Intelligent control method and intelligent control system based on digital yard

Abstract

The application provides an intelligent control method and system based on a digital yard, and relates to the technical field of computers. The method comprises the following steps: according to the task processing requirement of a target yard, controlling a collection device corresponding to the task processing requirement to collect data, and receiving the data collection result returned by the collection device; performing data analysis and processing according to the data collection result to obtain a data processing result corresponding to the task processing requirement; and uploading the data processing result to a cloud platform for information management and recording. The method realizes intelligent identification and digital management of information in the process of cargo transportation under the digital yard by using an integrated central device, improves the stability of data interaction and transmission, and thus improves the accuracy and reliability of the data processing result. Meanwhile, the complexity of device installation and the cost of devices are reduced.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to an intelligent control method and intelligent control system based on a digital freight yard. Background Technology

[0002] As the global logistics industry accelerates its digital and intelligent transformation, freight yards, as core nodes of logistics hubs, directly impact the overall operational efficiency of the supply chain. The core objective of digital freight yards is to transform traditional freight yards through digital means, integrate resource information, improve transportation efficiency, and drive the transformation of traditional freight yards into modern logistics service hubs.

[0003] Current control systems often combine multiple independent devices to achieve intelligent management of the freight yard.

[0004] However, the independent operation of each device increases the cost of use and results in poor system stability and reliability. Summary of the Invention

[0005] The purpose of this application is to address the shortcomings of the prior art by providing an intelligent control method and intelligent control system based on digital freight yards, so as to realize the intelligent and digital management of freight yards, while ensuring the stability and reliability of data processing and reducing costs.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows: In a first aspect, embodiments of this application provide an intelligent control method based on a digital freight yard, applied to a central device in an intelligent control system; the intelligent control system includes: a central device and at least one data acquisition device deployed on a spreader device in a target freight yard; the central device integrates a data acquisition and control module, an algorithm processing module, and a positioning module; each data acquisition device transmits data with the data acquisition and control module through a network exchange module; the data acquisition and control module communicates with an external cloud platform through a routing communication module; the method includes: Based on the task processing requirements of the target cargo yard, control the data acquisition device corresponding to the task processing requirements to collect data, and receive the data acquisition results returned by the data acquisition device; Based on the data collection results, data analysis and processing are performed to obtain the data processing results corresponding to the task processing requirements; The data processing results are uploaded to the cloud platform, where the cloud platform manages and records the information.

[0007] Optionally, the step of controlling the data acquisition device corresponding to the task processing requirements in the target cargo yard to perform data acquisition, and receiving the data acquisition results returned by the data acquisition device, includes: Based on the container transport monitoring requirements, data acquisition instructions are sent to at least one container number identification and acquisition device, at least one vehicle number identification and acquisition device, and at least one radio frequency identification device, respectively. Receive the first video frame sequence returned by each container number identification and acquisition device, the first video frame sequence including real-time images of containers within a first preset monitoring range acquired by the container number identification and acquisition device; The system receives a second video frame sequence returned by each vehicle number recognition and acquisition device. The second video frame sequence includes real-time images of a first type of vehicle within a second preset monitoring range collected by the vehicle number recognition and acquisition device. The first type of vehicle is a transport vehicle carrying at least one container, which is used to transport the container into the target cargo yard. The system receives RFID tags from each of the second type of vehicles returned by each RFID device. The second type of vehicles are transport vehicles that transport containers in sections, and the containers are transported to the target destination through the second type of vehicles.

[0008] Optionally, the step of performing data analysis and processing based on the data collection results to obtain the data processing results corresponding to the task processing requirements includes: The algorithm processing module calls the image detection algorithm to detect each frame in the first video frame sequence and extract the identification information of at least one container. The algorithm processing module calls the image detection algorithm to detect each frame in the second video frame sequence and extract at least one identification information of the first type of vehicle. The algorithm processing module identifies the radio frequency tags of each type of vehicle and extracts the identification information of each type of vehicle. Based on the real-time transportation images of each type of vehicle, the identification information of each type of vehicle is bound to the identification information of the container transported by each type of vehicle, and the identification information of each type of vehicle is bound to the identification information of the container transported by each type of vehicle, thus obtaining the data processing result.

[0009] Optionally, the step of controlling the data acquisition device corresponding to the task processing requirements of the target freight yard to perform data acquisition, and receiving the data acquisition results returned by the data acquisition device, includes: During the process of transporting containers by spreader equipment, a data collection command is sent to the weighing equipment according to the container weight detection requirements. The system receives the total weight of the container and the weight distribution data of each preset calibration angle of the container returned by the weighing equipment.

[0010] Optionally, the step of controlling the data acquisition device corresponding to the task processing requirements of the target freight yard to perform data acquisition, and receiving the data acquisition results returned by the data acquisition device, includes: Based on the container's location monitoring requirements, the latitude and longitude information and coordinate information of the center point of the spreader equipment are collected and obtained via the positioning module. or, Based on the container's location monitoring requirements, the latitude and longitude information and coordinate information of the center point of the spreader equipment are collected via the positioning module, and a collection command is sent to the encoder. The encoder receives the cumulative pulse value of the meter wheel during the rotation of the connecting rod shaft of the lifting device.

[0011] Optionally, the step of performing data analysis and processing based on the data collection results to obtain the data processing results corresponding to the task processing requirements includes: Based on the latitude and longitude information and coordinate information of the center point of the spreader, calculate the latitude and longitude of the center point of the container being lifted by the spreader and the layer height information of the container; or, Based on the latitude and longitude information and coordinate information of the center point of the spreader equipment, calculate the latitude and longitude of the center point of the container being lifted by the spreader equipment; The layer height information of the container is calculated based on the cumulative pulse value of the meter wheel of the encoder during the rotation of the connecting rod shaft of the spreader equipment. The latitude and longitude of the center point of the container and the layer height information of the container are bound with the identification information of the container to generate the real-time spatial location information of the container; the real-time spatial location information is used to indicate the position and layer height of the container at each moment during the lifting process by the spreader equipment.

[0012] Optionally, uploading the processing result to the cloud platform includes: Based on the container's opening and closing signals and the weight distribution data of each preset calibration angle of the container, it is determined whether the container is in a stable placement state. If so, the real-time spatial location information of the container will be sent to the cloud platform.

