Industrial Internet of Things security management method, system and medium based on management cloud platform

Abstract

The embodiments of this specification provide an industrial Internet of Things security management method, system and medium based on a management cloud platform, which is executed by a management cloud platform of an industrial Internet of Things security management system based on a management cloud platform, including: obtaining the security control area of ​​at least one production line; determining the security monitoring parameters of the security control area; generating security monitoring instructions; obtaining security monitoring information collected by the security monitoring device based on the security monitoring parameters; generating security management parameters of the security control area; in response to receiving confirmation information sent by the industrial Internet of Things management platform, generating security management instructions based on the confirmation information; sending the security management instructions to the industrial Internet of Things perception control platform through the industrial Internet of Things management platform; obtaining the execution results of the industrial Internet of Things perception control platform based on the security management instructions, and adjusting the security monitoring parameters based on the execution results. Accurate control of personnel and equipment is achieved to ensure the safety and efficiency of production.

Description

Technical Field

[0001] This specification relates to the field of production safety management, and in particular to an industrial Internet of Things safety management method, system and medium based on a management cloud platform. Background Art

[0002] Through the Industrial Internet of Things, real-time monitoring and data collection can be performed on the equipment and personnel in the factory. However, how to effectively manage personnel who perform different production tasks in different time periods, especially when the staff or operating equipment outside the current time period still stays in the production area, how to take early warning measures in time to avoid interference with normal production activities has become an urgent problem to be solved. In addition, when there are multiple production lines (or multiple processing workshops / factories), the Industrial Internet of Things corresponding to each production line is independent of each other, and it is not possible to effectively utilize data.

[0003] Therefore, it is necessary to provide an industrial Internet of Things security management method and system based on a management cloud platform to more accurately control personnel and equipment to ensure the safe and efficient operation of factory production. The management cloud platform can realize information exchange between various industrial Internet of Things and provide a reference for the information processing and operation of at least one industrial Internet of Things. Summary of the invention

[0004] One or more embodiments of the present specification provide an industrial Internet of Things security management method based on a management cloud platform, the method comprising: obtaining a security control area of ​​at least one production line through an industrial Internet of Things management platform corresponding to the at least one production line; determining security monitoring parameters of the security control area; generating security monitoring instructions based on the security monitoring parameters, and sending the instructions to a security monitoring device of an industrial Internet of Things perception control platform through the industrial Internet of Things management platform; obtaining security monitoring information collected by the security monitoring device based on the security monitoring parameters; generating security management parameters of the security control area based on the security monitoring information, the security management parameters including security warning parameters and / or production scheduling parameters, and The security management parameters are sent to the industrial Internet of Things management platform; in response to receiving the confirmation information sent by the industrial Internet of Things management platform, a security management instruction is generated based on the confirmation information; the security management instruction is sent to the industrial Internet of Things perception control platform through the industrial Internet of Things management platform, and the industrial Internet of Things perception control platform includes an early warning platform and an operation platform, the early warning platform controls the early warning device to issue a safety early warning signal based on the security early warning parameters, and / or the operation platform updates the operation parameters of the at least one production line based on the production scheduling parameters; and the execution result of the early warning platform based on the security management instruction is obtained, and the security monitoring parameters are adjusted based on the execution result.

[0005] One or more embodiments of the present specification provide an industrial Internet of Things security management system based on a management cloud platform, the system comprising a management cloud platform and at least one subsystem, the at least one subsystem comprising a subsystem corresponding to at least one production line, each subsystem in the at least one subsystem comprising an industrial Internet of Things user platform, an industrial Internet of Things service platform, an industrial Internet of Things management platform, an industrial Internet of Things sensor network platform and an industrial Internet of Things perception control platform. The management cloud platform is configured to: obtain the safety control area of ​​the at least one production line through the industrial Internet of Things management platform corresponding to the at least one production line; determine the safety monitoring parameters of the safety control area; generate a safety monitoring instruction based on the safety monitoring parameters, and send it to the safety monitoring device of the industrial Internet of Things perception control platform through the industrial Internet of Things management platform; obtain the safety monitoring information collected by the safety monitoring device based on the safety monitoring parameters; generate the safety management parameters of the safety control area based on the safety monitoring information, the safety management parameters include safety warning parameters and / or production scheduling parameters, and send the safety management parameters to the industrial Internet of Things management platform; in response to receiving the confirmation information sent by the industrial Internet of Things management platform, generate a safety management instruction based on the confirmation information; send the safety management instruction to the industrial Internet of Things perception control platform through the industrial Internet of Things management platform, the industrial Internet of Things perception control platform includes an early warning platform and an operation platform, the early warning platform controls the early warning device to send a safety warning signal based on the safety warning parameters, and / or the operation platform updates the operation parameters of the at least one production line based on the production scheduling parameters; and obtain the execution result of the early warning platform based on the safety management instruction, and adjust the safety monitoring parameters based on the execution result.

[0006] One or more embodiments of the present specification provide a computer-readable storage medium, wherein the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the method described in the above embodiments.

