333 results about "Safety management systems" patented technology

The invention relates to the technical field of data security management, and discloses a blockchain-based forestry data security management system and method, and the system comprises a data collection unit which is used for comprehensively obtaining a multi-dimensional information flow of forest ecology and resource states; the data processing unit is used for carrying out deep cleaning, standardized regulation and feature value extraction on the originally collected mass heterogeneous data; the block chain storage unit is used for constructing a permanent, tamper-proof and distributed secure storage infrastructure platform of the forestry core data; a verification unit; the safety control unit is used for constructing a covering data transmission, storage and access full-chain depth defense system structure model; a user interface unit; an auditing unit; and a network communication unit. The method is reasonable in design, and the intelligent analysis module is used for processing to form a forest interannual growth trend prediction function distribution map state visual output result set.

The invention discloses a petrochemical equipment fault prediction and safety management system and method, and belongs to petrochemical equipment management. The system comprises the following modules: a working condition sensing and classifying module for realizing real-time identification, classification and feature extraction of the equipment operation state; the health state evaluation module is used for calculating equipment health indexes and outputting an equipment performance degradation trend analysis result; the fault prediction and diagnosis module is used for predicting potential fault types and occurrence time, performing diagnosis analysis on fault mechanisms and providing credibility evaluation of diagnosis results; the risk assessment and early warning module comprehensively assesses multi-dimensional risk factors and generates graded early warning information through dynamic threshold optimization and a multi-stage early warning strategy; the maintenance decision support module is used for optimizing a maintenance strategy and providing resource scheduling and maintenance scheme suggestions based on the equipment health state, the fault prediction and the risk assessment result; and the management and optimization module ensures efficient cooperative operation of each module and continuously improves the system performance.

The invention discloses an intelligent management system for nuclear power plant personnel situation prediction and risk assessment, and relates to the field of intelligent safety management systems, and the system comprises a data collection unit, a multi-dimensional situation awareness unit, a risk prediction and assessment unit, an intelligent decision intervention unit and a visual interaction unit. And multi-source data acquisition, real-time situation construction, dynamic risk prediction and evaluation, intelligent early warning intervention and information visualization are realized. According to the invention, real-time monitoring, dynamic risk prediction and intelligent management of the safety state of the operating personnel can be realized, and the defects of real-time monitoring, dynamic prediction and intelligent management of the operating personnel in a high-risk area in the prior art are overcome, so that the safety management level is improved, the life safety is guaranteed, and the accident occurrence probability is reduced.

The invention discloses an intelligent building safety management system based on big data, and belongs to the technical field of intelligent buildings. Comprising the following modules: a multi-source data fusion and preprocessing module, which adopts intelligent data standardization and feature extraction technologies to realize efficient integration and semantic conversion of cross-source heterogeneous data and ensure data quality and consistency; the security risk dynamic knowledge graph construction module is used for constructing a semantic association network of building security elements through a graph neural network so as to continuously self-learn and dynamically update a risk feature relationship; the intelligent risk assessment and early warning module is used for carrying out comprehensive modeling, accurate positioning, layered assessment and intelligent early warning on building safety risks; the safety decision support module is used for providing an executable risk assessment report and an emergency decision suggestion; and the safety management visualization module adopts an interactive multi-dimensional visualization technology to intuitively present the dynamic evolution process of the building safety risk, so that the risk perception and management efficiency is remarkably improved.

The invention relates to the field of hospital patient safety management, and particularly discloses a hospital patient safety management system and method based on data analysis, and the method comprises the steps: firstly obtaining the hospitalization record of a patient, the heart rate values, collected by an intelligent device, of the patient at a plurality of preset time points, and the blood pressure values, collected by the intelligent device, of the patient at a plurality of preset time points; and then feature extraction and correlation analysis are carried out on the three by using a deep learning technology, and finally whether a patient safety early warning is sent out is judged through a classifier, so that the patient nursing quality is improved, and the response speed to the health condition of the patient is improved.

