of text information provided through any of the following techniques: data processing that ignores differences in the functions of words in the text, data processing that does not consider how words are combined, and dead word removal techniques. You can do it. Additionally, the preset key of the value extractor may correspond to the main item of the delivery information, and the value extractor may extract the value corresponding to the main item of the delivery information from the text.

The third delivery reception unit 101C can receive the user's voice information. The user's voice information may be transmitted from the user device to the server 100 through a messenger application or text message other than a dedicated application. The voice information may be voice data containing key information related to requesting delivery of a specific item from the origin to the destination. The third delivery reception unit 101C may include a voice analysis model, and may analyze voice information and configure delivery information through the voice analysis model.

The speech analysis model may include a preprocessor that performs preprocessing on the voice, a feature vector extraction unit that extracts a specific vector for the preprocessed voice, and a data mapping unit that matches the extracted feature vector with key items of delivery information. The data mapping unit maps feature vectors and key items of delivery information, identifies values corresponding to the main items, and configures delivery information based on the identified values.

The fourth delivery reception unit 101D may receive the user's image information. The user's image information may be transmitted from the user device to the server 100 through a messenger application or text message other than a dedicated application. The image information may be image data containing key information related to requesting delivery of a specific item from the origin to the destination.

The fourth delivery reception unit 101D may include an image analysis model, and may analyze image information and configure delivery information through the image analysis model.

The image analysis model consists of a text area identifier that identifies the text area in the image information, a text recognizer that recognizes text in the text area, a text dimensionality reducer that reduces the dimensionality of the recognized text, and corresponding preset keys in the dimensionally reduced text. It may include a value extractor that extracts the value and a delivery information configurator that configures delivery information based on the extracted value. Text dimensionality reducers reduce data throughput by reducing the dimensionality of text information provided through any of the following techniques: data processing that ignores differences in the functions of words in the text, data processing that does not consider how words are combined, and dead word removal techniques. You can do it. Additionally, the preset key of the value extractor may correspond to the main item of the delivery information, and the value extractor may extract the value corresponding to the main item of the delivery information from the text.

Referring to FIG. 6, delivery information configured in the first to fourth delivery reception units 101A to 101D may be provided to the delivery information verification unit 101E. The delivery information verification unit 101E can verify the validity of the provided delivery information. In other words, even if the user enters the information through the linked API, human error may occur, and errors may occur in the delivery information automatically configured through the remaining reception area, so verification may be necessary. As an example, the source address or destination address may be configured to be invalid in terms of administrative district.

In an embodiment, the delivery information verification unit 101E may further include a delivery information analysis model for verifying the validity of the delivery information configured in the first to fourth delivery reception units 101A to 101D. The delivery information analysis model may be pre-trained to determine the validity of the current delivery information by comparing the verified past delivery information stored in the database 107 with the delivery information configured through the current delivery reception module 101. . In some embodiments, the delivery information analysis model may be a deep learning-based artificial intelligence learning model that is pre-trained to determine verified past delivery information that matches the input delivery information.

However, it is not limited to this, and the delivery information analysis model may receive verification data from an external server and check the validity and accuracy of delivery information constructed based on the received verification data. As an example, the delivery information analysis model is configured to receive verification data for administrative districts from a server that can search administrative district information, or to search verification data, and is configured to retrieve verification data and deliver delivery information constructed through comparative analysis of the verification data and delivery information. Validity and accuracy can be checked.

If the delivery information verification unit 101E determines that the delivery information is valid according to the output result of the delivery information analysis model, the delivery information verification unit 101E may request the data analysis module 103 to construct a delivery plan corresponding to the delivery information. Additionally, delivery information determined to be valid is stored in the database 107 and used for verification and validity determination of the next delivery information.

If the delivery information verification unit 101E determines that the delivery information is invalid, the delivery information verification unit 101E may request confirmation of the delivery information from the user device and may allow the user to proceed with the process of modifying or confirming the delivery information.

The data collection module 102 may be configured to collect data from the middle mile management server 130, the last mile management server 140, the traffic information server 150, and the weather information server 160 through a network.

Here, the middle mile management server 130 may include a plurality of types of first to nth middle mile management servers, and the data collection module 102 may collect high-speed traffic information from each middle mile management server. there is. High-speed traffic information may include middle mile operation schedule information and middle mile goods transportation capacity information.

Additionally, the last mile management server 140 may include a plurality of types of first to kth middle mile management servers, and the data collection module 102 may collect last mile dispatch information from each last mile management server. You can. Last mile dispatch information may include last mile operation information and last mile location information.