[0007] The beneficial effects of one or more embodiments of the present specification include but are not limited to: (1) realizing information exchange between various industrial Internet of Things, providing reference for information processing and operation of at least one industrial Internet of Things, and realizing intelligent security management of the industrial Internet of Things; (2) automatically determining the safety monitoring parameters of the safety control area, and judging whether to issue a safety warning signal and / or update the operation parameters based on the information obtained, thereby reducing the possibility of safety accidents, improving production safety, and ensuring the coordinated operation of multiple production lines; (3) making full use of the big data learning, processing capabilities and data sharing characteristics of the management cloud platform, statistically analyzing the production information of multiple production lines to obtain safety control parameters, and determining the safety control area based on the safety control parameters, which is conducive to improving the efficiency and accuracy of determining the safety control area. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0009] Figure 1 It is a schematic diagram of the platform structure of an industrial Internet of Things security management system based on a management cloud platform according to some embodiments of this specification;

[0010] Figure 2 is an exemplary flow chart of an industrial Internet of Things security management method based on a management cloud platform according to some embodiments of this specification;

[0011] Figure 3 is an exemplary flow chart for obtaining a security control area according to some embodiments of this specification;

[0012] Figure 4 It is a model schematic diagram of the risk identification model shown in some embodiments of this specification. DETAILED DESCRIPTION

[0013] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly introduces the drawings required for describing the embodiments. The drawings do not represent all implementation methods.

[0014] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. If other words can achieve the same purpose, the words can be replaced by other expressions.

[0015] Unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0016] When the operations are performed according to the step description in the embodiments of this specification, unless otherwise specified, the order of the steps is interchangeable, the steps may be omitted, and other steps may be included in the operation process.

[0017] Figure 1 It is a schematic diagram of the platform structure of an industrial Internet of Things security management system based on a management cloud platform according to some embodiments of this specification.

[0018] like Figure 1 As shown, since there may be multiple production lines (or multiple processing workshops / factories) during production, the industrial Internet of Things security management system based on the management cloud platform (hereinafter referred to as the security management system 100) includes a management cloud platform 110 and at least one subsystem. One production line corresponds to one subsystem. Each subsystem includes an industrial Internet of Things user platform, an industrial Internet of Things service platform, an industrial Internet of Things management platform, an industrial Internet of Things sensor network platform, and an industrial Internet of Things perception control platform. At least one subsystem is respectively connected to the management cloud platform 110 for information sharing among the subsystems through the management cloud platform.

[0019] The management cloud platform refers to a platform for realizing information interaction between at least one subsystem. In some embodiments, the management cloud platform is configured as a server in the cloud and can interact with the industrial Internet of Things management platforms in different subsystems. The management cloud platform also includes a cloud storage to store data uploaded by at least one subsystem.

[0020] In some embodiments, the management cloud platform is configured to obtain the safety control area of ​​at least one production line, determine the safety monitoring parameters of the safety control area, and generate safety monitoring instructions based on the safety monitoring parameters. The management platform is also configured to obtain safety monitoring information, and generate safety management parameters of the safety control area based on the safety monitoring information. The management cloud platform is also configured to generate safety management instructions based on the confirmation information in response to receiving confirmation information sent by the industrial Internet of Things management platform, and obtain the execution results of the early warning platform based on the safety management instructions, and adjust the safety monitoring parameters based on the execution results.

[0021] In some embodiments, the management cloud platform is also configured to obtain production information of at least one production line and security control areas for multiple time periods; determine security control nodes based on the frequency of interference through the industrial Internet of Things management platform; and determine security control parameters of at least one production line based on production information.

[0022] In some embodiments, the management cloud platform is also configured to determine security control parameters based on mapping relationships and production information; update mapping relationships based on management perception information; determine security management parameters based on security risk data; and determine security risk data through a risk identification model based on security monitoring information and security control parameters.

[0023] In some embodiments, the management cloud platform is also configured to determine controllable data and uncontrollable data based on security risk data, determine safety warning parameters based on controllable data, and determine production scheduling parameters based on uncontrollable data and production information.

[0024] The industrial Internet of Things user platform refers to a platform for interacting with users. In some embodiments, the industrial Internet of Things user platform is configured as a terminal device and / or a terminal interface. The terminal device includes a mobile device or a tablet computer, etc. The terminal interface includes a terminal device interface and a web page, etc.

[0025] The industrial Internet of Things service platform refers to a platform that provides information and services to users. In some embodiments, the industrial Internet of Things service platform is configured on a local server. The industrial Internet of Things service platform can interact with the industrial Internet of Things user platform and the industrial Internet of Things management platform.

[0026] The industrial Internet of Things management platform refers to a platform for managing information and / or data related to the subsystem. In some embodiments, the industrial Internet of Things management platform includes a processor and a storage device. The storage device stores a variety of databases. The database refers to a database management system that supports high concurrent access. The processor includes a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction processor (ASIP), a graphics processing unit (GPU), etc. or any combination thereof.

[0027] The IIoT sensor network platform refers to a platform for integrated management of sensor information. In some embodiments, the IIoT sensor network platform is configured as a communication network or a gateway and a network interface, etc. The IIoT sensor network platform can interact with the IIoT management platform and the IIoT perception control platform.

[0028] The industrial Internet of Things perception control platform refers to a functional platform for generating perception information and executing control information. In some embodiments, the industrial Internet of Things perception control platform includes operating equipment and safety monitoring devices.

[0029] Operating equipment refers to equipment used for product production, such as storage equipment, transportation equipment, processing equipment, etc.

