Comprehensive early warning management system and method for scrap steel base

Abstract

The invention discloses a comprehensive early warning management system and method for a waste steel base, and belongs to the technical field of waste steel. A gate sentry early warning unit, an anti-theft early warning unit, an equipment early warning unit and an inventory early warning unit are integrated through a core early warning center, and gate sentry early warning verifies vehicle qualification based on a collection and sales plan and intercepts non-appointment rod lifting and process missing factory leaving behaviors; the anti-theft early warning depends on an electronic fence to capture illegal intrusion coordinates, and a camera is linked to automatically capture evidences; the equipment carries out early warning and real-time polling on the health states of a wagon balance, a gate and a camera, and triggers grading fault response; a material object-system inventory difference ratio model is constructed for inventory early warning, and yellow lamp / red lamp multi-level warning is achieved; a space-time anomaly analysis module is innovatively integrated, intelligent tracking is started for material pile / perimeter non-working time anomaly, and an early warning self-healing mechanism is established; the abnormal response efficiency can be improved, the equipment failure outage rate can be reduced, the inventory account and reality difference tracing time can be shortened, and the safety prevention and control and production continuity of the waste steel base can be remarkably enhanced.

Description

Technical Field

[0001] This invention relates to the field of scrap steel technology, specifically to a comprehensive early warning management system and method for scrap steel bases. Background Technology

[0002] In the safety management of scrap steel production bases, security vulnerabilities and operational anomalies are systematically caused by multiple bottlenecks, including blind spots in manual inspections, lack of oversight of equipment status, and fragmented data across multiple systems, resulting in delayed risk response. The current industry-reliant traditional discrete monitoring model has three core flaws: gatekeepers rely on paper-based verification, leading to lengthy entry times for unauthorized vehicles, and the independent operation of electronic fences and video surveillance results in missed theft reports; the status of critical equipment (weighbridges / gates) lacks real-time monitoring, and a single malfunction can trigger process interruptions, impacting base operations; physical inventory relies on monthly manual spot checks, often triggering audits only when there are significant discrepancies between system records and actual inventory, making it difficult to trace the source of these discrepancies. Currently, there is a lack of multi-dimensional intelligent risk correlation engines, tiered response models, and closed-loop mechanisms for handling and tracing the source of risks in scrap steel production bases, preventing theft and production stoppage risks from being prevented within minutes, severely hindering the standardization of safety production. Summary of the Invention

[0003] The purpose of this invention is to provide a comprehensive early warning management system and method for scrap steel bases. By integrating multi-dimensional intelligent monitoring and closed-loop disposal mechanisms, it solves core problems in traditional scrap steel management such as illegal release, asset theft, failure to detect equipment malfunctions, and discrepancies between inventory records and actual inventory, thereby achieving dynamic interception and self-healing control of risks across the entire base.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A comprehensive early warning management system for scrap steel production bases includes:

[0006] The core early warning center integrates the following early warning modules:

[0007] Gate early warning unit: Based on the matching of vehicle procurement and sales plan, the entry qualification is verified, and early warning is triggered for events such as unplanned gate lifting, incomplete process of leaving the factory, and abnormal manual gate lifting.

[0008] Anti-theft early warning unit: Monitors illegal intrusion into the factory area via electronic fence, automatically triggering video recording, photo taking, and alarms at the central control center;

[0009] Equipment anomaly early warning unit: Real-time monitoring of the health status of key equipment such as weighbridges, turnstiles, and cameras; push notifications of fault causes and shutdown instructions when anomalies occur.

[0010] Inventory safety early warning unit: compares the difference between physical inventory and system inventory, and triggers multi-level early warnings when the difference exceeds the threshold;

[0011] The early warning execution engine integrates the following modules:

[0012] Smart camera network module: captures photos of abnormal behavior, records video streams, and retains 3 months of historical data;

[0013] The central control center's large screen module displays real-time alerts, equipment status, and rotating information from all cameras within the base.

[0014] Early Warning Dashboard Module: Displays the number and handling rate of various early warnings for the month, categorized by type.