The data analysis module 103 can establish a delivery plan for performing delivery according to delivery information using the collected data. Here, the delivery plan may mean a plan to deliver goods from the origin to the destination using middle mile, a high-speed means of transportation. Additionally, the data analysis module 103 may perform last mile dispatch in response to the established delivery plan and last mile dispatch information.

Referring to FIG. 7, the data analysis module 103 corresponds to the delivery plan configuration unit 103A that configures a delivery plan using the middle mile based on delivery information and high-speed traffic information, and the configured delivery plan and last mile dispatch information. It may include a last mile dispatch department (103B) that performs last mile dispatch.

The delivery plan configuration unit 103A can establish a delivery plan that performs delivery using middle mile. The delivery plan configuration unit 103A may establish a delivery plan for a middle mile that can be operated based on delivery information and high-speed traffic information for at least one middle mile. The delivery plan configuration unit 103A may establish at least one delivery plan and provide it to the first user device 110, and may perform delivery in response to a command provided from the first user device 110. can be finally decided.

In an embodiment, the delivery plan configuration unit 103A may include a middle mile determination model (MD) learned to determine a middle mile that can be driven based on delivery information and high-speed traffic information of at least one middle mile. Additionally, the delivery plan configuration unit 103A may further include a delivery plan establishment model (PD) that establishes a delivery plan according to the middle mile determined in the middle mile determination model (MD).

Referring to (a) of FIG. 8, the middle mile determination model (MD) can determine the middle mile in a state suitable for the input delivery information from the high-speed traffic information, and the delivery plan establishment model (PD) can determine at least one of the determined At least one delivery plan can be established based on the middle mile. Illustratively, if the middle miles determined to be appropriate by the middle mile judgment model (MD) are the 1st to mth middle miles, the first to mth delivery plans corresponding to the first to mth middle miles will be established. You can. Additionally, each middle mile determined in the middle mile judgment model (MD) may be a different type of high-speed transportation, but is not limited thereto. Each middle mile may refer to a means of high-speed transportation with a different departure terminal even if it is of the same type, and may refer to a means of high-speed transportation with a different departure time even if the departure terminal and type are the same. The middle mile determined to be suitable in the middle mile judgment model (MD) is a candidate to be selected as a delivery plan and may therefore also be referred to as a candidate middle mile.

Here, delivery information may include origin information, destination information, and product information. At least the origin information includes departure location information and delivery reception time, the destination information includes arrival location information, and the product information may include product quantity information. Additionally, high-speed traffic information may include middle mile operation schedule information and goods transportation capacity information. The middle mile operation schedule information may include the departure terminal departure time, arrival terminal arrival time, travel route, and transportation cost of the middle mile. In other words, the middle mile decision model (MD) analyzes the input origin location information, delivery reception time, destination location information, and product quantity information and determines at least one middle mile with corresponding operation schedule information and product transportation capacity information. You can judge.

The middle mile determination model (MD) may be a classification model based on a machine learning model that has been trained in advance to determine at least one middle mile suitable for the input delivery information. In some embodiments, the middle mile decision model (MD) may be implemented with K-means clustering. The middle mile determination model (MD) extracts feature values corresponding to the input origin location information, delivery reception time, destination location information, and product quantity information, and classifies the extracted feature values into a plurality of groups. Here, the plurality of groups may be middle miles classified based on operation schedule information and product transportation capacity information. The middle mile judgment model (MD) may be pre-trained so that delivery information is classified into groups corresponding to middle miles that can meet conditions according to the delivery information.

However, the embodiment of the present invention is not limited to this, and the middle mile judgment model (MD) includes linear regression, logistic regression, decision trees, one-class support vector machine (OC-SVM), naive Bayes, and K-nearest neighbors. Neighborhood (KNN), isolation forest, local outlier factor (LOF), random forest, dimensionality reduction algorithms, gradient boosting algorithms, neural networks (e.g., convolution, recursion, perceptrons, short and long run) It may be implemented using memory (LSTM), Hopfield, Boltzmann, deep trust, deconvolution, generative adversarial and/or other types of machine learning models.

Referring to (b) of FIG. 8, the middle mile determination model (MD) determines the middle mile by further considering at least one of traffic condition information on the route corresponding to the delivery information and local weather condition information corresponding to the delivery information. You can. In other words, the middle mile judgment model (MD) can further receive at least one of traffic condition information on the route corresponding to the delivery information and local weather condition information corresponding to the delivery information, and the input traffic condition information and weather condition information. It may be in a state of learning to establish a delivery plan taking into account.

As an example, it may be possible to determine a middle mile with an available departure time by considering at least one of traffic condition information on the route corresponding to the delivery information and local weather condition information corresponding to the delivery information. In other words, if it is determined that it is difficult to use the middle mile with the earliest departure time due to heavy traffic congestion between the departure point and the departure terminal, the middle mile in the next time slot or the middle mile with a different departure terminal is judged to be the optimal middle mile. do.