[0030] The safety monitoring device refers to a device for monitoring the production line. In some embodiments, the safety monitoring device includes a high-definition camera with identity recognition function, an induction recognition device, etc. In some embodiments, the safety monitoring device can be connected to the management cloud platform.

[0031] The high-definition camera is configured to identify the identity of the operator in the security control area and the model and / or code of the operating equipment. The model and / or code of the operating equipment can reflect the type of the operating equipment. The type of operating equipment includes an automatic robot or material conveying equipment.

[0032] The sensing and identification device is configured to identify personnel or operating equipment entering the security control area. In some embodiments, the sensing and identification device includes an access control device, etc. In response to a person or equipment punching in through the access control device and entering the security control area, the industrial Internet of Things perception control platform can identify the person or operating equipment entering the security control area through the punching record.

[0033] For detailed description of the above, please refer to Figures 2 to 4 Related description.

[0034] In some embodiments of the present specification, based on the security management system 100, an information operation closed loop can be formed between various functional platforms to coordinate and operate regularly, thereby realizing the intelligent security management of the Industrial Internet of Things.

[0035] Figure 2 This is an exemplary flow chart of an industrial Internet of Things security management method based on a management cloud platform according to some embodiments of this specification. In some embodiments, process 200 can be executed by a management cloud platform of an industrial Internet of Things security management system based on a management cloud platform. Figure 2 As shown, process 200 includes the following steps:

[0036] In some embodiments, the management cloud platform obtains the security control area of ​​at least one production line through the industrial Internet of Things management platform corresponding to at least one production line; determines the security monitoring parameters of the security control area; and generates security monitoring instructions based on the security monitoring parameters. The management cloud platform obtains security monitoring information collected by the security monitoring device based on the security monitoring parameters; generates security management parameters of the security control area based on the security monitoring information; generates security management instructions based on the confirmation information in response to receiving the confirmation information sent by the industrial Internet of Things management platform, and obtains the execution results of the early warning platform based on the security management instructions, and adjusts the security monitoring parameters based on the execution results.

[0037] For more information on managing cloud-based industrial IoT security management systems, see Figure 1 Related description.

[0038] Step 210: Obtain a safety control area of ​​at least one production line through an industrial Internet of Things management platform corresponding to at least one production line.

[0039] The safety control area refers to the area on the production line that needs to be controlled or monitored, for example, the area where the workstations of each process on the production line are located or the area where the operating equipment needs to pass through.

[0040] In some embodiments, the management cloud platform can obtain the security control area in a variety of ways. For example, the user inputs the security control area through the Industrial Internet of Things user platform, the Industrial Internet of Things user platform sends the security control area to the Industrial Internet of Things management platform through the Industrial Internet of Things service platform, and the management cloud platform obtains the security control area through the Industrial Internet of Things management platform. In some embodiments, based on historical experience, the user uses workstations where security accidents often occur or areas where operating equipment needs to pass as security control areas. Security accidents include at least one of equipment failures or illegal operations.

[0041] In some embodiments, the management cloud platform can obtain the production information of at least one production line and the security control areas of multiple time periods through the industrial Internet of Things management platform. The security control areas of multiple time periods are determined by the industrial Internet of Things management platform corresponding to at least one production line. The industrial Internet of Things management platform determines the security control nodes based on the production information, and determines the security control areas of multiple time periods based on the security control nodes.

[0042] Production information refers to information related to production on a production line. In some embodiments, production information includes the type of processed product, production quantity, processing procedures, processing stations, models of operating equipment, production time periods of each procedure, work trajectories of operators, and operation procedures, etc. Among them, the operation procedures include the sequence of processing procedures, processing parameters, and the circulation path of materials used, etc.

[0043] In some embodiments, the management cloud platform obtains production information through the industrial Internet of Things management platform, and the industrial Internet of Things management platform obtains production information through the industrial Internet of Things user platform. The user pre-sets production information through the industrial Internet of Things user platform.

[0044] The safety control node refers to a node on the production line that needs to be avoided from being affected. In some embodiments, the safety control node includes at least one of a processing station, an operator, and an operating equipment.

[0045] In some embodiments, the industrial Internet of Things management platform determines the safety control nodes in a variety of ways based on the production information. For example, the industrial Internet of Things management platform queries the historical records of safety accidents in the historical safety database based on the processing stations, operators, and operating equipment models in the production information, and uses the processing stations, operators, and operating equipment in the historical records where safety accidents occurred as safety control nodes. The historical safety database includes multiple historical records of safety accidents. The historical safety database can be obtained from a pre-stored storage device.

[0046] In some embodiments, the production information includes equipment operation information. The management cloud platform determines the interference frequency of the operating equipment based on the equipment operation information through the industrial Internet of Things management platform; and determines the safety control node based on the interference frequency. The safety control node here only includes the operating equipment.

[0047] The following content takes a production line as an example for explanation.

[0048] The equipment operation information refers to information related to the operation equipment. In some embodiments, the equipment operation information includes the model, function and activity path of the operation equipment. The activity path refers to the path along which the operation equipment performs the operation.

[0049] In some embodiments, the management cloud platform obtains the equipment operation information through the industrial Internet of Things management platform, and the industrial Internet of Things management platform obtains the equipment operation information through the industrial Internet of Things user platform. The user pre-sets the equipment operation information through the industrial Internet of Things user platform.

