Intelligent storage and safety management integrated system for polyolefin products

Abstract

The application provides a kind of intelligent storage and safety control integrated system of polyolefin product, belongs to computer data processing technical field, to adopt the virtual dynamic security unit driven by creating order, and its whole life cycle collaborative control data processing method, can realize the dynamic focus of security resources and the active closed-loop management of operation risk.The application creates virtual dynamic security unit, carries out real-time, intelligent logic reorganization between static security resources and dynamic operation task, realizes the accurate focus of security ability on dynamic operation risk point and self-adaptive following, improves the pertinence and effectiveness of safety monitoring, also optimizes the overall resource utilization efficiency of system by avoiding redundant monitoring on non-operation area, carries out real-time cross verification and strategy self-adaptive adjustment on multi-source heterogeneous data inside virtual dynamic security unit.

Description

Technical Field

[0001] This invention relates to the field of computer data processing technology, and in particular to an integrated intelligent warehousing and safety management system for polyolefin products. Background Technology

[0002] As a bulk industrial raw material, polyolefin products require warehousing management involving multiple stages such as receiving, storage, inventory counting, and outbound delivery. This demands extremely high levels of safety, accuracy, and efficiency. Traditional warehousing management relies on a Warehouse Management System (WMS) for recording and updating inventory data, while video surveillance and access control systems provide physical security. These systems play their respective roles and are the fundamental technological infrastructure ensuring the normal operation of warehousing.

[0003] In existing technical solutions, warehouse management systems (WMS), video surveillance systems, and access control systems are typically deployed independently and loosely integrated. Operationally, warehouse managers process inbound and outbound orders in the WMS, generate work instructions, and then notify workers through manual scheduling or simple task assignment. Security personnel conduct macro-monitoring of the warehouse via a monitoring center's screen wall. The access control system controls the entry and exit of personnel and vehicles based on preset static permission rules. Data exchange between these systems is often asynchronous or requires manual intervention to establish connections.

[0004] The separate system architecture and operation mode have obvious defects. Security monitoring lacks targeting, and fixed monitoring strategies cannot dynamically focus on high-risk work areas that occur in real time. This results in both wasted monitoring resources and security blind spots. The data silos between systems are significant, and it is impossible to achieve automatic and real-time linkage verification of order information, operators, on-site behavior and access control permissions. This leaves room for violations and security vulnerabilities, and there is room for improvement. Summary of the Invention

[0005] This invention provides an integrated intelligent warehousing and security management system for polyolefin products. It employs a data processing method that creates order-driven virtual dynamic security units and performs collaborative management and control over them throughout their entire lifecycle. This enables dynamic focusing of security resources and proactive closed-loop management of operational risks.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, a smart warehousing and safety management integrated system for polyolefin products is provided, including: The order processing module is configured to receive and approve inbound and outbound orders for warehouse goods and generate order approval results. The virtual unit configuration module is configured to create a virtual dynamic security unit based on the order information of the inbound and outbound orders when the order review result is approved, and to configure a dynamic security strategy set for the virtual dynamic security unit; The resource dynamic binding module is configured to dynamically select a group of security devices from the global physical security device network based on the target location identifier of the virtual dynamic security unit and the dynamic security policy set, and logically bind the selected security device group to the virtual dynamic security unit to form a dedicated monitoring group and a virtual security channel. The entity compliance verification module is configured to obtain the identity of the present entity and match the identity of the present entity with the list of authorized entities of all created virtual dynamic security units. When the match is successful, the entity identity of the present entity is verified for compliance based on the dynamic security policy set. After the verification is successful, the target virtual dynamic security unit is activated, its dedicated monitoring group is instructed to enter the focused working mode, and its virtual security channel access permission is unlocked. The internal cross-verification module is configured to acquire real-time monitoring data collected by the dedicated monitoring group and work progress data reported by the associated work terminal with bidirectional communication function during the activation life cycle of the target virtual dynamic security unit, and cross-compare the two in the unit context environment to generate the unit internal verification result. The strategy adaptive intervention module is configured to dynamically adjust the dynamic security strategy set based on the internal verification results of the unit, and issue corresponding security intervention instructions to the global physical security device network or the associated operation terminal based on the adjusted dynamic security strategy set. The deconstruction and archiving module is configured to deconstruct the target virtual dynamic security unit, release all security devices bound to it, and encapsulate the operation logs and data indexes within the lifecycle of the unit into a traceable dataset for archiving after confirming that all job tasks associated with the target virtual dynamic security unit and the auxiliary tasks fed back by the auxiliary job subsystem have been completed.

[0007] Optionally, the virtual unit configuration module includes: The parameter extraction unit is used to extract job attribute parameters, warehouse location parameters, and time window parameters from the order information. The security level calculation unit is used to call a security benchmark calculation model, take the operation attribute parameters as input features, and calculate the initial security level. The spatiotemporal boundary generation unit is used to generate the unit spatial scope and unit time lifecycle of the virtual dynamic security unit based on the storage location parameters and the time window parameters. The strategy generation unit is used to call the strategy template library, inject the initial security level, the unit spatial scope, and the unit time lifecycle into the matching template, and instantiate the dynamic security strategy set.