Referring to (a) of FIG. 8, the delivery plan establishment model (PD) may establish a delivery plan for establishing delivery using at least one middle mile determined in the middle mile determination model (MD). Here, the delivery plan may include travel route, transportation cost, and transportation time. The movement route may refer to a route that sequentially moves to the departure point according to delivery information, the departure terminal of the middle mile, the arrival terminal of the middle mile, and the destination according to delivery information.

Transportation costs may include a first transportation cost for transporting goods from the origin to the departure terminal, a second transportation cost corresponding to the cost of using the middle mile, and a third transportation cost for moving from the arrival terminal to the destination. Here, the second transportation cost may be determined based on middle mile transportation cost information. The first transportation cost may be determined by considering the distance between the point of departure and the departure terminal of the middle mile and the cost of using the last mile. The third transportation cost can be determined by considering the distance between the destination terminal and the destination of the middle mile and the cost of using the last mile. That is, the first transportation cost and the third transportation cost may be predicted costs estimated by the delivery plan establishment model (PD), and the delivery plan establishment model (PD) estimates the first transportation cost and the third transportation cost and transports them. You can judge the cost.

The transportation time may include a first transportation time for transporting the goods from the origin to the departure terminal, a second transportation time corresponding to the cost of using the middle mile, and a third transportation time for moving from the arrival terminal to the destination. Here, the second transportation time may be determined based on the middle mile travel schedule information. The first transportation time may be determined considering the distance between the origin and the departure terminal of the middle mile and the average speed of the last mile. The third transportation time may be determined by considering the distance between the destination terminal and the destination of the middle mile and the average speed of the last mile. That is, the first transport time and the third transport time may be predicted times estimated by the delivery plan establishment model (PD), and the delivery plan establishment model (PD) estimates the first transport time and the third transport time and transports them. You can judge time.

The delivery plan establishment model (PD) may be a pre-trained generation model to establish a delivery plan based on the determined middle mile information, delivery information, and high-speed traffic information.

Referring to (b) of FIG. 8, the delivery plan establishment model (PD) may determine a delivery plan by further considering at least one of route traffic condition information and weather condition information according to the delivery information. In other words, the delivery plan establishment model (PD) can receive at least one more input of traffic state information and weather state information according to the delivery information, and is learned to establish a delivery plan by considering the input traffic state information and weather state information. It may be a state. Illustratively, at least one of the first transportation time and the first transportation cost may be determined by considering at least one of traffic state information and weather state information between the departure point according to the delivery information and the specific middle mile departure terminal. That is, at least one of the transportation time and transportation cost can be determined by taking into account delays in last mile movement due to traffic congestion or bad weather.

The delivery plan configured in the delivery plan configuration unit 103A may be established for each of at least one middle mile suitable for delivery information. By way of example, the delivery plan may be comprised of a plurality, and the server 100 may provide a plurality of established delivery plans to the first user, and the delivery plan to proceed with delivery in response to the first user's command may be determined. You can. Information on the middle mile that carries out the high-speed delivery that makes up each delivery plan, the total travel time according to the delivery plan, the estimated time of arrival, and the transportation cost are provided to the first user, so that the first user wants to use the delivery. We can assist you in choosing a plan.

However, the delivery information is not limited to this and may include at least one of the first user's preference information and request information. The preference information may be information about the preferred middle mile, and the middle mile corresponding to the preference information may have priority in determining the delivery plan. Additionally, the request information may be information about the middle mile for which the user wishes to perform delivery, and the middle mile corresponding to the request information may have priority in determining the delivery plan. The server 100 may determine a delivery plan corresponding to at least one of preference information and request information among a plurality of established delivery plans as the delivery plan to proceed with delivery.

Referring to FIG. 9, the last mile dispatch unit 103B may support last mile dispatch so that delivery is performed according to the delivery plan. The last mile dispatch unit 103B may perform last mile dispatch in response to the delivery plan and last mile dispatch information. The last mile dispatch information may be information provided from a plurality of last mile management servers 140, and the last mile dispatch unit 103B determines the last mile dispatch optimized for the delivery plan determined by considering the dispatch information of each of the plurality of last miles. can be performed.

In the delivery plan, the section requiring last mile dispatch may be the first last mile delivery section from the origin to the middle mile departure terminal and the second last mile delivery section from the middle mile arrival terminal to the destination. The last mile dispatch department (103B) considers the delivery plan and last mile dispatch information and determines dispatch for the last mile for delivering the first last mile delivery section and dispatch for the last mile for delivering the second last mile delivery section. Each can be performed.