[0050] The interference frequency is used to characterize the frequency of interference to the operating equipment. In some embodiments, the interference frequency is represented by a numerical value or the like, and the larger the numerical value, the higher the interference frequency.

[0051] In some embodiments, the industrial Internet of Things management platform constructs an equipment operation vector based on the equipment operation information, matches the historical equipment operation vectors that meet the preset matching conditions in the vector database, counts the management perception information corresponding to the historical equipment operation vectors, and determines the interference frequency based on the management perception information. The equipment operation vector is a feature vector constructed based on the equipment operation information. The preset matching conditions include the maximum vector similarity. The vector similarity is negatively correlated with the vector distance. The vector distance includes the Euclidean distance, etc.

[0052] Management perception information refers to information collected when the operating equipment is disturbed. In some embodiments, the management perception information includes the operating equipment and operating personnel that caused the interference when the disturbed operating equipment issued an alarm. For instructions on how to obtain management perception information, see Figure 3 and its related description.

[0053] In some embodiments, the industrial Internet of Things management platform determines the frequency of interference based on the management perception information corresponding to the historical equipment operation vector. For example, the more management perception information corresponding to the historical equipment operation vector, the more operating equipment and operating personnel causing interference in the management perception information, and the higher the frequency of interference.

[0054] In some embodiments, the industrial Internet of Things management platform constructs a historical equipment operation vector based on the historical equipment operation information in the historical data, and stores the management perception information of the operation equipment corresponding to the historical equipment operation vector in a production task and the historical equipment operation vector as a piece of data in a vector database. The historical equipment operation vector is a feature vector constructed based on the historical equipment operation information.

[0055] In some embodiments, the IIoT management platform determines the safety control node based on the frequency of interference. For example, the IIoT management platform identifies the operating equipment whose interference frequency is greater than the frequency threshold as a safety control node. The frequency threshold is pre-set based on historical experience.

[0056] In some embodiments, the frequency threshold is negatively correlated with the number of overlapping production lines. Overlapping production lines refer to other production lines whose production periods are the same as or partially overlap with the production period of the current production line. The industrial Internet of Things management platform obtains the production periods of other production lines through the management cloud platform, and determines other production lines whose production periods are the same as or partially overlap with the production period of the current production line as overlapping production lines.

[0057] The remaining production lines determine safety control nodes in a similar manner as described above.

[0058] In some embodiments of the present specification, since the operating equipment has a weak ability to actively avoid interference and is easily disturbed during the operation process, determining the operating equipment that needs to be designated as a safety control node based on the frequency of interference can increase the control of the operating equipment, which is beneficial to improving production efficiency and reducing the safety risks and maintenance costs of the operating equipment.

[0059] In some embodiments, the industrial Internet of Things management platform determines security control areas for multiple time periods based on the security control node. In some embodiments, the multiple time periods include multiple associated time periods corresponding to the security control node. The security control area includes an associated area.

[0060] The associated time period refers to the time period related to the safety control node, such as the production time period of the processing station, the working time period of the operator, and the operating time period of the operating equipment.

[0061] In some embodiments, the IIoT management platform determines the associated time period based on the production information. For example, the IIoT management platform directly uses the production time period of each process as the production time period of the processing station and the operation time period of the operator. For another example, the IIoT management platform determines the operation time period of the operating equipment based on the working rhythm of the operating equipment and the production time period of each process.

[0062] The work rhythm refers to data related to the working time of the operating equipment in the production process. In some embodiments, the work rhythm includes the operating frequency and working duration of the operating equipment. The industrial Internet of Things management platform uses the time period corresponding to the working duration in the production period of each process as the operating period of the operating equipment. The work rhythm is determined based on the historical working process of the operating equipment in the historical data.

[0063] The associated area refers to an area related to the security control node. In some embodiments, the industrial Internet of Things management platform searches for historical production information that is the same as the current production information in the historical data based on historical data, and uses the historical activity area of ​​the historical security control node corresponding to the historical production information as the associated area of ​​the current security control node. The activity area refers to the area where the operator or operating equipment works.

[0064] For each security control node, the management cloud platform uses the associated area as the security control area corresponding to the associated time period.

[0065] In some embodiments, the industrial Internet of Things management platform sends the security control areas of multiple time periods to the management cloud platform.

[0066] In some embodiments of the present specification, determining the security control area based on the security control node can automatically determine the security control area, improve the flexibility and accuracy of determining the security control area, and facilitate more accurate supervision of the security control area.

[0067] Step 220, determine the security monitoring parameters of the security control area.

[0068] Security monitoring parameters refer to relevant parameters for monitoring the security control area. In some embodiments, the security monitoring parameters include monitoring period and monitoring frequency.

[0069] The monitoring period refers to the time interval for monitoring the security control area.

[0070] In some embodiments, the management cloud platform determines the production period of each process and the operation period of the operating equipment as the monitoring period. The monitoring period also includes a preset time period before the production line starts operation. The preset time period can be pre-set based on historical experience. For an explanation of the production period of each process and the operation period of the operating equipment, see step 210 and its related description.

[0071] Monitoring frequency refers to the frequency of monitoring the security control area.