[0015] Base ERP interface: Synchronizes procurement and sales plans, vehicle reservation information, and inventory data to support early warning decisions.

[0016] Furthermore, the gate early warning unit performs the following operations:

[0017] Call the procurement and sales plan interface to verify vehicle reservation information; if a match is successful, the barrier will automatically lift to allow passage.

[0018] For vehicles without reservations, approval from the central control center is required and the operation log must be recorded.

[0019] When a vehicle leaves the factory, information on weighing, quality inspection, and unloading is obtained from the base's ERP interface. If any step is missing, an interception warning is triggered to ensure a closed-loop process.

[0020] Furthermore, the anti-theft warning unit includes:

[0021] Electronic fence control submodule: Deploy sensors along the fence of the scrap steel base to identify the coordinates of unauthorized intrusions;

[0022] Linked response submodule: When an intrusion event is triggered, the camera automatically turns to capture the image and starts recording 15 seconds of video.

[0023] Evidence Preservation Submodule: Generates anti-theft files by binding the time, location, and image data of abnormal events.

[0024] Furthermore, the device anomaly early warning unit implements:

[0025] Health polling mechanism: Every 30 minutes, the device query interface is called to check the status of the weighbridge, turnstile, and camera;

[0026] Fault classification push: If the weighbridge malfunctions, it will be immediately shut down and the maintenance team will be notified via SMS; if the gate loses connection, the gate backup plan will be triggered.

[0027] Feedback closed-loop management: Abnormal equipment is marked as "disabled" and needs to be manually enabled and verified by the central control center after repair.

[0028] Furthermore, the inventory safety early warning unit performs the following:

[0029] Month-end difference ratio calculation: The following information is statistically analyzed by warehouse, storage area, and material category:

[0030] Physical inventory: refers to the actual quantity of materials in the warehouse at the statistical point in time;

[0031] System inventory: refers to the quantity of materials in the warehouse module of the base ERP system at the statistical point in time;

[0032] Difference ratio = (BA) / A;

[0033] Where A represents physical inventory; B represents system inventory;

[0034] Multi-level early warning rules: A yellow light warning is issued when the difference ratio is ≤-10%, and a red light warning is issued and outbound operations are frozen when the difference ratio is ≤-50%.

[0035] Furthermore, it also includes a spatiotemporal anomaly analysis module, used for:

[0036] The scrap steel stockpile, weighbridge area, and perimeter wall are designated as sensitive areas.

[0037] During non-working hours, the system detects unauthorized entry by personnel or vehicles and triggers facial recognition and license plate capture via cameras.

[0038] If the system remains in the area for more than 5 minutes, it will be upgraded to a red alert and a notification will be sent to the security terminal.

[0039] Furthermore, the central control center's large screen provides:

[0040] Carousel of surveillance cameras within the base: The carousel displays real-time footage from all cameras within the base, allowing for remote monitoring of all situations within the base.

[0041] Warning event display: Displays the latest equipment warnings, gate warnings, and on-site operation logs, allowing the base to keep abreast of relevant situations;

[0042] 3D traceability view: Click on the above warning event to retrieve historical videos, captured images, and corresponding operation logs.

[0043] Furthermore, the early warning dashboard module provides:

[0044] The system displays the number of alerts, rectified alerts, unrectified alerts, and handling rates for gate security, theft prevention, inventory, and equipment in the current month, categorized as follows:

[0045] Processing rate = A / B;

[0046] Where A represents the number of issues that have been rectified, and B represents the total number of warnings;

[0047] Red highlighting rule for handling rate: When the handling rate of a certain type of early warning is <95%, it will be highlighted;

[0048] 3D traceability view: Click on the warning event to retrieve historical videos, captured images, and operation logs.

[0049] Furthermore, it also includes:

[0050] The early warning and self-healing mechanism executes the following process:

[0051] The base management responded to the yellow alert within one hour, formulated a response plan, and entered it into the system.

[0052] A red alert will be automatically escalated to headquarters oversight, and a follow-up process will be triggered if the issue remains unresolved for more than 24 hours.

