CN117114540A - Logistics transportation monitoring system and method based on Internet of things - Google Patents
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Abstract
The application discloses a logistics transportation monitoring system and method based on the Internet of things, which relate to the field of logistics transportation and comprise a data acquisition module, a risk assessment module, a data storage module and a monitoring display terminal; the system architecture is stored in the block chain platform by adopting a distributed database, so that the availability and the storage efficiency of the system are improved; evaluating risk in the logistics transportation process before transportation; the electronic tag is adopted to monitor in the transportation link, and the electronic tag reader-writer is used for comparing with order information in important links such as loading and unloading, transfer stations and the like, so that the problems of cargo loss, package adjustment and the like are avoided. According to the application, a transparent logistics transportation monitoring system is established by adopting the Internet of things and the blockchain technology, so that all related parties can access and share data, the safety and the integrity of the data are ensured, malicious tampering and data leakage are prevented, and any problem user in logistics can search related information through a distributed database, thereby realizing effective tracing.
Description
Technical Field
The application relates to the field of logistics transportation, in particular to a logistics transportation monitoring system and method based on the Internet of things.
Background
With the development of the logistics industry, many problems exist in the logistics transportation process, such as lack of effective monitoring means, difficulty in real-time monitoring of the transportation process, low logistics transportation efficiency, package loss and bin explosion problems, user information leakage problems and poor compensation mechanism. In addition, the traditional logistics transportation mode also has the problems of inaccurate monitoring data, asymmetric information, difficult data collection, no effective supervision platform and the like. In order to solve the problems, some monitoring systems and methods based on the internet of things have appeared, but the systems have some defects, such as weak real-time performance, difficult tracing of encountered problems, and the like.
Disclosure of Invention
The application aims to provide a logistics transportation monitoring system and method based on the Internet of things, which are used for solving the defects in the background technology.
In order to achieve the above object, the present application provides the following technical solutions: logistics transportation monitoring system based on Internet of things: the system comprises a data acquisition module, a data risk assessment module, a data storage module and a monitoring display terminal;
and a data acquisition module: collecting video monitoring information and logistics transportation risk assessment data in the logistics transportation process;
a data risk assessment module: the risk assessment method is used for carrying out risk assessment on the logistics transportation process;
and a data storage module: the system is used for storing transaction data and transportation data of the whole logistics link (an order release link, a production and processing link and a transportation link and a confirmation receiving link);
monitoring display terminal: the system is used for displaying the monitoring information and providing inquiry, management and tracing of the monitoring information.
In a preferred embodiment, the collected data of the data collection module is:
video monitoring information: loading and unloading vehicle monitoring data, article in-transit video data and station warehouse entry monitoring data;
risk assessment data: cargo information, vehicle information, driving information, road condition information, and in-car article status information.
The data acquisition module acquires information of a logistics participation main body (a sender, a transporter and a receiver) in advance, and records business license and operation qualification information for the transporter (a delivery enterprise) respectively; a sender (manufacturing and processing enterprises) inputs business license and qualification document information of the enterprises; the receiving party (order client) inputs the identity card information and the receiving information;
in a preferred embodiment, the risk assessment data is divided into 4 factor levels, and for each factor in each factor level, a corresponding judgment matrix is constructed according to the importance and influence degree of the factor.
The risk assessment data is divided into 4 factor layers, namely: factors of objects, transportation factors, road conditions and weather factors.
The factors of the objects comprise cargo information, namely cargo varieties, cargo shapes, fragility and object state information in a carriage;
the transportation factors comprise transportation modes, vehicle information, driving information and driving information;
the road condition factors comprise road condition information, road section construction and road closure;
weather factors include fog, storm, flood, heavy rain and ice and snow;
all the factors in the 4 hierarchical structures are compared pairwise to determine the importance relationship between the factors, and a comparison judgment matrix is constructed according to the pairwise comparison result. For n factors, the judgment matrix is a matrix of n rows and n columns.
For a judgment matrix A of n factors, calculating a characteristic vector V and a characteristic value beta;
dividing the elements in the feature vector V by the sum of the elements to obtain a normalized feature vector W;
according to the size of each element in the normalized feature vector W, calculating the weight of each factor in overall evaluation; if the value of the ith element in W is Wi, the weight of the ith element in the overall evaluation is Wi/Σwi (where Σwi is the sum of all elements in W);
in order to ensure the reliability and accuracy of the result, consistency test is required to be performed on the judgment matrix. The consistency ratio CR is calculated by the maximum eigenvalue βmax of the judgment matrix and the random consistency index RI to check the consistency of the judgment matrix. If CR is less than 0.1, the judgment matrix has better consistency, otherwise, the judgment matrix is appropriately adjusted.