[0008] Optionally, the resource dynamic binding module includes: A coordinate positioning unit is used to locate the core operation coordinate points in the warehouse electronic map based on the target warehouse location identifier; The path planning unit is used to call the path planning algorithm that integrates physical distance and security penalty factors, and calculate the optimal monitoring field path and necessary passage node sequence based on the core operation coordinate points and the dynamic security strategy set; The monitoring group delineation unit is used to select a set of cameras covering the optimal monitoring field of view from the global physical security device network and logically delineate them as the dedicated monitoring group based on the optimal monitoring field of view path. The channel generation unit is used to generate temporary access permission rules based on the necessary access node sequence and issue them to the associated access control devices to form the virtual security channel.

[0009] Optionally, the entity compliance verification module is specifically used to perform compliance verification as follows: Obtain the associated operational qualification requirements from the target virtual dynamic security unit, and retrieve historical qualification certificate data and real-time status data from the background database based on the on-site entity identifier; Based on the dynamic security strategy set, the qualification matching degree is calculated to generate qualification verification results, and the pre-entry conditions are parsed to generate status verification results. Perform a logical AND operation on the qualification verification result and the status verification result to generate the final compliance verification conclusion.

[0010] Optionally, the internal cross-validation module includes: The first feature extraction unit is used to perform real-time analysis on the video stream collected by the dedicated monitoring group using a scene recognition model that identifies warehousing operation behavior and cargo status, and generate a first monitoring feature sequence. The second feature extraction unit is used to parse the progress messages reported periodically by the associated job terminal and generate a second job feature sequence. The event alignment unit is used to align and associate two sets of feature sequences according to their timestamps to form a set of event pairs. The verification engine unit is used to call the rule engine, which contains logic for comparing behavioral consistency and quantity consistency, to perform logical verification on the event pair set and output the internal verification results of the unit.

[0011] Optionally, the policy adaptive intervention module is specifically used to: The abnormal event descriptions in the internal verification results of the unit are parsed, and an abnormal knowledge base that maintains the mapping relationship between abnormal features and risk levels is called to perform fuzzy matching to determine the abnormal level. Based on the anomaly level, the corresponding template is retrieved from the policy adjustment template library and applied to the currently active dynamic security policy set. The abnormal response rules are then enhanced or their ranges are corrected to generate the adjusted dynamic security policy set.

[0012] Optionally, the policy adaptive intervention module is specifically used to: When the anomaly level is low, a standardized operation reminder instruction is issued through the associated operation terminal of the two-way communication, and the dedicated monitoring group is instructed to perform video enhancement. When the anomaly level is high, cross-unit linkage instructions are executed, including sending collaborative alert requests to adjacent areas and issuing instructions to the access control system to narrow the passage range of the virtual security channel.

[0013] Optionally, the deconstruction and archiving module is specifically used for: Monitor the completion status of core inbound and outbound orders, and trigger unit destructive instructions based on the inspection or inventory completion confirmation signals fed back by the auxiliary operation subsystem. Based on the deconstruction instruction, the logical delineation of the dedicated monitoring group is revoked and the temporary access permission rule is deleted; All operation logs and records generated during the lifecycle of this unit are aggregated to generate a structured archive, which is then encrypted and digitally signed before being packaged to generate the traceable dataset.

[0014] Optionally, the system further includes a policy self-learning optimization module, configured for: Regularly collect archived datasets and extract unit operation efficiency indicators and anomaly handling indicators to form historical performance datasets; The historical performance dataset is used as a training sample and input into a machine learning model for maximizing the comprehensive benefit function for iterative training. Based on the training output, update the system's initial policy configuration parameters or device invocation rules, and apply the optimized policy generation rules to the subsequent configuration process of virtual dynamic security units.

[0015] Secondly, a method for integrated intelligent warehousing and safety management of polyolefin products is provided, which specifically includes the following steps: Receive and approve inbound and outbound orders for warehouse goods, and generate order approval results; When the order review result is approved, a virtual dynamic security unit is created based on the order information of the inbound and outbound orders, and a set of dynamic security strategies is configured for the virtual dynamic security unit; Based on the target location identifier of the virtual dynamic security unit and the dynamic security policy set, a group of security devices is dynamically selected from the global physical security device network, and the selected security device group is logically bound to the virtual dynamic security unit to form a dedicated monitoring group and a virtual security channel. Obtain the identifier of the present entity and match the present entity identifier with the list of authorized entities of all created virtual dynamic security units to obtain the matching result; When the matching result indicates that the present entity identifier is successfully matched with a target virtual dynamic security unit, the present entity identifier is subjected to compliance verification based on the dynamic security policy set of the target virtual dynamic security unit, and a compliance verification conclusion is obtained. If the compliance verification result is passed, the target virtual dynamic security unit is activated, its dedicated monitoring group is instructed to enter the focused working mode, and its virtual security channel access permission is unlocked. During the activation lifecycle of the target virtual dynamic security unit, real-time monitoring data collected by its dedicated monitoring group and work progress data reported by associated work terminals are obtained, and the real-time monitoring data and work progress data are cross-compared in the context of the target virtual dynamic security unit to generate internal verification results. Based on the internal verification results of the unit, the dynamic security strategy set of the target virtual dynamic security unit is dynamically adjusted to generate the adjusted dynamic security strategy set, and the corresponding security intervention command is executed based on the adjusted dynamic security strategy set. After confirming that all job tasks associated with the target virtual dynamic security unit have been completed, the target virtual dynamic security unit is deconstructed, all security devices bound to it are released, and all operation logs and data indexes during the lifecycle of the unit are encapsulated into a traceable dataset for archiving.