[0072] In some embodiments, the management cloud platform can obtain the frequency of multiple operating devices issuing alarms in the security control area based on the historical management perception information in the historical data, and determine the monitoring frequency based on the frequency. For example, the higher the frequency, the greater the monitoring frequency.

[0073] For more information on managing awareness information, see Figure 3 Step 320 and its related description in .

[0074] Step 230: Generate a security monitoring instruction based on the security monitoring parameters, and send it to the security monitoring device of the industrial Internet of Things perception control platform through the industrial Internet of Things management platform.

[0075] Safety monitoring instructions refer to control instructions used to control safety monitoring devices.

[0076] In some embodiments, the management cloud platform generates security monitoring instructions based on security monitoring parameters of different security control areas, and sends the security monitoring instructions to the industrial Internet of Things perception control platform through the industrial Internet of Things management platform and the industrial Internet of Things sensor network platform, to the security monitoring device corresponding to the security control area.

[0077] For instructions on the safety monitoring device, see Figure 1 and its related description.

[0078] Step 240: Acquire safety monitoring information collected by the safety monitoring device based on the safety monitoring parameters.

[0079] Safety monitoring information refers to relevant data acquired by the safety monitoring device. In some embodiments, the safety monitoring information includes multiple monitoring objects and the residence time and movement trajectory of each monitoring object in the safety control area. Among them, the monitoring object includes at least one of the operating personnel or operating equipment appearing in the safety control area.

[0080] In some embodiments, the safety monitoring device collects safety monitoring information based on the safety monitoring parameters and uploads the safety monitoring information to the industrial Internet of Things perception control platform. The industrial Internet of Things perception control platform uploads the safety monitoring information to the management cloud platform through the industrial Internet of Things sensor network platform and the industrial Internet of Things management platform.

[0081] Step 250: Generate security management parameters for the security control area based on the security monitoring information, and send the security management parameters to the industrial Internet of Things management platform.

[0082] Security management parameters refer to the relevant data for managing the security control area.

[0083] In some embodiments, the safety management parameters include safety warning parameters and / or production scheduling parameters.

[0084] The safety warning parameters refer to the relevant parameters for warning the operators or operating equipment on the production line. In some embodiments, the safety warning parameters include warning objects and warning levels.

[0085] The warning objects include irrelevant personnel and irrelevant equipment. Irrelevant personnel and irrelevant equipment refer to personnel and equipment that are irrelevant to the operation content of the current security control area. In some embodiments, the management cloud platform identifies the operating personnel and operating equipment that are not included in the production information as irrelevant personnel and irrelevant equipment based on the production information.

[0086] The warning level refers to data related to the warning degree of the warning. The warning level is expressed by levels, etc. The larger the level, the higher the warning level.

[0087] In some embodiments, the management cloud platform determines security warning parameters in a variety of ways based on security monitoring information. For example, in response to the time that an unrelated person and / or unrelated device stays in a security control area exceeding a stay time threshold, the management cloud platform may determine the unrelated person and / or unrelated device as a warning object, and determine the warning level based on the stay time. The longer the stay time exceeds the stay time threshold, the higher the warning level corresponding to the warning object.

[0088] The production scheduling parameters refer to the parameters for scheduling the production operations of multiple production lines. In some embodiments, the production scheduling parameters include adjusting the production time period of the production line and / or the operation time period of the operation equipment.

[0089] In some embodiments, the management cloud platform determines production scheduling parameters in a variety of ways based on security monitoring information. For example, if the operating equipment of the current production line receives multiple warnings and its movement trajectory is in the safety control area of ​​other production lines, the management cloud platform can adjust the production time periods of the current production line and other production lines and / or adjust the operating time periods of the operating equipment to achieve staggered operations, and use the adjustment results as production scheduling parameters.

[0090] Exemplarily, based on the production information of different production lines, the management cloud platform takes the production line whose activity area does not include the safety control area as the target production line, swaps the production time periods of the target production line with the current production line, and synchronously adjusts the operating time periods of the operating equipment of the two production lines after the production time periods are swapped, and uses the adjusted production time periods and operating time periods as production scheduling parameters. For an explanation of the activity area, see step 210 and its related description.

[0091] In some embodiments, the management cloud platform may determine safety risk data of at least one production line based on safety monitoring information; and determine safety management parameters based on the safety risk data.

[0092] Safety risk data refers to data related to possible safety accidents. In some embodiments, the safety risk data includes the target monitoring object and the accident level of the target monitoring object. The target monitoring object refers to the operating personnel and operating equipment that may cause safety accidents. The accident level of the target monitoring object refers to the accident level of the safety accident that may be caused by the target monitoring object.

[0093] In some embodiments, the management cloud platform determines security risk data based on security monitoring information in a variety of ways. For example, the management cloud platform can determine security risk data based on the following steps:

[0094] S11, obtain a historical monitoring database through a storage device. The historical monitoring database includes the triggering object of each historical safety accident in the historical data, the historical monitoring vector constructed by the historical safety monitoring information corresponding to the triggering object, and the accident level of the historical safety accident. The triggering object includes the person or equipment that triggers the safety accident. Among them, the historical monitoring vector refers to a feature vector constructed based on the historical safety monitoring information.

[0095] The accident level is used to characterize the severity of the safety accident. In some embodiments, the accident level is pre-set by a technician based on the size of the loss caused by the safety accident, etc. The greater the loss caused, the higher the accident level.