Here, the last mile dispatch information may include whether or not the last mile is dispatched and location information of the last mile. That is, based on the last mile dispatch information, the last mile that is available for dispatch can be identified, and the location of the last mile that can be dispatched can be identified. The last mile dispatch department (103B) performs dispatch for the last mile for delivering the first last mile delivery section in consideration of the location of the last mile and departure point where dispatch is possible, which is determined based on the last mile dispatch information. You can. In addition, the last mile dispatch unit 103B determines dispatch for the last mile for delivering the second last mile delivery section in consideration of the location of the last mile where dispatch is possible and the location of the destination, which are determined based on the last mile dispatch information. It can be done.

In some embodiments, the last mile dispatch unit 103B may consider the location of each last mile and set a priority dispatch area for the last mile based on the location of the last mile. For deliveries departing from an origin included in the priority dispatch area or from a departure terminal included in the priority dispatch area, the last mile may be dispatched first.

Referring to FIG. 10, the last mile dispatch unit 103B may receive last mile dispatch information for each of the first last mile (LM1) to the fourth last mile (LM4) from the management server of each last mile. Last mile dispatch information may be provided in response to a preset period, but is not limited thereto and may be provided in response to a request from the last mile dispatch unit 103B. The last mile dispatch unit 103B can set a priority dispatch area for each last mile based on the location information included in the last mile dispatch information. First, the dispatch area is an area set based on the location of the last mile, and may be set in a circular shape, but is not limited to this.

In the example of FIG. 10, the first priority dispatch area (R1) is set based on the location of the first last mile (LM1), and the second priority dispatch area (R2) is set based on the location of the second last mile (LM2). is set, a third priority dispatch area (R3) is set based on the location of the third last mile (LM3), and a fourth priority dispatch area (R4) is set based on the location of the fourth last mile (LM4). You can see that The last mile dispatch department (103B) can perform priority dispatch for the last mile by comparing the priority dispatch area and the departure point or departure terminal included in the delivery plan. That is, the last mile dispatch unit 103B may assign delivery to the first departure point S1 included in the first priority distribution area R1 to the first last mile LM1. Additionally, the last mile dispatch unit 103B may perform priority allocation to the last mile located closer to the departure point when a specific departure point is included in a plurality of priority dispatch areas. Illustratively, the second departure point (S2) is included in both the third priority dispatch area (R3) and the fourth priority dispatch area (R4), but is located closer to the third last mile (LM3). Dispatch for miles (LM3) can be performed.

Here, middle mile is a means of high-speed transportation with fixed departure and arrival times and can usually arrive at the arrival terminal at the set arrival time. However, arrival may be delayed due to unusual weather or traffic conditions. If the last mile for the second last mile delivery section is dispatched considering only the scheduled arrival time, it may not be possible to efficiently deal with middle mile arrival delays, which may result in a decrease in the efficiency of last mile operation. In some embodiments, delivery for the second last mile delivery segment may be determined by further considering the current location of the middle mile.

Referring to FIG. 11, the last mile dispatch unit 103B receives middle mile location information and last mile dispatch information (S200), and can determine whether the middle mile location has passed the critical point (S210). . Step S210 may be a step of checking the progress of the middle mile movement based on the location information of the middle mile, and the critical point may be a specific predetermined point on the movement route. In an embodiment, the critical point may be determined in response to the size of the last mile priority dispatch area. In other words, the last mile dispatch unit 103B operates at a critical point on the movement path of the middle mile so that the remaining distance that the middle mile must travel to the arrival terminal and the distance that the last mile for which dispatching is performed must travel to the arrival terminal are determined to be similar ranges. can be determined by considering the size of the priority dispatch area of the last mile.

The last mile dispatch unit 103B may proceed with last mile dispatch for the second last mile delivery section when the middle mile passes the critical point and is expected to arrive at the destination terminal. In other words, the middle mile where goods are being delivered and the last mile where dispatch is performed may arrive at the arrival terminal at a similar time. Accordingly, a situation where resources are wasted as the last mile waits for the arrival of the middle mile at the arrival terminal can be prevented, and efficient and optimized dispatch to the last mile can be carried out.

Referring again to FIG. 4 , the delivery management module 104 may be configured to guide the delivery plan to the first user and the second user. Additionally, guidance on stages that change as delivery progresses according to the delivery plan can be provided to the first user and the second user. By way of example, the delivery management module 104 may provide related information to the first user and the second user when collection is completed at the departure point and delivery to the departure terminal through the last mile is completed. Additionally, when goods depart from the departure terminal via middle mile, information related thereto may be provided to the first user and the second user.