[0013] Optionally, the step of controlling the data acquisition device corresponding to the task processing requirements of the target freight yard to perform data acquisition, and receiving the data acquisition results returned by the data acquisition device, includes: Based on security monitoring requirements, data acquisition commands are sent to the first and second surround view acquisition devices. The system receives a third video frame sequence returned by the first surround-view acquisition device and a fourth video frame sequence returned by the second surround-view acquisition device; the third video frame sequence includes real-time images of the lifting equipment within a third preset monitoring range around the first surround-view acquisition device; the fourth video frame sequence includes real-time images of the driver inside the cab of the lifting equipment, collected by the second surround-view acquisition device.

[0014] Optionally, the step of performing data analysis and processing based on the data collection results to obtain the data processing results corresponding to the task processing requirements includes: The algorithm processing module performs target object detection and analysis on each frame in the third video frame sequence to determine a first processing result. The first processing result is used to indicate whether there is a target object in the calibration area of ​​the lifting equipment. The algorithm processing module analyzes each frame in the fourth video frame sequence to determine a second processing result, which is used to indicate the driver's behavior status. The first processing result and the second processing result are used as the data processing result.

[0015] Secondly, embodiments of this application also provide an intelligent control system, including: a central device and at least one data acquisition device deployed on a spreader in a target freight yard; the central device integrates a data acquisition and control module, an algorithm processing module, a positioning module, a network switching module, and a routing communication module; each data acquisition device transmits data with the data acquisition and control module through the network switching module; the data acquisition and control module communicates with an external cloud platform through the routing communication module; The central device is used to perform the steps of the intelligent control method based on digital freight yard as described in any one of the first aspects above.

[0016] Thirdly, embodiments of this application provide an electronic device, including: a processor, a storage medium, and a bus. The storage medium stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to realize the intelligent control method based on digital freight yards as provided in the first aspect.

[0017] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, performs the intelligent control method based on a digital freight yard as provided in the first aspect.

[0018] The beneficial effects of this application are: This application provides an intelligent control method and intelligent control system based on a digital freight yard, comprising: controlling a data acquisition device corresponding to the task processing requirements of the target freight yard to acquire data, and receiving the data acquisition results returned by the acquisition device; performing data analysis and processing based on the data acquisition results to obtain the data processing results corresponding to the task processing requirements; and uploading the data processing results to a cloud platform for information management and recording. This method achieves intelligent identification and digital management of information during cargo transportation in a digital freight yard by employing an integrated central device, improving the stability of data interaction and transmission, thereby enhancing the accuracy and reliability of the data processing results. Simultaneously, it reduces the complexity of equipment installation and equipment costs.

[0019] Secondly, by identifying and binding the identification information of containers, the identification information of the first type of vehicles, and the identification information of the second type of vehicles, discrete information can be generated into digital objects that can be automatically tracked and managed in the information system, thereby realizing the intelligent identification and management of digital freight yards.

[0020] By calculating the latitude, longitude, and layer height of the container and binding it with the container's identification information to generate real-time spatial location information, it is possible to assist drivers in performing precise operations and to achieve accurate querying of the container's location.

[0021] Safety hazards can be avoided by monitoring the target objects around the lifting equipment and the behavior of the driver.

[0022] Big data analysis based on the generated data processing results can produce standardized operation data to regulate subsequent operation standards. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A schematic diagram of the architecture of an intelligent control system provided in an embodiment of this application; Figure 2 This application provides a schematic diagram of the architecture of a central device. Figure 3 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 1 ; Figure 4A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 2 ; Figure 5 This application provides a schematic diagram of the deployment of a data acquisition device in a gantry crane application scenario. Figure 6 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 3 ; Figure 7 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 4 ; Figure 8 This application provides a schematic diagram illustrating the relationship between the calibration lifting angle, antenna verticality, and lifting position of a lifting device. Figure 9 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 5 ; Figure 10 A schematic diagram illustrating the installation relationship between the encoder and the connecting rod shaft of the lifting device provided in this application embodiment; Figure 11 A schematic diagram of the algorithm theory provided for an embodiment of this application; Figure 12 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 6 ; Figure 13 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 7 ; Figure 14 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 8 ; Figure 15 This application provides a schematic diagram of the deployment of a data acquisition device in a front-mounted crane application scenario. Figure 16 This application provides a schematic diagram of the deployment of data acquisition equipment in an access control scenario; Figure 17 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0026] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0027] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0028] Figure 1 This is a schematic diagram of the architecture of an intelligent control system provided in an embodiment of this application, as shown below. Figure 1 As shown, the intelligent control system mainly includes: central equipment, a back-end server / freight yard management platform, and terminal equipment in the cab; it also includes multiple data acquisition devices deployed on the spreader equipment in the target freight yard, including but not limited to: F-TR locks, radio frequency identification (RFID), weighing equipment, active safety cameras, 360-degree surround view cameras / intrusion detection cameras, container number recognition cameras, vehicle number recognition cameras, encoders / LiDAR, and lock / unlock triggering devices.

[0029] Lifting equipment refers to equipment used for lifting goods in a freight yard, such as reach stackers and gantry cranes. Since this solution applies to the entire process of goods transportation and loading / unloading in a digital freight yard scenario, the aforementioned data collection equipment can also be deployed on forklifts to collect data during goods transportation. Alternatively, the data collection equipment can be deployed at entrances and exits to monitor the entry and exit of goods. This embodiment primarily uses the scenario of deploying the data collection equipment on lifting equipment as an example to illustrate the method and steps.

[0030] The central device, as the core of the system, is used to control the data acquisition equipment to collect data and analyze the results. It binds the cargo identification to the transport vehicle identification, weight information, location, and floor height, etc., to record the real-time status information of the cargo during transportation. It can also record the safety information around the lifting equipment in real time. This information is uploaded by the central device to the back-end server / freight yard management platform for unified information management.

[0031] The central equipment can also upload the above information to the terminal equipment in the driver's cab, and the above information can be visualized through the visual interface of the terminal equipment.

[0032] Figure 2 This is a schematic diagram of the architecture of a central device provided in an embodiment of this application, such as... Figure 2 As shown, the central device integrates a data acquisition and control module, an algorithm processing module, a positioning module, a network switching module, and a routing communication module; each data acquisition device and the data acquisition and control module transmit data through the network switching module; the data acquisition and control module communicates with the external cloud platform through the routing communication module.

[0033] The data acquisition and control module can be implemented using an Advanced Reduced Instruction Set Machine (ARM). The main responsibility of the data acquisition and control module is to send data acquisition commands to each acquisition device, process and analyze the acquisition results returned by the acquisition devices, and send the generated analysis results to the backend server / freight yard management platform and the terminal device in the driver's cab.

