Smart port management system based on blockchain

Abstract

Disclosed in the present invention is a smart port management system based on a blockchain. The system comprises: a cargo information collection module, which is used for collecting cargo information; an information uploading module, which is used for performing on-chain processing on the collected cargo information and uploading the cargo information to a blockchain; a cargo conveyance collection module, which is used for collecting information related to cargo conveyance in a port by unmanned conveying devices in the port; a vehicle information collection module, which is used for collecting information related to vehicles entering the port; a personnel information collection module, which is used for collecting personnel information in the port; a port protection collection module, which is used for collecting information related to protection devices at port terminals; and a security history collection module, which is used for collecting historical security information of the port. The present invention enables more comprehensive and smart port management.

Description

A blockchain-based smart port management system Technical Field

[0001] This invention relates to the field of management systems, and more specifically to a blockchain-based smart port management system. Background Technology

[0002] Port management refers to a series of activities involving the planning, organization, coordination, and supervision of ports and their related facilities, operations, and services. As a vital link between regions, ports play a significant role in promoting trade and economic development. The goals of port management are to improve port operational efficiency, reduce costs, optimize resource allocation, and provide high-quality services.

[0003] In the process of port management, a port management system is used to carry out a series of port management tasks.

[0004] Existing port management systems have low levels of intelligence and limited management types. In particular, when automated conveying equipment is used in ports, there are problems with poor optimization of conveying routes, which affects conveying efficiency and has a certain impact on the use of port management systems. Therefore, a smart port management system based on blockchain is proposed.

[0005] Summary of the Invention

[0006] The technical problem to be solved by this invention is: how to address the low level of intelligence and single management type of existing port management systems, especially the problem of poor optimization of conveying routes and impact on conveying efficiency when automatic conveying equipment is applied in ports. This invention provides a smart port management system based on blockchain.

[0007] The present invention solves the above-mentioned technical problems through the following technical solutions, the present invention comprising:

[0008] The cargo information collection module is used to collect cargo information;

[0009] The information upload module is used to process the collected cargo information on the blockchain and upload the cargo information to the blockchain.

[0010] The cargo transport data acquisition module is used to collect information related to cargo transport within the port using unmanned transport equipment.

[0011] The vehicle information collection module is used to collect relevant information about vehicles entering the port.

[0012] The personnel information collection module is used to collect personnel information within the port.

[0013] The port protection data acquisition module is used to collect information related to the protection equipment at port terminals.

[0014] The security history acquisition module is used to collect historical security information of the port.

[0015] The intelligent port management system analyzes information related to cargo transportation within the port from unmanned conveyor equipment to obtain cargo transportation management information;

[0016] The smart port management system processes vehicle-related information to obtain vehicle management information;

[0017] The smart port management system processes personnel information to obtain personnel management information;

[0018] The smart port management system processes information related to protective equipment to obtain management information for the protective equipment.

[0019] The smart port management system processes historical security information to obtain security training and management information.

[0020] Furthermore, the cargo transportation management information includes cargo route adjustment information and transportation equipment control information, and the specific processing procedure for the cargo transportation management information is as follows:

[0021] Extract the relevant information on cargo transportation within the port collected by the unmanned conveyor equipment. This information includes the cargo receiving point of the unmanned conveyor equipment, the cargo delivery point of the unmanned conveyor equipment, real-time transportation route information, cargo weight information, and historical failure information of the unmanned conveyor equipment.

[0022] Extract the cargo receiving point and cargo delivery point of the unmanned conveyor equipment, import the cargo receiving point and cargo delivery point of the unmanned conveyor equipment into the preset database, retrieve all route information between the cargo receiving point and cargo delivery point of the unmanned conveyor equipment within the port area from the preset database, obtain the conveying route, and mark it as Vi, where i is the route quantity information;

[0023] Then, the mileage of i transport routes V is measured, and the mileage of i transport routes V is processed to obtain the first influence parameter Ui of the transport route;

[0024] Then, collect the number of other conveying equipment and road width information on each conveying route within a preset time period; process the number of other conveying equipment on the conveying route within the preset time period to obtain the second influence parameter Zi, and process the road width information to obtain the third influence parameter Ki;

[0025] All routes are given a base score, which is the same value. The base score, the first influencing parameter Ui, the second influencing parameter Zi, and the third influencing parameter Ki are combined to obtain the comprehensive evaluation score.

[0026] The real-time transportation route information is then processed in the same way as the comprehensive evaluation score to obtain the real-time evaluation score;

[0027] The comprehensive evaluation score is marked as Tti. The two largest evaluation scores Ttmax and Ttmax-1 in Tti are extracted. The difference between Ttmax and Ttmax-1 is calculated to obtain the evaluation difference. When the evaluation difference is less than the preset value, Ttmax-1 is extracted as the benchmark score. When the real-time evaluation score is less than the benchmark score Ttmax-1, cargo route adjustment information is generated.

[0028] When the evaluation difference is greater than the preset value, Ttmax is extracted as the benchmark score. When the real-time evaluation score is less than the benchmark score Ttmax, cargo route adjustment information is generated.

[0029] Then extract the cargo weight information and cargo transportation frequency information. The cargo weight is the total transportation weight information of a single transportation device within a preset time period, and the transportation frequency information is the transportation frequency information of a single transportation device within a preset time period.