Giving a risk comment set: high risk, medium risk, low risk
An evaluation grade is given: 90-100 are classified as high risk, 60-80 are classified as medium risk, and 0-59 are classified as low risk.
A fuzzy evaluation matrix can be obtained according to the weight and the evaluation level of each factor, and finally, the risk level value of logistics transportation is calculated according to a multi-factor evaluation method, and then, the risk level value is corresponding to the risk level. And according to the risk level, corresponding risk management strategies and measures are formulated.
In a preferred embodiment, the data storage module stores the following steps: the transaction data and the monitoring information of each logistics link are associated with order information and stored in a database;
and (3) respectively storing the transaction data and the monitoring information of each logistics link to a plurality of different data storage servers by adopting a distributed database storage system. If a malicious party wants to tamper with or delete data, information modification must be performed on all blocks associated with the modified block in the whole data storage server, and this complex and huge modification work can effectively avoid false transactions and tampering of information.
In a preferred embodiment, the logistics transportation monitoring system is configured in a blockchain platform for monitoring logistics transportation, and the monitoring method comprises the following steps:
step S1: recording the whole logistics transaction process on a blockchain platform, encrypting and signing transaction data, and storing the transaction data in a plurality of data storage servers in a block mode;
step S2: monitoring the transportation process and uploading the monitoring data to a blockchain platform;
step S3: and checking transaction data at the monitoring display terminal, and tracing the object according to the requirement.
In a preferred embodiment, the process of trading the stream is as follows:
a sender (a user of a manufacturing and processing enterprise) creates a product catalog on a logistics transportation monitoring system; the order customer places an order according to the product catalog to form an order ID;
after confirming the order, the sender encrypts information by using a public key published by a receiver (order client) to form ciphertext information, and digitally signs by using a private key to form an associated transaction information block in the process, and stores the information into a distributed database;
after receiving goods, a transport party (delivery enterprise) firstly uses a private key to decrypt the ciphertext, then uses a public key published by a sender to carry out signature verification, and then starts logistics transportation, forms an associated transaction information block in the process, and stores information into a distributed database;
after receiving the goods, the user decrypts the ciphertext by using the private key, verifies the signature by using the public key published by the transport party, completes the receiving confirmation of the goods, forms an associated transaction information block in the process, and stores the information into a distributed database.
In a preferred embodiment, the method of monitoring the transport process is as follows:
the sender marks each article to be shipped with a shipment electronic tag;
the transport vehicle is provided with a vehicle-mounted GPS and a mobile electronic tag reader-writer;
when loading, reading an article shipment electronic tag, comparing the read information with order information, forming a loading record if the comparison is correct, and adding the loading record into the electronic tag to form a loading electronic tag; if the comparison is wrong, the wrong information is returned to the production and processing enterprises; until the goods are correct;
during the transportation of the vehicle, the vehicle positioning coordinates and the running information are obtained through a vehicle-mounted GPS; collecting a cargo in-transit video image through a camera in the vehicle;
when unloading, reading an electronic tag item of article loading, comparing the read information with a loading record, forming a shipment record by comparing the read information with the loading record, and adding the shipment record to the electronic tag to form an unloading electronic tag; if the comparison is wrong, the wrong information is returned to the distribution enterprise until the goods are correct;
when a station is put in storage, reading an article unloading electronic tag, comparing the read information with a shipment record, forming a storage record without errors, adding the storage record to the electronic tag, forming a logistics cycle closed-loop electronic tag, and printing and pasting the logistics cycle closed-loop electronic tag to the article; if the comparison is wrong, the wrong information is returned to the distribution enterprise until the goods are correct;
the loading records, the delivery records, the warehouse entry records, the vehicle positioning coordinates and the driving information during transportation and the goods information in the carriage are transmitted to a plurality of databases of the blockchain platform in a block mode.