[0053] Closed-loop verification requires uploading evidence of the actions taken, and the warning event is closed after approval at two levels.

[0054] The base risk index assessment module performs the following operations:

[0055] 1) Four-dimensional event statistics unit: The headquarters compiles monthly statistics on the number of warnings in the following four categories from each base:

[0056] G: Number of gate early warning events (base weight = 1.0, system-defined weights are supported);

[0057] F: Number of anti-theft alarm events (base weight = 1.2, system-defined weights supported);

[0058] K: Number of inventory warning events (base weight = 1.5, system-defined weights supported);

[0059] S: Number of device warning events (base weight = 0.8, system-defined weights supported);

[0060] 2) Responsibility Tracing Factor Unit: This assigns a management responsibility weight to each type of event.

[0061] Controllability coefficient (A): 1.0 for events that the base can eliminate on its own, and 1.5 for events that require headquarters assistance;

[0062] Timeout coefficient (B): 1.0 for timely processing, 2.0 for failure to process within the timeout period;

[0063] 3) Dynamic Index Calculation Unit: The base risk index is calculated using the following formula:

[0064] Total risk index = ∑[A×B×C];

[0065] Where A is the controllability coefficient, B is the timeout coefficient, and C is the weight corresponding to this type of risk;

[0066] 4) Hierarchical control unit:

[0067] When the index is greater than 15 points and less than or equal to 25 points, an improvement proposal will be sent to the headquarters leadership and they will be notified.

[0068] When the index is greater than 25 points;

[0069] a) Freeze the newly added reservation function for the base and forcibly initiate the rectification process;

[0070] b) Generate the "Base Risk Control Tracing Report", which requires the following information: root cause (related to the specific early warning event), overdue responsibility analysis (if any), and improvement plan for controllable issues;

[0071] c) After the report is electronically signed by the person in charge of the base, it will be sent to the headquarters risk control center for review within 72 hours.

[0072] A comprehensive early warning management method for scrap steel bases includes the following steps:

[0073] Step 1: Multi-source early warning trigger: Real-time collection of gate lifting events, electronic fence status, equipment health signals, and inventory difference data, and determination of abnormal events based on preset rules to generate two-level early warning levels (yellow / red);

[0074] Step 2, Multi-dimensional Response and Handling: Gate incidents are pushed to the central control center's approval queue, linked to vehicle history records to assist decision-making, and anti-theft incidents automatically activate camera tracking and generate an emergency report containing coordinates / images; if equipment malfunctions, a shutdown command is triggered and a maintenance work order is assigned;

[0075] Step 3: Closed-loop tracking of handling: The dashboard dynamically updates the warning status, and a red alert is displayed when the handling rate is below 95%; to close the warning, evidence of repair must be uploaded, and headquarters will conduct a review of red warnings.

[0076] Step 4: Early Warning Source Analysis: Retrieve historical videos and operation logs from the past 3 months to construct an event timeline and generate a monthly early warning analysis report, marking high-frequency abnormal areas and improvement suggestions.

[0077] Compared with the prior art, the beneficial effects of the present invention are:

[0078] 1. This invention achieves full-process compliance management of vehicles through a three-level linkage of procurement and sales planning, access control, and factory verification, eliminating the risk of unauthorized release.

[0079] 2. This invention constructs an anti-theft emergency response system based on electronic fences and camera intelligent tracking, thereby reducing asset loss rates.

[0080] 3. This invention employs an equipment polling-fault classification-closed-loop verification mechanism to improve the availability of key equipment to over 99.5%; and ensures that the consistency error between accounts and physical inventory is ≤5% through dynamic calibration of inventory difference ratio and multi-level freezing strategy. Attached Figure Description

[0081] Figure 1 This is a flowchart of the early warning processing of the present invention;

[0082] Figure 2This is a screenshot of the historical video viewing page of this invention;

[0083] Figure 3 This is a screenshot of the early warning query page of the present invention;

[0084] Figure 4 This is a screenshot of the device management page of the present invention;

[0085] Figure 5 This is a screenshot of the early warning dashboard page of the present invention;

