A wharf yard cargo intelligent management method, system, medium and program product

Abstract

A method, system, medium, and program product for intelligent cargo management in a terminal yard are disclosed, relating to the field of data processing systems specifically designed for management purposes. The method includes: extracting the preset location of the target cargo within the terminal yard from a cargo information database based on its cargo identifier; acquiring real-time location information of multiple operating devices equipped with RFID readers / writers within the terminal yard; determining, based on the real-time location information, a target operating device located within a preset proximity range of the preset cargo location; sending a read / write command to the RFID reader / writer on the target operating device to collect tag response data from the electronic tags on the target cargo; and verifying and updating the data information of the target cargo in the cargo information database based on the tag response data to complete the inventory operation. Implementing this application can improve the accuracy of cargo inventory.

Description

Technical Field

[0001] This application relates to the field of data processing systems specifically for management purposes, and more particularly to a method, system, medium, and program product for intelligent management of cargo in a terminal yard. Background Technology

[0002] As a core node in the global logistics network, the efficiency and accuracy of cargo handling in terminal yards are crucial to the stable operation of the entire supply chain. Faced with ever-increasing cargo throughput, complex operating environments, and stringent cost control requirements, traditional management models relying on manual recording and scheduling are no longer sustainable. Therefore, exploring and applying intelligent technologies to improve the precision and efficiency of yard management has become an inevitable trend in industry development and a focus of technological research.

[0003] In this technology, an electronic management solution based on Radio Frequency Identification (RFID) is employed. Specifically, upon receiving goods, an RFID electronic tag containing its unique identification information is attached. In subsequent warehousing, inventory, or outbound processes, on-site personnel use handheld RFID readers to scan the goods within a certain range. Once the reader successfully identifies the electronic tag, the corresponding goods information is displayed on the device screen. Personnel use this information to confirm the goods' identity and complete operations such as locating or inventorying the goods.

[0004] However, due to the presence of large metal objects that frequently move within the terminal yard, such as container trucks, reach stackers, and gantry cranes, these metal objects can cause metal signal interference to the UHF band RFID signals during their movement, affecting the accuracy of cargo inventory. Summary of the Invention

[0005] This application provides a method, system, medium, and program product for intelligent management of cargo in a terminal yard, which is used to improve the accuracy of cargo inventory.

[0006] Firstly, this application provides an intelligent cargo management method for a terminal yard, applied to a management system. The method includes: extracting the preset location of the target cargo within the terminal yard from a cargo information database based on the cargo identifier of the target cargo to be inventoried; acquiring real-time location information of multiple operating devices equipped with RFID readers / writers within the terminal yard; determining, based on the real-time location information, a target operating device located within a preset proximity range of the preset cargo location among the multiple operating devices; sending a read / write command to the RFID reader / writer on the target operating device to collect tag response data from the electronic tags on the target cargo; and verifying and updating the data information of the target cargo in the cargo information database based on the tag response data to complete the inventory operation of the target cargo.

[0007] In the above embodiments, the management system utilizes mobile operating equipment with positioning systems and RFID readers already deployed in the terminal yard to dynamically associate inventory tasks with the location information of the equipment. It can select nearby operating equipment as inventory execution units based on the preset location of the goods, replacing the traditional manual handheld device search and scan operation mode. This integrates inventory operations into the daily operation process of the yard, realizes opportunistic inventory of goods, reduces reliance on manual operations, improves the execution efficiency and coverage of inventory operations, and improves the accuracy of yard goods information.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the step of determining the target operating device located within a preset proximity range of the preset location of the goods among multiple operating devices based on real-time positioning information specifically includes: determining multiple candidate devices located within a preset proximity range of the preset location of the goods; acquiring historical trajectory information of the multiple candidate devices, calculating the moving speed and moving direction of each candidate device based on the historical trajectory information; and extracting candidate devices whose moving speed is lower than a preset speed threshold and whose moving direction is towards the preset location of the goods as the target operating device.

[0009] In the above embodiments, the management system analyzes the historical trajectory of candidate devices, calculates their moving speed and direction, and filters out devices that are decelerating or approaching the target goods at a low speed. This effectively eliminates irrelevant devices that are merely passing through the target area at high speed, ensuring that the selected target operating devices have stable conditions for performing inventory operations. This improves the accuracy of device selection, avoids sending invalid instructions to unsuitable devices, and ensures the success rate and reliability of RFID data collection operations.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, after determining multiple candidate devices located within a preset proximity range of the preset location of the goods, the method further includes: selecting one of the multiple candidate devices as the main acquisition device, and selecting at least two devices located at different azimuth angles as auxiliary observation devices to form an inventory observation array; synchronously instructing the main acquisition device and the auxiliary observation devices to perform tag acquisition operations, and aggregating their respective acquisition results to generate an observation result set containing device locations and successful acquisition status; and determining the inventory environment status of the preset location of the goods based on the observation result set.

[0011] In the above embodiments, the management system constructs an inventory observation array consisting of a main acquisition device and multi-directional auxiliary observation devices to achieve multi-angle collaborative detection of the target cargo location. When the main device fails to acquire data, the system can analyze the acquisition results of the auxiliary devices to determine the cause of the failure. For example, if all devices fail to acquire data, it may indicate that the cargo is indeed not in the preset location. If only some devices fail, it may indicate that there is signal obstruction or interference in a specific direction. The system can distinguish between cargo loss and environmental interference, providing diagnostic information for inventory failure and improving the accuracy of the system's judgment of inventory results in complex yard environments.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the step of sending read / write instructions to the RFID reader / writer on the target operating equipment to collect tag response data of the electronic tags on the target goods specifically includes: calculating the real-time distance between the target operating equipment and the preset location of the goods based on the real-time positioning information of the target operating equipment; adjusting the transmission power and reading frequency of the RFID reader / writer based on the real-time distance; and sending read / write instructions to the RFID reader / writer on the target operating equipment when the real-time distance is less than a preset distance threshold to collect tag response data of the electronic tags on the target goods.

[0013] In the above embodiments, the management system can use lower power to avoid interference when the device is far away; as the device gets closer, the power is gradually increased to ensure signal penetration; and the acquisition command is triggered when the optimal reading distance is reached, ensuring that the optimal acquisition configuration is used at different distances. This effectively avoids unnecessary interference to nearby tags due to excessive power, prevents reading failures due to insufficient power, and reduces signal crosstalk while ensuring the acquisition success rate and improving the accuracy of inventory.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, before the step of acquiring the real-time location information of multiple operating devices equipped with RFID readers and writers within the dockyard, the method further includes: acquiring environmental parameter information of the dockyard; the environmental parameter information includes temperature, humidity, and metal equipment distribution density; establishing an attenuation model for RFID signal propagation based on the environmental parameter information; calculating the optimal signal acquisition parameters under different environmental conditions based on the attenuation model, and sending the optimal signal acquisition parameters to the RFID readers and writers of the multiple operating devices.