In a preferred embodiment, the process of tracing an item is as follows:
if the article is not damaged, the user confirms the goods receiving;
if the article is damaged, rejecting the article by a user; the platform receives the rejection information and sends a notification to each party of the logistics participation main body;
after receiving the notification, each party of the logistics participation main body logs in the personal account number on the monitoring display terminal; inputting an order ID, and popping up database selection by the system; selecting any one of each link from order initiation to station database entry, and entering a database; inquiring loading records, unloading records, loading and unloading video images, warehousing records and warehousing video images according to the order ID, and inquiring responsible parties according to in-transit video images of cargoes in a carriage during transportation;
the responsibility sends a re-delivery and refund negotiation notice to the user, and if the user selects to re-deliver, the logistics flow is restarted; the user selects refund, and the platform initiates refund to the user;
if the responsible party does not negotiate with the user, according to the intelligent contracts of the blockchain platform, punishment notification can be directly sent to the responsible party.
So far, a complete logistics flow is finished.
In the technical scheme, the application has the technical effects and advantages that:
1. the whole-course monitoring of the cargo information in the transportation process is realized, the logistics transportation safety management level is improved, and the phenomena of cargo loss and package adjustment are reduced; and in important links of loading, unloading and entering the station, the consistency and the correctness of the article and the order information are controlled from the source by comparing the reader-writer information with the order information.
2. The data generated in the whole logistics process are managed on the blockchain platform, distributed storage, digital encryption and unique signature confirmation are achieved, the non-tamper-evident property of the logistics data is achieved, a user can conveniently inquire data of any link, the logistics data can be tracked rapidly, and good experience is provided for tracing the objects of the user. By means of intelligent contracts of the blockchain platform, clear responsibility and quick responsibility following can be achieved on problems in the logistics transportation process.
3. The risk assessment of logistics transportation is added, the risk in the logistics transportation process is assessed by adopting a scientific method, the possible risk is predicted, precautions can be taken in advance, and a scientific basis is provided for decision makers of logistics enterprises.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a system block diagram of the present application;
FIG. 2 is a flow chart of the method of the present application;
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In embodiment 1, referring to fig. 1, in order to achieve the above objective, the present application provides the following technical solutions: logistics transportation monitoring system based on Internet of things: the system comprises a data acquisition module, a data risk assessment module, a data storage module and a monitoring display terminal;
and a data acquisition module: collecting video monitoring information and logistics transportation risk assessment data in the logistics transportation process;
a data risk assessment module: the risk assessment method is used for carrying out risk assessment on the logistics transportation process;
and a data storage module: the system is used for storing transaction data and transportation data of the whole logistics link (an order release link, a production and processing link and a transportation link and a confirmation receiving link);
monitoring display terminal: the system is used for displaying the monitoring information and providing inquiry, management and tracing of the monitoring information.
The data acquisition module acquires the following data:
video monitoring information: loading and unloading vehicle monitoring data, article in-transit video data and station warehouse entry monitoring data;
risk assessment data: cargo information, vehicle information, driving information, road condition information, and in-car article status information.
The data acquisition module acquires information of a logistics participation main body (a sender, a transporter and a receiver) in advance, and records business license and operation qualification information for the transporter (a delivery enterprise) respectively; a sender (manufacturing and processing enterprises) inputs business license and qualification document information of the enterprises; the receiving party (order client) inputs the identity card information and the receiving information;
and (3) carrying out risk assessment on the logistics transportation process, dividing the acquired risk assessment data into 4 factor layers, and constructing a corresponding judgment matrix according to the importance and influence degree of each factor in each factor layer.
The risk assessment data is divided into 4 factor layers, namely: factors of objects, transportation factors, road conditions and weather factors.
The factors of the objects comprise cargo information, namely cargo varieties, cargo shapes, fragility and object state information in a carriage;
the transportation factors comprise transportation modes, vehicle information, driving information and driving information;
the road condition factors comprise road condition information, road section construction and road closure;
weather factors include fog, storm, flood, heavy rain and ice and snow;
all the factors in the 4 hierarchical structures are compared pairwise to determine the importance relationship between the factors, and a comparison judgment matrix is constructed according to the pairwise comparison result.
For 16 factors, the matrix is judged to be a matrix of 16 rows and 16 columns.