[0086] Figure 6 This is a screenshot of the physical system inventory difference report page of the present invention;

[0087] Figure 7 This is a screenshot of the centralized control screen page of the present invention. Detailed Implementation

[0088] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0089] To address core issues in traditional scrap steel management, such as unauthorized release, asset theft, failure to detect equipment malfunctions, and discrepancies between inventory records and actual stock, and to achieve dynamic risk interception and self-healing control across the entire facility, please refer to [link to relevant documentation]. Figure 1-7 This embodiment provides the following technical solution:

[0090] A comprehensive early warning management system for scrap steel production bases includes:

[0091] 1. Core Early Warning Center: This center integrates the following modules:

[0092] The gate early warning unit verifies the vehicle procurement and sales plan through the base ERP interface: if a match is successful, the gate automatically opens; vehicles without reservations require approval from the central control center and are logged (e.g., Figure 7 The completeness of the weighing / quality inspection / unloading process is verified at the factory. If any step is missing, an interception warning will be triggered.

[0093] The anti-theft early warning unit uses the electronic fence of the wall (such as...) Figure 2 It monitors unauthorized intrusions, and when an event is triggered, the camera automatically turns to capture and record a 15-second video, generating an anti-theft profile containing time, location, and image data.

[0094] The equipment anomaly early warning unit polls the status of the weighbridge, turnstile, and camera every 30 minutes (e.g., Figure 4): Weighbridge malfunctions will be immediately shut down and an SMS alarm will be sent; if the gate loses connection, the manual gate control procedure will be activated; after repair, the central control center needs to manually activate and verify the system.

[0095] The inventory safety warning unit calculates the difference ratio monthly (e.g.) Figure 6 ):

[0096] Physical inventory (A): The actual quantity of materials in the warehouse at the time of statistics;

[0097] System Inventory (B): The quantity of materials in the base ERP system at the point in time;

[0098] Difference ratio = (BA) / A;

[0099] Multi-level early warning rules: A yellow light warning is issued when the difference ratio is ≤-10%, and a red light warning is issued and outbound operations are frozen when the difference ratio is ≤-50%.

[0100] 2. Early Warning Execution Engine: This engine integrates the following modules:

[0101] The intelligent camera network covers key nodes in the factory area, captures abnormal behavior, and stores three months of historical data (such as...). Figure 2 ).

[0102] The large screen in the central control center (such as...) Figure 7 It rotates through all camera live feeds, displays warning events and equipment status, and provides 3D traceability (clicking on an event allows you to retrieve historical videos and operation logs).

[0103] Early warning dashboard module (such as) Figure 5 Monthly statistics on the number and handling rate of alerts related to gate security, theft prevention, inventory, and equipment:

[0104] Disposal rate = A / B (A: number of rectified cases, B: total number of warnings);

[0105] When the handling rate of a certain type of early warning is less than 95%, it will be highlighted in red.

[0106] 3. Spatiotemporal Anomaly Analysis Module: Designates material storage areas, weighbridges, and perimeter walls as sensitive areas. When personnel / vehicles intrude outside of working hours, the module automatically captures faces / license plates (linked to smart cameras). If a person stays in an area for more than 5 minutes, a red alert is issued and pushed to the security terminal.

[0107] 4. Early Warning Self-Healing Mechanism: Yellow alerts require the base management to formulate a handling plan and enter it into the system within 1 hour; red alerts are automatically escalated to headquarters supervision, and if not handled within 24 hours, a follow-up process is triggered; closing an alert requires uploading evidence of repair, and approval through two levels: initial review by the base manager and final review by headquarters risk control (e.g., Figure 3 ).

[0108] 5. Base Risk Index Assessment Module: Achieves precise risk control through a four-dimensional weighted model.

[0109] 1) Multi-source data governance: The headquarters system collects four types of core early warning events monthly:

[0110] G: Gate Guard Early Warning (Base weight = 1.0, supports system customization)

[0111] F: Anti-theft alert (base weight = 1.2, supports system customization)

[0112] K: Inventory Alert (Base weight = 1.5, supports system customization)

[0113] S: Device Alert (Base weight = 0.8, supports system customization)

[0114] 2) Responsibility Weighting System: Each type of event is subject to a dual management coefficient.