The invention relates to the technical field of safety management, in particular to an intelligent safety management system based on municipal engineering, which comprises a construction area risk dynamic assessment module, a hierarchical dynamic inspection frequency optimization module, an inspection path optimization module, an abnormal behavior monitoring module and a high-risk area early warning module. According to the method, quantitative safety assessment basis is provided for different types of operation by utilizing the environmental data of the construction area, combining with historical accident records and calculating the construction risk level, the inspection frequency is dynamically adjusted according to the risk level of the construction area, the self construction progress and abnormal records, so that the inspection resources are inclined to a high-risk area, and the inspection efficiency is improved. The polling efficiency is improved, meanwhile, the pertinence of safety management is enhanced, in combination with positioning information of constructors and boundary data of a high-risk area, the moving track of the constructors is analyzed, early warning is triggered when the constructors enter the high-risk area, safety risks are intervened in time, the safety supervision capacity of municipal engineering construction is improved, and the probability of construction safety accidents is reduced.

Disclosed is a BMS-based battery energy storage safety management system. The system comprises a BMS module, a control center module, an evaluation analysis module, a coupling analysis module, a prediction module, and a data storage module. The BMS module collects monitoring data of a battery under different operation states and then, according to the monitoring data, performs initial monitoring of a real-time health state of the battery. The evaluation analysis module, according to a change in data indicators in the monitoring data, evaluates and analyzes all fault analysis models in the BMS module to obtain an evaluation analysis result. Then the coupling analysis module combines the evaluation analysis result with the data indicators of the monitoring data to retrieve multidimensional spatio-temporal data, and constructs a coupling field model to perform coupling analysis on battery operation state. The prediction module then constructs a fault prediction model by using a coupling data set as training data, accurately locates coupling faults of different coupling surfaces, and implements comprehensive analysis and location of coupling faults.

The invention discloses a safety production management method and a production safety management system based on safety helmet detection, and relates to the technical field of production safety management. Multi-modal data acquisition is realized by constructing an explosion-proof intelligent camera cluster and a wearable positioning terminal, an improved YOLOv7-Tiny model and an HRNet key point detection technology are adopted, illumination compensation, atomization elimination and data enhancement technologies are combined, and precise recognition of the wearing state, the angle deviation and the compliance of the safety helmet is completed; triggering hierarchical response in real time based on a five-level dynamic early warning rule, predicting a future risk probability of an operator through an optimized MLP prediction network in combination with historical violation data, and formulating a personalized scheme; according to the invention, a closed-loop management system of real-time monitoring, intelligent early warning, behavior prediction and active intervention is formed, the occurrence rate of safety accidents is significantly reduced, and the safety standardization of operators and the safety management efficiency of enterprises are improved.

The invention discloses a block chain-based blood full-process traceability tracking and safety management system and method, and relates to the technical field of blood management, and the method comprises the steps: distributing an encrypted digital identifier with a timestamp for each blood unit; collecting physical characteristic data of the blood storage environment in real time; dynamically adjusting the state mark of the blood product based on a preset plasma quality evaluation model; a threshold signature technology is adopted to ensure that multiple medical institutions complete blood information verification and sharing on the premise of protecting privacy; when it is monitored that the blood environment parameters exceed a safety threshold value, graded early warning is generated, and an emergency processing flow is started; and establishing a blood circulation whole process auditing tracking system. The system has the advantages that the blood whole-process traceability system based on the block chain is constructed, transparent credible management of the whole life cycle of blood products from collection to use is achieved, the trust and privacy protection problem in multi-mechanism cooperation is solved, and the blood safety management level and the emergency processing efficiency are comprehensively improved.

The invention relates to the technical field of intelligent manufacturing and industrial Internet of Things, in particular to an intelligent factory equipment safety management system and method, and the system comprises an identity authentication module, a dynamic safety interaction module, an intelligent monitoring response module and a self-adaptive optimization module. An identity authentication module; through fusion of multi-dimensional information authentication, block chain decentralized storage, intelligent algorithm behavior analysis, encrypted communication and fine-grained authority control, multi-source data threat detection and reinforcement learning driven strategy optimization, a whole-process security system is constructed. The method comprises the steps of identity authentication, security interaction, monitoring response and adaptive optimization. The problems that in a traditional industrial scene, equipment identity authentication is fragile, data transmission is not safe, threat response lags and strategies are staticized are solved, high-safety authentication, dynamic encryption communication, real-time threat response and strategy self-optimization are achieved, and the equipment safety protection capacity and the system intelligence level are improved.