[0015] In the above embodiments, the management system acquires parameters that affect RFID signal propagation, such as temperature, humidity, and distribution of metal equipment, establishes an environmental attenuation model, and calculates the optimal RFID basic acquisition parameters accordingly. This enables the initial settings of the RFID reader / writer to proactively adapt to the current environmental conditions, rather than being passively adjusted after acquisition problems occur. This compensates for the negative impact of environmental changes on signal propagation, provides a more reliable hardware parameter basis for subsequent inventory operations, and improves the adaptability and stability of the RFID system in complex and ever-changing environments.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after the step of sending read / write instructions to the RFID reader / writer on the target work equipment to collect tag response data of electronic tags on the inventory target goods, the method further includes: continuously collecting tag information within a preset collection period to generate a response dataset containing multiple tag identities and corresponding signal strengths; calculating the occurrence frequency and cumulative signal strength of tag identities in the response dataset, and determining the dominant tag identity with the highest occurrence frequency and the highest cumulative signal strength; when the dominant tag identity is inconsistent with the goods identification of the inventory target goods, generating a proximity interference record containing the inventory target goods, the dominant tag identity, and the collection location.

[0017] In the above embodiments, the management system determines the dominant tag by calculating the frequency of tag occurrence and cumulative signal strength. This method can effectively filter out instantaneous or weak cross-read signals and identify the tag source with the most stable and strongest signal. When the identified dominant tag does not match the target goods, the system does not directly determine that the inventory has failed, but generates a nearby interference record, which improves the robustness of the identification of the target goods and provides effective data clues for discovering and locating potential problems of misplaced or overly densely stacked goods.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, after generating a proximity interference record containing the target cargo, the advantageous tag identity, and the collection location when the advantageous tag identity is inconsistent with the cargo identifier of the target cargo to be inventoried, the method further includes: extracting the advantageous preset location corresponding to the advantageous tag identity from the cargo information database; instructing another operating device located within a preset proximity range of the advantageous preset location to collect the tag indication data of the target cargo to be inventoried; and when the other operating device successfully collects the tag indication data, exchanging the cargo preset location of the target cargo to the advantageous preset location of the advantageous tag identity.

[0019] In the above embodiments, after identifying nearby interference, the management system uses the dominant tag information in the interference record to infer that the cargo positions may be swapped, and instructs the device at another location to perform reverse verification; if the cross-verification is successful, the system will exchange the position information of the two cargoes in the database, realizing closed-loop self-correction of cargo position information and improving the accuracy and real-time performance of the database information.

[0020] In a second aspect, embodiments of this application provide a management system comprising: one or more processors and a memory; the memory being coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the management system to perform the methods described in the first aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a management system, cause the management system to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a management system, cause the management system to execute the method described in the first aspect and any possible implementation thereof.

[0023] Understandably, the management system provided in the second aspect, the computer storage medium provided in the third aspect, and the computer program product provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0025] 1. By adopting a technical solution that uses the preset location of goods and combines the real-time positioning information of multiple operating equipment in the yard to determine the target operating equipment within the preset proximity range and instruct it to perform RFID collection operations, the management system can dynamically allocate inventory tasks to the most suitable mobile equipment. This effectively solves the problems of low efficiency, high labor costs, and incomplete inventory coverage caused by relying on manual operations for goods inventory in existing technologies, thereby realizing intelligent inventory of goods in the terminal yard and improving the efficiency and accuracy of inventory.

[0026] 2. By adopting a technical solution that first filters out multiple nearby candidate devices before determining the target operating device, then calculates the moving speed and direction based on their historical trajectory information, and extracts the low-speed device that is heading towards the target cargo as the final target, the management system can accurately identify devices with clear operating intentions. This effectively solves the problem in existing technologies where devices that may randomly pass by at high speed or are irrelevant to the operation may be selected, leading to data collection failures or low reliability. This optimizes the selection of target operating devices and improves the success rate of inventory instructions.

[0027] 3. By adopting a technical solution that dynamically adjusts the transmission power and reading frequency of the RFID reader based on the real-time distance between the target equipment and the preset position of the goods, and only triggers collection when the distance is less than a threshold, the management system can optimize parameters in real time for each collection task. This effectively solves the problem of short-range cross-reading interference or long-range reading failure caused by using fixed transmission power in the existing technology. As a result, it achieves fine control of the RFID collection process, reduces the misread rate, and improves the accuracy of inventory and the overall performance of the system. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating an intelligent cargo management method for a terminal yard in this application.

[0029] Figure 2 This is another flowchart illustrating the intelligent cargo management method for terminal yards in this application embodiment;

[0030] Figure 3 This is a schematic diagram of the physical device structure of a management system in an embodiment of this application. Detailed Implementation

[0031] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions a, an, the above, the, and this are intended to also include the plural expressions unless the context clearly indicates otherwise. It should also be understood that the terms used in this application refer to any or all possible combinations that include one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0033] The intelligent cargo management scenario in the terminal yard described in this application involves a series of technical terms and entities. For example, when the management system needs to inventory a specific container, that container is the target cargo. Each container has a globally unique container number, which, or its corresponding electronic code, serves as the cargo identifier. The management system uses this identifier to query its information in the cargo information database (typically part of the Terminal Operating System (TOS), including its recorded stacking location, i.e., the preset cargo location, which is usually represented in a zone-row-column-layer coordinate system.

[0034] The terminal yard operates a large number of heavy machines, such as quay cranes, yard cranes, reach stackers, container trucks, and inspection vehicles, all of which are operational equipment. These machines are equipped with high-precision differential GPS or BeiDou positioning modules, providing the management system with real-time geographic coordinates, i.e., real-time location information. Simultaneously, these machines are also equipped with RFID readers to identify electronic tags attached to cargo. When freight trucks and other external vehicles enter the yard, they are issued portable RFID readers with positioning modules, thus making them also operational equipment.

[0035] When the management system determines that a certain piece of equipment has entered within a certain distance of the preset location of the goods (i.e., the preset proximity range), it selects that equipment as the target equipment and issues a command to it. Once activated, the reader / writer emits a radio frequency signal and receives a response signal from the electronic tag. This signal contains data such as the tag's unique identification code; this is the tag response data. The management system ultimately verifies the goods information based on this data.

[0036] The following describes the process of the method provided in this implementation. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating a method for intelligent cargo management in a terminal yard, as described in this application.

[0037] S101. Based on the cargo identifier of the target cargo to be inventoried, extract the preset cargo location of the target cargo in the terminal yard from the cargo information database.