[0115] a) Controllability Coefficient: The system automatically determines whether a problem falls within the scope of the base's independent management (e.g., gatekeepers allowing unauthorized passage). Problems that the base can resolve independently are assigned a coefficient of 1.0, while those requiring headquarters intervention are assigned a coefficient of 1.5.

[0116] b) Timeout coefficient: Determined based on the self-healing mechanism time limit (1 hour for yellow alerts / 24 hours for red alerts), 1.0 for timely handling, and 2.0 for exceeding the timeout.

[0117] 3) Dynamic exponent formula:

[0118] Total risk index = ∑[A×B×C];

[0119] Where A is the controllability coefficient, B is the timeout coefficient, and C is the weight corresponding to this type of risk.

[0120] 4) Intelligent control strategy:

[0121] When the index is greater than 15 points and less than or equal to 25 points, an improvement proposal will be sent to the relevant departments and headquarters leaders will be notified.

[0122] When the index is greater than 25 points

[0123] a) Freeze the newly added reservation function for the base and forcibly initiate the rectification process;

[0124] b) Generate the "Base Risk Control Tracing Report", which requires the following information: root cause (related to the specific early warning event), overdue responsibility analysis (if any), and improvement plan for controllable issues;

[0125] c) After the report is electronically signed by the person in charge of the base, it will be sent to the headquarters risk control center for review within 72 hours.

[0126] A comprehensive early warning management method for scrap steel bases, applied to the above system, includes the following steps:

[0127] Step 1: Multi-source early warning triggering: Real-time collection of gatekeeper barrier lifting events, electronic fence status, equipment health signals, and inventory difference data; abnormal events are determined according to preset rules, generating yellow / red two-level early warnings (e.g., Figure 1 );

[0128] Step 2, Multi-dimensional Response and Handling: Gate incidents are pushed to the central control center's approval queue and linked to vehicle history records for decision-making; anti-theft incidents activate camera tracking and generate an emergency report containing coordinates / images; equipment malfunctions trigger shutdown commands and assign maintenance work orders;

[0129] Step 3: Closed-loop tracking of handling: The dashboard dynamically updates the early warning status, and a red alert is displayed when the handling rate is <95% (e.g., Figure 5 To disable a red alert, evidence of repair needs to be uploaded, and headquarters will review flights under a red alert.

[0130] Step 4: Early Warning Source Tracing Analysis: Retrieve historical videos and operation logs from the past 3 months to construct an event timeline (e.g., Figure 2 This generates monthly early warning analysis reports, marking high-frequency abnormal areas and providing improvement suggestions.

[0131] In summary, this invention integrates four types of early warning units—gatekeeper, anti-theft, equipment, and inventory—through a core early warning hub: Gatekeeper early warning verifies vehicle qualifications based on procurement and sales plans, intercepting vehicles leaving the factory without prior appointments or with missing procedures; Anti-theft early warning relies on electronic fences to capture the coordinates of illegal intrusions and automatically captures evidence through cameras; Equipment early warning polls the health status of weighbridges, turnstiles, and cameras in real time, triggering tiered fault responses; Inventory early warning constructs a physical-to-system inventory difference ratio model to achieve multi-level yellow / red light alarms; Innovatively, a spatiotemporal anomaly analysis module is integrated to intelligently track abnormalities in material piles / perimeters during non-working hours and establishes an early warning self-healing mechanism, marking a red alert when the handling rate falls below a certain percentage, with red alerts automatically escalating to headquarters for supervision; The supporting methods cover four stages: multi-source risk perception, multi-dimensional response and handling, closed-loop tracking, and traceability analysis, constructing a three-dimensional traceability chain by binding historical videos and operation logs to a centralized control screen; This can improve anomaly response efficiency, reduce equipment downtime, shorten inventory discrepancy tracing time, and significantly strengthen the safety control and production continuity of scrap steel bases.