[0016] Thirdly, an electronic device is provided, comprising: a processor and a memory; the memory is used to store a computer program, which, when executed by the processor, causes the electronic device to perform the integrated intelligent warehousing and security management system for polyolefin products described in the first aspect.

[0017] In one possible design, the electronic device described in the third aspect may further include a transceiver. This transceiver may be a transceiver circuit or an interface circuit. The transceiver can be used for communication between the electronic device described in the third aspect and other electronic devices.

[0018] In the embodiments of the present invention, the electronic device described in the third aspect may be a terminal, or a chip (system) or other component or assembly disposed in the terminal, or a system containing the terminal.

[0019] Fourthly, a computer-readable storage medium is provided, comprising: a computer program or instructions; when the computer program or instructions are executed on a computer, the computer causes the computer to execute the integrated intelligent warehousing and safety management system for polyolefin products described in the first aspect.

[0020] In summary, the above methods and systems have the following technical effects: This invention creates virtual dynamic security units, which intelligently and in real-time logically reorganize static security resources with dynamic operational tasks. This enables security capabilities to accurately focus on and adaptively follow dynamic operational risk points, improving the targeting and effectiveness of security monitoring. Furthermore, by avoiding redundant monitoring of non-operational areas, it optimizes the overall resource utilization efficiency of the system. Through real-time cross-validation and adaptive strategy adjustment of multi-source heterogeneous data within the virtual dynamic security unit, it can instantly detect potential operational anomalies and implement tiered interventions, enhancing the initiative and response speed of risk management and reducing the probability of safety incidents such as cargo damage and misdelivery. By encapsulating the entire process data of each operation into an independent, tamper-proof dataset, it provides a complete and reliable chain of evidence for post-event auditing and liability determination. This highly transparent management not only enhances the credibility of warehouse operations but also provides a solid data foundation for continuous optimization of management processes and security strategies. Attached Figure Description

[0021] Figure 1 A flowchart illustrating the integrated intelligent warehousing and safety management system for polyolefin products provided in this embodiment of the invention. Detailed Implementation

[0022] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0023] In this embodiment of the invention, "instruction" can include direct and indirect instructions, as well as explicit and implicit instructions. The information indicated by a certain piece of information is called the information to be instructed. In specific implementation, there are many ways to instruct the information to be instructed, such as, but not limited to, directly instructing the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly instruct the information to be instructed by instructing other information, where there is a correlation between the other information and the information to be instructed. It can also instruct only a part of the information to be instructed, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. Simultaneously, common parts of various pieces of information can be identified and uniformly indicated to reduce the instruction overhead caused by individually indicating the same information.

[0024] Furthermore, the specific indication method can also be any existing indication method, such as, but not limited to, the above-mentioned indication methods and their various combinations. Specific details of various indication methods can be found in existing technologies, and will not be elaborated upon here. As described above, for example, when multiple pieces of information of the same type need to be indicated, the indication methods for different pieces of information may differ. In specific implementation, the required indication method can be selected according to specific needs. This embodiment of the invention does not limit the selected indication method; therefore, the indication methods involved in this embodiment of the invention should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated.

[0025] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information messages sent separately, and the sending period and / or timing of these sub-information messages can be the same or different. The specific sending method is not limited in this embodiment of the invention. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the sending device by sending configuration information to the receiving device.

[0026] "Predefined" or "pre-configured" can be achieved by pre-saving corresponding codes, tables, or other means that can be used to indicate relevant information in the device. This embodiment of the invention does not limit the specific implementation method. "Saving" can refer to saving in one or more memories. These memories can be separate installations or integrated into the encoder, decoder, processor, or electronic device. Alternatively, some memories can be separately installed, while others are integrated into the decoder, processor, or electronic device. The type of memory can be any form of storage medium, and this embodiment of the invention does not limit this.

[0027] In the embodiments of this invention, the “protocol” may refer to a protocol family in the field of communication, a standard protocol with a similar protocol family frame structure, or a related protocol applied to the intelligent warehousing and safety management integrated system for future polyolefin products. The embodiments of this invention do not specifically limit this.

[0028] In this embodiment of the invention, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a specific time. They do not require the device to make a judgment action during implementation, nor do they imply any other limitations.