[0038] In this context, inventory target cargo refers to cargo units whose current status and location need to be confirmed, such as a container or a pallet. Cargo identification is a unique code assigned to the cargo, such as the BIC code of a container or the EPC code associated with an RFID electronic tag. The cargo information database is a central database storing detailed information about all cargo at the terminal, such as the database of the Terminal Operating System (TOS). The cargo preset location is the theoretical storage location of the cargo recorded in the database, typically a specific yard coordinate.

[0039] Specifically, when an inventory task is initiated, the management system receives the cargo identifiers for one or more goods to be inventoried. This task can be triggered by a pre-set inventory plan (such as daily full-site inventory or key area inventory) or by a specific event (such as cargo preparation confirmation before a ship arrives at port). The management system uses the received cargo identifier as a query keyword to access the cargo information database and retrieve the record corresponding to that identifier. From this record, the system extracts the location field information, which is the preset location of the target cargo for inventory, serving as the geographical target for subsequent steps.

[0040] In some embodiments, this step can be implemented in several ways to improve flexibility: Optionally, the management system can provide a batch import interface, allowing operators to upload a list file (such as a CSV or Excel file) containing multiple cargo identifiers. The system then batch processes all cargo identifiers in the list, extracting all corresponding preset locations from the database at once and generating an inventory task queue. Optionally, the management system can interface with external systems (such as shipping agency systems or customer ERP systems) via API. When an external system initiates a query request for a specific cargo, the request triggers the inventory process, and the system extracts the preset location of the cargo in real time. It is understood that other methods can also be used to implement this step, such as inputting cargo identifiers by scanning barcodes on paper work orders; this is not limited here.

[0041] In some embodiments, there may be instances where the preset location information in the cargo information database is itself incorrect or outdated. In response, the management system retrieves the location information along with its last update time or verification status field. If a location piece of information has not been verified by any operation (such as receiving, shipping, moving, or inventory) for an extended period, the system can mark it as low-reliability and assign it higher priority in subsequent inventory planning. Alternatively, it can record this as one of the possible reasons for inventory failure to aid in human decision-making.

[0042] S102. Obtain real-time location information of multiple operating devices equipped with RFID readers and writers within the dock yard.

[0043] Operating equipment refers to mobile machinery that performs cargo handling and stacking operations within the terminal yard, such as gantry cranes (RMG / RTG), reach stackers, forklifts, and container trucks. RFID readers are radio frequency identification devices installed on these operating equipment, used for contactless data communication with electronic tags on the cargo. Real-time location information is high-precision coordinate data generated by positioning systems (such as DGPS, BeiDou, and UWB) installed on the operating equipment.

[0044] Specifically, the management system establishes a continuous communication connection with all operating equipment within the site equipped with positioning modules and RFID readers. The onboard terminals on the operating equipment periodically (e.g., 1-5 times per second) send information such as latitude and longitude coordinates, altitude, and equipment ID obtained by their positioning systems to the management system via wireless networks (such as 5G or Wi-Fi). The management system receives and parses this data, maintaining a dynamic map or data table in memory representing the current location and status of all monitored equipment, providing a real-time data foundation for subsequent target equipment selection.

[0045] In some embodiments, this step can be implemented in several ways to ensure data quality: Optionally, the management system can deploy a message queue middleware (such as MQTT or Kafka), where each working device acts as a producer, publishing location data to a specific topic, and the management system acts as a consumer, subscribing to that topic. This publish / subscribe model can support large-scale device access and reduce coupling. Optionally, for location data, the management system can have a built-in data preprocessing module that uses Kalman filtering or moving average algorithms to smooth the received raw coordinate sequence, eliminating instantaneous jumps and noise in the location signal and outputting a more stable and accurate device trajectory. It is understood that other methods can also be used to implement this step, such as combining inertial measurement unit (IMU) data for fusion positioning to perform trajectory estimation during the brief period of GPS signal loss; this is not limited here.

[0046] In some embodiments, the location information of some operating devices may be interrupted or delayed. To address this, the management system assigns a timestamp and validity period to the location information of each device. If no updated data is received from a device within a preset time window (e.g., 5 seconds), the system marks it as having an unknown location or being offline, and temporarily removes it from the pool of candidate target devices available for inventory. Once the device's communication is restored and it uploads new location information, the system reinstates it to the monitoring scope, ensuring the real-time nature of the data used for decision-making.

[0047] S103. Based on real-time positioning information, determine the target operating equipment located within a preset proximity range of the preset location of the goods among multiple operating equipment.

[0048] The preset proximity range is a three-dimensional spatial area defined centered on the preset location of the goods. Its size can be configured according to factors such as the type of operation, equipment accuracy, and RFID reading distance. The target operating equipment is the specific operating equipment that, at a certain moment, physically enters the preset proximity range and is selected by the system to perform the inventory task.

[0049] Specifically, the management system continuously compares the real-time location coordinates of each operating device obtained in step S102 with the preset location coordinates of the inventory target goods extracted in step S101. For each moving operating device, the system calculates the spatial distance between it and the preset location of the target goods. When this distance is less than a threshold of a preset proximity range (e.g., a horizontal distance of less than 10 meters and a height difference that conforms to the stacking hierarchy), the management system determines that the device has entered the valid area where inventory operations can be performed and identifies it as the target operating device.

[0050] In some embodiments, this step can be implemented in several ways to optimize the selection logic: Optionally, the preset proximity range can be a dynamic, irregular shape. For example, for a gantry crane, its effective working range is a rectangular area below its main track. The system can define a corresponding polygonal area based on the type and size of the gantry crane to make more precise judgments about points within the polygon. Optionally, when multiple devices enter the proximity range simultaneously, the system can introduce a priority ranking mechanism. For example, devices performing operations related to the target cargo (such as planning to grab the cargo) have the highest priority, or devices whose type is more suitable for precise reading (such as readers on the telescopic boom of a reach stacker) have a higher priority. It is understood that other methods can also be used to implement this step, such as using the device's operating status information (such as whether the spreader is locked) to assist in the judgment, which is not limited here.

[0051] S104. Send read / write instructions to the RFID reader / writer on the target operating equipment to collect tag response data from the electronic tags on the target goods.

[0052] The read / write command is a specific command generated by the management system and sent to the target operating equipment. This command instructs the equipment to activate the RFID reader / writer and perform a tag reading operation. An electronic tag is a passive or active RFID tag attached to the inventory target goods. Tag response data is a data packet containing its unique identifier (EPC) and other possible information, reflected back after the electronic tag is activated by the reader / writer's radio frequency field.