[0034] The algorithm processing module is mainly used to perform tasks such as image recognition and target behavior detection; the positioning module is mainly responsible for obtaining the geographical location information of the machinery where the goods are located; the data exchange between each acquisition device and the acquisition control module is realized through the network exchange module, which can be a gigabit network exchange module; the routing communication module is a 4G / 5G communication module with routing function, and the acquisition control module can upload information to the backend server / freight yard management platform and to the terminal device through the routing communication module.

[0035] All the aforementioned modules are integrated onto a printed circuit board (PCB) to form a central device. High-speed signal interconnection between modules is achieved via PCB traces, eliminating the need for external network cables. Furthermore, all modules share a common power input unit, achieving centralized integration. The centralized design of multiple functional modules on a single PCB saves material resources, utilizes a unified power input, and eliminates redundant and unnecessary functional circuits, maximizing resource utilization, reducing costs, and increasing efficiency. This makes the central device more suitable for applications such as gantry cranes, reach stackers, and access control systems. The PCB traces between modules eliminate the need for external wiring, effectively solving the problem of slow signal response and improving the stability of signal transmission quality and the reliability of the entire system. Moreover, the integrated design reduces hardware size, allows for debugging of individual module functions during development, and enables remote commissioning after on-site installation, reducing construction and installation difficulties and saving labor costs.

[0036] In addition, the core of this solution, namely the central device, can be installed on the main device. In this embodiment, the lifting device is used as the main device. In actual application, this system can be used in different scenarios. Therefore, the central device and these acquisition devices can also be deployed on the corresponding main devices in other scenarios as needed.

[0037] The central device can connect to the main device's Controller Area Network (CAN) and RS-485 bus interface, collect data through the JT808 multimedia monitoring protocol, send the data processing results to the terminal devices on the main device for visualization display through the JT1078 protocol, and upload the data processing results to the cloud platform through the JT1078 protocol.

[0038] Central devices can use Over-the-Air (OTA) software download technology to unlock value-added functions. Through OTA software deployment, customized software functions can be implemented, enabling software expansion, e-commerce, service subscriptions, and other functions, thereby increasing the product's versatility.

[0039] Figure 3 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 1 The executing entity of this method can be the aforementioned central device, such as... Figure 3 As shown, the method includes: S101. Based on the task processing requirements of the target cargo yard, control the data acquisition device corresponding to the task processing requirements to collect data, and receive the data acquisition results returned by the data acquisition device.

[0040] The target cargo yard can refer to the cargo yard that needs to be monitored or managed. The task processing requirements can include multiple types, such as container location monitoring, weight monitoring, real-time monitoring of the transportation process, and safety monitoring.

[0041] Different task processing requirements necessitate different types of data to be processed, and these different types of data can be acquired through appropriate acquisition devices.

[0042] Based on the current task processing requirements, the acquisition control module can send data acquisition instructions to the corresponding acquisition devices. The devices that receive the acquisition instructions will collect the specified type of data within their monitoring range in real time and return the acquisition results to the acquisition control module.

[0043] S102. Perform data analysis and processing based on the data collection results to obtain the data processing results corresponding to the task processing requirements.

[0044] Depending on the data type and the required processing method, the corresponding processing method can be used for data analysis and processing to obtain the data processing results corresponding to the task processing requirements.

[0045] For example, for image data, image recognition can be performed to extract key information from the image; for text data, text processing calculations can be performed to obtain calculation results, etc.

[0046] S103. Upload the data processing results to the cloud platform for information management and recording.

[0047] The data acquisition and control module can upload the generated data processing results to the cloud platform, which can refer to the aforementioned server / freight yard management platform, where information is uniformly managed and recorded.

[0048] In summary, the intelligent control method based on a digital freight yard provided in this embodiment includes: controlling the data acquisition device corresponding to the task processing requirements of the target freight yard to collect data, and receiving the data acquisition results returned by the acquisition device; performing data analysis and processing based on the data acquisition results to obtain the data processing results corresponding to the task processing requirements; and uploading the data processing results to a cloud platform for information management and recording. This method achieves intelligent identification and digital management of information during the cargo transportation process in a digital freight yard by using an integrated central device, improving the stability of data interaction and transmission, thereby improving the accuracy and reliability of data processing results. At the same time, it reduces the complexity of equipment installation and equipment costs.

[0049] Figure 4 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 2Optionally, in step S101, based on the task processing requirements in the target cargo yard, the data acquisition device corresponding to the task processing requirements is controlled to perform data acquisition, and the data acquisition results returned by the acquisition device are received, including: S201. Based on the container transport monitoring requirements, send data acquisition instructions to at least one container number identification and acquisition device, at least one vehicle number identification and acquisition device, and at least one radio frequency identification device.

[0050] Typically, goods in a freight yard are transported primarily by containers, and each container has its own unique identifier, also known as a container serial number, used to uniquely distinguish different containers. The goods carried by each container are linked to the container itself, thus enabling the monitoring of goods through container identification.

[0051] Of course, when applied to different scenarios, the objects to be identified can be adapted and are not limited to containers.

[0052] In some embodiments, it is necessary to automatically track and manage the entire process of containers from being transported into the target yard, being lifted by spreader equipment in the target yard, being distributed and transported to different destinations, and loading and unloading of containers.

[0053] Based on the monitoring needs of container transportation, data collection instructions can be sent to container number recognition and collection equipment, vehicle number recognition and collection equipment, and radio frequency identification (RFID) equipment respectively. There may be one or more of these equipment deployed to collect relevant data from different monitoring perspectives.

[0054] Figure 5 This diagram illustrates the deployment of data acquisition equipment in a gantry crane application scenario, as provided in this embodiment. It shows six container number recognition acquisition devices, each corresponding to a different monitoring angle to capture images of containers in different areas; one vehicle number recognition acquisition device is deployed to acquire images of the first type of vehicle; and radio frequency identification (RFID) devices are typically installed on the telescopic boom of the spreader (not shown in the diagram), with two RFID devices mounted on the boom to acquire RFID tags for the second type of vehicle. It should be noted that the intelligent hub (red box) shown in the diagram is the aforementioned central device, which is the core equipment of this solution.

[0055] S202, Receive the first video frame sequence returned by the box number identification and acquisition device.

[0056] The first video frame sequence includes real-time images of containers within a first preset monitoring range captured by the container number identification and acquisition device.