[0029] In the description of the embodiments of the present invention, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of the present invention is merely a description of the relationship between the related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of the embodiments of the present invention, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Additionally, to facilitate a clear description of the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or order of execution, and that "first," "second," etc., are not necessarily different. Furthermore, in the embodiments of this invention, words such as "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this invention should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0030] The network architecture and business scenarios described in the embodiments of this invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0031] Figure 1 This is a flowchart illustrating the method provided in an embodiment of the present invention. The integrated intelligent warehousing and safety management system for polyolefin products includes: The order processing module is configured to receive and approve inbound and outbound orders for warehouse goods and generate order approval results. The virtual unit configuration module is configured to create a virtual dynamic security unit based on the order information of the inbound and outbound orders when the order review result is approved, and to configure a dynamic security strategy set for the virtual dynamic security unit; The resource dynamic binding module is configured to dynamically select a group of security devices from the global physical security device network based on the target location identifier of the virtual dynamic security unit and the dynamic security policy set, and logically bind the selected security device group to the virtual dynamic security unit to form a dedicated monitoring group and a virtual security channel. The entity compliance verification module is configured to obtain the identity of the present entity and match the identity of the present entity with the list of authorized entities of all created virtual dynamic security units. When the match is successful, the entity identity of the present entity is verified for compliance based on the dynamic security policy set. After the verification is successful, the target virtual dynamic security unit is activated, its dedicated monitoring group is instructed to enter the focused working mode, and its virtual security channel access permission is unlocked. The internal cross-verification module is configured to acquire real-time monitoring data collected by the dedicated monitoring group and work progress data reported by the associated work terminal with bidirectional communication function during the activation life cycle of the target virtual dynamic security unit, and cross-compare the two in the unit context environment to generate the unit internal verification result. The strategy adaptive intervention module is configured to dynamically adjust the dynamic security strategy set based on the internal verification results of the unit, and issue corresponding security intervention instructions to the global physical security device network or the associated operation terminal based on the adjusted dynamic security strategy set. The deconstruction and archiving module is configured to deconstruct the target virtual dynamic security unit, release all security devices bound to it, and encapsulate the operation logs and data indexes within the lifecycle of the unit into a traceable dataset for archiving after confirming that all job tasks associated with the target virtual dynamic security unit and the auxiliary tasks fed back by the auxiliary job subsystem have been completed.

[0032] The specific physical mapping is as follows: The cloud-based management layer, including the order processing and virtual unit configuration modules, is deployed on a private cloud server. It receives WMS commands via RESTful API and uses Redis to store unit states. Edge parsing layer: The internal cross-validation module runs on the nearest AI edge computing gateway in the storage area, such as an inference box with an integrated GPU. It pulls the camera video stream via the RTSP protocol and uses MQTT to receive progress messages from the PDA handheld terminal. Physical end-point execution layer perception, dedicated monitoring group corresponding to IP camera cluster; physical compliance verification corresponding to RFID card reader and biometric terminal at the entrance; During control, the virtual safety channel is mapped to an access control electric lock and an audio-visual guidance device driven by a PLC controller; During communication, the global security equipment and associated operation terminals achieve two-way closed-loop linkage through Wi-Fi 6 or 5G industrial private network.

[0033] Optionally, the virtual unit configuration module includes: The parameter extraction unit is used to extract job attribute parameters, warehouse location parameters, and time window parameters from the order information. The security level calculation unit is used to call a security benchmark calculation model, take the operation attribute parameters as input features, and calculate the initial security level. The spatiotemporal boundary generation unit is used to generate the unit spatial scope and unit time lifecycle of the virtual dynamic security unit based on the storage location parameters and the time window parameters. The strategy generation unit is used to call the strategy template library, inject the initial security level, the unit spatial scope, and the unit time lifecycle into the matching template, and instantiate the dynamic security strategy set.

[0034] In one specific embodiment, the process of verifying the results within the generation unit specifically includes: During the activation of the target virtual dynamic security unit, the system performs dual-stream feature extraction in parallel.

[0035] The first path: Collects video streams from a dedicated monitoring group, feeds them into a scene recognition model based on a convolutional neural network, identifies operational behavior events and cargo status events in real time, and outputs a first monitoring feature sequence with timestamps and confidence scores.

[0036] The second route: receives progress messages from associated operation terminals according to a preset communication cycle, parses and extracts the operation action type and cargo processing quantity, adds a receiving timestamp, and generates a second operation feature sequence.

[0037] The system uses a unified timeline as a benchmark and uses a preset time window, such as 5 seconds before and after, to align and associate the first monitoring feature sequence and the second operation feature sequence to form an event pair set. Then, it calls the verification rule engine to perform behavior consistency rule verification and quantity consistency error verification on the event pair set. When there is a conflict between the monitoring feature and the operation feature in the time dimension or logical dimension, it outputs a comprehensive internal verification result including an abnormal event description and confidence score.

[0038] In one specific embodiment, the scene recognition model employs a spatiotemporal behavior detection neural network jointly constructed based on a deep residual network (ResNet) and YOLO architecture. The offline training process of this model includes: collecting historical surveillance videos from the warehouse site containing typical operational events, such as forklift lifting, manual handling, and unauthorized crossing of boundaries, as a training sample set; manually labeling the entity targets and their behavioral states in the video frames to generate ground truth values ​​containing bounding box coordinates and category labels; calculating the error between the network output and the ground truth values ​​using the cross-entropy loss function, and updating the network weights through the backpropagation algorithm. During the online deployment phase, the model extracts the real-time video stream into a continuous sequence of image frames and inputs it into the network, outputting a feature tensor with timestamps, event categories, and confidence scores, thereby parsing and generating the first surveillance feature sequence.