[0030] Finally, the historical fault count information of the unmanned conveyor equipment is extracted, the ratio of cargo weight information to cargo transportation count information is calculated, and transportation analysis parameters are obtained. When the transportation analysis parameters are greater than the preset value, and the historical fault count information of the unmanned conveyor equipment is also greater than the preset value, the conveyor equipment control information is generated.

[0031] Furthermore, the process of obtaining the first influence parameter Ui is as follows: extract the mileage of i transport routes V, and formulate the first influence parameter Ui based on the mileage of transport routes V. When the mileage of transport route V is greater than the preset value a1, the first influence parameter Ui is the preset value m1. When the mileage of transport route V is between the preset values ​​a1 and a2, the first influence parameter Ui is the preset value m2. When the mileage of transport route V is less than the preset value a2, the first influence parameter Ui is the preset value m3, where a1 > a2, 0 < m1 < m2 < m3 < 1.

[0032] The process of obtaining the second influencing parameter Zi is as follows: extract the number of other conveying equipment passing through the conveying route within a preset time period on the i conveying routes, calculate the ratio of the number of other conveying equipment passing through the conveying route within the preset time period to the preset time period, obtain the number of passages per unit time, and analyze the number of passages per unit time to obtain the second influencing parameter Zi;

[0033] When the number of passages per unit time is greater than the preset value b1, the second influencing parameter Zi is the preset value e1. When the number of passages per unit time is between the preset values ​​b1 and b2, the second influencing parameter Zi is the preset value e2. When the number of passages per unit time is less than the preset value b2, the second influencing parameter Zi is the preset value e3, b1>b2, 0<e1<e2<e3<1.

[0034] The process of obtaining the third influencing parameter Ki is as follows: extract the road width information of i transport routes V, then collect the width information of the transport equipment, calculate the ratio of the road width information to the width information of the transport equipment, obtain the evaluation ratio, and analyze the evaluation ratio to obtain the third influencing parameter Ki;

[0035] When the evaluation ratio is greater than the preset value c1, the third influence parameter Ki is the preset value p1. When the evaluation ratio is between the preset values ​​c1 and c2, the third influence parameter Ki is the preset value p2. When the evaluation ratio is less than the preset value c2, the third influence parameter Ki is the preset value p3, c1>c2, 0<p1<p2<p3<1.

[0036] The specific processing procedure for the comprehensive evaluation score is as follows: Extract the basic score, and compare the basic score, the first influencing parameter Ui, the second influencing parameter Zi, and the third influencing parameter Ki. The basic score is the basic score of all routes and is a fixed value T. The comprehensive evaluation score Tti is obtained by using the formula T*(1+Ui)*(1+Zi)*(1+Ki)=Tti.

[0037] Furthermore, the vehicle management information includes vehicle warning information, vehicle entry control information, and abnormal vehicle warning information. The specific process for obtaining the vehicle management information is as follows:

[0038] Extract the relevant information of vehicles entering the port, including vehicle image information and vehicle speed information.

[0039] Extract vehicle image information, which includes vehicle image information before entering the port and vehicle image information after entering the port.

[0040] Analyze the image information before entering the port to obtain real-time vehicle parameter information, compare the real-time vehicle parameter information with the vehicle parameters registered during the vehicle access registration, and generate vehicle entry control information if the comparison is successful.

[0041] Analyze vehicle images after they enter the port to obtain vehicle warning information;

[0042] By analyzing vehicle images and speed information after vehicles enter the port, abnormal vehicle warning information can be obtained.

[0043] Furthermore, the specific processing procedure for the vehicle entry control information is as follows: extract the collected image information before entering the port. The image information before entering the port consists of real-time vehicle image information collected by two image acquisition devices set at a preset distance from the vehicle entry gate at the port. One of the real-time vehicle image information is the image information of the front of the vehicle, and the other real-time vehicle image information is the image information of the top of the vehicle.

[0044] The image information of the front of the vehicle is analyzed and processed. When the vehicle is registered, at least three preset markers are placed on the front of the vehicle. Then, the image information of the front of the vehicle is collected for the preset markers, the markers are identified, and after the markers are identified, they are marked with numbers. The markers are connected in order of numbers to obtain three line segments. The area enclosed by the three line segments is the first marker area. The area of ​​the marker area is measured to obtain the real-time first evaluation area.

[0045] Next, the image information of the vehicle top is extracted. When the vehicle is registered, at least three preset markers are also preset on the vehicle top. Then, the image information of the vehicle top is collected for the preset markers, the markers are identified, and after the markers are identified, a number is set on the markers. The markers are connected according to the number order to obtain three line segments. The area enclosed by the three line segments is the second marker area. The area of ​​the marker area is measured to obtain the real-time second evaluation area.

[0046] Next, the vehicle license plate information is extracted from the vehicle image information, and then the vehicle license plate information is imported into the database. The database is then used to retrieve the first and second assessed areas of the corresponding vehicle at the time of registration.

[0047] The absolute value of the difference between the real-time first assessment area and the first assessment area at the time of registration is calculated to obtain the first vehicle assessment parameters;

[0048] The absolute value of the difference between the real-time second assessment area and the second assessment area at the time of registration is calculated to obtain the second vehicle assessment parameters;

[0049] When both the first and second vehicle evaluation parameters exceed the preset range, vehicle entry control information is generated; when no preset marker is identified in either of the two real-time vehicle image information, vehicle registration warning information is generated and sent to the preset receiving terminal, which then plays a prompt message to remind the corresponding vehicle to register.