[0057] After receiving the data acquisition command, each container identification and acquisition device will capture images of its own monitoring range in real time. The captured continuous frame images constitute the first video frame sequence and are sent to the acquisition control module. When a container is transported into the frame, it will be captured, and the first video frame sequence will record the real-time images of the container from entering the monitoring range to leaving the monitoring range.

[0058] S203, Receive the second video frame sequence returned by each vehicle number recognition and acquisition device.

[0059] The second video frame sequence includes real-time images of a first type of vehicle within a second preset monitoring range, captured by the vehicle number recognition and acquisition device. The first type of vehicle is a transport vehicle carrying at least one container, which is used to transport the container into the target cargo yard.

[0060] The first type of vehicle can be a train in a freight yard scenario, and trains can be divided into open wagons and flatbed wagons; usually, containers can be transported from outside to the target freight yard by the first type of vehicle.

[0061] The second video frame sequence records continuous frame images captured in real time by the vehicle number recognition and acquisition device to record the footage of the first type of vehicle transporting containers.

[0062] S204. Receive the RFID tags of each type II vehicle returned by each RFID device.

[0063] The second type of vehicle is a transport vehicle that transports containers in sections, and the containers are transported to the target destination by the second type of vehicle.

[0064] The second type of vehicle can be a container truck, which is typically used to transport containers from the target yard to the designated destination.

[0065] Typically, different containers carry different goods and may be destined for different destinations, so different containers may be transported by different Type II vehicles.

[0066] Optionally, an RFID tag will be installed on a designated part of the body of each Type II vehicle. The RFID tag is used to identify the identity information of the Type II vehicle, similar to a license plate number. The RFID device installed on the hoisting equipment can identify the RFID tags of Type II vehicles that enter the monitoring range of the RFID device in order to collect the RFID tag data of the Type II vehicles.

[0067] Figure 6 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 3Optionally, in step S102, data analysis and processing are performed based on the data collection results to obtain the data processing results corresponding to the task processing requirements, including: S301. The algorithm processing module calls the image detection algorithm to detect each frame in the first video frame sequence and extract the identification information of at least one container.

[0068] In some embodiments, after receiving the first video frame sequence, the acquisition control module can send the first video frame sequence to the algorithm processing module. The algorithm processing module calls a pre-trained Optical Character Recognition (OCR) region detection model to detect each frame in the first video frame sequence and extract the OCR region detection results.

[0069] Among them, the OCR region detection model can be obtained by training a deep learning neural network model on container sample images labeled with container identification information tags (which can be serial number tags).

[0070] Based on the OCR region detection model, OCR region detection results can be obtained from each frame. The OCR region can be a region containing character information. If an OCR region is detected in the image, the frame is cropped according to the OCR region to obtain the OCR region image. Based on the OCR region image, the character detection model is called to recognize the characters in the OCR region image to obtain the container identification information.

[0071] The character detection model is obtained by training a deep learning neural network model based on image samples labeled with character tags.

[0072] During the process of the container number identification and acquisition device acquiring images, the number of containers entering its monitoring field of view is not limited to one or more. Therefore, based on the first video frame sequence acquired by a container number identification and acquisition device, the identification information of one or more containers can be identified and extracted.

[0073] S302. The algorithm processing module calls the image detection algorithm to detect each frame in the second video frame sequence and extract the identification information of at least one type of vehicle.

[0074] The identification method for the second video frame sequence is the same as that for container identification. The identification information of the first type of vehicle is extracted from the second video frame sequence.

[0075] S303. The algorithm processing module identifies the radio frequency tags of each type of vehicle and extracts the identification information of each type of vehicle.

[0076] Each Type 2 vehicle's RFID tag contains a globally unique serial number that cannot be altered, similar to an ID card number.

[0077] When a second type of license plate carrying an RFID tag enters the recognition range of the RFID device, the RFID device identifies the RFID tag, obtains the radio frequency signal, and can restore the identification information of the second type of vehicle by demodulating the radio frequency signal.

[0078] S304. Based on the real-time transportation images of each type of vehicle, bind the identification information of each type of vehicle to the identification information of the container transported by each type of vehicle, and bind the identification information of each type of vehicle to the identification information of the container transported by each type of vehicle to obtain the data processing results.

[0079] Since each container is transported into the target yard by a specific Type 1 vehicle and ultimately transported to its corresponding destination by a designated Type 2 vehicle, in this embodiment, the real-time images of the container being transported by the Type 1 and Type 2 vehicles can be used to determine which Type 1 vehicle and which Type 2 vehicle transported the container. This allows the container's identification information to be bound to the identification information of the Type 1 vehicle, and the container's identification information to the identification information of the Type 2 vehicle. These scattered pieces of information are then bound together to generate a digital object that can be automatically tracked and managed in the information system.

[0080] Afterwards, by querying the container's identifier and based on the above binding relationship, it is possible to quickly find out which type 1 vehicle transported the container into the target freight yard and which type 2 vehicle transported it to the destination, thus realizing the digital management of the freight yard.

[0081] In some embodiments, the timestamps of each frame can also be recorded simultaneously and stored in association with the binding relationship described above, so that it can be queried later when the container was transported by which vehicle.

[0082] Figure 7 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 4 Optionally, in step S101, based on the task processing requirements of the target freight yard, the data acquisition device corresponding to the task processing requirements is controlled to perform data acquisition, and the data acquisition results returned by the acquisition device are received, including: S401. During the process of transporting a container by a spreader, a data collection command is sent to the weighing equipment according to the container weight detection requirements.

[0083] During each operation, the lifting equipment can detect the weight of the container, and the data acquisition and control module can send data acquisition instructions to the weighing equipment.

[0084] S402, Receive the total weight of the container returned by the weighing equipment and the weight distribution data of each preset calibration angle of the container.

[0085] After receiving the data acquisition command, the weighing equipment begins to detect the total weight of the container on the spreader. Additionally, it can detect off-center load data, which can be obtained by detecting the weight distribution data at each preset calibration angle of the container. These preset calibration angles refer to the four corners of the container's bottom edge. The detection results are returned to the data acquisition and control module.

[0086] The data acquisition and control module can associate and store the container's identification information with the container's total weight and the weight distribution data of each preset calibration angle, thereby enabling weight management of the container. The associated storage results will be uploaded to the cloud platform for storage and can also be sent to terminal devices for real-time display to the driver.