[0096] S12, the management cloud platform screens the security monitoring information based on the monitoring objects, determines the security monitoring information corresponding to each monitoring object, and takes the monitoring objects corresponding to irrelevant personnel and / or irrelevant equipment as target monitoring objects.

[0097] S13, the management cloud platform constructs a monitoring information vector based on the safety monitoring information of the target monitoring object, retrieves the historical monitoring vectors that meet the similarity condition in the historical monitoring database, and determines the historical accident level corresponding to the historical monitoring vector as the accident level of the target monitoring object. The target monitoring object and its corresponding accident level are determined as safety risk data. The similarity condition includes that the vector similarity is greater than the similarity threshold. The similarity threshold is pre-set based on historical experience.

[0098] In some embodiments, the management cloud platform determines security risk data through a risk identification model. For more information, see Figure 4 and its related description.

[0099] In some embodiments, the management cloud platform determines the safety management parameters in a variety of ways based on the safety risk data. For example, the management cloud platform selects the target monitoring objects that need safety warning and / or production scheduling based on the accident level of the target monitoring objects in the safety risk data.

[0100] In some embodiments, the management cloud platform can determine the safety control level of the security control area based on the accident level and the corresponding relationship between the accident level and the safety control level. When the safety control level is greater than the preset level threshold, the management cloud platform determines that the target monitoring object needs to be scheduled for production. When the safety control level is not greater than the preset level threshold, the management cloud platform determines that the target monitoring object needs a safety warning.

[0101] For instructions on determining the security control level and the preset level threshold, see Figure 3 Related description.

[0102] For target monitoring objects that require production scheduling, the management cloud platform determines the production scheduling parameters of the target monitoring objects based on production information related to the target monitoring objects through the above-mentioned method for determining production scheduling parameters.

[0103] For target monitoring objects that require security warnings, the management cloud platform determines security warning parameters based on the accident level of the target monitoring object in the security risk data. For example, the higher the accident level, the higher the warning level in the security warning parameters.

[0104] In some embodiments, the management cloud platform determines controllable data and uncontrollable data based on security risk data, determines safety warning parameters based on controllable data, and determines production scheduling parameters based on uncontrollable data and production information.

[0105] Controllable data refers to safety risk data that can be controlled. In some embodiments, the controllable data includes safety risk data corresponding to objects that can be removed. Objects that can be removed include operators unrelated to the production line and non-working equipment.

[0106] Uncontrollable data refers to security risk data that cannot be controlled. In some embodiments, the uncontrollable data includes security risk data corresponding to objects that cannot be transferred away. Objects that cannot be transferred away include workers and equipment that need to pass through the security control area due to production tasks of other production lines.

[0107] In some embodiments, the management cloud platform determines controllable data and uncontrollable data based on the security risk data. For example, based on production information, the management cloud platform counts the necessary paths of the target monitoring object in the security risk data, calculates the degree of overlap between the necessary routes and the action trajectories corresponding to the target monitoring object in the security monitoring data, and divides the security risk data of the target monitoring object into the first data or the second data based on the degree of overlap. The necessary paths include the work trajectories of the operators and / or the activity paths of the operating equipment.

[0108] In some embodiments, the management cloud platform calculates the percentage of the portion of the necessary route that overlaps with the action trajectory, and confirms the obtained percentage as the overlap between the necessary route and the action trajectory corresponding to the target monitoring object in the security monitoring data.

[0109] In some embodiments, in response to the overlap of the target monitoring object being greater than the overlap threshold, the management cloud platform classifies the security risk data corresponding to the target monitoring object as uncontrollable data. In response to the overlap of the target monitoring object being not greater than the overlap threshold, the management cloud platform classifies the security risk data corresponding to the target monitoring object as controllable data. The overlap threshold can be preset based on historical experience.

[0110] For uncontrollable data, the management cloud platform determines the production scheduling parameters of the target monitoring object contained in the uncontrollable data based on the production information related to the target monitoring object through the above-mentioned method of determining the production scheduling parameters.

[0111] For controllable data, the management cloud platform determines the safety warning parameters of the target monitoring object contained in the controllable data based on the residence time of the target monitoring object through the above-mentioned method for determining the safety warning parameters.

[0112] In some embodiments of the present specification, the security risk data is distinguished into controllable data and uncontrollable data using the overlap, which can further distinguish the security risk data and further improve the accuracy of determining the security management parameters.

[0113] In some embodiments of the present specification, by determining the security risk data, the management cloud platform can judge the possible security accidents that may occur, and based on the possible security accidents, further determine the security management parameters that can effectively ensure production safety.

[0114] In some embodiments, the management cloud platform sends the security management parameters to the industrial Internet of Things management platform.

[0115] Step 260, in response to receiving the confirmation information sent by the industrial Internet of Things management platform, generate a security management instruction based on the confirmation information.

[0116] Confirmation information refers to information indicating confirmation of security management parameters. Confirmation information includes confirmation instructions and security management parameters. Confirmation instructions are expressed in the form of numerical values, for example, 1 indicates confirmation and 0 indicates rejection.

[0117] In some embodiments, the IIoT management platform sends the received security management parameters to the IIoT user platform, and the administrator of the IIoT user platform determines whether the security management parameters are appropriate and generates confirmation information, and sends the confirmation information to the IIoT management platform. The IIoT management platform sends the confirmation information to the management cloud platform.