[0050] Furthermore, the specific process for obtaining the vehicle warning information and the abnormal vehicle warning information is as follows:

[0051] Extract the vehicle image information after the vehicle enters the port, collect human images from the vehicle image information after the vehicle enters the port, measure the distance between the human image information and the vehicle after the human image information is collected, obtain the warning assessment distance, and generate vehicle warning information when the warning assessment distance is less than the preset value.

[0052] Then, the vehicle image information after the vehicle enters the port is analyzed to obtain the vehicle's real-time speed information.

[0053] The difference between the vehicle's real-time speed and the vehicle speed information is then calculated to obtain the speed difference. When the speed difference is greater than a preset value, a vehicle abnormality warning message is generated.

[0054] Furthermore, the specific processing procedure for the personnel management information is as follows: extract the personnel information collected in the port, which is the personnel image in the port; import the safety helmet model, work clothes model, and reflective mark model into the personnel image in the port; and perform safety helmet recognition, work clothes recognition, and reflective mark recognition.

[0055] Next, human body recognition is performed. After the human body is recognized, safety helmet recognition, work clothing recognition, and reflective mark recognition are performed on the human body. If any of these three recognition methods fails to be recognized, personnel management information is generated.

[0056] Simultaneously, the color of the work clothes on the person is identified. After the color is identified, it is imported into the database. The work location corresponding to the work clothes of that color is retrieved. Then, the current image acquisition location is collected. If the current image acquisition location is not the work location corresponding to the work clothes, and the person stays at the current image acquisition location for more than the preset time, personnel management information is generated.

[0057] Furthermore, the specific processing procedure for the management information of the protective equipment is as follows: extract the collected information related to the protective equipment, which includes the length and height of the port guardrail and the number of safety warning signs;

[0058] Next, port information is collected, including port area information and port shoreline length.

[0059] The length of the port guardrail and the length of the port shoreline are processed to obtain guardrail evaluation parameters;

[0060] The port area information and the number of safety warning signs are processed to obtain warning sign evaluation parameters;

[0061] When any of the guardrail evaluation parameters or the warning sign evaluation parameters is abnormal, protective equipment management information is generated.

[0062] Furthermore, the process of obtaining the guardrail evaluation parameters and the anomaly determination process are as follows: extract the length of the port guardrail and the length of the port shoreline, calculate the difference between the length of the port guardrail and the length of the port shoreline, and obtain the length evaluation difference, i.e., the guardrail evaluation parameters. When the guardrail evaluation parameters are less than the preset value, it indicates that there is an anomaly.

[0063] The process of obtaining the warning sign evaluation parameters and the anomaly determination process are as follows: Extract the port area information and the number of safety warning signs, and mark them as Y1 and Y2. Obtain the warning sign evaluation parameter Yy by using the formula Y1 / Y2*α=Yy. When the warning sign evaluation parameter Yy is less than the preset value, it indicates that there is an anomaly. α is a correction value, 1.01≤α≤1.1.

[0064] Furthermore, the specific process for acquiring the security training management information is as follows: extracting the collected security history information, which includes the number of security incidents within a preset time period, security training record information, and personnel safety test scores;

[0065] Process the safety training records to obtain the safety training intervals;

[0066] Security training management information is generated when the number of security incidents within a preset time period exceeds a preset value and the security training interval exceeds a preset value.

[0067] Security training management information is also generated when the number of safety incidents within a preset time period is less than the preset value, the safety training interval is less than the preset value, but the personnel safety test score is less than the preset value.

[0068] The process for obtaining personnel safety test scores is as follows: Testers are selected based on the number of port employees, with the number of testers being at least 1 / 10 of the total number of port employees. Then, during non-working hours, test content is sent to the testers, who fill in the test content and receive the test evaluation. After completing three tests, the average test score of all testers in the three tests is calculated, which is the personnel safety test score. The three tests must be spaced at least one week apart.

[0069] Compared with existing technologies, this invention has the following advantages: This blockchain-based smart port management system can upload cargo information in the port to the blockchain, and then use blockchain technology to track and trace the cargo throughout the entire process. From the moment the cargo enters the port to loading, transportation, and unloading, all relevant information is recorded on the blockchain, ensuring the authenticity and immutability of the data, improving cargo traceability, and reducing the risk of cargo loss or damage. It also enhances supply chain transparency and improves customer trust. Through the generated cargo transportation management information, it intelligently manages the automated conveying equipment in the port, ensuring the stability and efficiency of automated cargo transportation in the port. Through the generated vehicle management information, it manages vehicles entering the port more intelligently, and can promptly detect any abnormalities in vehicles entering the port. At the same time, it also generates personnel management information, protective equipment management information, and security training management information for a more comprehensive integration, making the system more worthy of widespread use. Attached Figure Description

[0070] Figure 1 is a system block diagram of the present invention. Detailed Implementation

[0071] The embodiments of the present invention are described in detail below. These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the following embodiments.

[0072] As shown in Figure 1, this embodiment provides a technical solution: a blockchain-based smart port management system, including: a cargo information collection module for collecting cargo information;

[0073] The information upload module is used to process the collected cargo information on the blockchain, enabling end-to-end tracking and traceability of cargo within the port. From the moment cargo enters the port to loading, transportation, and unloading, all relevant information is recorded on the blockchain, ensuring data authenticity and immutability, improving cargo traceability, reducing the risk of loss or damage, enhancing supply chain transparency, and increasing customer trust.