In some embodiments, the delivery management module 104 may provide a user environment in which the first user and the second user can check the real-time location of the goods by displaying the location of the goods on the movement path according to the delivery plan. Here, the delivery management module 104 can determine the location of the product based on the location of the last mile or middle mile where the product is delivered, and display the determined location of the product on the movement route. .

The cost payment module 105 may provide a function for the user to pay transportation costs according to the delivery plan. Here, payment of the transportation cost may be made by the first user who requested delivery, but is not limited to this, and at least one of the first user and the second user may request payment for the transportation cost according to the determined delivery plan.

Referring to FIG. 12, the cost payment module 105 may include a payment request unit 105A, a simple payment unit 105B, and a cyber money payment unit 105C.

The payment request unit 105A may request payment for transportation costs from at least one of the first user and the second user in response to the delivery plan being determined. Here, the delivery information may include information on the person responsible for bearing the cost, and the payment request unit 105A may request payment for the transportation cost based on the information on the person responsible for the cost. In an embodiment, the information on the subject of cost burden may include information on the ratio in which the first user and the second user pay the cost together but each bear the cost. That is, the payment request unit 105A may divide the payment cost according to the ratio information included in the delivery information and provide a payment request for the divided cost to the first user and the second user, respectively. The payment request unit 105A may support a process in which the first user and the second user make a payment through various payment methods in response to a payment request.

The simple payment unit 105B can support registering a simple password for card payment or account transfer for each user account using the service environment. In other words, the simple payment unit 105B can support the user registering card information and secret card information for card payment and registering a simple password for authentication. Additionally, the simple payment unit 105B can support the user registering account information and account secret information for account transfer and a simple password for authenticating the same. Additionally, the simple payment unit 105B can support the user to make payment for transportation costs using the registered simple password, allowing the first user and the second user to easily make the payment.

The cyber money payment unit 105C may support configuring a cyber money account for each user account using the service environment. That is, the cyber money payment unit 105C can support the user to pay transportation costs through cyber money.

Additionally, in some embodiments, the simple payment unit 105B may support regular payment in which the first user or the second user regularly pays a certain cost according to a preset cycle. Expenses paid through regular payments can be accumulated as cyber money in a cyber money account. In other words, users can pay for transportation costs through cyber money accumulated in the account through a regular payment system.

Additionally, in some embodiments, if the balance of cyber money accumulated in the cyber money account is less than the transportation cost, the cyber money payment unit 105C may proceed with the payment in a negative state and request settlement from the corresponding user at a later date.

The cost settlement module 106 may support cost settlement for middle mile and last mile delivery performed according to the delivery plan.

Referring to FIG. 13, the cost settlement module 106 includes an operation scheduler 106A, a cost settlement unit 106B, a cyber money management unit 106C, and a cost payment unit 106D.

The operation scheduler 106A may configure the operation schedule by organizing the middle mile and last mile operated in response to the delivery plan into daily units. In some embodiments, the operation scheduler 106A may collect information about the middle mile and last mile operated in response to the delivery plan through the delivery management module 104, and configures a operation schedule based on the collected information. can do. Additionally, the travel scheduler 106A may perform verification and confirmation of the configured travel schedule through the middle mile management server 130 or the last mile management server 140 periodically or in response to a user command.

The cost settlement unit 106B may determine the cost settlement according to the operation schedule configured in the operation scheduler 106A. The cost settlement unit 106B can determine the cost to be paid for each middle mile for which the operation is performed, and can determine the cost to be paid for each last mile for which the operation is performed. This settlement operation of the cost settlement unit 106B may be performed on a daily basis, but is not limited to this.

The cyber money management unit 106C can configure accounts corresponding to each middle mile and accounts corresponding to each last mile. The cyber money management unit 106C may deposit corresponding cyber money into the middle mile account and the last mile account, respectively, according to the settlement cost determined by the cost settlement unit 106B. In other words, the settlement cost can be determined by checking the operation history confirmed according to the operation schedule every day, and the settlement cost can be settled in the account of each operation entity as cymer money.

Cyber money stored in each middle mile account and last mile account can be withdrawn to an individual bank account when necessary through the expense payment department (106D). Conventionally, human errors that occur as settlements and transfers are carried out manually by the payment manager can be prevented and manpower and time resources can be saved.

In some embodiments, the data analysis module 103 may integrate and manage high-speed traffic information collected from the middle mile management server 130. The data analysis module 103 can establish a delivery plan based on integrated high-speed traffic information.

The data analysis module 103 receives first high-speed traffic information from the first middle mile management server 130_1, second high-speed traffic information from the second middle mile management server 130_2, and manages the nth middle mile. Nth high-speed traffic information may be provided from the server 130_n. Data collection may be performed through the data collection module 102, and the data collection module 102 may provide the collected data to the data analysis module 103.

