KR102592925B1 - Ai-based cold chain logistics management system and method - Google Patents

Abstract

Based on a previously learned pattern classification model, the present invention analyzes patterns of pharmaceutical transactions between buyers and sellers and provides them to buyers and sellers, and provides delivery information including the temperature and humidity of medicines delivered to buyers in real time. Provides an AI-based cold chain logistics management method and system that can

Description

AI-based cold chain logistics management system and method {AI-BASED COLD CHAIN LOGISTICS MANAGEMENT SYSTEM AND METHOD}

The present invention relates to an AI-based cold chain logistics management system and method.

To manage the production and distribution of products, a management system using RFID tags has recently been used. In order to manage products from production to distribution, RFID tags are attached to manufactured products and the unique identification information of the product is recorded in the attached RFID tag.

When tagging with an RFID tag, the identification information of the product is recognized, so the process from production to distribution of the product can be managed.

RFID consists of a reader that performs reading and decoding functions and a tag that provides information. The tag attached to the product contains information about the entire process of production, distribution, storage, and consumption, and allows the reader to connect to the antenna. Please read this information through .

Additionally, blockchain can be used to prevent product information from being changed during the process from production to distribution. Blockchain uses a method of preventing data falsification by sharing data with multiple participants. Blockchain ensures the integrity of information by including a decentralized structure in which all network participants share and store information.

The above description is intended to aid understanding of the technology described in the present invention, and corresponds to prior art well known to those skilled in the art.

The purpose of the present invention is to provide a logistics management system and method that allows purchasers to receive information on temperature and humidity in real time to improve the purchaser's reliability of transported pharmaceuticals.

Another purpose of the present invention is to provide a logistics management system and method in which a pharmaceutical transportation plan can be derived by a previously learned algorithm and provided to transporters, buyers, and sellers.

Another purpose of the present invention is to provide a logistics management system and method that provides information derived by a previously learned pattern prediction algorithm to buyers and sellers.

The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned can be clearly understood by those skilled in the art from the description below.

The AI-based cold chain logistics management method according to an embodiment of the present invention to solve the above-described problem is a method performed by a computer, and the predictive information and recommended information analyzed based on a pattern analysis algorithm previously learned from the buyer. providing a; Receiving a delivery request from the seller who received the buyer's order; storing delivery condition information of the delivery request in a database; Calculating a logistics plan based on the recommended information and the operation information of the transportation vehicle; And transmitting the packaging information and dispatch information of the medicine according to the logistics plan to the logistics warehouse and the transport vehicle.

In addition, the forecast information includes at least one of demand forecast information, inventory forecast information, inventory management forecast information, cargo volume forecast information, and warehouse movement forecast information, and the recommended information includes automatic drug order information, transaction company recommendation information, and logistics delivery. It includes at least one of recommendation information, and the logistics delivery recommendation information is derived using at least one of the cargo volume prediction information, the warehouse movement prediction information, and the operation information.

Additionally, receiving delivery information from the warehouse and the transport vehicle; And transmitting the delivery information to the purchaser, wherein the delivery information includes at least one of temperature information and humidity information inside the container packaging the medicine, location information, time information, vehicle information, and delivery status information. Contains information about one.

In addition, the demand forecast information includes forecast information about the type, quantity, and timing of the drug to be purchased by the buyer, the inventory forecast information includes information about the drug inventory of at least one of the buyer and the seller, and the inventory management forecast. The information includes information on the storage period and transformation rate of the medicine held by the seller, and the volume prediction information includes information on the quantity of medicines received and shipped from each warehouse, and the warehouse movement prediction. The information includes information about the times when medicines are received and shipped from the warehouse.

In addition, the medicine automatic order information includes information on the type and quantity of medicine that the purchaser is expected to purchase, and the medicine automatic order information is derived based on at least one of the inventory forecast information and the demand forecast information. .

In addition, the trading company recommendation information includes information on sellers who have medicines that the buyer wishes to purchase, but which have medicines with an expiration date of more than a preset period and whose transformation rate is less than or equal to a preset transformation rate, and the trading company. Recommendation information is derived based on the seller's inventory forecast information and the inventory management forecast information.