[0074] The process includes contract and document management. The workflow involves storing port contract and document information on a blockchain to achieve electronic and paperless management. Smart contracts automatically execute contract terms, reducing human intervention and errors.

[0075] Improve the efficiency and accuracy of contract and document processing; reduce management costs and decrease the use and storage of paper documents.

[0076] Logistics Collaboration and Information Sharing: Establish a blockchain-based logistics collaboration platform to achieve seamless connectivity and information sharing among ports, shipping companies, cargo owners, freight forwarders, container yards, and warehousing facilities. Blockchain technology ensures the authenticity and real-time nature of information.

[0077] Improve logistics collaboration efficiency and reduce information silos; enhance supply chain transparency and predictability, and reduce operational risks.

[0078] Fund settlement and payment are automated using blockchain technology within the port. Smart contracts automatically execute payment operations according to contract terms, reducing human intervention and fraud risks. This improves the efficiency and security of fund settlement and payment, lowers transaction costs, and enhances customer satisfaction.

[0079] In terms of safety and regulation, the immutability and transparency of blockchain technology can be leveraged to strengthen port safety supervision. By recording safety incidents and violations within the port, blockchain provides regulatory authorities with authentic and reliable data support, improving the level of port safety supervision; enhancing the transparency and credibility of supervision; and reducing regulatory costs.

[0080] The blockchain-based smart port management process achieves a comprehensive upgrade of port operations through the optimization and integration of aspects such as cargo tracking and tracing, contract and document management, logistics collaboration and information sharing, fund settlement and payment, and security and supervision.

[0081] The cargo transport data acquisition module is used to collect information related to cargo transport within the port by unmanned transport equipment, and to analyze the information related to cargo transport by unmanned transport equipment to obtain cargo transport management information.

[0082] The vehicle information collection module is used to collect relevant information about vehicles entering the port and process the relevant information to obtain vehicle management information.

[0083] The personnel information collection module is used to collect personnel information within the port and process the personnel information to obtain personnel management information.

[0084] The port protection data acquisition module is used to collect information related to the protection equipment at port terminals and to process this information to obtain protection equipment management information.

[0085] The security history collection module is used to collect historical security information of the port and process the historical security information to obtain security training and management information.

[0086] Cargo transportation management information includes cargo route adjustment information and transportation equipment control information. The specific processing procedure for cargo transportation management information is as follows:

[0087] Extract the relevant information on cargo transportation within the port collected by the unmanned conveyor equipment. This information includes the cargo receiving point of the unmanned conveyor equipment, the cargo delivery point of the unmanned conveyor equipment, real-time transportation route information, cargo weight information, and historical failure information of the unmanned conveyor equipment.

[0088] Extract the cargo receiving point and cargo delivery point of the unmanned conveyor equipment, import the cargo receiving point and cargo delivery point of the unmanned conveyor equipment into the preset database, retrieve all route information between the cargo receiving point and cargo delivery point of the unmanned conveyor equipment within the port area from the preset database, obtain the conveying route, and mark it as Vi, where i is the route quantity information;

[0089] Then, the mileage of i transport routes V is measured, and the mileage of i transport routes V is processed to obtain the first influence parameter Ui of the transport route;

[0090] Then, collect the number of other conveying equipment and road width information on each conveying route within a preset time period; process the number of other conveying equipment on the conveying route within the preset time period to obtain the second influence parameter Zi, and process the road width information to obtain the third influence parameter Ki;

[0091] All routes are given a base score, which is the same value. The base score, the first influencing parameter Ui, the second influencing parameter Zi, and the third influencing parameter Ki are combined to obtain the comprehensive evaluation score.

[0092] The real-time transportation route information is then processed in the same way as the comprehensive evaluation score to obtain the real-time evaluation score;

[0093] The comprehensive evaluation score is marked as Tti. The two largest evaluation scores Ttmax and Ttmax-1 in Tti are extracted. The difference between Ttmax and Ttmax-1 is calculated to obtain the evaluation difference. When the evaluation difference is less than the preset value, Ttmax-1 is extracted as the benchmark score. When the real-time evaluation score is less than the benchmark score Ttmax-1, cargo route adjustment information is generated.

[0094] When the evaluation difference is greater than the preset value, Ttmax is extracted as the benchmark score. When the real-time evaluation score is less than the benchmark score Ttmax, cargo route adjustment information is generated. The above process first analyzes the maximum values ​​of the two evaluation scores, Ttmax and Ttmax-1. When the difference between Ttmax and Ttmax-1 is too large, it means that the deviation between Ttmax and Ttmax-1 is too large and has no reference value. Therefore, Ttmax is selected as the benchmark score. Conversely, when the deviation between Ttmax and Ttmax-1 is small, Ttmax-1 can be used to judge whether the current cargo transportation route is suitable. The above process is to determine whether to make adjustments when the real-time evaluation score of the existing route is small compared with Ttmax or Ttmax-1, i.e., to maintain the current transportation route. However, when the real-time evaluation score of the existing route is large compared with Ttmax or Ttmax-1, it means that there are more optimized routes to choose from. Therefore, it is necessary to select the transportation route of the automatic conveyor equipment.