The invention relates to a big data security management system, and provides a security management system covering a whole life cycle aiming at the problems of untrusted source end, link leakage, centralized storage of single points, extensive authorization, disposal lag and the like. The system comprises an acquisition security module, a transmission encryption module, a storage security module, an access control module, a threat detection module, a situation awareness module, a traceability module and an emergency response module. A session basis is generated through multi-factor authentication, a dynamic key is derived according to time slices, and data fragments are encrypted one by one; distributed storage is adopted, and metadata is chained to be non-tampered; implementing fine-grained authorization by taking the attribute as a core; utilizing a sequence model linkage knowledge graph to identify abnormity and calculate a risk index; and when the threshold is exceeded, automatically reconstructing a log chain and executing isolation, alarm or recording. According to the system, trusted acquisition, confidential transmission, traceable storage, fine authorization and automatic disposal are realized, and the safety and compliance are remarkably improved.

The invention discloses a thermoelectric enterprise safety management system and method based on integration, and relates to the technical field of thermoelectric production safety control. The system performs quantification processing on the collected real-time disturbance data set through a preset coupling algorithm to generate a risk pre-coupling factor representing a multi-source disturbance coupling risk; generating a predicted operation state of a future time node in combination with a current operation state set representing the operation condition of the equipment; the prediction operation state is compared with a preset operation safety threshold value, the safety and stability margin is calculated, an original control target of the unit is dynamically adjusted, and the system generates a prediction error by comparing the prediction operation state with a subsequently collected actual operation state; and the prediction model correction parameters of the prediction model are corrected by using the prediction error, and online adaptive adjustment of the prediction model is realized, so that quantitative evaluation of multiple disturbance coupling effects is realized, and a decision basis is provided for predictive risk prevention and control.

The invention provides a chemical industry park safety management system and method based on the Internet of Things. The method comprises the following steps: collecting multi-source monitoring data in a chemical industry park to generate a dynamic monitoring data set; applying space-time causal constraints to multi-hop connection paths in the topological graph of the equipment in the chemical industrial park to generate path confidence distribution; constructing entity feature embedding of each device in the chemical industry park, and determining a time-varying causal incidence matrix through all entity feature embedding and path confidence distribution; dividing risk equipment groups with different risk levels, and constructing a risk propagation tensor of the equipment risk partition topology network in the chemical industry park through each risk equipment group; and generating a dynamic risk vector through the time-varying causal incidence matrix and the risk propagation tensor, and carrying out early warning on the safety risk in the chemical industry park based on the dynamic risk vector. By adopting the scheme of the invention, time-space registration can be carried out on the multi-source monitoring data of the sensing nodes of the Internet of Things, and the time-varying causal relationship between the devices can be mined, so that dynamic safety risk early warning can be realized.

The invention relates to the technical field of lithium battery safety, in particular to a lithium battery energy storage safety management system and method. The method comprises the following steps: acquiring a real-time heterogeneous invasion characteristic quantity of an environment where a lithium battery is located, analyzing heterogeneous pollutant invasion characteristics based on the real-time heterogeneous invasion characteristic quantity, and integrating to form a multi-source invasion data set; based on the multi-source invasion data set, performing multi-level security risk coupling modeling, and outputting a comprehensive risk level; based on the comprehensive risk level, a defense mechanism is activated in a self-adaptive mode, and a cross-dimension defense strategy is generated; and according to the cross-dimensional defense strategy, evaluating the state of the battery after defense, and generating and outputting a security defense efficiency report. According to the method, a dynamic mutual feedback mechanism of pollutant invasion characteristics and multi-level safety risks is combined, safety weak points and evolution trends of the lithium battery energy storage system on the underground inspection robot are identified, rapid response to high-risk invasion scenes is realized, potential risks are timely solved, and local abnormity is prevented from being upgraded into systematic safety accidents.

Disclosed is a method of more effectively managing and displaying an Information Security Management System (ISMS), or Cybersecurity Framework, by an application executing on a computer device for computing and displaying real time dynamic metrics and market comparison for the User. The method includes authenticated and authorized Users to conduct security baselines based on industry accepted standards in order to establish a plurality of metric baselines dynamically and in real time. The method further includes projects submitted to be measured against organizational goals and simulate the impact to the Security baselines. The method further includes the ability to provide financial visibility into the financial exposure of a Security Breach, or Data exfiltration and other available financial metrics. The method further includes a platform by which companies may request Virtual CISO's services from a pool of executive level resources.