[0132] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A comprehensive early warning management system for scrap steel bases, characterized in that: include: The core early warning center integrates the following early warning modules: Gate early warning unit: Based on the matching of vehicle procurement and sales plan, the entry qualification is verified, and early warning is triggered for events such as unplanned gate lifting, incomplete process of leaving the factory, and abnormal manual gate lifting. Anti-theft early warning unit: Monitors illegal intrusion into the factory area via electronic fence, automatically triggering video recording, photo taking, and alarms at the central control center; Equipment anomaly early warning unit: Real-time monitoring of the health status of key equipment such as weighbridges, turnstiles, and cameras; push notifications of fault causes and shutdown instructions when anomalies occur. Inventory safety early warning unit: compares the difference between physical inventory and system inventory, and triggers multi-level early warnings when the difference exceeds the threshold; The early warning execution engine integrates the following modules: Smart camera network module: captures photos of abnormal behavior, records video streams, and retains 3 months of historical data; The central control center's large screen module displays real-time alerts, equipment status, and rotating information from all cameras within the base. Early Warning Dashboard Module: Displays the number and handling rate of various early warnings for the month, categorized by type. Base ERP interface: Synchronizes procurement and sales plans, vehicle reservation information, and inventory data to support early warning decisions.

2. The integrated early warning management system for scrap steel bases according to claim 1, characterized in that: The gate early warning unit performs the following operations: Call the procurement and sales plan interface to verify vehicle reservation information; if a match is successful, the barrier will automatically lift to allow passage. For vehicles without reservations, approval from the central control center is required and the operation log must be recorded. When a vehicle leaves the factory, information on weighing, quality inspection, and unloading is obtained from the base's ERP interface. If any step is missing, an interception warning is triggered to ensure a closed-loop process.

3. The integrated early warning management system for scrap steel bases according to claim 1, characterized in that: The anti-theft early warning unit includes: Electronic fence control submodule: Deploy sensors along the fence of the scrap steel base to identify the coordinates of unauthorized intrusions; Linked response submodule: When an intrusion event is triggered, the camera automatically turns to capture the image and starts recording 15 seconds of video. Evidence Preservation Submodule: Generates anti-theft files by binding the time, location, and image data of abnormal events.

4. The integrated early warning management system for scrap steel bases according to claim 1, characterized in that: The equipment anomaly early warning unit achieves the following: Health polling mechanism: Every 30 minutes, the device query interface is called to check the status of the weighbridge, turnstile, and camera; Fault classification push: If the weighbridge malfunctions, it will be immediately shut down and the maintenance team will be notified via SMS; if the gate loses connection, the gate backup plan will be triggered. Feedback closed-loop management: Abnormal devices are marked as "disabled" and need to be manually enabled and verified by the central control center after repair.

5. The integrated early warning management system for scrap steel bases according to claim 1, characterized in that: The inventory safety early warning unit executes: Month-end difference ratio calculation: The following information is statistically analyzed by warehouse, storage area, and material category: Physical inventory: refers to the actual quantity of materials in the warehouse at the statistical point in time; System inventory: refers to the quantity of materials in the warehouse module of the base ERP system at the statistical point in time; Difference ratio = (BA) / A; Where A represents physical inventory; B represents the system inventory; Multi-level early warning rules: A yellow light warning is issued when the difference ratio is ≤-10%, and a red light warning is issued and outbound operations are frozen when the difference ratio is ≤-50%.

6. The integrated early warning management system for scrap steel bases according to claim 1, characterized in that: It also includes a spatiotemporal anomaly analysis module, used for: The scrap steel stockpile, weighbridge area, and perimeter wall are designated as sensitive areas. During non-working hours, the system detects unauthorized entry by personnel or vehicles and triggers facial recognition and license plate capture via cameras. If the system remains in the area for more than 5 minutes, it will be upgraded to a red alert and a notification will be sent to the security terminal.