[0095] Then extract the cargo weight information and cargo transportation frequency information. The cargo weight is the total transportation weight information of a single transportation device within a preset time period, and the transportation frequency information is the transportation frequency information of a single transportation device within a preset time period.

[0096] Finally, the historical fault count information of the unmanned conveyor equipment is extracted, the ratio of cargo weight information to cargo transportation count information is calculated, and transportation analysis parameters are obtained. When the transportation analysis parameters are greater than the preset value, and the historical fault count information of the unmanned conveyor equipment is also greater than the preset value, the conveyor equipment control information is generated.

[0097] Through the above process, the transportation-related information and fault information of the unmanned conveyor equipment are analyzed. When an anomaly is detected, the conveyor equipment control information is generated to reduce the transportation volume or number of trips of the unmanned conveyor equipment with the anomaly detected, thereby extending the service life of the unmanned conveyor equipment and reducing the occurrence of situations where the failure of the unmanned conveyor equipment during the transportation process affects the efficiency of cargo transportation.

[0098] The process of obtaining the first influence parameter Ui is as follows: extract the mileage of i transport routes V, and formulate the first influence parameter Ui based on the mileage of transport route V. When the mileage of transport route V is greater than the preset value a1, the first influence parameter Ui is the preset value m1. When the mileage of transport route V is between the preset values ​​a1 and a2, the first influence parameter Ui is the preset value m2. When the mileage of transport route V is less than the preset value a2, the first influence parameter Ui is the preset value m3, where a1>a2, 0<m1<m2<m3<1.

[0099] The process of obtaining the second influencing parameter Zi is as follows: Extract the number of other conveying devices traveling on the i conveying routes within a preset time period, calculate the ratio of the number of other conveying devices traveling on the conveying routes within the preset time period to the preset time period, obtain the number of devices traveling per unit time, and analyze the number of devices traveling per unit time to obtain the second influencing parameter Zi; when the number of devices traveling per unit time is greater than the preset value b1, the second influencing parameter Zi is the preset value e1; when the number of devices traveling per unit time is between the preset values ​​b1 and b2, the second influencing parameter Zi is the preset value e2; when the number of devices traveling per unit time is less than the preset value b2, the second influencing parameter Zi is the preset value e3, b1>b2, 0<e1<e2<e3<1;

[0100] The process of obtaining the third influencing parameter Ki is as follows: extract the road width information of i transport routes V, then collect the width information of the transport equipment, calculate the ratio of the road width information to the width information of the transport equipment, obtain the evaluation ratio, and analyze the evaluation ratio to obtain the third influencing parameter Ki;

[0101] When the evaluation ratio is greater than the preset value c1, the third influence parameter Ki is the preset value p1. When the evaluation ratio is between the preset values ​​c1 and c2, the third influence parameter Ki is the preset value p2. When the evaluation ratio is less than the preset value c2, the third influence parameter Ki is the preset value p3. c1>c2, 0<p1<p2<p3<1.

[0102] Through the above process, more accurate parameters can be obtained, thereby ensuring the accuracy of the final evaluation score of each route. This ensures whether to generate cargo route adjustment information to adjust the transportation route of the unmanned transportation equipment. In the above process, factors such as route mileage, road width, and the number of other unmanned transportation equipment passing through the route are fully considered.

[0103] The specific processing procedure for the comprehensive evaluation score is as follows: Extract the basic score, and compare the basic score, the first influencing parameter Ui, the second influencing parameter Zi, and the third influencing parameter Ki. The basic score is the base score for all routes and is a fixed value T.

[0104] The comprehensive evaluation score Tti can be obtained by using the formula T*(1+Ui)*(1+Zi)*(1+Ki)=Tti.

[0105] Vehicle management information includes vehicle warning information, vehicle entry control information, and abnormal vehicle warning information. The specific process for obtaining vehicle management information is as follows:

[0106] Extract the relevant information of vehicles entering the port, including vehicle image information and vehicle speed information.

[0107] Extract vehicle image information, which includes vehicle image information before entering the port and vehicle image information after entering the port.

[0108] The system analyzes the video information before vehicles enter the port to obtain real-time vehicle parameter information. It then compares this real-time parameter information with the vehicle parameters registered during the vehicle access registration process. If the comparison is successful, it generates vehicle access control information, which verifies the vehicles entering the port. Once the verification is successful, the vehicles are allowed to enter.

[0109] By analyzing vehicle images after they enter the port, vehicle warning information can be obtained. Since most of the transport vehicles in the port are large vehicles with many blind spots, the images of vehicles in the port are collected in real time by the image acquisition equipment in the port. The images are then analyzed to detect when people are approaching the vehicle while it is in motion, and to reduce the occurrence of accidents.

[0110] The system analyzes vehicle images and speed information after vehicles enter the port to obtain abnormal vehicle warning information. Specifically, when a vehicle enters the port, its speed is collected through vehicle images. If there is a discrepancy between the speed collected through vehicle images and the speed uploaded by the vehicle, an abnormal vehicle warning message is generated to provide a notification, thereby reducing the occurrence of accidents caused by abnormal vehicle speed.

[0111] The specific processing procedure for vehicle entry control information is as follows: Extract the collected image information before entering the port. The image information before entering the port consists of real-time vehicle image information collected by two image acquisition devices set at a preset distance from the vehicle entry gate at the port. One real-time vehicle image information is the image information of the front of the vehicle, and the other real-time vehicle image information is the image information of the top of the vehicle.