Referring to FIG. 14, the data analysis module 103 may further include an integrated information generation unit 103C.

The integrated information generator 103C may generate integrated high-speed traffic information based on a plurality of high-speed traffic information. In some embodiments, each of the first to nth high-speed traffic information is data including operation schedule information and transportation capacity information of the corresponding middle mile, and may be data files provided in different formats. That is, the first to nth high-speed traffic information may be unstructured document files, and the integrated information generating unit 103C may generate integrated high-speed traffic information that has been standardized from these unstructured document files.

In some embodiments, the integrated information generator 103C may include a reference template that serves as a standard for extracting valid values from the first to nth high-speed traffic information. It may be reference information for matching the main items constituting the integrated high-speed traffic information with the items of each high-speed traffic information provided in different formats. The integrated information generator 103C may identify items corresponding to the main items of the standard template from the first to nth high-speed traffic information, extract the values of the identified items, and generate integrated high-speed traffic information. .

In some embodiments, the integrated information generator 103C extracts valid values from the first to nth high-speed traffic information, and generates integrated high-speed traffic information through the extracted valid values based on pre-trained machine learning. It may include an integrated information generation model. In some embodiments, the integrated information generation model may be an adversarial generation model, and the integrated information generation model extracts effective values from the first to nth high-speed traffic information, and provides integrated high-speed traffic information through the extracted effective values. It may include a generation model that generates and a verification model that performs verification on the integrated high-speed traffic information generated from the generation model. The verification model can check whether the information constituting the integrated high-speed traffic information matches the actual high-speed traffic information, and the integrated high-speed traffic information that passes the verification process of the verification model can be finally generated.

Generation of such integrated high-speed traffic information can be performed at preset intervals or in response to user requests. The generated integrated high-speed traffic information may be stored in the database 107.

In some embodiments, the middle mile decision model (MD) of the delivery plan configuration unit 103A of the data analysis module 103 described above may be learned based on the integrated high-speed traffic information configured as above, and may be more accurate. Middle mile judgment may be possible.

Additionally, in some embodiments, the data analysis module 103 is provided with first last mile dispatch information from the first last mile management server 140_1 and second last mile dispatch information from the second last mile management server 140_2. is provided, and the k-th last mile dispatch information may be provided from the k-th last mile management server 140_k. The data collection module 102 may collect data from each management server and provide the collected information to the data analysis module 103.

The integrated information generator 103C of the data analysis module 103 may generate integrated last mile dispatch information based on a plurality of last mile dispatch information. In some embodiments, each of the first last mile dispatch information to the kth last mile dispatch information is data including dispatch availability and location information of the corresponding last mile, and may be data files provided in different formats. That is, the first last mile dispatch information to the kth last mile dispatch information may be unstructured document files, and the integrated information generation unit 103A may generate integrated last mile dispatch information that is standardized from these unstructured document files. You can.

The integrated information generation unit 103C extracts valid values from the first last mile dispatch information to the kth last mile dispatch information, and integrates pre-trained machine learning to generate integrated last mile dispatch information through the extracted valid values. It may include a dispatch information generation model (BD), and integrated last mile dispatch information can be generated through this integrated dispatch information generation model (BD). The integrated dispatch information generation model (BD) may be an adversarial generation model. The integrated dispatch information generation model (BD) extracts valid values from the first last mile dispatch information to the kth last mile dispatch information, and generates a generation model (BD1) that generates integrated last mile dispatch information through the extracted valid values. It may include a verification model (BD2) that performs verification of the integrated last mile dispatch information generated in the model (BD1). The verification model (BD2) can check whether the information constituting the integrated last mile dispatch information matches the actual last mile dispatch information, and the integrated last mile dispatch information that passes the verification process of the verification model (BD2) is finally can be created. If the information constituting the integrated last mile dispatch information does not match the actual last mile dispatch information, the verification model (BD2) may provide feedback information indicating the mismatch to the generation model (BD1). The generation model (BD1) reflects the feedback information and generates integrated last mile dispatch information again.

Generation of such integrated last mile dispatch information may be performed at a preset cycle or in response to a user's request. The generated integrated last mile dispatch information may be stored in the database 107.

The P2P delivery system and server according to some embodiments of the present invention can provide same-day P2P delivery at a low price by using high-speed transportation as the middle mile, and general consumers can also provide same-day delivery using high-speed transportation with a simple operation through a user device. We can support you in progress.

Additionally, the P2P delivery system and server according to some embodiments of the present invention can support efficient P2P delivery by analyzing the optimal delivery route and supporting optimized dispatch.