In addition, the logistics delivery recommendation information includes information on the delivery route and delivery company, and the logistics delivery recommendation information is derived based on the cargo volume prediction information, the warehouse movement prediction information, and the operation information, and the operation information is It includes information on the location of the transport vehicle, whether it is in operation, and whether it has empty space or turns.

Additionally, transmitting dispatch information according to the logistics plan to the transport vehicle; Receiving delivery processing results from the transport vehicle; and calculating costs according to the delivery processing results.

Additionally, the delivery status information may be information generated when an RFID reader recognizes the RFID tag attached to the medicine.

In addition, the AI-based cold chain logistics management system according to an embodiment of the present invention is a system including a cold chain server, a buyer terminal, a seller terminal, a warehouse, and a transportation vehicle, and the cold chain server is connected to the buyer terminal. Provides predicted information and recommendation information analyzed based on a previously learned pattern analysis algorithm, receives a delivery request from the seller terminal that has received the order from the buyer terminal, and stores delivery condition information of the delivery request in the database. , calculates a logistics plan based on the recommendation information and the operation information of the transport vehicle, and transmits packaging information and dispatch information of medicines according to the logistics plan to the warehouse and the transport vehicle, and transmits the logistics plan to the warehouse and the transport vehicle. Receiving delivery information from a vehicle and transmitting the delivery information to the buyer, the prediction information includes at least one of demand prediction information, inventory prediction information, inventory management prediction information, cargo volume prediction information, and warehouse movement prediction information; , the recommendation information includes at least one of automatic drug ordering information, transaction company recommendation information, and logistics delivery recommendation information, and the logistics delivery recommendation information includes at least one of the volume prediction information, the warehouse movement prediction information, and the operation information. It is derived using

In addition, the transport vehicle includes a communication module; A housing configured to control temperature; and a temperature and humidity sensor configured to detect temperature information and humidity information inside the housing, wherein the delivery information includes at least one of the temperature information, the humidity information, location information, time information, vehicle information, and delivery status information. The delivery status information may be information generated by the RFID reader recognizing the RFID tag attached to the medicine.

In addition to this, another method for implementing the present invention, another system, and a computer-readable recording medium recording a computer program for executing the method may be further provided.

According to the present invention as described above, purchasers' reliability of transported drugs is improved, the efficiency of drug transportation is improved, and buyers and sellers can purchase and sell drugs more conveniently.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

Figure 1 is a conceptual diagram of an AI-based cold chain logistics management system according to an embodiment of the present invention.
FIG. 2 is a conceptual diagram showing components included in the transportation vehicle according to FIG. 1.
FIG. 3 is a conceptual diagram illustrating an embodiment of the blockchain 12 according to FIG. 1.
Figure 4 is a flowchart of an AI-based cold chain logistics management method according to an embodiment of the present invention.
Figures 5 and 6 are conceptual diagrams showing the process of learning the pattern prediction algorithm of the present invention.
FIG. 7 is a conceptual diagram illustrating prediction information and recommendation information that can be provided by the cold chain server according to FIG. 1.
Figure 8 is a flowchart of an AI-based cold chain logistics management method according to an embodiment of the present invention.
Figure 9 is a block diagram showing the configuration of a cold chain processing device according to an embodiment of the present invention.

The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. The present embodiments are merely provided to ensure that the disclosure of the present invention is complete and to provide a general understanding of the technical field to which the present invention pertains. It is provided to fully inform the skilled person of the scope of the present invention, and the present invention is only defined by the scope of the claims.

The terminology used herein is for describing embodiments and is not intended to limit the invention. As used herein, singular forms also include plural forms, unless specifically stated otherwise in the context. As used in the specification, “comprises” and/or “comprising” does not exclude the presence or addition of one or more other elements in addition to the mentioned elements. Like reference numerals refer to like elements throughout the specification, and “and/or” includes each and every combination of one or more of the referenced elements. Although “first”, “second”, etc. are used to describe various components, these components are of course not limited by these terms. These terms are merely used to distinguish one component from another. Therefore, it goes without saying that the first component mentioned below may also be a second component within the technical spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings commonly understood by those skilled in the art to which the present invention pertains. Additionally, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless clearly specifically defined.

Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings.

Prior to explanation, the meaning of terms used in this specification will be briefly explained. However, since the explanation of terms is intended to aid understanding of the present specification, it should be noted that if it is not explicitly described as limiting the present invention, it is not used in the sense of limiting the technical idea of the present invention.

Figure 1 is a conceptual diagram of an AI-based cold chain logistics management system according to an embodiment of the present invention.

Referring to FIG. 1, the logistics management system is comprised of a cold chain platform system 10, a logistics warehouse 21, a transportation vehicle 22, a buyer 30, and a seller 40.

Buyer (30) and seller (40) refer to companies or individuals that purchase or sell medicines through the cold chain platform system (10).

The buyer 30 can purchase medicines from the seller 40 through the cold chain platform system 10. When the buyer 30 sends a request to the seller 40 to deliver medicines through the cold chain platform system 10, the seller 40 requests delivery to the cold chain platform system 10.

The cold chain platform system 10 performs and controls the process in which medicines are delivered from the seller 40 to the buyer 30.

Medicines may be delivered directly from the seller 40 to the buyer 30, or may be delivered to the buyer 30 after passing through the distribution warehouse 21. Medicines are loaded on a transport vehicle (22) and transported to a logistics warehouse (21) or purchaser (30).

Since medicines may be damaged by changes in temperature/humidity depending on the type, the transport vehicle 22 is configured to maintain the set temperature/humidity.

Referring to FIG. 2, the transportation vehicle 22 includes a temperature-controlled housing 221. The temperature control housing 221 has an internal space capable of accommodating the medicine 221a, and is configured to maintain the temperature of the internal space at a preset temperature/humidity. The medicine 221a is attached with a barcode for sales and distribution and an RFID tag to control the delivery process.

The temperature control housing 221 may be configured to receive power from a vehicle AC power source. In addition, the temperature control housing 221 includes a separate power supply battery (not shown) and is configured to maintain a preset temperature/humidity by receiving power from the power supply battery when the power supply from the vehicle is cut off. You can.

In addition, the temperature control housing 221 includes a temperature and humidity sensor 221b configured to detect the temperature/humidity of the internal space where the medicine 221a is accommodated. In one embodiment, the BME280 sensor may be used as the temperature and humidity sensor 221b.

Additionally, the temperature control housing 221 includes a temperature/humidity logger 221c configured to display and store the temperature/humidity detected by the temperature/humidity sensor 221b. The temperature and humidity logger 221c may include a micro SD card (Secure Digital) to store the detected temperature/humidity.

Additionally, the temperature control housing 221 may include a communication module 221d for communicating with the cold chain platform system 10. Information on temperature/humidity measured in the temperature control housing 221 is transmitted to the cold chain platform system 10 through the communication module 221d.

Personnel involved in the delivery of the medicine 221a recognize the RFID tag attached to the medicine 221a as an RFID reader. For example, when the medicine 221a is received from the seller 40, when the medicine 221a is received or shipped from the warehouse 21, and when the buyer 30 receives the medicine 221a, the RFID Tag can be recognized by an RFID reader. As the RFID tag is recognized, information about the delivery status of the medicine 221a can be transmitted to the cold chain platform system 10 through the RFID reader.

That is, at least one of information about the current temperature/humidity of the medicine 221a, information about delivery status, vehicle information, and information about location/time may be transmitted to the cold chain platform system 10 and stored. In one embodiment, the temperature control housing 221 may include a GPS receiver to detect information about the current location/time of the medicine 221a.

Therefore, through the received information, the cold chain platform system 10 determines whether the temperature/humidity of the medicines 221a being delivered is appropriate, which transport vehicle 22 they are being delivered by, where they are currently located, and what their current status is ( You can check whether the product is in/out of the logistics warehouse, in progress, etc.) and transmit this to the buyer (30).

Since the buyer 30 can continuously receive information including the temperature/humidity of the ordered medicine 221a from the cold chain platform system 10, it can be trusted that the medicine 221a being delivered will not be damaged during the delivery process. .