[0039] Optionally, the resource dynamic binding module includes: A coordinate positioning unit is used to locate the core operation coordinate points in the warehouse electronic map based on the target warehouse location identifier; The path planning unit is used to call the path planning algorithm that integrates physical distance and security penalty factors, and calculate the optimal monitoring field path and necessary passage node sequence based on the core operation coordinate points and the dynamic security strategy set; The monitoring group delineation unit is used to select a set of cameras covering the optimal monitoring field of view from the global physical security device network and logically delineate them as the dedicated monitoring group based on the optimal monitoring field of view path. The channel generation unit is used to generate temporary access permission rules based on the necessary access node sequence and issue them to the associated access control devices to form the virtual security channel.

[0040] In one specific embodiment, the invocation of a path planning algorithm capable of integrating physical distance and security strategies specifically employs an improved A* (A-Star) heuristic search algorithm. In the topological node network of the warehouse electronic map, this algorithm calculates the comprehensive cost of node expansion using the following cost function incorporating security factors:

[0041] Where F(n) is the comprehensive cost of node n; G(n) is the actual physical movement distance from the starting point to the current node n; H(n) is the heuristic estimated distance from node n to the core operation coordinate point (such as the Manhattan distance); S(n) is the security penalty factor, which is quantified by the system based on the camera coverage density of node n and whether it overlaps with high-risk operation areas. For example, when a node has no camera coverage, S(n) takes a maximum value to reduce the probability that the path is selected. , , All are preset optimization weight coefficients, and ; Optionally, the entity compliance verification module is specifically used to perform compliance verification as follows: Obtain the associated operational qualification requirements from the target virtual dynamic security unit, and retrieve historical qualification certificate data and real-time status data from the background database based on the on-site entity identifier; Based on the dynamic security strategy set, the qualification matching degree is calculated to generate qualification verification results, and the pre-entry conditions are parsed to generate status verification results. Perform a logical AND operation on the qualification verification result and the status verification result to generate the final compliance verification conclusion.

[0042] In one specific embodiment, the anomaly knowledge base is maintained using a Trie Tree data structure, which maps historically accumulated anomaly event feature vectors to preset risk levels. When parsing the anomaly event description, the system extracts a multi-dimensional feature string containing data source conflict type, entity object, and spatial boundary crossing flags. Subsequently, using a fuzzy matching algorithm based on Levenshtein Distance, the similarity score between the feature string and the standard anomaly templates in the leaf nodes of the trie tree is calculated. The level corresponding to the template with the highest similarity score and a value greater than a threshold is selected as the final determined anomaly level. Optionally, the internal cross-validation module includes: The first feature extraction unit is used to perform real-time analysis on the video stream collected by the dedicated monitoring group using a scene recognition model that identifies warehousing operation behavior and cargo status, and generate a first monitoring feature sequence. The second feature extraction unit is used to parse the progress messages reported periodically by the associated job terminal and generate a second job feature sequence. The event alignment unit is used to align and associate two sets of feature sequences according to their timestamps to form a set of event pairs. The verification engine unit is used to call the rule engine, which contains logic for comparing behavioral consistency and quantity consistency, to perform logical verification on the event pair set and output the internal verification results of the unit.

[0043] In one specific embodiment, configuring a dynamic security policy set for the virtual dynamic security unit specifically includes the following steps: Step A1: Extract the operation attribute parameters from the received inbound and outbound order data packets. The operation attribute parameters include the goods value level and the operation complexity level.

[0044] Step A2: Invoke the preset security level calculation model, using the cargo value level and operational complexity level as input features, to calculate the initial security level; the security level calculation model specifically adopts the following weighted evaluation formula:

[0045] Where L represents the initial security level of the output (e.g., a discrete integer from level 1 to level 3); V represents the cargo value level obtained from the product master data table; and C represents the operational complexity level calculated based on the cargo's physical attributes and loading / unloading tool requirements. and These are the weighting coefficients for the impact of goods value and the weighting coefficients for the impact of operational complexity, preset in the system configuration file, for example... f is a preset rounding or piecewise mapping function.

[0046] Step A3: Parse the warehouse location parameters and time window parameters of the inbound and outbound orders, expand the preset buffer radius outward at the corresponding coordinates on the warehouse electronic map to generate the unit space scope; and add preset preparation margin and cleanup margin based on the time window parameters to generate the unit time lifecycle.

[0047] Step A4: Using the calculated initial security level as an index, match the corresponding rule template from the policy template library, and inject the unit space scope and unit time lifecycle as constraints into the rule template to instantiate and generate a dynamic security policy set specific to the current virtual dynamic security unit. Optionally, the policy adaptive intervention module is specifically used to: The abnormal event descriptions in the internal verification results of the unit are parsed, and an abnormal knowledge base that maintains the mapping relationship between abnormal features and risk levels is called to perform fuzzy matching to determine the abnormal level. Based on the anomaly level, the corresponding template is retrieved from the policy adjustment template library and applied to the currently active dynamic security policy set. The abnormal response rules are then enhanced or their ranges are corrected to generate the adjusted dynamic security policy set.