[0118] In some embodiments, the management cloud platform may generate security management instructions based on the confirmation information.

[0119] Security management instructions refer to instructions used to control the industrial Internet of Things perception control platform to execute security management parameters.

[0120] Step 270: Send the security management instruction to the industrial Internet of Things perception control platform through the industrial Internet of Things management platform.

[0121] In some embodiments, the industrial Internet of Things perception control platform includes an early warning platform and an operation platform. The early warning platform controls the early warning device to send a safety early warning signal based on the safety early warning parameters in the safety management parameters. The operation platform updates the operation parameters of at least one production line based on the production scheduling parameters in the safety management parameters.

[0122] The early warning platform refers to a platform that controls the early warning device. For example, the early warning platform controls the early warning device and issues a safety early warning signal based on the safety early warning parameters.

[0123] The early warning device refers to a device that sends out a safety early warning signal. The early warning device includes at least one of the audio and video equipment on the production line, the user equipment, and the early warning accessories of the operating equipment. Among them, the user equipment includes a smart phone or a tablet computer. The early warning accessories include a control chip configured on the operating equipment for receiving the safety early warning signal.

[0124] In some embodiments, the early warning platform sends a safety early warning signal to the operating personnel in the security control area through audio and video equipment and / or user equipment, and sends a safety early warning signal to the operating equipment through the early warning accessories of the operating equipment.

[0125] In some embodiments, a safety control area corresponds to multiple early warning devices. The early warning platform controls the multiple early warning devices to send safety early warning signals to the operating personnel or operating equipment in the safety control area.

[0126] In some embodiments, the safety warning signal includes at least one of a sound signal or a light signal.

[0127] The warning level in the safety warning parameters is reflected through the loudness of the sound and brightness of the light emitted by the warning device.

[0128] The operation platform refers to a platform for updating the operation parameters of the production line. For example, the operation platform updates the operation parameters of at least one production line based on the production scheduling parameters. The operation parameters include the operation time period of the production line and / or the operation time period of the operation equipment. Updating the operation parameters includes adjusting or increasing or decreasing the operation time period and / or the operation time period.

[0129] Step 280, obtaining the execution result of the early warning platform based on the security management instruction, and adjusting the security monitoring parameters based on the execution result.

[0130] The execution result refers to the result of the early warning platform executing the security management instruction. The execution result includes irrelevant personnel and / or irrelevant equipment leaving or not leaving the security control area.

[0131] In some embodiments, if the irrelevant personnel and / or irrelevant equipment have not left the security control area, the management cloud platform adjusts the security monitoring parameters, wherein adjusting the security monitoring parameters includes increasing the monitoring frequency in the security monitoring parameters.

[0132] In some embodiments, the management cloud platform determines an adjustment amount based on the warning level of the security warning parameter (for example, the higher the warning level, the greater the adjustment amount), and increases the monitoring frequency based on the adjustment amount. The adjustment amount refers to the amplitude of adjusting the monitoring frequency.

[0133] In some embodiments, the management cloud platform divides a plurality of adjustment levels based on the frequency range between the default monitoring frequency and the maximum monitoring frequency. Each adjustment level corresponds to an early warning level. The management cloud platform selects the corresponding adjustment level based on the early warning level, determines the middle value of the frequency range corresponding to the selected adjustment level, and uses the difference between the middle value and the current monitoring frequency as the adjustment amount. The default monitoring frequency refers to the monitoring frequency used in daily production. The default monitoring frequency is pre-set by technical personnel based on historical experience. The maximum monitoring frequency refers to the highest monitoring frequency that the safety monitoring device can reach. The maximum monitoring frequency is determined by the factory parameters of the safety monitoring device.

[0134] In some embodiments of the present specification, information exchange between various industrial Internet of Things can be achieved through the management cloud platform, the safety monitoring parameters of the safety control area can be automatically determined, and it can be determined whether to issue a safety warning signal and / or update the operating parameters based on the information obtained, thereby reducing the possibility of safety accidents, improving production safety, and ensuring the coordinated operation of multiple production lines.

[0135] It should be noted that the above description of the process 200 is only for example and illustration, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to the process 200 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0136] Figure 3 is an exemplary flow chart for obtaining a security control area according to some embodiments of this specification. In some embodiments, process 300 can be executed by a management cloud platform of an industrial Internet of Things security management system based on a management cloud platform. Figure 3 As shown, process 300 includes the following steps:

[0137] In some embodiments, the management cloud platform obtains production information of at least one production line through the Industrial Internet of Things management platform; determines safety control parameters of at least one production line based on the production information; sends the safety control parameters to the Industrial Internet of Things management platform, and the Industrial Internet of Things management platform determines the safety control area of ​​at least one production line based on the safety control parameters; and obtains the safety control area through the Industrial Internet of Things management platform.

[0138] Step 310: Obtain production information of at least one production line through the industrial Internet of Things management platform.

[0139] For more information about this section, see Figure 2 Related description.

[0140] Step 320: Determine safety control parameters of at least one production line based on the production information.

[0141] Safety control parameters refer to data related to the control of the production line. In some embodiments, the safety control parameters include each processing step on the production line and the safety control level and key control targets corresponding to the processing step.