[0087] Optionally, in step S101, according to the task processing requirements of the target cargo yard, the data acquisition device corresponding to the task processing requirements is controlled to perform data acquisition, and the data acquisition results returned by the acquisition device are received, including: according to the location monitoring requirements of the container, the latitude and longitude information and coordinate information of the center point of the spreader equipment are acquired through the positioning module.

[0088] In some embodiments, when the lifting device is a front-end lifting device, based on the structural characteristics of the front-end lifting device itself, the latitude and longitude information and coordinate information of the center point of the lifting device can be directly collected through the positioning module.

[0089] During operation, the positioning module can collect the latitude and longitude information and coordinate information of the center point of the spreader in real time. The collection results can be transmitted to the acquisition control module through the RJ45 network port (Registered Jack 45, RJ45), and the acquisition control module can calculate the position and layer height information of the container being lifted by the spreader.

[0090] Alternatively, based on the container's location monitoring requirements, the latitude and longitude information and coordinate information of the center point of the spreader equipment can be collected via the positioning module, and a collection command can be sent to the encoder; the cumulative pulse value of the encoder's meter wheel during the rotation of the spreader equipment's connecting rod shaft can be received from the encoder.

[0091] In other embodiments, when the spreader is a gantry crane, the latitude and longitude information and coordinate information of the center point of the spreader cannot be used to calculate the container's layer height. Therefore, an encoder is required to calculate the container's layer height. Specifically, the encoder's measuring wheel can be fitted into the connecting rod shaft on the spreader, so that the rotation of the spreading machine's connecting rod shaft drives the measuring wheel. Calibration is required after the initial installation.

[0092] The data acquisition and control module needs to send data acquisition commands to the encoder. The encoder collects the cumulative pulse value of the meter wheel to calculate the layer height information of the container.

[0093] Optionally, in step S102, data analysis and processing are performed based on the data collection results to obtain the data processing results corresponding to the task processing requirements, including: calculating the latitude and longitude of the center point of the container being lifted by the spreader equipment and the layer height information of the container based on the latitude and longitude information and coordinate information of the center point of the spreader equipment.

[0094] Figure 8 This diagram illustrates the relationship between the calibration lifting angle, antenna verticality, and lifting device position of a lifting device according to an embodiment of this application. For frontal lifting, the main antenna and secondary antenna connected to the positioning module need to be installed on the lifting device. Both antennas need to be installed vertically, and the positions of the four corners of the lifting device are calibrated as 1, 2, 3, and 4 in the diagram. During operation, when the lifting device is static, the distance and azimuth offset from the main antenna to the center point of the lifting device are calculated based on the position and heading angle of the main antenna, thereby further calculating the latitude and longitude of the main antenna to the center point of the lifting device.

[0095] The calculation logic for the coordinate information of the center point of the spreading equipment is roughly as follows: The coordinates of the positioning point in the northeast plane are denoted as Pi=(Ni,Ei), where N is the north coordinate and E is the east coordinate; the azimuth angle θ is defined as the angle of clockwise rotation from north, with a value range of [0°, 360°), and is calculated by atan2(ΔE, ΔN); Angle difference normalized to ( [180°, 180°], where the deflection angle indicates the direction of rotation.

[0096] Step 1: The lifting equipment is stationary, and the positioning module is fixed. Step 2: Collect the position data of the four calibrated hanging angles 1, 2, 3, and 4 clockwise, and calculate the center point positioning data A of the rectangle formed by 1, 2, 3, and 4; Collect four points 1, 2, 3, and 4 to form a rectangle. Assume the points were collected sequentially, with points 1, 2, 3, and 4 arranged clockwise. We need to calculate the coordinates of the center point A of the rectangle. Since it's a rectangle, the center point A = ((x1+x3) / 2, (y1+y3) / 2) or ((x1+x2+x3+x4) / 4). Because the midpoints of opposite sides of the rectangle coincide, we can average the midpoints of the diagonals of points 1 and 3, or points 2 and 4. However, there might be errors in the data collection, so it's best to average the four points: ((x1+x2+x3+x4) / 4, (y1+y2+y3+y4) / 4). As long as they form a rectangle, this average will also be the center. Formula: Ax = (x1+x2+x3+x4) / 4, Ay = (y1+y2+y3+y4) / 4. Alternatively, we can use the diagonal points; since it's clockwise, points 1 and 3 are diagonal, and points 2 and 4 are diagonal. Assuming 1, 2, 3, 4 are clockwise, then 1 and 3 are diagonally opposite, and 2 and 4 are diagonally opposite. Center A = ((x1+x3) / 2, (y1+y3) / 2) = ((x2+x4) / 2, (y2+y4) / 2); Step 3: Collect the positioning data B and C of the main and secondary antennas, including the positioning data B(xb, yb) of the main antenna and the positioning data C(xc, yc) of the secondary antenna; Step 4: Calculate the heading angle K between positions B and C using B and C; Calculate the heading angle K: the azimuth from B to C. K = atan2(yc - yb, xc - xb), where x points north and y points east; 0° is north, and 90° is east. Formula: K = mod(atan2(EC - EB, NC - NB)) 180 / π, 360). (The variable names for the East / North coordinates need to be determined); Step 5: Calculate the heading angle M between positions B and A using B and A, M = atan2(EA - EB, NA - NB), and convert it to 0~360°. Step 6: Calculate the straight-line distance J between B and A using B and A, in meters. J = sqrt((NA - NB)^2 +(EA - EB)^2); Step 7: The heading angle offset X = MK. This needs to handle angle differences within the range of [-180, 180] or [0, 360), because it states later that "B offsets X° at heading angle K, and then travels Ym," so X is the rotation angle, with positive and negative indicating the direction of rotation. Usually, X = M - K, and normalization to (-180, 180] or [0, 360) is acceptable, but the offset X° can be signed. You can get a signed offset by X = (M - K + 180) mod 360 - 180, where a positive value indicates clockwise (right turn) and a negative value indicates counterclockwise (left turn). Alternatively, you can keep it within the range of 0~360. Step 8: Distance offset Y=J; Step 9: Calculate the coordinates of A from B using the formula: Offset B by X° at heading angle K, then travel Y to obtain the coordinates of A. Starting from B, rotate X° along heading angle K to obtain the new direction (M), then travel a distance Y to reach A. Formula: AN = BN + Y cos(M π / 180) = BN + Y cos((K+X) π / 180), AE = BE + Y sin(M π / 180) =BE + Y sin((K+X) (π / 180). This is obviously true because M = K + X, Y = J. Therefore, conversely, if B, K, X, Y are known, the coordinates of A can be obtained.