[0048] Optionally, the policy adaptive intervention module is specifically used to: When the anomaly level is low, a standardized operation reminder instruction is issued through the associated operation terminal of the two-way communication, and the dedicated monitoring group is instructed to perform video enhancement. When the anomaly level is high, cross-unit linkage instructions are executed, including sending collaborative alert requests to adjacent areas and issuing instructions to the access control system to narrow the passage range of the virtual security channel.

[0049] Optionally, the deconstruction and archiving module is specifically used for: Monitor the completion status of core inbound and outbound orders, and trigger unit destructive instructions based on the inspection or inventory completion confirmation signals fed back by the auxiliary operation subsystem. Based on the deconstruction instruction, the logical delineation of the dedicated monitoring group is revoked and the temporary access permission rule is deleted; All operation logs and records generated during the lifecycle of this unit are aggregated to generate a structured archive, which is then encrypted and digitally signed before being packaged to generate the traceable dataset.

[0050] Optionally, the system further includes a policy self-learning optimization module, configured for: Regularly collect archived datasets and extract unit operation efficiency indicators and anomaly handling indicators to form historical performance datasets; The historical performance dataset is used as a training sample and input into a machine learning model for maximizing the comprehensive benefit function for iterative training. Based on the training output, update the system's initial policy configuration parameters or device invocation rules, and apply the optimized policy generation rules to the subsequent configuration process of virtual dynamic security units.

[0051] In one specific embodiment, the optimization of the policy generation rules specifically includes: The system periodically decrypts and parses archived historical datasets to extract unit operation efficiency indicators that characterize resource utilization, as well as anomaly handling indicators that measure the effectiveness of risk management.

[0052] The system groups the indicator data according to the initial security strategy configuration parameters to form a performance profile, and uses the initial security strategy configuration parameters as input features to feed into a pre-set machine learning model. The machine learning model iteratively optimizes itself by maximizing the comprehensive benefit function as the training objective. The specific formula of the comprehensive benefit function is as follows:

[0053] Where S represents the comprehensive benefit score; E represents the comprehensive efficiency index after normalizing the unit operation efficiency indicators; and R represents the comprehensive risk index after normalizing the anomaly handling indicators. and These are preset weighting coefficients used to balance system operating efficiency and safety level.

[0054] Through iterative training of the machine learning model, updated weight coefficient combinations or device call boundary parameters are output, thereby generating optimized policy generation rules that override the current system configuration.

[0055] The system provided by the embodiments of the present invention has been described in detail above. The method for implementing the system provided by the embodiments of the present invention is described in detail below, specifically including the following steps: Receive and approve inbound and outbound orders for warehouse goods, and generate order approval results; When the order review result is approved, a virtual dynamic security unit is created based on the order information of the inbound and outbound orders, and a set of dynamic security strategies is configured for the virtual dynamic security unit; Based on the target location identifier of the virtual dynamic security unit and the dynamic security policy set, a group of security devices is dynamically selected from the global physical security device network, and the selected security device group is logically bound to the virtual dynamic security unit to form a dedicated monitoring group and a virtual security channel. Obtain the identifier of the present entity and match the present entity identifier with the list of authorized entities of all created virtual dynamic security units to obtain the matching result; When the matching result indicates that the present entity identifier is successfully matched with a target virtual dynamic security unit, the present entity identifier is subjected to compliance verification based on the dynamic security policy set of the target virtual dynamic security unit, and a compliance verification conclusion is obtained. If the compliance verification result is passed, the target virtual dynamic security unit is activated, its dedicated monitoring group is instructed to enter the focused working mode, and its virtual security channel access permission is unlocked. During the activation lifecycle of the target virtual dynamic security unit, real-time monitoring data collected by its dedicated monitoring group and work progress data reported by associated work terminals are obtained, and the real-time monitoring data and work progress data are cross-compared in the context of the target virtual dynamic security unit to generate internal verification results. Based on the internal verification results of the unit, the dynamic security strategy set of the target virtual dynamic security unit is dynamically adjusted to generate the adjusted dynamic security strategy set, and the corresponding security intervention command is executed based on the adjusted dynamic security strategy set. After confirming that all job tasks associated with the target virtual dynamic security unit have been completed, the target virtual dynamic security unit is deconstructed, all security devices bound to it are released, and all operation logs and data indexes during the lifecycle of the unit are encapsulated into a traceable dataset for archiving.

[0056] The electronic device provided in this embodiment of the invention, exemplarily, can be a network device, or a chip (system) or other component or assembly that can be disposed in a network device. The electronic device may include a processor. Optionally, the electronic device may also include a memory and / or a transceiver. The processor is coupled to the memory and transceiver, for example, by means of a communication bus connection.

[0057] The following is a detailed introduction to the various components of the electronic device: In this context, the processor is the control center of the electronic device. It can be a single processor or a collective term for multiple processing elements. For example, a processor can be one or more central processing units (CPUs), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0058] Alternatively, the processor can perform various functions of the electronic device, such as the methods described above, by running or executing software programs stored in memory and by calling data stored in memory.

[0059] In a specific implementation, as one example, the processor may include one or more CPUs, such as CPU0 and CPU1.