[0053] Specifically, after the target work equipment is identified in step S103, the management system constructs a read / write instruction conforming to a predetermined communication protocol. This instruction may include parameters such as the target tag's EPC mask (if partial encoding is known), suggested read power, and read duration. The instruction is sent to the vehicle-mounted terminal of the target work equipment via a wireless network. The vehicle-mounted terminal parses the instruction and controls its connected RFID reader / writer via an internal bus (such as CAN or Ethernet). The reader / writer, according to the instruction, transmits radio frequency signals to the area pointed to by its antenna and listens for the returned tag response data. The collected data is then transmitted back to the management system.

[0054] In some embodiments, this step can be implemented in several ways to enhance the acquisition effect: Optionally, the read / write instruction can be a composite instruction that requires the read / write device to perform multiple scans within a specified time and return all read tag IDs and their corresponding Received Signal Strength Indications (RSSI). The management system can determine which tag is closest based on the RSSI value, improving the accuracy of target identification. Optionally, for read / write devices equipped with multiple antennas, the instruction can specify which antenna(s) to enable reading. For example, based on the relative position of the device and the goods, the antenna facing the direction of the goods can be selected to achieve more directional and accurate acquisition. It is understood that other methods can also be used to implement this step, such as instructing the reader / writer to perform a write operation on a specific tag to update its status, which is not limited here.

[0055] In some embodiments, signal obstruction or multipath effects may cause a read / write command to fail to acquire target tag data. To address this, the management system implements a retry mechanism. If the expected tag response data is not received within a preset timeout period after the initial command execution, the system will not immediately determine that the inventory has failed. It will wait for a short period (e.g., wait for a slight change in the location of the operating equipment) and then resend the read / write command. This retry operation can be performed a preset number of times (e.g., 3 times). Only after all retries have failed will the system mark the inventory operation as a failure and record relevant environmental parameters for analysis.

[0056] S105. Based on the tag response data, verify and update the data information of the target goods in the goods information database to complete the inventory operation of the target goods.

[0057] The verification and updating of data information refers to comparing the collected tag information with the expected information in the database, and updating the status of the goods in the database, such as inventory time and confirmed location, based on the comparison results. The completion of the inventory operation marks a successful confirmation of the presence of a single inventory target item.

[0058] Specifically, after receiving the tag response data from the target operating equipment, the management system extracts the tag EPC code. The system compares this EPC code with the known cargo identifier of the target cargo for which the inventory task was initiated. If they match, it proves that the target cargo is indeed located near its preset location, and the inventory is successful. The management system then updates the cargo record in the cargo information database; for example, updating the last inventory time to the current time and marking the location status as verified. If the received EPC code does not match the expectation, or no response is received, the inventory fails, and the system records this failure event.

[0059] In some embodiments, this step can be implemented in several ways to handle complex results: Optionally, if multiple tag responses are collected, the system will traverse all response data to find a record that matches the target cargo identifier. Even if the target tag signal is weak, as long as it exists in the response set, the inventory can be considered successful, while other strong signal tags are recorded as potential sources of interference. Optionally, when updating the database, in addition to updating the status, the system can also store information such as the operating equipment ID that performed the inventory, the precise coordinates at the time of collection, and the signal strength (RSSI) in the inventory log, providing a detailed historical record for subsequent data analysis and process optimization. It is understood that other methods can also be used to implement this step, for example, after successful verification, a notification event can be triggered to inform relevant parties (such as yard dispatchers) that the cargo has been confirmed; this is not limited here.

[0060] In some embodiments, there may be instances where the collected tag response data does not match the target cargo identifier but matches the identifier of another cargo (i.e., cross-reading). In such cases, the management system does not simply mark it as a failure. It performs a correlation query to check the preset location of the cargo corresponding to the misread tag (the interfering cargo). If the preset location of the interfering cargo is very close to the current inventory location, the system generates a proximity cross-read warning, indicating that the two cargoes may be stacked too close together, posing a risk of operational confusion, rather than directly determining an inventory failure.

[0061] To address the more complex dynamic environment in terminal yards, such as the high uncertainty of equipment movement paths and numerous sources of RFID signal interference, relying solely on basic location matching may be insufficient to guarantee the efficiency and accuracy of inventory management. Therefore, another embodiment of this application introduces more refined equipment screening, adaptive parameter adjustment, and anomaly handling mechanisms on top of the basic process to further enhance the robustness and intelligence of the method.

[0062] The following provides a more detailed description of the process of the method provided in this implementation. Please refer to [link / reference]. Figure 2 This is another flowchart illustrating the intelligent cargo management method for wharf yards in this application.

[0063] S201. Based on the cargo identifier of the target cargo to be inventoried, extract the preset cargo location of the target cargo in the terminal yard from the cargo information database.

[0064] Refer to step S101, which will not be repeated here.

[0065] S202. Obtain real-time location information of multiple operating devices equipped with RFID readers and writers within the dockyard.

[0066] Refer to step S102, which will not be repeated here.

[0067] S203. Identify multiple candidate devices located within a preset proximity range of the preset location of the goods.

[0068] Candidate equipment refers to the set of all operating equipment whose location at a given time meets the condition of entering the vicinity of the preset location of the goods. This step is the first step in the target operating equipment screening process, aiming to initially identify a pool of equipment with the potential to perform inventory checks.

[0069] Specifically, the management system executes a location comparison logic similar to step S103, but its purpose is not to select a single target device. Instead, it identifies all operating devices that meet the condition of being within a preset proximity range threshold and adds them to a temporary candidate device list. This list is dynamically updated as devices move within the yard, with some entering or leaving the proximity range. This step provides input data for subsequent, more refined screening (such as steps S204 and S205).

[0070] In some embodiments, this step can be implemented in several ways: Optionally, the system can maintain an independent candidate device list for each inventory task and set a dwell timer for each candidate device. Only devices that stay in the vicinity for more than a certain time (e.g., 2 seconds) are formally added to the candidate list to filter out devices that quickly cross the area. Optionally, when determining candidate devices, the system can initially assess the status of their RFID reader / writer devices, such as whether the device is online or whether the antenna is intact, and directly exclude devices with abnormal hardware status from the candidate list. It is understood that other methods can also be used to implement this step, such as preliminary screening based on device type, prioritizing device types more suitable for performing fine inventory (e.g., forklifts) to enter the candidate list; this is not limited here.

[0071] In some embodiments, there may be situations where no equipment enters the vicinity for an extended period, preventing the inventory task from starting. To address this, the management system sets a task waiting timeout threshold. If an inventory task, after starting, fails to identify any candidate equipment within a preset timeout period (e.g., 30 minutes), the system marks the task status as pending scheduling and can proactively send a request to the yard scheduling system, suggesting that an idle piece of equipment be dispatched to the target area to perform a dedicated inventory task, thus transforming passive waiting into proactive scheduling.

[0072] S204. Obtain historical trajectory information of multiple candidate devices, and calculate the moving speed and moving direction of each candidate device based on the historical trajectory information.