In an embodiment not shown, the cold chain platform system 10 provides at least one of information about the current temperature/humidity of the medicine 221a being delivered, information about the delivery status, vehicle information, and information about the location/time to the seller. It can be sent to (40).

Referring again to FIG. 1, the cold chain platform system 10 includes a cold chain server 11 and a blockchain 12.

Blockchain 12 is a decentralized network system comprised of multiple nodes. In the illustrated embodiment, the three illustrated blockchains 12 represent each node. In the illustrated embodiment, there are three, but it is not limited thereto.

The nodes 12 that make up the decentralized network are electronic devices with computational capabilities, such as computers and mobile terminals. Nodes 12 may be people or electronic devices that download the blockchain with software that distributes the blockchain. For example, the nodes 12 may be electronic devices provided in the warehouse 21 and the transportation vehicle 22, or may be electronic devices provided by the buyer 30 and the seller 40.

A plurality of nodes 12 can store a blockchain containing the same data blocks through mutual information exchange. Some of the plurality of nodes 12 may be full nodes that generate new data blocks, transmit them to other nodes 12, verify the received data blocks, and include them in the blockchain. In one embodiment, the cold chain server 11 and the warehouse 21 may be full nodes. Additionally, in one embodiment, the transportation vehicle 22, the purchaser 30, and the purchaser 30 may be lightweight nodes.

For example, an RFID reader can recognize an RFID tag, create a new data block, and then share the data block by transmitting it to a blockchain network. Therefore, the recognized information can be updated by including it in the data block. A data block may be created containing information including at least one of information about the current temperature/humidity of the medicine 221a, information about delivery status, vehicle information, and information about location/time.

Referring to FIG. 3, a conceptual diagram illustrating an embodiment of the blockchain 12 according to FIG. 1 is shown.

1 and 2 are simply represented as a logistics warehouse 21, a buyer 30, and a seller 40, but these are smartphones operated by the personnel of the warehouse 21, the buyer 30, and the seller 40. , refers to a computer device or telecommunication device such as a tablet, PDA, laptop, desktop, server, etc.

Referring to Figure 4, a specific flow of the AI-based cold chain logistics management method according to an embodiment of the present invention is shown.

The cold chain server 11 provides prediction information to the buyer 30 (S10).

Prediction information can be analyzed and provided using a previously learned pattern prediction algorithm.

Referring to Figures 5 and 6, the process by which a pattern prediction algorithm is learned is shown.

First, the cold chain server 11 can collect information about drugs from the Ministry of Food and Drug Safety, the Pharmaceutical Information Center, and pharmaceutical companies/importers. However, it is not limited to this, and information can be collected through information sources that can provide information on drugs, in addition to the Ministry of Food and Drug Safety, Pharmaceutical Information Center, and pharmaceutical companies/importers. In one implementation, information about the drug may include information about the drug name, ingredients, and expiration date.

Additionally, the cold chain server 11 can collect delivery information from cold chain logistics companies belonging to the cold chain logistics management system. Cold chain logistics companies refer to logistics companies that deliver medicines 221a through the above-described warehouse 21 and transport vehicles 22. In addition, the delivery information may include information on the current temperature/humidity of the above-mentioned medicine 221a, information on delivery status, vehicle information, and location/time, and in addition, the inventory status of the warehouse 21 It may include information about, information about changes in inventory, information about the seller 40 using the logistics warehouse 21, etc.

Additionally, the cold chain server 11 can collect order and delivery information from the buyer 30 and the seller 40. Order and delivery information may include information on the type, quantity, and transaction time of medicines traded by the buyer 30 and the seller 40. In addition, the cold chain server 11 can collect information about the drug inventory of the buyer 30 and the seller 40.

The cold chain server 11 stores the collected information in a database. The stored information is classified and processed into a data set through preprocessing. After inputting the processed data set into an AI-based algorithm, a pattern prediction algorithm can be derived through feature extraction, variable setting, and parameter optimization.

The process of optimizing parameters refers to the process of generating learning data using the results of an algorithm and then adjusting parameters based on the learning data. In one embodiment, the pattern prediction algorithm may be learned using a recurrent neural network.