For a judgment matrix A of 16 factors, calculating a characteristic vector V and a characteristic value beta;
dividing the elements in the feature vector V by the sum of the elements to obtain a normalized feature vector W;
according to the size of each element in the normalized feature vector W, calculating the weight of each factor in overall evaluation; if the value of the ith element in W is Wi, the weight of the ith element in the overall evaluation is Wi/Σwi (where Σwi is the sum of all elements in W);
in order to ensure the reliability and accuracy of the result, consistency test is required to be performed on the judgment matrix. The consistency ratio CR is calculated by the maximum eigenvalue βmax of the judgment matrix and the random consistency index RI to check the consistency of the judgment matrix. If CR is less than 0.1, the judgment matrix has better consistency, otherwise, the judgment matrix is appropriately adjusted.
Giving a risk comment set: high risk, medium risk, low risk
An evaluation grade is given: 90-100 are classified as high risk, 60-90 are classified as medium risk, and 0-59 are classified as low risk.
A fuzzy evaluation matrix can be obtained according to the weight and the evaluation level of each factor, and finally, the risk level value of the logistics transportation is calculated according to a multi-factor evaluation method, if the calculation result is 0.82, the risk evaluation of the logistics transportation is as follows: the risk is high. And according to the risk level, corresponding risk management strategies and measures are formulated.
The storage mode of the data storage module is as follows: and (3) respectively storing the transaction data of each logistics link to a plurality of different data storage servers by adopting a distributed database storage system. If a malicious party wants to tamper with or delete data, information modification must be performed on all blocks associated with the modified block in the whole data storage server, and this complex and huge modification work can effectively avoid false transactions and tampering of information.
The logistics transportation monitoring method based on the Internet of things is characterized in that the logistics transportation monitoring method is constructed in a blockchain platform and used for monitoring logistics transportation, and comprises the following steps:
step S1: logistics participation subjects log in a logistics transportation monitoring system based on the Internet of things, a alliance is formed among all logistics participation subjects through transaction, and related transaction records of all links of logistics are stored in a block mode in the transaction process;
step S2: monitoring the transportation process and uploading monitoring data to a blockchain platform;
step S3: the users of all the participants in the logistics can check the transaction data at the monitoring display terminal, and can trace the transaction process.
The logistic transaction process is as follows:
the method comprises the steps that a production and processing enterprise creates a product catalog on a logistics transportation monitoring system based on the Internet of things; when the user decides to purchase a certain product, negotiating with the enterprise through the system, automatically generating an intelligent contract by the system after the agreement is reached, and then verifying the execution of the contract in the action related to the later transaction, wherein the execution comprises payment collection and handover proof;
after purchasing the commodity, the order client forms an order ID, and simultaneously generates a transaction block and the transaction information is stored in a distributed database; after the order is confirmed, the production and processing enterprises use the asymmetric encryption public key published by the users to encrypt information to form ciphertext information, wherein the ciphertext information comprises material information, production and processing information of products, the self signature private key is used for digital signature, then the goods information is transmitted to the distribution enterprises and meanwhile related information is bound and transmitted, an associated transaction information block is formed in the process, and the information is stored in a distributed database.
After receiving goods, the distribution enterprises firstly decrypt the ciphertext by using a private key, then carry out signature verification by using a public key published by the production and processing enterprises, confirm the integrity of data and the identity of the production and processing enterprises, then confirm the goods, encrypt related information of the transportation process of the distribution enterprises by using an asymmetric encryption public key published by order users after confirming the goods, carry out digital signature by using the private key of the distribution enterprises, then start logistics transportation, and carry out real-time transmission on the goods state in the transportation process, form a transaction block in the process, and store transaction information into a distributed database; this process is also a monitoring during the transport of the logistics.
After receiving the goods, the user firstly uses the private key of the user to decrypt the ciphertext, then uses the public signature key published by the distribution enterprise to carry out signature verification, confirms the identity of the distribution enterprise and the integrity of the data, and after confirming without errors, completes the receiving confirmation of the goods, forms a transaction block and stores the transaction block.