The invention discloses a dangerous and large project safety management system, and belongs to the technical field of building construction safety monitoring. According to the system, vibration sensors are arranged on the boundary of a construction area, inclination sensors are installed on the surface of a supporting structure, static force level gauges are arranged corresponding to settlement monitoring points, and soil pressure boxes are buried in the side wall of a foundation pit in a layered mode, so that multi-dimensional data collection is achieved. A finite element analysis model is adopted in an edge calculation unit arranged in the area controller, supporting structure material parameters serve as input, and theoretical values are dynamically calculated in combination with real-time monitoring data. When the deviation between the measured data and the theoretical value exceeds a first threshold value, the historical mean value is automatically fused for iterative calculation, and if the deviation still exceeds a second threshold value after continuous three times of iteration, primary early warning is triggered. The system can evaluate the safety state of the supporting structure in real time, effectively prevents collapse accidents, and is suitable for safety management of dangerous and large projects such as building foundation pits and tunnels.

The invention provides a hydropower station full-scene intelligent inspection and safety supervision method and device. A two-legged inspection robot with anti-explosion and anti-vibration capabilities is deployed to realize all-terrain autonomous inspection of equipment nodes in the hydropower station; based on a digital twinborn model and an edge computing platform, fusing equipment state data and personnel behavior data acquired by a robot in real time, identifying equipment defects and personnel violation behaviors through an AI algorithm, and generating graded early warning information; the robot is controlled to carry out real-time intervention through a voice module, early warning information is pushed to a safety management system, and an equipment operation authority locking mechanism is linked; through optimizing a path planning algorithm and a multi-robot cooperative scheduling strategy, rapid response and autonomous obstacle avoidance of the robot under an emergent task are realized. According to the method, full-scene automatic inspection of the hydropower station and real-time supervision of personnel behaviors can be realized, the equipment defect identification accuracy and the emergency response efficiency are remarkably improved, and the manual inspection cost and the non-planned shutdown risk are reduced.

The invention discloses a building construction safety management method and system based on artificial intelligence, and relates to the technical field of building construction safety, the system automatically identifies structure information in a CAD drawing through artificial intelligence, and generates a layout point in combination with point cloud data; a sensor group is installed at a layout point to collect state data of a supporting structure in real time and transmit the state data to a building construction safety management system for preprocessing, and a geometric state data set and a stress effect data set are formed; performing structure geometric state evaluation by constructing a structure geometric instability index jgs, executing a dynamic load impact analysis instruction when the support structure is evaluated to be normal, and performing structure impact stability evaluation by constructing a comprehensive steady state evolution index wty; the risk level is generated according to the two evaluation results, and a multi-level response strategy is executed, so that the structural risk dynamic perception, evaluation and intervention in the construction process are realized, and the construction safety intelligent level is improved.

The invention relates to the technical field of port safety management, and discloses a safety management system and method suitable for a port complex environment, and the system comprises a positioning collection module which employs UWB and RTK technologies to carry out the positioning of the dynamic positions of indoor and outdoor personnel; the spatial modeling module is used for constructing a three-dimensional model of the belt conveyor system based on laser point cloud scanning and a BIM technology, and marking equipment coordinates; the hierarchical management and control module is used for dividing an electronic fence area based on the three-dimensional model; a data fusion module; an intelligent early warning module; and a scheduling execution module. According to the method, the UWB is used for inhibiting steel structure signal attenuation to guarantee indoor continuous tracking, the RTK is used for achieving outdoor centimeter-level positioning, outputting three-dimensional coordinates and mapping the three-dimensional coordinates to a transfer tower floor, the three-dimensional coordinates serve as a core base to be fused into a space-time engine, an electronic fence is driven in real time to trigger dynamic equipment emergency stop control, and a digital human system is linked to automatically dispatch recent security officers to execute closed-loop protection. And linkage regulation and control of personnel and equipment resources are realized.

The invention discloses an equipment interlocking safety management system and method of a CNC production chain, particularly relates to the technical field of safety management, and integrates multi-source sensor data and a deep learning model, extracts equipment fatigue and fault features, and evaluates an equipment risk level by using a fuzzy Bayesian neural network. Meanwhile, a wearable brain-computer interface is introduced, the nerve state of an operator is monitored in real time, the fatigue index is quantified, and double monitoring of the man-machine state is achieved. The system can automatically adjust the interlocking safety level based on the risk level, optimizes the man-machine interaction strategy through reinforcement learning, and improves the safety and intelligent level of the industrial production process. And meanwhile, a man-machine interaction protocol is optimized through a reinforcement learning training self-adaptive strategy.