Referring to FIG. 6, an example of a process for deriving a pre-learned pattern prediction algorithm of the present invention is shown.

Referring to FIG. 7, prediction information and recommendation information that can be provided by the cold chain server 11 according to the present invention are shown.

The cold chain server 11 includes demand forecast information, inventory forecast information, inventory management forecast information, cargo volume forecast information, and warehouse movement forecast information through a previously learned pattern prediction algorithm.

The demand forecast information includes forecast information on the type, quantity, and timing of the medicine 221a to be purchased by the purchaser 30. Inventory prediction information includes information about the drug inventory of the buyer 30 or the seller 40. Inventory management forecast information includes information on the storage period and transformation rate of medicines held by the seller (40). Inventory management prediction information can be derived by a pattern algorithm learned using the purchase time, expiration date, temperature and humidity information of the place where the medicines are stored, etc., of the medicines held by the seller 40. The volume prediction information includes information on the volume of medicines 221a to be received and shipped from each warehouse 21. The warehouse movement prediction information includes information about the times when the medicine 221a is received and shipped from the warehouse 21.

The cold chain server 11 can provide recommendation information to the buyer 30 and the seller 40 using the prediction information.

Recommended information may include automatic drug ordering information, inventory transaction recommendation information, transaction company recommendation information, and logistics delivery recommendation information.

The automatic medicine ordering information includes information on the type and quantity of medicine 221a needed by the purchaser 30. Automatic ordering information for medicines can be derived using the inventory forecast information and demand forecast information of the purchaser 30.

The inventory transaction recommendation information includes information about inventory medicines 221a that can be traded between sellers 40. For example, if a buyer who mainly transacts with seller A is expected to purchase c1 medicine, but seller A does not have c1 medicine in stock, the cold chain server 11 provides information about seller B, who has a large amount of c1 medicine left in stock. can be provided to seller A. Through this, the circulation of funds of sellers 40 becomes faster, so sellers 40 can generate more profits compared to the same amount of time.

Inventory transaction recommendation information can be derived using inventory forecast information of sellers (40) and demand forecast information of buyers (30).

Transaction company recommendation information may be provided to the buyer 30. The transaction company recommendation information may include information about the seller 40 that has the drug 221a with a sufficiently expired shelf life and has a low deformation rate among the sellers 40 that have the drug 221a that the buyer 30 wants to purchase. You can. Transaction company recommendation information can be derived using the inventory forecast information and inventory management forecast information of the seller 40.

The logistics delivery recommendation information includes information on the optimal logistics plan for delivering the medicine 221a from the seller 40 to the buyer 30. Logistics plans can include information about delivery routes and delivery companies. Logistics delivery recommendation information can be derived using water volume forecast information and warehouse movement forecast information.

Referring again to FIG. 4, the buyer 30 transmits a delivery request including preset delivery condition information to the seller 40 (S20). The preset delivery condition information may include information about the type, quantity, and delivery deadline of the medicine 221a desired to be delivered.

When a delivery request is received, the seller 40 transmits a delivery request including preset delivery condition information to the cold chain server 11 (S30). The preset delivery condition information may include information on the type, quantity, temperature/humidity conditions, and delivery deadline of the medicine 221a for which delivery is requested.

When a delivery request is received, the cold chain server 11 stores the received delivery condition information in the database (S40).

When the delivery condition information is stored, the cold chain server 11 establishes a logistics plan using AI (S50). As described above, AI may be a pattern prediction algorithm learned by processing information collected by the cold chain server 11. Specifically, the cold chain server 11 can establish a logistics plan using logistics delivery recommendation information. The logistics delivery recommendation information includes information on the optimal logistics plan for delivering the medicine 221a from the seller 40 to the buyer 30. Logistics plans can include information about delivery routes and delivery companies. Logistics delivery recommendation information can be derived using water volume forecast information and warehouse movement forecast information. Additionally, logistics delivery recommendation information can be derived using the operation information of the transportation vehicles 22. The operation information includes information about the current transportation status of the transportation vehicles 22. That is, the operation information may include information on the location of the transportation vehicles 22, whether they are in operation, and whether there are empty spaces or turns.