[0073] Historical trajectory information refers to a series of timestamped location coordinates of the candidate device over a short period of time (e.g., the past 10 seconds). Movement speed is the magnitude of the device's displacement per unit time. Movement direction is the direction of the device's displacement vector.

[0074] Specifically, for each candidate device identified in step S203, the management system retrieves the most recent segment of trajectory data from its location data cache. This is done by calculating the difference in location coordinates between two adjacent time points. and time difference t,

[0075] The magnitude of the instantaneous velocity can be calculated: t,

[0076] and direction: .

[0077] To obtain more stable results, the system usually performs calculations based on multiple consecutive time points. For example, the least squares method is used to perform linear fitting on a small segment of the trajectory. The slope and length of the fitted line can more accurately reflect the recent average speed and direction.

[0078] In some embodiments, the calculation process for this step can be implemented in several ways: Optionally, the system can maintain a sliding window buffer containing recent (e.g., the past minute) trajectory data of all devices. When calculation is needed, data can be efficiently retrieved directly from this buffer without having to backtrack and query the historical database each time. Optionally, the calculation of the movement direction can not only determine the device's own forward direction but also the change in the azimuth angle of the device relative to the location of the inventory target goods. This helps determine whether the device is approaching, moving away from, or circling the target. It is understood that other methods can also be used to implement this step, such as offloading the speed and direction calculation tasks to the on-board terminal of the operating equipment. The terminal directly reports the calculated motion status to the management system to reduce the computational burden on the central server.

[0079] In some embodiments, when the equipment is performing non-horizontal movement operations such as turning in place or lifting the spreader, its horizontal position changes very little, resulting in a calculated speed close to zero and an unclear direction. To address this, the management system can combine other status information obtained from the onboard terminal, such as steering wheel angle and spreader height sensor data. If the system detects that the equipment is performing such non-movement operations, even if its horizontal speed is very low, it can determine whether it is suitable to perform inventory checks based on the nature of the operation. For example, a gantry crane performing spreader lifting is very suitable for inventory checks of the container directly below it.

[0080] S205. Extract candidate equipment whose moving speed is lower than the preset speed threshold and whose moving direction is towards the preset position of the goods, and use them as target operating equipment.

[0081] The preset speed threshold is an upper speed limit used to determine whether the equipment is in a slow-moving or near-stationary state, such as 5 km / h. "Movement direction toward the preset cargo position" means that the angle between the equipment's movement direction vector and the vector pointing from the equipment's current position to the preset cargo position is less than a preset angle threshold (e.g., 30 degrees).

[0082] Specifically, the management system iterates through all candidate devices and their moving speed and direction calculated in step S204. For each candidate device, the system performs two checks:

[0083] First, check if its moving speed is less than the preset speed threshold;

[0084] Second, calculate the vector pointing from its current position to the preset position of the goods, and compare it with the movement direction vector of the equipment to check whether the angle between the two is within the allowable range.

[0085] Only candidate equipment that meets both of these conditions is considered to have a clear intention to conduct inventory and good inventory conditions, and is ultimately identified as the target equipment. If multiple equipment meet the conditions, one (e.g., the closest one) or all of them can be selected as the target.

[0086] In some embodiments, the filtering logic for this step can be implemented in several ways: Optionally, a weighted scoring model can be used instead of a simple threshold judgment. For example, the lower the speed, the higher the score; the smaller the directional angle, the higher the score; and the closer the distance, the higher the score. The system calculates the total score for each candidate device and selects the device with the highest score as the target operating device. This approach is more flexible and refined. Optionally, the filtering conditions can be associated with the device type. For example, for container trucks, the speed threshold can be set higher, while for gantry cranes running on rails, the main judgment is whether they stop above the target container position, and the weight of speed and direction can be reduced. It is understood that other methods can also be used to implement this step, which are not limited here. In some embodiments, there may be a situation where a device briefly stops near the target and then accelerates away, and is selected as the target device at the exact moment of stopping, but has already accelerated away when the instruction arrives, resulting in inventory failure. To address this, after extracting the target device, the management system can introduce a state prediction step. Based on the device's past speed and acceleration, its position and speed in the next few seconds are predicted. Only when the prediction results indicate that the equipment will remain slow or stationary is it finally confirmed as the target operating equipment and instructions are sent, thus improving the foresight of the decision-making process.

[0087] S206. Calculate the real-time distance between the target operating equipment and the preset position of the goods based on the real-time positioning information of the target operating equipment.

[0088] Among them, real-time distance refers to the three-dimensional spatial distance between the current position of the target operating equipment and the preset position of the goods, which is continuously calculated by the management system during the preparation stage before sending read and write instructions.

[0089] Specifically, after the target operating equipment is identified in step S205, the management system does not immediately send read / write commands, but instead enters a proximity monitoring phase. In this phase, the system acquires the real-time location information of the target equipment at a higher frequency (e.g., 10 times per second) and continuously calculates the Euclidean distance between it and the preset location point of the goods.

[0090] .

[0091] This real-time changing distance value will serve as the basis for further adjustments to the RFID parameters.

[0092] In some embodiments, this step can be implemented in several ways: Optionally, the distance calculation can take into account the specific structure of the equipment. For example, for a reach stacker, the system calculates not the distance from its GPS antenna position to the cargo, but rather estimates the actual distance from its front-end RFID antenna to the cargo based on the equipment's size model and the boom's extension length and angle, which is more accurate; Optionally, the distance calculation can be not only a scalar value, but also a vector, which represents not only the distance magnitude, but also the equipment's orientation relative to the cargo (such as in front, to the left, or above), providing a basis for subsequent antenna selection or beam direction adjustment. It is understood that other methods can also be used to implement this step, which are not limited here.

[0093] In some embodiments, inaccurate height (Z-axis) data in the positioning information can lead to significant errors in the calculated spatial distance. To address this, the management system can employ a simplified two-dimensional distance calculation, considering only the horizontal distance and treating height as an independent criterion. For example, only when the equipment's spreader height matches the layer height of the target goods is it considered to be at a valid inventory height, and then subsequent operations are performed based on the horizontal distance. This multi-dimensional approach reduces the reliance on Z-axis positioning accuracy.

[0094] S207. Adjust the transmission power and reading frequency of the RFID reader / writer based on real-time distance.

[0095] Transmit power refers to the strength of the radio frequency signal emitted by the RFID reader / writer, typically measured in dBm. Read frequency can be understood as the number or rate of read / write operations initiated per unit time. Adjustment based on real-time distance means these parameters are not fixed but dynamically change with distance.