The monitoring method for the logistics transportation process comprises the following steps:
the sender marks each article to be shipped with a shipment electronic tag;
the transport vehicle is provided with a vehicle-mounted GPS and a mobile electronic tag reader-writer;
when loading, reading an article shipment electronic tag, comparing the read information with order information, forming a loading record if the comparison is correct, and adding the loading record into the electronic tag to form a loading electronic tag; if the comparison is wrong, the wrong information is returned to the production and processing enterprises; until the goods are correct;
during the transportation of the vehicle, the vehicle positioning coordinates and the running information are obtained through a vehicle-mounted GPS; collecting a cargo in-transit video image through a camera in the vehicle;
when unloading, reading an electronic tag item of article loading, comparing the read information with a loading record, forming a shipment record by comparing the read information with the loading record, and adding the shipment record to the electronic tag to form an unloading electronic tag; if the comparison is wrong, the wrong information is returned to the distribution enterprise until the goods are correct;
when a station is put in storage, reading an article unloading electronic tag, comparing the read information with a shipment record, forming a storage record without errors, adding the storage record to the electronic tag, forming a logistics cycle closed-loop electronic tag, and printing and pasting the logistics cycle closed-loop electronic tag to the article; if the comparison is wrong, the wrong information is returned to the distribution enterprise until the goods are correct;
the loading records, the delivery records, the warehouse entry records, the vehicle positioning coordinates and the driving information during transportation and the goods information in the carriage are transmitted to a plurality of databases of the blockchain platform in a block mode.
In the receiving link, if a problem exists, the tracing process of the user on the article is as follows:
in the whole logistics system flow, the relevant enterprise information of production and processing enterprises, the product information of production and processing enterprises and the qualification certificate used for submitting auditing are stored into a distributed database in a block mode as data information, real-time data monitored by a supervision mechanism in the whole process are automatically uploaded based on the supervision requirement, and for each participating main body, the situation that the data information is not disclosed to be opaque due to centralized storage does not exist, and the participating main body can enter an information platform at any time according to own requirement to inquire the relevant information.
If the article is not damaged, the user confirms the goods receiving; the user can scan the electronic tag on the goods package by using the WeChat or the code scanning of the payment bank, and can check the information of the whole logistics process;
if the article is damaged, rejecting the article by a user; the platform receives the rejection information and sends a notification to each party of the logistics participation main body;
after receiving the notification, each party of the logistics participation main body logs in the personal account number on the monitoring display terminal; inputting an order ID, and popping up database selection by the system; selecting any one of each link from order initiation to station database entry, and entering a database; inquiring loading records, unloading records, loading and unloading video images, warehousing records and warehousing video images according to the order ID, and inquiring responsible parties according to in-transit video images of cargoes in a carriage during transportation;
the responsibility sends a re-delivery and refund negotiation notice to the user, and if the user selects to re-deliver, the logistics flow is restarted; the user selects refund, and the platform initiates refund to the user;
if the responsible party does not negotiate with the user, according to the intelligent contracts of the blockchain platform, punishment notification can be directly sent to the responsible party.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. Logistics transportation monitoring system based on Internet of things, characterized in that: the risk assessment system comprises a data acquisition module, a risk assessment module, a data storage module and a monitoring display terminal;
and a data acquisition module: collecting video monitoring information and logistics transportation risk assessment data in the logistics transportation process;
risk assessment module: the risk assessment method is used for carrying out risk assessment on the logistics transportation process;
and a data storage module: the system is used for storing transaction data and transportation data of the whole logistics link;
monitoring display terminal: the system is used for displaying the monitoring information and providing inquiry, management and tracing of the monitoring information.
2. The internet of things-based logistics transportation monitoring system of claim 1, wherein: the data acquisition module acquires the following data:
video monitoring information: loading and unloading vehicle monitoring data, article in-transit video data and station warehouse entry monitoring data;
risk assessment data: cargo information (cargo variety, cargo shape, fragility), weather information, vehicle information, travel information, driving information, road condition information, and in-cabin article status information.
3. The internet of things-based logistics transportation monitoring system of claim 2, wherein: the risk assessment data are divided into 4 factor levels, and corresponding judgment matrixes are constructed according to importance and influence degrees of the factors in each factor level.
4. The internet of things-based logistics transportation monitoring system of claim 3, wherein: and calculating the feature vector and the maximum feature value of the judgment matrix to obtain the weight of each factor in the overall evaluation.
5. The internet of things-based logistics transportation monitoring system of claim 4, wherein: comprehensively considering the weight of each factor, and comprehensively evaluating various risks possibly occurring in the logistics transportation process to obtain an evaluation level value;
and according to the evaluation level value, corresponding to the corresponding risk level, and accordingly formulating corresponding risk management strategies and measures.