When a logistics plan is established, the cold chain server 11 transmits packaging and dispatch information according to the logistics plan (S60). Specifically, packaging and dispatch information according to the logistics plan is transmitted to the logistics warehouse 21 and the transport vehicle 22. Packaging information may include information on the packaging type of the medicine 221a and the temperature and humidity to be maintained. In addition, the dispatch information is from seller (40) to seller (40), from seller (40) to buyer (30), from seller (40) to warehouse (21), from warehouse (21) to warehouse (21), and from warehouse (21) to warehouse (21). It may include information about the dispatch of the transport vehicle 22 that will transport the medicine 221a from (21) to the purchaser 30.

When delivery begins, the cold chain server 11 provides delivery information to the buyer 30 (S70). Delivery information may include information on the current temperature/humidity of the medicine 221a being delivered, information on delivery status, vehicle information, and location/time. In an embodiment not shown, the cold chain server 11 may provide delivery information to the seller 40.

Referring to FIG. 8, the process of delivery by the transport vehicle 22 after dispatch information is calculated is shown.

When the dispatch information is calculated, the cold chain server 11 transmits the dispatch information to at least one transport vehicle 22 included in the dispatch information (S110). Dispatch information includes information about travel route and time.

The transport vehicle 22 receives the received dispatch information (S120), and whether the transport vehicle 22 receives the dispatch information can be transmitted to the cold chain server 11.

When at least one transport vehicle 22 included in the dispatch information completes delivery (S130), the buyer 30 receives the product (S140). Whether the buyer 30 has received the product may be transmitted to the cold chain server 11.

When delivery is completed, the transport vehicle 22 transmits the processing result to the cold chain server 11 (S150). Processing results may include information such as delivery completion, refusal of receipt, and buyer absence.

The cold chain server 11 checks the processing results and then reflects the settlement according to the processing results (S160).

Referring to FIG. 9, the cold chain processing device 300 according to the present invention includes a communication module 310, a database 320, and a processor 330.

The processor 330 transmits or receives information to another device through the communication module 310. Additionally, the processor 330 stores received or calculated information in the database 320. The database 320 stores programs for performing each function of the processor 330, and the processor 330 executes the programs stored in the database 320. As the program is executed, preset information may be calculated.

The cold chain processing device 300 may correspond to the above-described cold chain server 11, blockchain (node, 12), the computing device of the logistics warehouse 21, and the computer devices of the buyer 30 and the seller 40. there is.

The communication module 310, database 320, and processor 330 included in the cold chain processing device 300 operate organically to operate the cold chain server 11, blockchain (node, 12), and logistics warehouse ( The computer device of 21) can perform the functions of the computer devices of the buyer 30 and the seller 40.

The AI-based cold chain logistics management system according to an embodiment of the present invention is operated by the cold chain platform system 10, the warehouse 21, the transport vehicle 22, the buyer 30, and the seller 40. As an implemented system, only the category of the invention is different from the AI-based cold chain logistics management method explained through FIGS. 1 to 9, and since the content is the same, overlapping descriptions and examples will be omitted.

The method according to an embodiment of the present invention described above may be implemented as a program (or application) and stored in a medium in order to be executed in conjunction with a server, which is hardware.

The above-mentioned program is C, C++, JAVA, machine language, etc. that can be read by the processor (CPU) of the computer through the device interface of the computer in order for the computer to read the program and execute the methods implemented in the program. It may include code coded in a computer language. These codes may include functional codes related to functions that define the necessary functions for executing the methods, and include control codes related to execution procedures necessary for the computer's processor to execute the functions according to predetermined procedures. can do. In addition, these codes may further include memory reference-related codes that indicate at which location (address address) in the computer's internal or external memory additional information or media required for the computer's processor to execute the above functions should be referenced. there is. In addition, if the computer's processor needs to communicate with any other remote computer or server in order to execute the above functions, the code uses the computer's communication module to determine how to communicate with any other remote computer or server. It may further include communication-related codes regarding whether communication should be performed and what information or media should be transmitted and received during communication.