[0096] Specifically, the management system internally pre-defines one or more functions / lookup tables that define the relationship between transmit power and distance. For example, a simple linear relationship could be:

[0097] ,in It's the transmission power. That is the maximum power. d is the attenuation coefficient, and d is the real-time distance. When the equipment is far from the goods, the system command reading and writing device uses lower power; as the distance decreases, the system gradually increases the power when sending commands. Simultaneously, the reading frequency can also be adjusted, for example, low-frequency attempts at long distances and high-frequency intensive readings at close distances. These adjustment commands are sent to the target operating equipment in real time.

[0098] In some embodiments, the adjustment strategy for this step can be implemented in several ways: Optionally, the adjustment strategy can be non-linear. For example, a piecewise function can be established, employing different power adjustment slopes in the long-range, medium-range, and short-range regions to more precisely match the propagation characteristics of RFID signals in space; Optionally, the adjustment strategy can be combined with the preset distance threshold in step S208, employing a parameter configuration of a search mode (lower power, wide-angle antenna) when the distance is greater than the threshold, and switching to a precise reading mode (optimized power, narrow-beam antenna) once the distance is less than the threshold. It is understood that other methods can also be used to implement this step, such as introducing a machine learning model to learn and optimize this adjustment function based on historical acquisition data (distance, power, environment, success rate), which is not limited here.

[0099] In some embodiments, there may be a network delay between the issuance of power adjustment commands and changes in device location, causing parameter adjustments to lag behind actual distance changes. To address this, the management system can attach a target parameter based on location prediction when sending the adjustment command. For example, if the system predicts that the device will arrive at a certain location in 0.5 seconds, it can directly send power parameters applicable to that future location. This predictive feedforward control can compensate for communication delays, making parameter adjustments more synchronous and effective.

[0100] S208. When the real-time distance is less than the preset distance threshold, send a read / write command to the RFID reader / writer on the target operating equipment to collect the tag response data of the electronic tags on the target goods.

[0101] The preset distance threshold is the distance limit for determining whether the device has entered the optimal reading area, for example, 3 meters. This step is the final decision point to trigger the actual inventory operation.

[0102] Specifically, during the continuous monitoring and parameter adjustment process in step S207, the management system continuously compares the calculated real-time distance with this preset distance threshold. Once the real-time distance is detected to be less than or equal to the threshold for the first time, the system immediately determines that this is the optimal time to read the data and immediately executes the operation described in step S104, that is, generating and sending the final read / write command with optimized parameters to the target operating device to perform the core tag data acquisition.

[0103] In some embodiments, the triggering mechanism for this step can be implemented in several ways: Optionally, the triggering condition can be a hysteresis comparator logic, meaning that the device must move from a distance greater than a threshold to a distance less than a threshold before triggering. If the device remains within the threshold range, the trigger will not be repeated to avoid unnecessary duplicate inventory checks. The trigger will only occur again when the device leaves the threshold range and re-enters. Optionally, the triggering condition can be combined with speed judgment. For example, it may require not only that the distance is less than the threshold but also that the device's speed is below a more stringent stationary threshold (e.g., 0.5 km / h) to ensure that the reading is performed in the most stable state of the device. It is understood that other methods can also be used to implement this step, and no limitation is made here.

[0104] In some embodiments, the device may move rapidly back and forth around the threshold, causing the trigger condition to be frequently met and not met, resulting in a large number of unstable trigger events (jitter phenomenon). To address this, the management system can introduce an entry confirmation time window. When the distance first falls below the threshold, the system starts a short timer (e.g., 0.5 seconds). Only if the device remains within the threshold range within this time window is the trigger condition finally confirmed and a command sent. This time filtering method can effectively suppress false triggers caused by position data jitter or minor device vibrations.

[0105] S209. Based on the tag response data, verify and update the data information of the target goods in the goods information database to complete the inventory operation of the target goods.

[0106] Refer to step S105, which will not be repeated here.

[0107] To further enhance the system's ability to perceive the inventory environment and its intelligence in handling abnormal situations, some embodiments of this application also introduce advanced functions such as collaborative observation, environment modeling, interference identification, and data self-correction.

[0108] In some embodiments, after determining candidate devices, in order to diagnose potential inventory failures due to reasons such as signal obstruction, the management system selects one of the multiple candidate devices as the main acquisition device and selects at least two devices located at different azimuth angles as auxiliary observation devices to form an inventory observation array; synchronously instructs the main acquisition device and auxiliary observation devices to perform tag acquisition operations, and aggregates their respective acquisition results to generate an observation result set containing device locations and acquisition success status; based on the observation result set, the inventory environment status of the preset location of the goods is determined.

[0109] The primary acquisition device is typically the candidate device that is closest or in the best location. Auxiliary observation devices are selected from the candidate devices and are located in a different orientation (relative to the target cargo) from the primary device. The inventory observation array is a temporary collaborative working group composed of these devices. The observation result set is structured data that records the location of each observation device, whether the acquisition command was successfully executed, and whether the target tag was read. The inventory environment status is a qualitative or quantitative assessment of the RFID signal reachability of the target cargo's location.

[0110] Specifically, when multiple candidate devices (e.g., three or more) are near the target cargo, the system designates one as the primary device and the rest as auxiliary devices. The system synchronously sends acquisition commands to all devices in the array. After receiving the acquisition results from all devices, the system performs a comprehensive analysis. For example, if the primary device fails, but an auxiliary device located on the other side of the cargo succeeds, the system can infer that there is signal obstruction in the direction of the primary device, but the cargo itself is in place. If all devices fail, the possibility that the cargo is not in place increases. If all devices succeed, it indicates a good signal environment.

[0111] In some embodiments, this step can be implemented in several ways: Optionally, the system can generate a local snapshot of a signal coverage heatmap based on the observation result set, visually displaying the signal strength distribution around the target cargo and providing a basis for manual judgment; Optionally, the inventory environment status can be quantified into an inventoryability score, for example, the more successful observation devices, the higher the score. This score can be stored in a database to assess the long-term inventory difficulty of a specific storage location. It is understood that other methods can also be used to implement this step, for example, when it is determined that there is an obstruction, the system can suggest to the scheduling system to relocate the obstruction (if known), which is not limited here.

[0112] In some embodiments, there may be a situation where there are not enough candidate devices to form an effective observation array. To address this, the management system can employ an alternative approach: time-series multi-point observation. When only one device is nearby, the system can instruct that device to collect data multiple times at different locations around the target cargo (e.g., by traveling a short distance around the cargo). By aggregating the data collected by the device at different times and locations, the effect of multi-angle observation can be simulated, allowing for a judgment on the inventory environment status.

[0113] In some embodiments, before the inventory task begins, the management system will proactively adapt to changes in the yard environment in order to fundamentally improve the success rate of RFID collection. That is, the management system will acquire environmental parameter information of the dock yard, including temperature, humidity and metal equipment distribution density; establish an attenuation model for RFID signal propagation based on the environmental parameter information; calculate the optimal signal collection parameters under different environmental conditions based on the attenuation model, and send the optimal signal collection parameters to the RFID reading and writing devices of multiple operating equipment.