In addition, the P2P delivery system and server according to some embodiments of the present invention performs the dispatch of the last mile departing from the arrival terminal by considering the location of the middle mile, so the operation of the last mile can be performed more efficiently.

In addition, the P2P delivery system and server according to some embodiments of the present invention can provide a system environment that satisfies both users and deliverers by providing various payment methods and reasonable cost settlement methods.

The above description is merely an illustrative explanation of the technical idea of the present embodiment, and those skilled in the art will be able to make various modifications and variations without departing from the essential characteristics of the present embodiment. Accordingly, the present embodiments are not intended to limit the technical idea of the present embodiment, but rather to explain it, and the scope of the technical idea of the present embodiment is not limited by these examples. The scope of protection of this embodiment should be interpreted in accordance with the claims below, and all technical ideas within the equivalent scope should be interpreted as being included in the scope of rights of this embodiment.

Claims (10)

A delivery reception module that receives delivery information provided from a user device, wherein the delivery information includes origin information, destination information, and product information;
a data collection module configured to collect high-speed traffic information of at least one middle mile and collect last mile dispatch information of at least one last mile;
A data analysis module including a delivery plan component that configures a delivery plan using the middle mile based on the delivery information and the high-speed traffic information, wherein the delivery plan includes a movement route, transportation cost, and transportation time using the middle mile. , data analysis module; and
Includes a cost payment module for the user to pay the transportation cost,
The delivery plan configuration unit analyzes the delivery information and establishes a middle mile determination model for determining at least one middle mile with corresponding high-speed traffic information and a delivery plan for establishing a delivery plan corresponding to the determined at least one middle mile. Contains a model,
The data analysis module corresponds to the configured delivery plan and the last mile dispatch information and provides last mile dispatch for the first last mile delivery section from the origin to the departure terminal of the middle mile and the last mile dispatch from the arrival terminal of the middle mile to the destination. Further comprising a last mile dispatch department that performs at least one of last mile dispatch for the second last mile delivery section,
The last mile dispatch information includes location information of the corresponding last mile,
The last mile dispatch unit sets a priority dispatch area for the last mile based on the location information of the last mile,
The last mile dispatch unit performs dispatch for the first last mile delivery section in consideration of the departure point and the priority dispatch area of the last mile,
The data collection module collects location information of the middle mile moving according to the delivery plan,
The last mile dispatch unit performs dispatch for the second last mile delivery section in consideration of the arrival terminal and the priority dispatch area of the last mile, and determines whether the location of the middle mile has passed a critical point on the travel route. Determine, and proceed with last mile dispatch for the second last mile delivery section in a state where the middle mile passes the critical point and is expected to arrive at the arrival terminal,
The last mile dispatch unit determines the critical point of the middle mile by considering the size of the priority dispatch area of the last mile,
The cost payment module includes a simple payment unit that supports registering a simple password for card or account transfer for each user account and supports payment of the transportation cost through the registered simple password,
The delivery reception module includes first to fourth delivery reception units that analyze information provided from the user device and receive the delivery information,
The first delivery reception unit is configured to analyze the API linkage information of the delivery information provided by the user device to check authority and to receive the delivery information when it is confirmed that the user is an authorized user,
The second delivery reception unit includes a text analysis model trained in advance to construct the delivery information by analyzing the user's text information provided from the user device,
The third delivery reception unit includes a voice analysis model previously learned to construct the delivery information by analyzing the user's voice information provided from the user device,
The fourth delivery reception unit includes a pre-trained image analysis model to construct the delivery information by analyzing the user's image information provided from the user device,
The delivery reception module further includes a delivery information verification unit for verifying delivery information received by any one of the first delivery reception unit to the fourth delivery reception unit,
The delivery information verification unit further includes a delivery information analysis model for analyzing the validity of the delivery information,
The delivery information analysis model is an artificial intelligence-based learning model that is pre-trained to determine the validity of the delivery information by comparing the delivery information and past delivery information,
If the delivery information verification unit determines that the delivery information is valid according to the output result of the delivery information analysis model, the delivery information verification unit requests the data analysis module to configure the delivery plan and stores the delivery information in the database,
The delivery information verification unit is configured to request confirmation of the delivery information from the user device when the delivery information is determined to be invalid according to the output result of the delivery information analysis model.
server.
delete delete According to claim 1,
The departure location information includes departure location information and delivery reception time,
The destination information includes arrival location information,
The product information includes product quantity information,
The high-speed traffic information includes operation schedule information and transportation capacity information of the corresponding middle mile,
The middle mile determination model is machine learning that is pre-trained to determine at least one middle mile with operation schedule information and product transport capacity information corresponding to the input origin location information, delivery reception time, destination location information, and product quantity information. Characterized by being a model-based classification model,