The storage medium refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specifically, examples of the storage medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc., but are not limited thereto. That is, the program may be stored in various recording media on various servers that the computer can access or on various recording media on the user's computer. Additionally, the medium may be distributed to computer systems connected to a network, and computer-readable code may be stored in a distributed manner.

The steps of the method or algorithm described in connection with embodiments of the present invention may be implemented directly in hardware, implemented as a software module executed by hardware, or a combination thereof. The software module may be RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, hard disk, removable disk, CD-ROM, or It may reside on any type of computer-readable recording medium well known in the art to which the present invention pertains.

Above, embodiments of the present invention have been described with reference to the attached drawings, but those skilled in the art will understand that the present invention can be implemented in other specific forms without changing its technical idea or essential features. You will be able to understand it. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive.

10: Cold chain platform system
11: Cold chain server
12: Blockchain
21: Logistics warehouse
22: Transportation vehicle
30: Buyer
40: seller
300: Cold chain processing device
310: communication module
320: database
330: processor

Claims (10)

A method performed by a computer, comprising:
Providing predicted information and recommended information analyzed based on a previously learned pattern prediction algorithm to the buyer;
Receiving a delivery request from the seller who has received a delivery request containing preset delivery condition information from the buyer - The preset delivery condition information includes the type, quantity, temperature condition, humidity condition, and delivery deadline of the drug for which delivery is requested. Contains information about -;
storing the preset delivery condition information in a database;
Calculating a logistics plan based on the recommended information and the operation information of the transportation vehicle; and
A step of transmitting packaging information and dispatch information of pharmaceuticals according to the logistics plan to the logistics warehouse and the transport vehicle,
The forecast information includes at least one of demand forecast information, inventory forecast information, inventory management forecast information, volume forecast information, and warehouse movement forecast information,
The recommended information includes automatic drug ordering information, inventory transaction recommendation information, transaction company recommendation information, and logistics delivery recommendation information,
The inventory transaction recommendation information includes information on inventory medicines that can be traded between sellers, and is derived based on the inventory forecast information for each of the sellers and the demand forecast information for each buyer,
The transaction company recommendation information includes information on sellers among the sellers who have the medicine that the buyer wants to purchase, who have medicines with an expiration date of more than a preset period and whose transformation rate is less than or equal to the preset transformation rate,
The trading company recommendation information is derived based on the inventory forecast information and the inventory management forecast information of the seller,
The logistics delivery recommendation information includes information on the delivery route and delivery company, and is derived using at least one of the cargo volume prediction information, the warehouse movement prediction information, and the operation information of the transportation vehicle,
The previously learned pattern prediction algorithm is,
Data by storing, classifying and pre-processing information on medicines collected from the Ministry of Food and Drug Safety, Pharmaceutical Information Center, pharmaceutical companies and importers, delivery information collected from cold chain logistics companies, and order and delivery information collected from wholesalers or retailers. After processing it into a set and inputting the processed data set into an artificial intelligence-based algorithm, it is learned through feature extraction, variable setting, and parameter optimization.
The parameter optimization involves generating learning data using the results according to the artificial intelligence-based algorithm and then adjusting parameters based on the learning data,
Information on the medicine includes information on the name, ingredients, and expiration date of the medicine,
The delivery information includes temperature information and humidity information, location information, time information, vehicle information, and delivery status information of the internal space where the medicine is accommodated in the transport vehicle,
The order and delivery information includes information on the type, quantity, and transaction time of medicines transacted by the buyer and the seller, and information on the medicine inventory of the buyer and the seller,
AI-based cold chain logistics management method. According to paragraph 1,
Receiving delivery information from the warehouse and the transport vehicle; and
Further comprising: transmitting the delivery information to the buyer,
AI-based cold chain logistics management method. According to paragraph 1,
The demand forecast information includes forecast information on the type, quantity, and timing of the drug to be purchased by the purchaser,
The inventory prediction information includes prediction information about the drug inventory of at least one of the buyer and the seller,
The inventory management forecast information includes forecast information on the storage period and transformation rate of the medicine held by the seller,