[0060] In a specific implementation, as one example, the electronic device may also include multiple processors. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0061] The memory is used to store the software program that executes the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can be referred to the above method embodiment, and will not be repeated here.

[0062] Optionally, the memory can be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, random access memory (RAM) or other types of dynamic storage devices capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory can be integrated with the processor or exist independently and coupled to the processor through the interface circuit of the electronic device; the embodiments of the present invention do not specifically limit this.

[0063] A transceiver is used for communication with other electronic devices. For example, if the electronic device is a terminal, the transceiver can be used to communicate with a network device or with another terminal device. Similarly, if the electronic device is a network device, the transceiver can be used to communicate with a terminal or with another network device.

[0064] Optionally, the transceiver may include a receiver and a transmitter. The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.

[0065] Optionally, the transceiver can be integrated with the processor or exist independently and coupled to the processor through the interface circuit of the electronic device. This embodiment of the invention does not specifically limit this.

[0066] It is understood that the structure of the electronic device in this embodiment does not constitute a limitation on the electronic device. The actual electronic device may include more or fewer components, or combine certain components, or have different component arrangements.

[0067] Furthermore, the technical effects of the electronic device can be referred to the technical effects of the method described in the above method embodiments, and will not be repeated here.

[0068] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0069] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0070] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0071] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0072] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0073] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0074] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0075] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0076] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, 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 devices or units may be electrical, mechanical, or other forms.

[0077] 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.

[0078] In addition, the functional units in the various embodiments of the present invention 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.

[0079] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. 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.

[0080] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An integrated intelligent warehousing and safety management system for polyolefin products, characterized in that, include: The order processing module is configured to receive and approve inbound and outbound orders for warehouse goods and generate order approval results. The virtual unit configuration module is configured to create a virtual dynamic security unit based on the order information of the inbound and outbound orders when the order review result is approved, and to configure a dynamic security strategy set for the virtual dynamic security unit; The resource dynamic binding module is configured to dynamically select a group of security devices from the global physical security device network based on the target location identifier of the virtual dynamic security unit and the dynamic security policy set, and logically bind the selected security device group to the virtual dynamic security unit to form a dedicated monitoring group and a virtual security channel. The entity compliance verification module is configured to obtain the identity of the present entity and match the identity of the present entity with the list of authorized entities of all created virtual dynamic security units. When the match is successful, the entity identity of the present entity is verified for compliance based on the dynamic security policy set. After the verification is successful, the target virtual dynamic security unit is activated, its dedicated monitoring group is instructed to enter the focused working mode, and its virtual security channel access permission is unlocked. The internal cross-verification module is configured to acquire real-time monitoring data collected by the dedicated monitoring group and work progress data reported by the associated work terminal with bidirectional communication function during the activation life cycle of the target virtual dynamic security unit, and cross-compare the two in the unit context environment to generate the unit internal verification result. The strategy adaptive intervention module is configured to dynamically adjust the dynamic security strategy set based on the internal verification results of the unit, and issue corresponding security intervention instructions to the global physical security device network or the associated operation terminal based on the adjusted dynamic security strategy set. The deconstruction and archiving module is configured to deconstruct the target virtual dynamic security unit, release all security devices bound to it, and encapsulate the operation logs and data indexes within the lifecycle of the unit into a traceable dataset for archiving after confirming that all job tasks associated with the target virtual dynamic security unit and the auxiliary tasks fed back by the auxiliary job subsystem have been completed.

2. The integrated intelligent warehousing and safety management system for polyolefin products according to claim 1, characterized in that, The virtual unit configuration module includes: The parameter extraction unit is used to extract job attribute parameters, warehouse location parameters, and time window parameters from the order information. The security level calculation unit is used to call a security benchmark calculation model, take the operation attribute parameters as input features, and calculate the initial security level. The spatiotemporal boundary generation unit is used to generate the unit spatial scope and unit time lifecycle of the virtual dynamic security unit based on the storage location parameters and the time window parameters. The strategy generation unit is used to call the strategy template library, inject the initial security level, the unit spatial scope, and the unit time lifecycle into the matching template, and instantiate the dynamic security strategy set.

3. The integrated intelligent warehousing and safety management system for polyolefin products according to claim 2, characterized in that, The resource dynamic binding module includes: A coordinate positioning unit is used to locate the core operation coordinate points in the warehouse electronic map based on the target warehouse location identifier; The path planning unit is used to call the path planning algorithm that integrates physical distance and security penalty factors, and calculate the optimal monitoring field path and necessary passage node sequence based on the core operation coordinate points and the dynamic security strategy set; The monitoring group delineation unit is used to select a set of cameras covering the optimal monitoring field of view from the global physical security device network and logically delineate them as the dedicated monitoring group based on the optimal monitoring field of view path. The channel generation unit is used to generate temporary access permission rules based on the necessary access node sequence and issue them to the associated access control devices to form the virtual security channel.

4. The integrated intelligent warehousing and safety management system for polyolefin products according to claim 1, characterized in that, The entity compliance verification module is specifically used for performing compliance verification as follows: Obtain the associated operational qualification requirements from the target virtual dynamic security unit, and retrieve historical qualification certificate data and real-time status data from the background database based on the on-site entity identifier; Based on the dynamic security strategy set, the qualification matching degree is calculated to generate qualification verification results, and the pre-entry conditions are parsed to generate status verification results. Perform a logical AND operation on the qualification verification result and the status verification result to generate the final compliance verification conclusion.