A safety management system for building construction monitoring disclosed by the present invention comprises a sensing layer, an edge layer and a platform layer, the sensing layer is used for full-dimensional data acquisition, and the sensing layer comprises a personnel safety monitoring module, an equipment state monitoring module, an environment monitoring module and a structure health monitoring module. The personnel safety monitoring module comprises an intelligent safety helmet and a positioning bracelet, the equipment state monitoring module comprises a tower crane monitoring subsystem and an elevator monitoring subsystem, the environment monitoring module comprises a gas detection array and a micro meteorological station, and the structure health monitoring module is composed of a fiber bragg grating sensing network. According to the safety management system for building construction monitoring, the problems of monitoring blind areas and data islands existing in traditional monitoring are effectively solved, a complete data base is provided for safety management, emergency time is shortened by more than 80% compared with traditional manual disposal, and the transmission reliability of key data is ensured while wide-area coverage is ensured.

The application provides a security management system and method applied to a smart education platform, wherein the system comprises: a platform application security management module, which is used for performing security management on a data application layer of the smart education platform; a data security management module, which is used for performing security management on a data storage layer of the smart education platform; and a big data component security management module, which is used for performing security management on a big data basic component layer of the smart education platform. The security management system applied to the smart education platform of the application performs security management on the data application layer, the data storage layer and the big data basic component layer of the smart education platform through the platform application security management module, the data security management module and the big data component security management module, so that the security of the big data platform is ensured.

A large ship safety supervision system, configured to realize shipmen monitoring and ship safety supervision, wherein shipmen monitoring comprising monitoring of real time positions of shipmen in cabins and shipmen health data, and ship safety supervision comprises oceanic condition warning, on board devices running condition monitoring, ship navigation / construction monitoring and ship remote guidance. Data transmission in between ships and shores is realized by the hybrid self-adaptive compression technology based on model classification and the data transmission link intelligent selection technology based on fuzzy neural network creatively, in the meanwhile, real time safety management and supervision and ship remote work analysis and guidance can be realized.

The invention discloses an intelligent alarm system based on a real-time video stream of a platform, and relates to the technical field of video processing early warning, and the intelligent alarm system comprises a data collection module which carries out the real-time monitoring based on a monitoring camera, reads the image data of a point position camera, carries out the standardization and normalization of the data, and carries out the unified input of the image data; and the target discovery module is used for inputting the preprocessed image frame and the monitored area, identifying and positioning pedestrians in the image frame by adopting an algorithm based on target detection, performing label processing on the identified pedestrians based on a detected tracking algorithm byterack, and outputting the residence time of the current frame target in the monitored area. According to the platform safety management system, various advantages are brought to platform safety management, the alarm threshold value can be flexibly adjusted, decision support is provided, management personnel are helped to analyze passenger flow, optimize deployment and troubleshoot hidden dangers by recording related data, a'early warning-processing-optimization 'closed loop is formed, the safety management and control level is improved, and safety accidents are effectively prevented.

The invention discloses an intelligent safety management system for a transformer substation and an implementation management method. The system comprises a remote intelligent patrol subsystem, an intelligent analysis subsystem and a client interaction subsystem. The remote intelligent inspection subsystem is deployed at a substation end and is composed of an inspection host, a multi-modal data acquisition device and a communication module. The intelligent analysis subsystem is deployed in a cloud server and comprises an image preprocessing module, an anomaly recognition module, an equipment classification module and a risk assessment module, the recognition precision is improved through multi-algorithm fusion, the image quality problem in a complex environment is solved through CycleGAN preprocessing, the anomaly recognition accuracy is improved through the combination of YOLOv5 and CycleGAN, and the risk assessment accuracy is improved. By combining with a random forest classifier, the equipment classification accuracy is improved; closed-loop management from data acquisition to decision support is intelligently realized in the whole process, so that the inspection efficiency is improved. According to the invention, by fusing multiple algorithms and the Internet of Things technology, the substation inspection efficiency and the safety management level are improved.