[0112] The image information of the front of the vehicle is analyzed and processed. When the vehicle is registered, at least three preset markers are placed on the front of the vehicle. Then, the image information of the front of the vehicle is collected for the preset markers, the markers are identified, and after the markers are identified, they are marked with numbers. The markers are connected in order of numbers to obtain three line segments. The area enclosed by the three line segments is the first marker area. The area of ​​the marker area is measured to obtain the real-time first evaluation area.

[0113] Next, the image information of the vehicle top is extracted. When the vehicle is registered, at least three preset markers are also preset on the vehicle top. Then, the image information of the vehicle top is collected for the preset markers, the markers are identified, and after the markers are identified, a number is set on the markers. The markers are connected according to the number order to obtain three line segments. The area enclosed by the three line segments is the second marker area. The area of ​​the marker area is measured to obtain the real-time second evaluation area.

[0114] Next, the vehicle license plate information is extracted from the vehicle image information, and then the vehicle license plate information is imported into the database. The database is then used to retrieve the first and second assessed areas of the corresponding vehicle at the time of registration.

[0115] The absolute value of the difference between the real-time first assessment area and the first assessment area at the time of registration is calculated to obtain the first vehicle assessment parameters;

[0116] The absolute value of the difference between the real-time second assessment area and the second assessment area at the time of registration is calculated to obtain the second vehicle assessment parameters;

[0117] When both the first and second vehicle evaluation parameters exceed the preset range, vehicle entry control information is generated; when no preset marker is identified in either of the two real-time vehicle image information, vehicle registration warning information is generated and sent to the preset receiving terminal, which then plays a prompt message to remind the corresponding vehicle to register.

[0118] The real-time vehicle image information collected by the two image acquisition devices in the above process is collected by two image acquisition devices set at a preset distance from the port entrance gate. That is, the vehicle is analyzed when it enters the preset distance from the port, thereby reducing the occurrence of traffic jams caused by identification anomalies due to the vehicle entering the gate equipment and then being analyzed. In addition, the setting of simultaneous verification of two images in the above process can avoid the situation where a vehicle cannot enter the port due to a single verification error.

[0119] The specific process for obtaining vehicle warning information and abnormal vehicle warning information is as follows:

[0120] Extract the vehicle image information after the vehicle enters the port, collect human images from the vehicle image information after the vehicle enters the port, measure the distance between the human image information and the vehicle after the human image information is collected, and obtain the warning assessment distance. When the warning assessment distance is less than the preset value, a vehicle warning message is generated. At this time, the specific content of the vehicle warning message is that there are people around the vehicle and you need to drive carefully.

[0121] Then, the vehicle image information after the vehicle enters the port is analyzed to obtain the vehicle's real-time speed information.

[0122] The difference between the vehicle's real-time speed and the vehicle speed information is then calculated to obtain the speed difference. When the speed difference is greater than a preset value, a vehicle abnormality warning message is generated. The specific content of the vehicle abnormality warning message is: "Vehicle speed is abnormal, please slow down."

[0123] The specific processing procedure for personnel management information is as follows: Extract the personnel information collected in the port, which is the personnel image in the port. Import the safety helmet model, work clothes model, and reflective mark model into the personnel image in the port, and perform safety helmet recognition, work clothes recognition, and reflective mark recognition.

[0124] First, human body recognition is performed. After the human body is recognized, safety helmet recognition, work uniform recognition, and reflective mark recognition are performed on the human body. If any of these recognitions fails, personnel management information is generated. At this time, the personnel management information is: There is a person not wearing a safety helmet / work uniform / reflective mark, please put it on immediately. At the same time, the color of the work uniform on the human body is recognized. After the color is recognized, it is imported into the database. The work location corresponding to the work uniform of this color is retrieved. Then, the current image acquisition location is captured. If the current image acquisition location is not the work location corresponding to the work uniform, and the person stays at the current image acquisition location for more than the preset time, personnel management information is generated. At this time, the personnel management information is: There is a person abnormally staying in a non-work area, please return to the allowed work area immediately.

[0125] The specific processing procedure for protective equipment management information is as follows: Extract the collected protective equipment related information, which includes the length and height of the port guardrail and the number of safety warning signs;

[0126] Next, port information is collected, including port area information and port shoreline length.

[0127] The length of the port guardrail and the length of the port shoreline are processed to obtain guardrail evaluation parameters;

[0128] The port area information and the number of safety warning signs are processed to obtain warning sign evaluation parameters;

[0129] When any one of the guardrail evaluation parameters or the warning sign evaluation parameters is abnormal, protective equipment management information is generated.

[0130] When the guardrail assessment parameters are abnormal, the specific information in the protective equipment management information should be that the guardrail length needs to be increased to ensure safety.

[0131] When the evaluation parameters of the warning sign are abnormal, the specific content of the protective equipment management information should be that a warning and protective sign is required to ensure safety.

[0132] The process of obtaining the guardrail evaluation parameters and the process of anomaly judgment are as follows: extract the length of the port guardrail and the length of the port shoreline, calculate the difference between the length of the port guardrail and the length of the port shoreline, and obtain the length evaluation difference, that is, the guardrail evaluation parameter. When the guardrail evaluation parameter is less than the preset value, it indicates that there is an anomaly.