5. The integrated intelligent warehousing and safety management system for polyolefin products according to claim 1, characterized in that, The internal cross-validation module includes: The first feature extraction unit is used to perform real-time analysis on the video stream collected by the dedicated monitoring group using a scene recognition model that identifies warehousing operation behavior and cargo status, and generate a first monitoring feature sequence. The second feature extraction unit is used to parse the progress messages reported periodically by the associated job terminal and generate a second job feature sequence. The event alignment unit is used to align and associate two sets of feature sequences according to their timestamps to form a set of event pairs. The verification engine unit is used to call the rule engine, which contains logic for comparing behavioral consistency and quantity consistency, to perform logical verification on the event pair set and output the internal verification results of the unit.

6. The integrated intelligent warehousing and safety management system for polyolefin products according to claim 5, characterized in that, The policy adaptive intervention module is specifically used to adjust the policy set as follows: The abnormal event descriptions in the internal verification results of the unit are parsed, and an abnormal knowledge base that maintains the mapping relationship between abnormal features and risk levels is called to perform fuzzy matching to determine the abnormal level. Based on the anomaly level, the corresponding template is retrieved from the policy adjustment template library and applied to the currently active dynamic security policy set. The abnormal response rules are then enhanced or their ranges are corrected to generate the adjusted dynamic security policy set.

7. The integrated intelligent warehousing and safety management system for polyolefin products according to claim 6, characterized in that, The policy adaptive intervention module is specifically used to: When issuing instructions, the module is used to: When the anomaly level is low, a standardized operation reminder instruction is issued through the associated operation terminal of the two-way communication, and the dedicated monitoring group is instructed to perform video enhancement. When the anomaly level is high, cross-unit linkage instructions are executed, including sending collaborative alert requests to adjacent areas and issuing instructions to the access control system to narrow the passage range of the virtual security channel.

8. The integrated intelligent warehousing and safety management system for polyolefin products according to claim 1, characterized in that, The deconstruction and archiving module is specifically used for: Monitor the completion status of core inbound and outbound orders, and trigger unit destructive instructions based on the inspection or inventory completion confirmation signals fed back by the auxiliary operation subsystem. Based on the deconstruction instruction, the logical delineation of the dedicated monitoring group is revoked and the temporary access permission rule is deleted; All operation logs and records generated during the lifecycle of this unit are aggregated to generate a structured archive, which is then encrypted and digitally signed before being packaged to generate the traceable dataset.

9. The integrated intelligent warehousing and safety management system for polyolefin products according to claim 1, characterized in that, The system also includes a policy self-learning optimization module, configured for: Regularly collect archived datasets and extract unit operation efficiency indicators and anomaly handling indicators to form historical performance datasets; The historical performance dataset is used as a training sample and input into a machine learning model for maximizing the comprehensive benefit function for iterative training. Based on the training output, update the system's initial policy configuration parameters or device invocation rules, and apply the optimized policy generation rules to the subsequent configuration process of virtual dynamic security units.

10. A method for integrated intelligent warehousing and safety management of polyolefin products, applied to the integrated intelligent warehousing and safety management system for polyolefin products as described in any one of claims 1-9, characterized in that, Specifically, the following steps are included: Receive and approve inbound and outbound orders for warehouse goods, and generate order approval results; When the order review result is approved, a virtual dynamic security unit is created based on the order information of the inbound and outbound orders, and a set of dynamic security strategies is configured for the virtual dynamic security unit; Based on the target location identifier of the virtual dynamic security unit and the dynamic security policy set, a group of security devices is dynamically selected from the global physical security device network, and the selected security device group is logically bound to the virtual dynamic security unit to form a dedicated monitoring group and a virtual security channel. Obtain the identifier of the present entity and match the present entity identifier with the list of authorized entities of all created virtual dynamic security units to obtain the matching result; When the matching result indicates that the present entity identifier is successfully matched with a target virtual dynamic security unit, the present entity identifier is subjected to compliance verification based on the dynamic security policy set of the target virtual dynamic security unit, and a compliance verification conclusion is obtained. If the compliance verification result is passed, the target virtual dynamic security unit is activated, its dedicated monitoring group is instructed to enter the focused working mode, and its virtual security channel access permission is unlocked. During the activation lifecycle of the target virtual dynamic security unit, real-time monitoring data collected by its dedicated monitoring group and work progress data reported by associated work terminals are obtained, and the real-time monitoring data and work progress data are cross-compared in the context of the target virtual dynamic security unit to generate internal verification results. Based on the internal verification results of the unit, the dynamic security strategy set of the target virtual dynamic security unit is dynamically adjusted to generate the adjusted dynamic security strategy set, and the corresponding security intervention command is executed based on the adjusted dynamic security strategy set. After confirming that all job tasks associated with the target virtual dynamic security unit have been completed, the target virtual dynamic security unit is deconstructed, all security devices bound to it are released, and all operation logs and data indexes during the lifecycle of the unit are encapsulated into a traceable dataset for archiving.

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