server.
According to claim 1,
The cost payment module configures a cyber money account for each user account to further support payment of the transportation cost through cyber money charged to the cyber money account by the user.
server.
delete delete According to claim 1,
The at least one middle mile is a wide-area transportation means for moving between different regions based on the terminal,
The last mile is characterized in that it is a means of transportation that allows free movement within a specific area,
server.
According to claim 1,
Further comprising a cost settlement module for calculating the last mile transportation cost and the middle mile transportation cost,
The cost settlement module includes a travel scheduler that organizes the middle mile and last mile operated on a daily basis,
The settlement amount is confirmed by verifying the settlement details on a daily basis according to the above operation scheduler,
The cost settlement module configures a cyber money account for each middle mile or each last mile, and is configured to deposit cyber money corresponding to the confirmed settlement amount into the account.
server.
a first user device of a first user;
a second user device of a second user to whom the first user delivers goods;
a server supporting peer-to-peer delivery that delivers the product to the second user in response to a delivery request sent from the first user device;
A middle mile management server that manages the middle mile responsible for middle mile delivery among the P2P delivery; and
Includes a last mile management server that manages the last mile responsible for last mile delivery during the P2P delivery,
The server is,
a delivery reception module that receives delivery information provided from the first user device, wherein the delivery information includes origin information, destination information, and product information;
a data collection module configured to collect high-speed traffic information of at least one middle mile from the middle mile management server and collect last mile dispatch information of at least one last mile from the last mile management server;
A data analysis module including a delivery plan component that configures a delivery plan using the middle mile based on the delivery information and the high-speed traffic information, wherein the delivery plan includes a movement route, transportation cost, and transportation time using the middle mile. , data analysis module; and
Includes a cost payment module for the user to pay the transportation cost,
The delivery plan configuration unit analyzes the delivery information and establishes a middle mile determination model for determining at least one middle mile with corresponding high-speed traffic information and a delivery plan for establishing a delivery plan corresponding to the determined at least one middle mile. Contains a model,
The data analysis module is,
Last mile distribution for the first last mile delivery section from the origin to the departure terminal of the middle mile and the second last mile delivery from the arrival terminal of the middle mile to the destination in response to the configured delivery plan and the last mile dispatch information. Further comprising a last mile dispatch department that performs at least one of the last mile dispatch for the section,
The last mile dispatch information includes location information of the corresponding last mile,
The last mile dispatch unit sets a priority dispatch area for the last mile based on the location information of the last mile,
The last mile dispatch unit performs dispatch for the first last mile delivery section in consideration of the departure point and the priority dispatch area of the last mile,
The data collection module collects location information of the middle mile moving according to the delivery plan,
The last mile dispatch unit performs dispatch for the second last mile delivery section in consideration of the arrival terminal and the priority dispatch area of the last mile, and determines whether the location of the middle mile has passed a critical point on the travel route. Determine, and proceed with last mile dispatch for the second last mile delivery section in a state where the middle mile passes the critical point and is expected to arrive at the arrival terminal,
The last mile dispatch unit determines the critical point of the middle mile by considering the size of the priority dispatch area of the last mile,
The cost payment module includes a simple payment unit that supports registering a simple password for card or account transfer for each user account and supports payment of the transportation cost through the registered simple password, and the delivery The reception module includes a first delivery reception unit to a fourth delivery reception unit that analyzes information provided from the user device and receives the delivery information,
The first delivery reception unit is configured to analyze the API linkage information of the delivery information provided by the user device to check authority and to receive the delivery information when it is confirmed that the user is an authorized user,
The second delivery reception unit includes a text analysis model trained in advance to construct the delivery information by analyzing the user's text information provided from the user device,
The third delivery reception unit includes a voice analysis model previously learned to construct the delivery information by analyzing the user's voice information provided from the user device,
The fourth delivery reception unit includes a pre-trained image analysis model to construct the delivery information by analyzing the user's image information provided from the user device,
The delivery reception module further includes a delivery information verification unit for verifying delivery information received by any one of the first delivery reception unit to the fourth delivery reception unit, and the delivery information verification unit analyzes the validity of the delivery information. It further includes a delivery information analysis model for
The delivery information analysis model is an artificial intelligence-based learning model that is pre-trained to determine the validity of the delivery information by comparing the delivery information and past delivery information,
If the delivery information verification unit determines that the delivery information is valid according to the output result of the delivery information analysis model, the delivery information verification unit requests the data analysis module to configure the delivery plan and stores the delivery information in the database,
The delivery information verification unit is configured to request confirmation of the delivery information from the user device when the delivery information is determined to be invalid according to the output result of the delivery information analysis model.
P2P delivery system.

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