[0133] The process of obtaining the warning sign evaluation parameters and the anomaly judgment process are as follows: Extract the port area information and the number of safety warning signs, and mark them as Y1 and Y2. Obtain the warning sign evaluation parameter Yy through the formula Y1 / Y2*α=Yy. When the warning sign evaluation parameter Yy is less than the preset value, it indicates that there is an anomaly. α is the correction value, 1.01≤α≤1.1.

[0134] Through the above process, more accurate relevant parameters can be obtained, thereby ensuring the accuracy of the generated management information for protective equipment.

[0135] The specific process for obtaining security training management information is as follows: Extract the collected security historical information, which includes the number of security incidents within a preset time period, security training record information, and personnel safety test scores;

[0136] Process the safety training records to obtain the safety training intervals;

[0137] When the number of safety incidents within a preset time period exceeds a preset value, and the safety training interval also exceeds a preset value, security training management information is generated. In this case, the specific information indicates that the safety training interval is too long and the number of safety training sessions needs to be increased. When the number of safety incidents within a preset time period is less than a preset value, and the safety training interval is less than a preset value, but the personnel's safety test score is less than a preset value, security training management information is also generated. In this case, the specific information indicates that the personnel's safety awareness is poor and the number of safety training sessions needs to be increased.

[0138] The process for obtaining personnel safety test scores is as follows: Testers are selected based on the number of port employees, with the number of testers being at least 1 / 10 of the total number of port employees. Then, during non-working hours, test content is sent to the testers, who fill in the test content and receive the test evaluation. After completing three tests, the average test score of all testers in the three tests is calculated, which is the personnel safety test score. The three tests must be spaced at least one week apart.

[0139] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0140] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0141] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A blockchain-based smart port management system, characterized in that, include: The cargo information collection module is used to collect cargo information; The information upload module is used to process the collected cargo information on the blockchain and upload the cargo information to the blockchain. The cargo transport data acquisition module is used to collect information related to cargo transport within the port using unmanned transport equipment. The vehicle information collection module is used to collect relevant information about vehicles entering the port. The personnel information collection module is used to collect personnel information within the port. The port protection data acquisition module is used to collect information related to the protection equipment at port terminals. The security history acquisition module is used to collect historical security information of the port. The intelligent port management system analyzes information related to cargo transportation within the port from unmanned conveyor equipment to obtain cargo transportation management information; The smart port management system processes vehicle-related information to obtain vehicle management information; The smart port management system processes personnel information to obtain personnel management information; The smart port management system processes information related to protective equipment to obtain management information for the protective equipment. The smart port management system processes historical security information to obtain security training and management information.

2. The blockchain-based smart port management system according to claim 1, characterized in that: The cargo transportation management information includes cargo route adjustment information and transportation equipment control information. The specific processing procedure for the cargo transportation management information is as follows: Extract the relevant information on cargo transportation within the port collected by the unmanned conveyor equipment. This information includes the cargo receiving point of the unmanned conveyor equipment, the cargo delivery point of the unmanned conveyor equipment, real-time transportation route information, cargo weight information, and historical failure information of the unmanned conveyor equipment. Extract the cargo receiving point and cargo delivery point of the unmanned conveyor equipment, import the cargo receiving point and cargo delivery point of the unmanned conveyor equipment into the preset database, retrieve all route information between the cargo receiving point and cargo delivery point of the unmanned conveyor equipment within the port area from the preset database, obtain the conveying route, and mark it as Vi, where i is the route quantity information; Then, the mileage of i transport routes V is measured, and the mileage of i transport routes V is processed to obtain the first influence parameter Ui of the transport route; Then collect information on the number of other conveying equipment and road width on each conveying route within a preset time period; The number of other conveying equipment passing through the conveying route within a preset time period is processed to obtain the second influence parameter Zi, and the road width information is processed to obtain the third influence parameter Ki; All routes have a base score set, with the same base score. The base score, the first influencing parameter Ui, and the second... The influencing parameter Zi and the third influencing parameter Ki are combined to obtain the comprehensive evaluation score; The real-time transportation route information is then processed in the same way as the comprehensive evaluation score to obtain the real-time evaluation score; The comprehensive evaluation score is marked as Tti. The two largest evaluation scores Ttmax and Ttmax-1 in Tti are extracted. The difference between Ttmax and Ttmax-1 is calculated to obtain the evaluation difference. When the evaluation difference is less than the preset value, Ttmax-1 is extracted as the benchmark score. When the real-time evaluation score is less than the benchmark score Ttmax-1, cargo route adjustment information is generated. When the evaluation difference is greater than the preset value, Ttmax is extracted as the benchmark score. When the real-time evaluation score is less than the benchmark score Ttmax, cargo route adjustment information is generated. Then extract the cargo weight information and cargo transportation frequency information. The cargo weight is the total transportation weight information of a single transportation device within a preset time period, and the transportation frequency information is the transportation frequency information of a single transportation device within a preset time period. Finally, the historical fault count information of the unmanned conveyor equipment is extracted, the ratio of cargo weight information to cargo transportation count information is calculated, and transportation analysis parameters are obtained. When the transportation analysis parameters are greater than the preset value, and the historical fault count information of the unmanned conveyor equipment is also greater than the preset value, the conveyor equipment control information is generated.