7. The integrated early warning management system for scrap steel bases according to claim 1, characterized in that: The central control center's large screen provides: Carousel of surveillance cameras within the base: The carousel displays real-time footage from all cameras within the base, allowing for remote monitoring of all situations within the base. Warning event display: Displays the latest equipment warnings, gate warnings, and on-site operation logs, allowing the base to keep abreast of relevant situations; 3D traceability view: Click on the above warning event to retrieve historical videos, captured images, and corresponding operation logs.

8. The integrated early warning management system for scrap steel bases according to claim 1, characterized in that: The early warning dashboard module provides: The system displays the number of alerts, rectified alerts, unrectified alerts, and handling rates for gate security, theft prevention, inventory, and equipment in the current month, categorized as follows: Processing rate = A / B; Where A represents the number of issues that have been rectified, and B represents the total number of warnings; Red highlighting rule for handling rate: When the handling rate of a certain type of early warning is <95%, it will be highlighted; 3D traceability view: Click on the warning event to retrieve historical videos, captured images, and operation logs.

9. The integrated early warning management system for scrap steel bases according to claim 1, characterized in that: Also includes: The early warning and self-healing mechanism executes the following process: The base management responded to the yellow alert within one hour, formulated a response plan, and entered it into the system. A red alert will be automatically escalated to headquarters oversight, and a follow-up process will be triggered if the issue remains unresolved for more than 24 hours. Closed-loop verification requires uploading evidence of the actions taken, and the warning event is closed after approval at two levels. The base risk index assessment module performs the following operations: 1) Four-dimensional event statistics unit: The headquarters compiles monthly statistics on the number of warnings in the following four categories from each base: G: Number of gate early warning events (base weight = 1.0, system-defined weights are supported); F: Number of anti-theft alarm events (base weight = 1.2, system-defined weights supported); K: Number of inventory warning events (base weight = 1.5, system-defined weights supported); S: Number of device warning events (base weight = 0.8, system-defined weights supported); 2) Responsibility Tracing Factor Unit: This assigns a management responsibility weight to each type of event. Controllability coefficient (A): 1.0 for events that the base can eliminate on its own, and 1.5 for events that require headquarters assistance; Timeout coefficient (B): 1.0 for timely processing, 2.0 for failure to process within the timeout period; 3) Dynamic Index Calculation Unit: The base risk index is calculated using the following formula: Total risk index = ∑[A×B×C]; Where A is the controllability coefficient, B is the timeout coefficient, and C is the weight corresponding to this type of risk; 4) Hierarchical control unit: When the index is greater than 15 points and less than or equal to 25 points, an improvement proposal will be sent to the headquarters leadership and they will be notified. When the index is greater than 25 points; a) Freeze the newly added reservation function for the base and forcibly initiate the rectification process; b) Generate the "Base Risk Control Tracing Report", which requires the following information: root cause (related to the specific early warning event), overdue responsibility analysis (if any), and improvement plan for controllable issues; c) After the report is electronically signed by the person in charge of the base, it will be sent to the headquarters risk control center for review within 72 hours.

10. A comprehensive early warning management method for scrap steel bases, implemented based on the comprehensive early warning management system for scrap steel bases as described in any one of claims 1-9, characterized in that: Includes the following steps: Step 1: Multi-source early warning trigger: Real-time collection of gate gate lifting events, electronic fence status, equipment health signals, and inventory difference data, and determination of abnormal events based on preset rules to generate two-level early warning levels (yellow / red); Step 2, Multi-dimensional Response and Handling: Gate incidents are pushed to the central control center's approval queue, linked to vehicle history records to assist decision-making, and anti-theft incidents automatically activate camera tracking to generate an emergency report containing coordinates / images; If the equipment malfunctions, a shutdown command will be triggered and a maintenance work order will be assigned. Step 3: Closed-loop tracking of handling: The dashboard dynamically updates the warning status, and a red alert is displayed when the handling rate is below 95%; to close the warning, evidence of repair must be uploaded, and headquarters will conduct a review of red warnings. Step 4: Early Warning Source Analysis: Retrieve historical videos and operation logs from the past 3 months to construct an event timeline and generate a monthly early warning analysis report, marking high-frequency abnormal areas and improvement suggestions.

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