[0114] Environmental parameter information can be obtained from environmental sensors (thermometers and hygrometers) within the yard and from the equipment scheduling system (which acquires the location and quantity of nearby large metal equipment such as other cranes and containers). The attenuation model is a mathematical model used to describe how RFID signal strength attenuates with distance, medium (air humidity), and obstacles (metal reflection and absorption). Optimal signal acquisition parameters are calculated by the model to achieve the best signal-to-noise ratio and coverage combination of RFID readers (such as transmit power, receive sensitivity, modulation method, etc.) under the current environment.

[0115] Specifically, the management system periodically collects environmental data from the entire yard or a specific area. This data is input into a pre-established signal propagation model, such as a model based on the Friis transmission equation with added environmental correction terms. The model outputs a set of optimal RFID baseline parameters for the current environment (e.g., high temperature, humidity, high metal density). The management system then broadcasts or sends these parameters individually to the RFID readers on all operating equipment within the yard, updating their default configurations. Thus, when any equipment is selected to perform inventory checks, it is already in an initial operating state optimized for the current environment.

[0116] In some embodiments, this step can be implemented in several ways: Optionally, the attenuation model can be a machine learning-based model. The system can use historical inventory data (including environmental parameters, RFID settings, and collection results) to train a neural network to predict the optimal parameters under different conditions. This model has better adaptability and accuracy than a physical model. Optionally, the distribution of optimal parameters does not have to be global but regional. The system can divide the storage yard into different environmental zones and distribute different optimal parameters to the equipment in each zone. It is understood that other methods can also be used to implement this step, which are not limited here.

[0117] In some embodiments, environmental parameters (especially the distribution of metal equipment) may change rapidly, causing delays in model calculation and parameter distribution, resulting in suboptimal parameters. To address this, the management system can combine the baseline optimal parameters calculated in this step with the dynamically adjusted parameters based on real-time distance in step S207. The baseline parameters provide a good starting point for adapting to the macroscopic environment, while the dynamic adjustment handles microscopic, real-time distance changes. The combination of these two forms a more robust parameter optimization system with complementary long and short-term cycles.

[0118] In some embodiments, after the management system collects data, in order to distinguish the target signal from nearby strong interference signals and extract effective information from them, the management system will continuously collect tag information within a preset collection period to generate a response dataset containing multiple tag identities and corresponding signal strengths; calculate the occurrence frequency and cumulative signal strength of tag identities in the response dataset, and determine the dominant tag identity with the highest occurrence frequency and the highest cumulative signal strength; when the dominant tag identity is inconsistent with the cargo identifier of the inventory target cargo, generate a nearby interference record containing the inventory target cargo, the dominant tag identity, and the collection location.

[0119] The preset acquisition period refers to a short period of continuous operation of the read / write device, such as 1-2 seconds. The response dataset is the collection of all tag information (EPC, RSSI, number of reads) read during this period. The dominant tag identity refers to the tag that performs best in the dataset, is read the most times, and has the largest total signal strength. The neighbor interference record is a structured log that records who (target cargo) was interfered with by whom (dominant tag) and where (acquisition location).

[0120] Specifically, after a read / write command is issued, the reader continuously scans within a set period. The management system collects all returned data during this period. Then, the system performs aggregate analysis on the data: grouping by tag EPC, and calculating the sum (or average) of the occurrence frequency and RSSI value for each EPC. The system identifies the EPC with the highest occurrence frequency and cumulative RSSI, defining it as the dominant tag. Finally, the system compares the EPC with the target cargo EPC for this inventory task. If they do not match, a detailed proximity interference record is created and stored in the database.

[0121] In some embodiments, this step can be implemented in several ways: Optionally, the algorithm for determining the dominant label can be more complex, such as employing a comprehensive score where the weights of frequency and signal strength can be dynamically adjusted. In open areas, the weight of RSSI can be higher; in areas with severe multipath effects, the stability of the frequency of occurrence may be more important; Optionally, the generated neighbor interference record can trigger a real-time alarm, highlighting the location on the yard map through a visualization interface to alert the dispatcher to potential cargo mixing issues in that area. It is understood that other methods can also be used to implement this step, and no limitation is made here.

[0122] In some embodiments, the signal characteristics of the target tag and interfering tags may be very similar, making it difficult to distinguish the unique dominant tag based solely on frequency and intensity. To address this, the management system can introduce phase information as an additional criterion. Modern RFID readers can provide phase information of the tag response signal; the phase of the same tag at a fixed location is relatively stable. The system can analyze the phase stability of different EPC tags, identifying tags with more stable phases as stationary tags, which are more likely to be the target source, thus improving resolution in densely stacked scenarios.

[0123] In some embodiments, after generating a proximity interference record, the management system aims not only to identify problems but also to proactively resolve data inconsistencies and achieve closed-loop self-correction. Specifically, the management system extracts the preferred preset location corresponding to the preferred tag identity from the cargo information database; instructs another operating device located within a preset proximity range of the preferred preset location to collect the tag indication data of the target cargo; and when the other operating device successfully collects the tag indication data, it exchanges the preferred cargo location of the target cargo with the preferred preset location of the preferred tag identity.

[0124] In this context, the dominant tag identity refers to the interfering tag EPC identified in the previous step. The dominant preset location is the theoretical location of this interfering tag recorded in the database. The other operating equipment is the operating equipment located near this dominant preset location. Tag indication data refers to the tag information of the original inventory target goods. Exchanging locations means updating the location fields of these two goods in the database to align them with the actual situation in the physical world.

[0125] Specifically, after generating a proximity interference record, the system initiates a cross-validation subprocess. It first queries the database to locate the correct position of the misread advantageous tag (preferred advantageous position). Then, the system applies the method of this invention to locate a working device near this preferred advantageous position and instructs it to attempt to read the tag of the original inventory target goods. If the device successfully reads the tag of the original target goods, the system obtains strong evidence that the positions of the two goods have likely been swapped. Based on this, the system performs a database operation to exchange the position records of the two goods and records this correction event.

[0126] In some embodiments, this step can be implemented in several ways: Optionally, before performing the exchange operation, the system can set up a confirmation step, such as sending a request to the dispatcher's terminal asking "Do you want to confirm correction if there is a suspected misplacement of goods?", and only performing the database exchange after manual confirmation, thus increasing the security of the operation; Optionally, if cross-validation fails (i.e., the original target goods cannot be found at the preferred preset location), the system can mark both goods as having abnormal locations and generate a work order requiring manual intervention, instead of simply ending the process. It is understood that other methods can also be used to implement this step, which are not limited here.