3. The blockchain-based smart port management system according to claim 1, characterized in that: The vehicle management information includes vehicle warning information, vehicle entry control information, and abnormal vehicle warning information. The specific process for obtaining the vehicle management information is as follows: Extract the relevant information of vehicles entering the port, including vehicle image information and vehicle speed information. Extract vehicle image information, which includes vehicle image information before entering the port and vehicle image information after entering the port. Analyze the image information before entering the port to obtain real-time vehicle parameter information, compare the real-time vehicle parameter information with the vehicle parameters registered during the vehicle access registration, and generate vehicle entry control information if the comparison is successful. Analyze vehicle images after they enter the port to obtain vehicle warning information; By analyzing vehicle images and speed information after vehicles enter the port, abnormal vehicle warning information can be obtained.

4. The smart port management system based on blockchain according to claim 3, characterized in that: The specific processing procedure for the vehicle entry control information is as follows: Extract the collected image information before entering the port. The image information before entering the port consists of real-time vehicle image information collected by two image acquisition devices set at a preset distance from the vehicle entry gate at the port. One of the real-time vehicle image information is the image information of the front of the vehicle, and the other real-time vehicle image information is the image information of the top of the vehicle. The image information of the vehicle's front is analyzed and processed. At least three preset markers are affixed to the front of the vehicle during registration. The image information of the vehicle's front is then used to collect and identify these markers. Once the markers are identified... The markers are numbered. The markers are connected in order of number to obtain three line segments. The area enclosed by the three line segments is the first marker area. The area of ​​the marker area is measured to obtain the real-time first evaluation area. Next, the image information of the vehicle top is extracted. When the vehicle is registered, at least three preset markers are also preset on the vehicle top. Then, the image information of the vehicle top is collected for the preset markers, the markers are identified, and after the markers are identified, a number is set on the markers. The markers are connected according to the number order to obtain three line segments. The area enclosed by the three line segments is the second marker area. The area of ​​the marker area is measured to obtain the real-time second evaluation area. Next, the vehicle license plate information is extracted from the vehicle image information, and then the vehicle license plate information is imported into the database. The database is then used to retrieve the first and second assessed areas of the corresponding vehicle at the time of registration. The absolute value of the difference between the real-time first assessment area and the first assessment area at the time of registration is calculated to obtain the first vehicle assessment parameters; The absolute value of the difference between the real-time second assessment area and the second assessment area at the time of registration is calculated to obtain the second vehicle assessment parameters; When both the first vehicle evaluation parameter and the second vehicle evaluation parameter exceed the preset range, vehicle entry control information is generated. When no preset marker is identified in either of the two real-time vehicle image feeds, a vehicle registration warning message is generated and sent to a preset receiving terminal. The preset receiving terminal then plays a prompt message to remind the corresponding vehicle to register.

5. A blockchain-based smart port management system according to claim 4, characterized in that: The specific process for obtaining the vehicle warning information and the abnormal vehicle warning information is as follows: Extract the vehicle image information after the vehicle enters the port, collect human images from the vehicle image information after the vehicle enters the port, measure the distance between the human image information and the vehicle after the human image information is collected, obtain the warning assessment distance, and generate vehicle warning information when the warning assessment distance is less than the preset value. Then, the vehicle image information after the vehicle enters the port is analyzed to obtain the vehicle's real-time speed information. The difference between the vehicle's real-time speed and the vehicle speed information is then calculated to obtain the speed difference. When the speed difference is greater than a preset value, a vehicle abnormality warning message is generated.

6. The smart port management system based on blockchain according to claim 1, characterized in that: The specific processing procedure for the personnel management information is as follows: Extract the personnel information collected in the port, which is the personnel image in the port. Import the safety helmet model, work clothes model, and reflective mark model into the personnel image in the port, and perform safety helmet recognition, work clothes recognition, and reflective mark recognition. Next, human body recognition is performed. After the human body is recognized, safety helmet recognition, work clothing recognition, and reflective mark recognition are performed on the human body. If any of these three recognition methods fails to be recognized, personnel management information is generated. Simultaneously, the color of the work clothes on the person is identified. After the color is identified, it is imported into the database. The work location corresponding to the work clothes of that color is retrieved. Then, the current image acquisition location is collected. If the current image acquisition location is not the work location corresponding to the work clothes, and the person stays at the current image acquisition location for more than the preset time, personnel management information is generated.

7. A blockchain-based smart port management system according to claim 1, characterized in that: The specific processing procedure for the management information of the protective equipment is as follows: extract the collected information related to the protective equipment, which includes the length and height of the port guardrail and the number of safety warning signs; Next, port information is collected, including port area information and port shoreline length. The length of the port guardrail and the length of the port shoreline are processed to obtain guardrail evaluation parameters; The port area information and the number of safety warning signs are processed to obtain warning sign evaluation parameters; When any of the guardrail evaluation parameters or the warning sign evaluation parameters is abnormal, protective equipment management information is generated.

8. A blockchain-based smart port management system according to claim 1, characterized in that: The specific process for obtaining the security training management information is as follows: extract the collected security history information, which includes the number of security incidents within a preset time period, security training record information, and personnel safety test scores; Process the safety training records to obtain the safety training intervals; Security training management information is generated when the number of security incidents within a preset time period exceeds a preset value and the security training interval exceeds a preset value. Security training management information is also generated when the number of safety incidents within a preset time period is less than the preset value, the safety training interval is less than the preset value, but the personnel safety test score is less than the preset value.

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