[0097] Figure 9 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 5 Optionally, in step S102, data analysis and processing are performed based on the data collection results to obtain the data processing results corresponding to the task processing requirements, including: S501. Calculate the latitude and longitude of the center point of the container being lifted by the spreader equipment based on the latitude, longitude, and coordinate information of the center point of the spreader equipment.

[0098] Based on the received latitude, longitude, and coordinate information of the center point of the spreader equipment, the data acquisition and control module can calculate the actual latitude, longitude, and layer height information of the container's center point according to a logical calculation formula. The actual latitude and longitude information of the container's center point indicates the container's specific spatial location, while the layer height information clarifies the container's specific location within the target cargo yard's container area.

[0099] Containers can be lifted from the ground and transported to their target locations in the container area for storage using hoisting equipment. The container area is usually divided into multiple zones, each containing multiple layers of racks. Each rack can hold multiple containers. Based on real-time calculated layer height information, it can be determined which layer the target container is on and how many layers are needed to reach the target location. Furthermore, based on the real-time calculated latitude and longitude of the container's center point, its exact location can be determined. By combining layer height information and latitude and longitude, the driver can be instructed to perform precise hoisting operations.

[0100] When a container is successfully hoisted to the floor where the target container is located, it is unloaded and placed on the target container. At this time, the floor height information and latitude and longitude can be linked with the container's identification information. Subsequently, the container's specific placement location within the container area can be queried based on the container's identification.

[0101] S502. Calculate the container's stack height information based on the cumulative pulse value of the encoder's meter wheel during the rotation of the connecting rod shaft of the spreader equipment.

[0102] During the lifting of containers, the spreader's linkage shaft is linked to the measuring wheel. The encoder transmits the data collected by the measuring wheel to the acquisition and control module via the RS-485 bus port. The acquisition and control module performs algorithm calculations. At the same time, the signal collected by the proximity switch sensor every time the linkage shaft rotates is also sent to the acquisition and control module. The module automatically corrects the parameter deviation obtained by the encoder, calculates the corrected data, and calculates the container's layer height information.

[0103] Figure 10 This diagram illustrates the installation relationship between the encoder and the connecting shaft of the lifting device, as provided in this embodiment. During calibration, the measuring wheel remains linked as the connecting shaft of the lifting device rotates. The encoder obtains raw data, and combined with the signal detected by the proximity switch sensor for each rotation of the connecting shaft, a reference parameter is calculated to determine the range of the measuring wheel corresponding to one rotation of the connecting shaft. The lifting device is operated from 0 meters above the ground to the furthest point above the ground, and then from the furthest point above the ground back to 0 meters above the ground. This process is repeated twice. If the range parameters are consistent in both operations, the data values ​​corresponding to the number of rotations of the connecting shaft in each range are compared and corrected. Correction is performed on the individual travel distance, and if the error is within the required range, the calibration is complete. Subsequent operations use the calibrated parameters and software algorithms to collect data, and the data for each rotation of the connecting shaft is automatically corrected.

[0104] Figure 11This is a schematic diagram of an algorithm theory provided in an embodiment of this application; one revolution of the connecting rod shaft is the range Q1, the total stroke Q, the range corresponding to the meter wheel is W1, the total stroke W, Q1 / W1=Q2 / W2=Qn / Wn, Qmax1 is the total range of the first connecting rod shaft, Qmax2 is the total range of the second connecting rod shaft, Nmax1 is the number of connecting rod shaft revolutions from 0 meters on the ground to the highest point in the first total range, Nmax2 is the number of connecting rod shaft revolutions from the highest point to 0 meters on the ground in the second total range, Wmax1 is the total range of the meter wheel corresponding to the total range of the first connecting rod shaft, and Wmax2 is the total range of the meter wheel corresponding to the total range of the second connecting rod shaft.

[0105] S503. Bind the latitude and longitude of the container's center point and the container's layer height information with the container's identification information to generate the container's real-time spatial location information.

[0106] Real-time spatial location information is used to indicate the position and floor height of the container at various times during the lifting process by the spreader equipment.

[0107] In some embodiments, the latitude and longitude of the container's center point and the container's layer height information, calculated in real time throughout the entire lifting process, can be bound with the container's identification information to generate real-time spatial location information of the container. This real-time spatial location information is then uploaded to the terminal device in the cab to assist the driver in performing precise lifting operations. Figure 12 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 6 Optionally, in step S103, the processing result is uploaded to the cloud platform, including: S601. Based on the container's opening and closing lock signals and the weight distribution data of each preset calibration angle of the container, determine whether the container is in a stable placement state.

[0108] In some embodiments, the container's opening and closing signals, along with the weight distribution data of each preset calibration angle of the container, can be used to determine whether the container is in a stable placement state.

[0109] During the lifting process, the container is locked. Once the container is successfully lifted and placed in the target location, it is unlocked. The driver can trigger the unlocking and locking device to control the container's locking and unlocking. The unlocking and locking device may include unlock and lock buttons. The locking and unlocking can be triggered by pressing the buttons. The unlocking and locking signal can be transmitted to the acquisition and control module through the unlocking and locking detection port.

[0110] In addition, once the container is successfully placed in the target location, the weight distribution of the container's preset calibration angle is theoretically the same (excluding minor errors). Therefore, by combining the weight distribution of the preset calibration angle and the opening and closing information, it can be determined whether the container is in a stable placement state.

[0111] S602. If so, the real-time spatial location information of the container will be sent to the cloud platform.

[0112] Once the container is in a stable position, that is, after it has been successfully placed in the target location, the data acquisition and control module can send the container's real-time spatial location information to the cloud platform for recording. Subsequently, various data during the lifting process can be queried based on the container's identification, as well as the container's specific placement location.

[0113] Figure 13 A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 7 Optionally, in step S101, based on the task processing requirements of the target freight yard, the data acquisition device corresponding to the task processing requirements is controlled to perform data acquisition, and the data acquisition results returned by the acquisition device are received, including: S701. Based on the security monitoring requirements, send acquisition instructions to the first surround view acquisition device and the second surround view acquisition device.

[0114] In some embodiments, workplace safety can also be monitored, such as... Figure 5 As shown, the first surround view acquisition device can be the personnel intrusion detection device in the figure, and the second surround view acquisition device can be a panoramic camera of the car; both the first and second surround view acquisition devices can achieve 360-degree surround view acquisition.