The invention belongs to the field of smart park safety management, relates to a data analysis technology, is used for solving the problem that comprehensive analysis cannot be carried out by combining risk priorities of routing inspection nodes and spatial distribution conditions among the nodes in the prior art, and particularly relates to an operation and maintenance safety management system adaptive to a smart park. Comprising a confidence evaluation module, a double-line analysis module, an inspection configuration module and a task distribution module which are in communication connection in sequence, and the double-line analysis module, the inspection configuration module and the task distribution module are all in communication connection with a database; according to the method, the inspection task is planned from two core dimensions of risk priority and inspection efficiency; the confidence route ensures that the high-risk nodes can be processed preferentially, and the efficiency route ensures that the total routing inspection path is shortest; the bidirectional analysis mechanism enables the system to better balance the urgency and the overall efficiency of inspection in the subsequent configuration and distribution process.

The invention relates to the technical field of steel production management, and particularly discloses an intelligent safety management system for steel production, which comprises a multi-source data acquisition module, a data fusion processing module, a digital twin modeling module, a production risk identification module, a dynamic risk assessment module and an intelligent early warning decision module. The method comprises the following steps: acquiring multi-source data of steel production, carrying out fusion processing on the multi-source data, constructing a digital twinborn model of a steel production line, updating the digital twinborn model of steel production based on security situation awareness data, generating a corresponding production risk coefficient and an environment risk coefficient, and further establishing a steel production dynamic risk assessment model. Performing dynamic risk assessment on steel production; by introducing multi-source heterogeneous data fusion, digital twin model dynamic evolution and quantitative risk assessment technologies, the real-time performance, accuracy and decision-making efficiency of steel production safety management are improved, and an innovative solution is provided for safety management and control of a complex industrial system.

The utility model relates to the field of building safety, in particular to a building fire alarm device which comprises a base, a shell and a protective cover, a controller is installed at the bottom of the base, a photoelectric sensor is installed on one side of the front face of the controller, and a networking module is installed on the other side of the front face of the controller; the base is provided with a photoelectric sensor and a controller, the front surface of the controller is provided with an ion type sensor, the bottom of the base is provided with an ionization chamber through the controller, the ionization chamber is covered with a shell, and the bottom of the shell is provided with a protective cover. The detection sensitivity and accuracy are improved, the false alarm rate is reduced, the built-in networking module supports multiple communication protocols, butt joint with various fire control systems and safety management systems is facilitated, remote monitoring and instant alarm are achieved, and the fire prevention and control efficiency and response speed are improved.

The invention discloses a multifunctional safety box and a safety management system, and relates to the technical field of safety access. A multifunctional safety box safety management system comprises a multi-dimensional access verification module, a real-time joint scoring module, a risk reevaluation module, an event sequence analysis module, a linkage control module and an evolution management module. According to the method, the behavior-environment collaborative vector between the access behavior characteristics and the environment state is constructed, initial risk scoring is performed based on state deviation degree modeling, and a coupling strength judgment mechanism is introduced on the basis, so that the sensitivity and recognition accuracy of behavior and environment co-occurrence anomalies can be remarkably improved; the coupling strength is calculated through the abnormal co-occurrence frequency, the similarity and the information interaction degree in the behavior-environment vector, and the coupling strength exceeding a threshold value is used for dynamically adjusting the initial scoring level, so that the recognition capability of the composite potential attack behavior is effectively enhanced.

The invention provides a private key full-life-cycle security management system and method based on a mobile terminal anti-quantum cryptography algorithm. The method comprises the following steps: generating a key pair based on the anti-quantum cryptography algorithm; acquiring a certificate containing a public key in the key pair; calling a mobile terminal key management system to generate a symmetric encryption key, encrypting a private key in the key pair by using the symmetric encryption key, storing the encrypted private key into a sandbox, and storing a certificate into the sandbox; extracting a private key and a certificate in the encrypted key pair from the sandbox, calling the hardware-level key management system, and decrypting the private key by using the symmetric encryption key to obtain a decrypted private key; calling an interface matched with the purpose of the private key through a preset anti-quantum algorithm library, and executing signature, signature verification or key exchange operation by using the decrypted private key; and after the operation is completed, clearing the memory area for storing the private key plaintext. According to the method, the life cycle of the anti-quantum private key can be safely managed on the premise of not depending on the native support of a mobile system.