6. The internet of things-based logistics transportation monitoring system of claim 1, wherein: the storage process of the data storage module is as follows:
the transaction data and the transportation data of each logistics link are associated with order information and stored in a database;
the data storage mode adopts a distributed database system.
7. A logistics transportation monitoring method based on the Internet of things comprises the following steps: the method is characterized in that: the logistics transportation monitoring system is configured in a blockchain platform and used for monitoring logistics transportation, and the monitoring method comprises the following steps:
step S1: recording the whole logistics transaction process on a blockchain platform, encrypting and signing transaction data, and storing the transaction data in a plurality of data storage servers in a block mode;
step S2: monitoring the transportation process and uploading the monitoring data to a blockchain platform;
step S3: and checking transaction data at the monitoring display terminal, and tracing the object according to the requirement.
8. The internet of things-based logistics transportation monitoring method of claim 6, wherein the method comprises the steps of: the logistic transaction process is as follows:
the sender creates a product catalog on the logistics transportation monitoring system; the receiver places an order according to the product catalog to form an order ID;
the sender confirms the order, encrypts the information by using the public key published by the receiver to form ciphertext information, digitally signs by using the private key, forms an associated transaction information block in the process, and stores the information into a distributed database;
after receiving goods, the transport party firstly decrypts the ciphertext by using the private key, then verifies the signature by using the public key published by the sender, and then starts logistics transport, forms an associated transaction information block in the process, and stores the information into a distributed database;
after receiving the goods, the receiver decrypts the ciphertext by using the private key, then verifies the signature by using the public key published by the transporter, completes the receiving confirmation of the goods, forms an associated transaction information block in the process, and stores the information into a distributed database.
9. The internet of things-based logistics transportation monitoring method of claim 7, wherein the method comprises the steps of: the monitoring transportation process is as follows:
the sender marks each article to be shipped with a shipment electronic tag;
the transport vehicle is provided with a vehicle-mounted GPS and a mobile electronic tag reader-writer;
when loading, reading an article shipment electronic tag, comparing the read information with order information, forming a loading record if the comparison is correct, and adding the loading record into the electronic tag to form a loading electronic tag; if the comparison is wrong, the wrong information is returned to the sender; until the goods are correct;
during the transportation of the vehicle, the vehicle positioning coordinates and the running information are obtained through a vehicle-mounted GPS; collecting a cargo in-transit video image through a camera in the vehicle;
when unloading, reading the electronic tag of goods loading, comparing the read information with the loading record, forming a shipment record without error, and adding the shipment record to the electronic tag to form an unloading electronic tag; if the comparison is wrong, the wrong information is returned to the transport party until the goods are correct;
when a station is put in storage, reading an article unloading electronic tag, comparing the read information with a shipment record, forming a storage record without errors, adding the storage record to the electronic tag, forming a logistics cycle closed-loop electronic tag, and printing and pasting the logistics cycle closed-loop electronic tag to the article; if the comparison is wrong, the wrong information is returned to the transport party until the goods are correct;
the loading records, the delivery records, the warehouse entry records, the vehicle positioning coordinates and the driving information during transportation and the in-transit video image data of cargoes in the carriage are transmitted to a plurality of databases of the blockchain platform in a block mode.
10. The internet of things-based logistics transportation monitoring method of claim 6, wherein the method comprises the steps of: the tracing process for the article is as follows:
if the article is not damaged, the user confirms the goods receiving;
if the article is damaged, rejecting the article by a user; the platform receives the rejection information and sends a notification to each party of the logistics participation main body;
after receiving the notification, each party of the logistics participation main body logs in the personal account number on the monitoring display terminal; inputting an order ID, and monitoring the display terminal to pop up database selection; selecting any one of links from order initiation to station database entry, and entering a database; inquiring loading records, unloading records, loading and unloading video images, warehousing records and warehousing video images according to the order ID, and inquiring responsible parties according to in-transit video images of cargoes in a carriage during transportation;
the responsibility sends a re-delivery and refund negotiation notice to the user, and if the user selects to re-deliver, the logistics flow is restarted; the user selects refund, and the platform initiates refund to the user;
if the responsible party does not negotiate with the user, according to the intelligent contracts of the blockchain platform, punishment notification can be directly sent to the responsible party.
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| CN117893122A (en) * | 2024-03-15 | 2024-04-16 | 青岛冠成软件有限公司 | Logistics information management method based on electronic tag |
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