[0115] S702, Receive the third video frame sequence returned by the first surround view acquisition device and the fourth video frame sequence returned by the second surround view acquisition device.

[0116] The third video frame sequence includes real-time images of the third preset monitoring range around the lifting equipment captured by the first surround-view acquisition device; the fourth video frame sequence includes real-time images of the driver inside the cab of the lifting equipment captured by the second surround-view acquisition device.

[0117] The first surround view acquisition device is responsible for acquiring images around the spreader equipment, continuously monitoring the side or rear areas that are difficult for the driver to see directly, as well as information on obstacles around the spreader equipment when reversing or turning.

[0118] The second surround view acquisition device is responsible for capturing images of the driver inside the cab to monitor the driver's physiological state and behavior for safety purposes.

[0119] Figure 14A flowchart illustrating the intelligent control method based on digital freight yards provided in the embodiments of this application. Figure 8 Optionally, in step S102, data analysis and processing are performed based on the data collection results to obtain the data processing results corresponding to the task processing requirements, including: S801. The algorithm processing module performs target object detection and analysis on each frame in the third video frame sequence to determine the first processing result.

[0120] The first processing result is used to indicate whether a target object exists within the calibrated area of ​​the lifting equipment.

[0121] Based on the frames in the acquired third video frame sequence, target objects in each frame can be detected. Target objects can be people or obstacles, etc. According to the detection results, it can be determined whether a target object has appeared in the monitored area, so as to prevent unauthorized personnel from entering the site or sudden personnel or equipment from entering, causing safety hazards.

[0122] S802. The algorithm processing module analyzes each frame in the fourth video frame sequence to determine the second processing result.

[0123] The second processing result is used to indicate the driver's behavioral status.

[0124] Based on each frame in the fourth video frame sequence, the driver's behavior can be analyzed, including but not limited to: fatigue, smoking, making phone calls, taking both hands off the steering wheel, and other behaviors and actions. At the same time, the timestamps of each behavior and action can be marked to generate the driver's state and behavior detection results for each time period.

[0125] S803. The first processing result and the second processing result are used as the data processing result.

[0126] The target object detection results and driver behavior monitoring results mentioned above can be used as the final data processing results. These results can also be uploaded to the terminal equipment in the driver's cab and the cloud platform.

[0127] The terminal equipment can also remind drivers of violations and alert them to the presence of target objects around the lifting equipment through voice broadcasts or indicator lights.

[0128] In some embodiments, the cloud platform can also perform big data analysis on the received data to generate standardized database standards, which can then be used to reverse analyze the data from each operation to standardize the operation process and time.

[0129] Optionally, based on the generated data standards, timeout warnings can be issued for subsequent tasks using the standard task time, and pop-up windows and voice prompts can be provided for tasks that are about to time out or have already timed out.

[0130] For example, by using big data analysis to determine the standard time required to transport a container from point A to point B, and then using this standard time to issue warnings and announcements about the actual transportation time from point A to point B.

[0131] Optionally, the data acquisition and control module can also acquire information such as the initial installation time, maintenance records, and the most recent maintenance time of each data acquisition device. By combining this information with manually set maintenance times, maintenance prediction can be achieved to predict the next maintenance time for each data acquisition device and provide early warning prompts for device health.

[0132] Figure 15 This is a schematic diagram of the deployment of a data acquisition device in a front-mounted crane application scenario provided by an embodiment of this application. The tablet device shown in the figure can refer to the terminal device in the cab mentioned above. The RTK positioning and antenna are the positioning module and the antenna of the positioning module. The RFID identification device is also known as the radio frequency identification device. The train flatbed number identification device and the train open wagon identification device both refer to the wagon number identification and acquisition device. The 360 ​​camera realizes the functions of the first surround view acquisition device and the second surround view acquisition device.

[0133] Figure 16 This diagram illustrates the deployment of data acquisition equipment in an access control scenario, as provided in this application. The types of data acquisition equipment required and their deployment locations vary depending on the specific scenario.

[0134] In summary, the intelligent control method based on a digital freight yard provided in this embodiment includes: controlling the data acquisition device corresponding to the task processing requirements of the target freight yard to collect data, and receiving the data acquisition results returned by the acquisition device; performing data analysis and processing based on the data acquisition results to obtain the data processing results corresponding to the task processing requirements; and uploading the data processing results to a cloud platform for information management and recording. This method achieves intelligent identification and digital management of information during the cargo transportation process in a digital freight yard by using an integrated central device, improving the stability of data interaction and transmission, thereby improving the accuracy and reliability of data processing results. At the same time, it reduces the complexity of equipment installation and equipment costs.

[0135] Secondly, by identifying and binding the identification information of containers, the identification information of the first type of vehicles, and the identification information of the second type of vehicles, discrete information can be generated into digital objects that can be automatically tracked and managed in the information system, thereby realizing the intelligent identification and management of digital freight yards.

[0136] By calculating the latitude, longitude, and layer height of the container and binding it with the container's identification information to generate real-time spatial location information, it is possible to assist drivers in performing precise operations and to achieve accurate querying of the container's location.

[0137] Safety hazards can be avoided by monitoring the target objects around the lifting equipment and the behavior of the driver.

[0138] Big data analysis based on the generated data processing results can produce standardized operation data to regulate subsequent operation standards.

[0139] Figure 17 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The device can be a computing device with data processing function, and the device can be the aforementioned central device.

[0140] The device includes a processor 801, a storage medium 802, and a bus 803. The storage medium 802 stores program instructions that can be executed by the processor 801. When the electronic device is running, the processor 801 communicates with the storage medium 802 through the bus 803. The processor 801 executes the program instructions to realize the intelligent control method based on digital freight yard as described in the embodiment.

[0141] The storage medium 802 stores program code, which, when executed by the processor 801, causes the processor 801 to perform various steps in the intelligent control method based on a digital freight yard according to various exemplary embodiments of this application as described in the "Exemplary Methods" section above.

[0142] The processor 801 can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0143] Storage medium 802, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The storage medium can include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type storage medium, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic storage medium, magnetic disk, optical disk, etc. The storage medium is any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. In the embodiments of this application, storage medium 802 can also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0144] Optionally, this application also provides a program product, such as a computer-readable storage medium, including a program that, when executed by a processor, performs the above-described method embodiments.

[0145] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0146] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0147] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in a combination of hardware and software functional units.