The volume forecast information includes forecast information on the volume of pharmaceuticals to be received and shipped from each warehouse,
The warehouse movement prediction information includes prediction information about the times when medicines are received and shipped from the warehouse,
AI-based cold chain logistics management method. According to paragraph 3,
The automatic ordering information for medicines includes information on the type and quantity of medicines that the purchaser is expected to purchase,
The automatic drug order information is derived based on at least one of the inventory forecast information and the demand forecast information,
AI-based cold chain logistics management method. delete According to paragraph 3,
The logistics delivery recommendation information includes information about the delivery route and delivery company,
The logistics delivery recommendation information is derived based on the cargo volume prediction information, the warehouse movement prediction information, and the operation information,
The operation information includes information on the location of the transport vehicle, whether it is in operation, and whether there is a gap/turn,
AI-based cold chain logistics management method. According to paragraph 1,
Transmitting dispatch information according to the logistics plan to the transport vehicle;
Receiving delivery processing results from the transport vehicle; and
Including; settling the cost according to the delivery processing results.
AI-based cold chain logistics management method. According to paragraph 2,
The delivery status information is information generated by the RFID reader recognizing the RFID tag attached to the medicine.
AI-based cold chain logistics management method. Combined with a computer as hardware and stored in a medium to execute the method of any one of claims 1 to 4 and 6 to 8,
program. A system that includes a cold chain server, buyer terminal, seller terminal, warehouse, and transportation vehicle,
The cold chain server is,
Provides predicted information and recommendation information analyzed based on a previously learned pattern prediction algorithm to the buyer terminal,
A delivery request is received from the seller terminal, which has received a delivery request containing preset delivery condition information from the buyer terminal - the preset delivery condition information includes the type, quantity, temperature condition, humidity condition, and Contains information about delivery deadlines -;
Store the preset delivery condition information in a database,
Calculate a logistics plan based on the recommended information and the operation information of the transportation vehicle,
Transmitting packaging information and dispatch information of pharmaceuticals according to the logistics plan to the warehouse and the transport vehicle,
Receive delivery information from the warehouse and the transport vehicle,
The delivery information is transmitted to the buyer,
The forecast information includes at least one of demand forecast information, inventory forecast information, inventory management forecast information, volume forecast information, and warehouse movement forecast information,
The recommended information includes automatic drug ordering information, inventory transaction recommendation information, transaction company recommendation information, and logistics delivery recommendation information,
The inventory transaction recommendation information includes information on inventory medicines that can be traded between sellers, and is derived based on the inventory forecast information for each of the sellers and the demand forecast information for each buyer,
The transaction company recommendation information includes information on sellers among the sellers who have the medicine that the buyer wants to purchase, who have medicines with an expiration date of more than a preset period and whose transformation rate is less than or equal to the preset transformation rate,
The trading company recommendation information is derived based on the inventory forecast information and the inventory management forecast information of the seller,
The logistics delivery recommendation information includes information on the delivery route and delivery company, and is derived using at least one of the cargo volume prediction information, the warehouse movement prediction information, and the operation information of the transportation vehicle,
The transport vehicle is,
communication module;
A housing having an internal space for accommodating the medicine, and configured to be adjustable so that the temperature and humidity of the internal space can be maintained at a preset temperature and humidity; and
It includes a temperature and humidity sensor configured to detect temperature and humidity information of the internal space,
The previously learned pattern prediction algorithm is,
Data by storing, classifying and pre-processing information on medicines collected from the Ministry of Food and Drug Safety, Pharmaceutical Information Center, pharmaceutical companies and importers, delivery information collected from cold chain logistics companies, and order and delivery information collected from wholesalers or retailers. After processing it into a set and inputting the processed data set into an artificial intelligence-based algorithm, it is learned through feature extraction, variable setting, and parameter optimization.
The parameter optimization involves generating learning data using the results of the artificial intelligence-based algorithm and then adjusting parameters based on the learning data,
Information on the medicine includes information on the name, ingredients, and expiration date of the medicine,
The delivery information includes the temperature information, humidity information, location information, time information, vehicle information, and delivery status information,
The order and delivery information includes information on the type, quantity, and transaction time of medicines transacted by the buyer and the seller, and information on the medicine inventory of the buyer and the seller,
AI-based cold chain logistics management system.