[0127] In some embodiments, chain misalignments may exist, such as A misaligned to B, B misaligned to C, and C misaligned to A. Simple pairwise cross-validation may not solve this problem. To address this, upon detecting a neighboring interference, the management system can delay initiating cross-validation and instead store the interference record in a pending processing pool. Once multiple related interference records have accumulated, the system can initiate a graph theory algorithm, treating goods as nodes and interference relationships as directed edges, to search for misalignment cycles or chains in the graph and propose a globally optimal correction scheme, resolving the misalignment problem of multiple goods at once.

[0128] In this embodiment, by employing a dynamic, opportunistic inventory mechanism based on the real-time location of mobile equipment, and combining a series of technical means such as intelligent screening based on equipment motion status, closed-loop parameter optimization based on real-time distance, environmental diagnosis based on multi-point collaborative observation, and closed-loop self-correction based on interference data analysis, this application can transform the inventory operation of the terminal yard from an independent, labor-intensive task into a highly intelligent data maintenance process integrated into daily operations. This effectively solves the problems of low efficiency, high cost, and insufficient accuracy in complex dynamic environments faced by traditional manual inventory or fixed RFID solutions. As a result, it achieves near real-time, high-precision verification and updating of cargo information in the terminal yard, improving the level of refinement of yard management and overall operational efficiency.

[0129] The management system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of a management system in an embodiment of this application.

[0130] It should be noted that, Figure 3 The structure of the management system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0131] like Figure 3 As shown, the management system includes a CPU 301, which can perform various appropriate actions and processes based on a program stored in ROM 302 or a program loaded from storage section 308 into RAM 303, such as executing the methods described in the above embodiments. RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via bus 304. I / O interface 305 is also connected to bus 304.

[0132] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including hard disks, etc.; and communication section 309 including network interface cards such as LAN (Local Area Network) cards, modems, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0133] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by CPU 301, it performs the various functions defined in the present invention.

[0134] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0135] Specifically, the management system in this embodiment includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it implements the intelligent cargo management method for the terminal yard provided in the above embodiment.

[0136] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the management system described in the above embodiments; or it may exist independently and not incorporated into the management system. The storage medium carries one or more computer programs that, when executed by a processor of the management system, cause the management system to implement the intelligent cargo management method for the terminal yard provided in the above embodiments.

[0137] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0138] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning if... or after... or in response to determining... or in response to detecting... Similarly, depending on the context, the phrase "when determining... or if (the stated condition or event) is interpreted as meaning if determining... or in response to determining... or in response to detecting (the stated condition or event)" or in response to detecting (the stated condition or event).

Claims

1. A method for intelligent management of cargo in a terminal yard, characterized in that, Applied to a management system, the method includes: Based on the cargo identifier of the target cargo to be inventoried, the preset location of the target cargo in the terminal yard is extracted from the cargo information database. Obtain real-time location information of multiple operating devices equipped with RFID readers and writers within the wharf yard; Based on the real-time positioning information, determine the target operating device among the plurality of operating devices that is located within a preset proximity range of the preset location of the goods; Send read / write instructions to the RFID reader / writer on the target operating equipment to collect tag response data from the electronic tags on the inventory target goods; Based on the tag response data, the data information of the target goods to be inventoried in the goods information database is verified and updated to complete the inventory operation of the target goods.

2. The method according to claim 1, characterized in that, The step of determining the target operating device located within a preset proximity range of the preset location of the goods among the plurality of operating devices based on the real-time positioning information specifically includes: Identify multiple candidate devices located within a preset proximity range of the preset location of the goods; Obtain historical trajectory information of the multiple candidate devices, and calculate the moving speed and moving direction of each candidate device based on the historical trajectory information; Candidate devices whose moving speed is lower than a preset speed threshold and whose moving direction is toward the preset position of the cargo are selected as the target operating devices.

3. The method according to claim 2, characterized in that, After the step of determining multiple candidate devices located within a preset proximity range of the preset location of the goods, the method further includes: One of the candidate devices is selected as the main acquisition device, and at least two devices located at different azimuth angles are selected as auxiliary observation devices to form a storage observation array; The synchronous instruction commands the main acquisition device and the auxiliary observation device to perform tag acquisition operations, and to aggregate their respective acquisition results to generate an observation result set that includes the device location and acquisition success status; Based on the observation results set, the inventory environment status of the goods at the preset location is determined.

4. The method according to claim 1, characterized in that, The step of sending read / write commands to the RFID reader / writer on the target operating equipment to collect tag response data from the electronic tags on the inventory target goods specifically includes: Based on the real-time positioning information of the target operating equipment, calculate the real-time distance between the target operating equipment and the preset position of the goods; The transmission power and reading frequency of the RFID reader / writer are adjusted based on the real-time distance. When the real-time distance is less than a preset distance threshold, a read / write command is sent to the RFID reader / writer on the target operating equipment to collect the tag response data of the electronic tags on the inventory target goods.

5. The method according to claim 1, characterized in that, Before the step of obtaining the real-time location information of multiple operating devices equipped with RFID readers within the terminal yard, the method further includes: Obtain environmental parameter information of the wharf yard; the environmental parameter information includes temperature, humidity, and density of metal equipment distribution; An attenuation model for RFID signal propagation is established based on the aforementioned environmental parameter information; The optimal signal acquisition parameters under different environmental conditions are calculated based on the attenuation model, and the optimal signal acquisition parameters are sent to the RFID reading and writing devices of the multiple operating equipment.

6. The method according to claim 1, characterized in that, After the step of sending read / write instructions to the RFID reader / writer on the target operating equipment to collect tag response data from the electronic tags on the inventory target goods, the method further includes: Tag information is continuously collected within a preset collection period to generate a response dataset containing multiple tag identities and corresponding signal strengths; Calculate the occurrence frequency and cumulative signal strength of the tag identities in the response dataset, and determine the dominant tag identities with the highest occurrence frequency and the highest cumulative signal strength; When the advantageous tag identity is inconsistent with the cargo identifier of the target cargo being inventoried, a proximity interference record is generated that includes the target cargo being inventoried, the advantageous tag identity, and the collection location.

7. The method according to claim 6, characterized in that, After the step of generating a proximity interference record containing the target inventory item, the advantageous tag identity, and the collection location when the advantageous tag identity does not match the item identifier of the inventory target item, the method further includes: Extract the pre-defined advantageous location corresponding to the advantageous tag identity from the cargo information database; The instruction is given to another working device located within a preset proximity range of the aforementioned advantageous preset location to collect the tag indication data of the inventory target goods; When the other operating device successfully collects the tag indication data, the preset location of the inventory target goods is exchanged with the preset location of the advantage tag identity.

8. A management system, characterized in that, The management system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the management system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are run on the management system, the management system performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the management system, the management system performs the method as described in any one of claims 1-7.

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