[0148] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. An intelligent control method based on digital freight yards, characterized in that, A central device applied in an intelligent control system; the intelligent control system includes: a central device and at least one data acquisition device deployed on a spreader in a target freight yard; the central device integrates a data acquisition and control module, an algorithm processing module, and a positioning module; each data acquisition device transmits data with the data acquisition and control module through a network exchange module; the data acquisition and control module communicates with an external cloud platform through a routing communication module; the method includes: Based on the task processing requirements of the target cargo yard, control the data acquisition device corresponding to the task processing requirements to collect data, and receive the data acquisition results returned by the data acquisition device; Based on the data collection results, data analysis and processing are performed to obtain the data processing results corresponding to the task processing requirements; The data processing results are uploaded to the cloud platform, where the cloud platform manages and records the information.

2. The method according to claim 1, characterized in that, The step of controlling the data acquisition device corresponding to the task processing requirements in the target cargo yard to perform data acquisition, and receiving the data acquisition results returned by the data acquisition device, includes: Based on the container transport monitoring requirements, data acquisition instructions are sent to at least one container number identification and acquisition device, at least one vehicle number identification and acquisition device, and at least one radio frequency identification device, respectively. Receive the first video frame sequence returned by each container number identification and acquisition device, the first video frame sequence including real-time images of containers within a first preset monitoring range acquired by the container number identification and acquisition device; The system receives a second video frame sequence returned by each vehicle number recognition and acquisition device. The second video frame sequence includes real-time images of a first type of vehicle within a second preset monitoring range collected by the vehicle number recognition and acquisition device. The first type of vehicle is a transport vehicle carrying at least one container, which is used to transport the container into the target cargo yard. The system receives RFID tags from each of the second type of vehicles returned by each RFID device. The second type of vehicles are transport vehicles that transport containers in sections, and the containers are transported to the target destination through the second type of vehicles.

3. The method according to claim 2, characterized in that, The step of performing data analysis and processing based on the data collection results to obtain the data processing results corresponding to the task processing requirements includes: The algorithm processing module calls the image detection algorithm to detect each frame in the first video frame sequence and extract the identification information of at least one container. The algorithm processing module calls the image detection algorithm to detect each frame in the second video frame sequence and extract at least one identification information of the first type of vehicle. The algorithm processing module identifies the radio frequency tags of each type of vehicle and extracts the identification information of each type of vehicle. Based on the real-time transportation images of each type of vehicle, the identification information of each type of vehicle is bound to the identification information of the container transported by each type of vehicle, and the identification information of each type of vehicle is bound to the identification information of the container transported by each type of vehicle, thus obtaining the data processing result.

4. The method according to claim 1, characterized in that, The step of controlling the data acquisition device corresponding to the task processing requirements of the target freight yard to perform data acquisition, and receiving the data acquisition results returned by the data acquisition device, includes: During the process of transporting containers by spreader equipment, a data collection command is sent to the weighing equipment according to the container weight detection requirements. The system receives the total weight of the container and the weight distribution data of each preset calibration angle of the container returned by the weighing equipment.

5. The method according to claim 1, characterized in that, The step of controlling the data acquisition device corresponding to the task processing requirements of the target freight yard to perform data acquisition, and receiving the data acquisition results returned by the data acquisition device, includes: Based on the container's location monitoring requirements, the latitude and longitude information and coordinate information of the center point of the spreader equipment are collected and obtained via the positioning module. or, Based on the container's location monitoring requirements, the latitude and longitude information and coordinate information of the center point of the spreader equipment are collected via the positioning module, and a collection command is sent to the encoder. The encoder receives the cumulative pulse value of the meter wheel during the rotation of the connecting rod shaft of the lifting device.

6. The method according to claim 5, characterized in that, The step of performing data analysis and processing based on the data collection results to obtain the data processing results corresponding to the task processing requirements includes: Based on the latitude and longitude information and coordinate information of the center point of the spreader, calculate the latitude and longitude of the center point of the container being lifted by the spreader and the layer height information of the container; or, Based on the latitude and longitude information and coordinate information of the center point of the spreader equipment, calculate the latitude and longitude of the center point of the container being lifted by the spreader equipment; The layer height information of the container is calculated based on the cumulative pulse value of the meter wheel of the encoder during the rotation of the connecting rod shaft of the spreader equipment. The latitude and longitude of the center point of the container and the layer height information of the container are bound with the identification information of the container to generate the real-time spatial location information of the container; the real-time spatial location information is used to indicate the position and layer height of the container at each moment during the lifting process by the spreader equipment.

7. The method according to claim 6, characterized in that, Uploading the processing result to the cloud platform includes: Based on the container's opening and closing signals and the weight distribution data of each preset calibration angle of the container, it is determined whether the container is in a stable placement state. If so, the real-time spatial location information of the container will be sent to the cloud platform.

8. The method according to claim 1, characterized in that, The step of controlling the data acquisition device corresponding to the task processing requirements of the target freight yard to perform data acquisition, and receiving the data acquisition results returned by the data acquisition device, includes: Based on security monitoring requirements, data acquisition commands are sent to the first and second surround view acquisition devices. The system receives a third video frame sequence returned by the first surround-view acquisition device and a fourth video frame sequence returned by the second surround-view acquisition device; the third video frame sequence includes real-time images of the lifting equipment within a third preset monitoring range around the first surround-view acquisition device; the fourth video frame sequence includes real-time images of the driver inside the cab of the lifting equipment, collected by the second surround-view acquisition device.

9. The method according to claim 8, characterized in that, The step of performing data analysis and processing based on the data collection results to obtain the data processing results corresponding to the task processing requirements includes: The algorithm processing module performs target object detection and analysis on each frame in the third video frame sequence to determine a first processing result. The first processing result is used to indicate whether there is a target object in the calibration area of ​​the lifting equipment. The algorithm processing module analyzes each frame in the fourth video frame sequence to determine a second processing result, which is used to indicate the driver's behavior status. The first processing result and the second processing result are used as the data processing result.

10. An intelligent control system, characterized in that, include: The system includes a central hub and at least one data acquisition device deployed on a spreader in the target cargo yard; the central hub integrates a data acquisition and control module, an algorithm processing module, a positioning module, a network switching module, and a routing communication module; each data acquisition device transmits data with the data acquisition and control module through the network switching module; the data acquisition and control module communicates with an external cloud platform through the routing communication module. The central device is used to execute the steps of the intelligent control method based on digital freight yard as described in any one of claims 1-9.

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