[0142] The safety control level is used to characterize the degree to which a processing procedure requires control.

[0143] Key prevention and control targets include operating personnel and / or operating equipment.

[0144] In some embodiments, the management cloud platform determines safety control parameters based on production information in a variety of ways.

[0145] For example, the management cloud platform determines security control parameters based on the following steps:

[0146] S21, based on the production information, determining the processing characteristics of each processing step on the production line.

[0147] Processing features refer to features related to the processing of a processing step. In some embodiments, processing features include the type of processed product, operating equipment, and the transportation of materials and workpieces (such as the preceding and following processes of materials and workpieces, etc.).

[0148] In some embodiments, the management cloud platform extracts processing features from production information through feature processing methods such as principal component analysis.

[0149] S22, based on the historical safety accident data of multiple production lines, builds a prevention and control parameter database.

[0150] Historical safety accident data refers to historical data related to historical safety accidents. In some embodiments, the historical safety accident data includes the accident level of the historical safety accident and the historical processing characteristics and accident information of the corresponding processing steps. The processing steps corresponding to the historical safety accident refer to the processing steps where the historical safety accident occurred. For an explanation of the accident level, see Figure 2 and its related description.

[0151] Accident information refers to information related to a safety accident. In some embodiments, the accident information includes the operator or operating equipment that caused the accident, the location and time of the accident, and the work being performed by the operator or operating equipment when the accident occurred.

[0152] The prevention and control parameter database includes multiple historical processing features and the reference prevention and control level and reference prevention and control object corresponding to each historical processing feature.

[0153] In some embodiments, the management cloud platform selects historical processing features of processing procedures corresponding to historical safety accidents based on historical safety accident data, determines the safety prevention and control level based on the accident level of the historical safety accident, and determines the key prevention and control targets based on the accident information. The management cloud platform uses the safety prevention and control level and key prevention and control targets corresponding to the historical safety accidents as the reference prevention and control level and reference prevention and control targets corresponding to the historical processing features, and includes the historical processing features and the reference prevention and control level and reference prevention and control targets corresponding to the historical processing features in the prevention and control parameter database.

[0154] In some embodiments, the safety prevention and control level is positively correlated with the accident level of historical safety accidents. The higher the accident level, the higher the safety prevention and control level.

[0155] In some embodiments, the key prevention and control objects are determined based on a variety of methods. For example, the key prevention and control objects are pre-set by technical personnel based on accident information. For another example, the management cloud platform determines the key prevention and control objects based on accident information and through an accident model.

[0156] The accident model refers to a model used to determine the key prevention and control targets. In some embodiments, the accident model is a machine learning model.

[0157] The management cloud platform trains the accident model based on sample accident information and the actual key prevention and control targets corresponding to the sample accident information through methods such as gradient descent.

[0158] In some embodiments, the sample accident information is obtained based on historical data. The actual key prevention and control targets corresponding to the sample accident information are pre-set by technical personnel based on actual conditions.

[0159] In some embodiments, the accident model can be trained by: inputting multiple sample accident information into the initial accident model, constructing a loss function through labels and the prediction results of the initial accident model, updating the initial accident model based on the iteration of the loss function, and completing the accident model training when the loss function of the initial accident model meets the preset conditions. The preset conditions may be that the loss function converges, the number of iterations reaches a set value, etc.

[0160] S23, for each processing procedure on the production line, based on the processing characteristics of the processing procedure, the historical processing characteristics that meet the preset search conditions are retrieved from the control parameter database, and the reference control level and reference control object corresponding to the historical processing characteristics are used as the safety control level and key control object of the processing procedure. Among them, the preset search conditions include that the similarity between the processing characteristics and the historical processing characteristics is the highest. The similarity between the processing characteristics and the historical processing characteristics can be determined by constructing vectors and calculating vector distances.

[0161] In some embodiments, the management cloud platform uses each processing procedure on the production line and the safety control level and key control objects corresponding to the processing procedure as safety control parameters.

[0162] In some embodiments, the management cloud platform can determine the mapping relationship between effective prevention and control parameters and production information based on security monitoring information; and determine the security prevention and control parameters based on the mapping relationship and production information.

[0163] For more information on safety monitoring, see Figure 2 Related description.

[0164] Effective prevention and control parameters refer to safe prevention and control parameters that produce effective prevention and control effects.

[0165] In some embodiments, the management cloud platform counts the security monitoring information of the security control area and the number of security warning signals issued, calculates the ratio of the number of security warning signals to the number of monitored objects in the security monitoring information, obtains the proportion of warnings, and responds to the proportion of warnings being greater than a preset ratio threshold, uses the security control parameters corresponding to the security control area as effective control parameters. The preset ratio threshold is pre-set based on historical experience.

[0166] The preset ratio threshold can be adjusted based on actual conditions. For example, if a safety accident occurs in a safety control area due to the failure to issue a safety warning signal, the preset ratio threshold is lowered.

[0167] In some embodiments, the mapping relationship between effective prevention and control parameters and production information includes a definition domain, a value range, and a corresponding relationship between the definition domain and the value range.

[0168] In some embodiments, the management cloud platform determines the mapping relationship in a variety of ways. For example, the management cloud platform puts the production information as an independent variable into the definition domain and puts the updated prevention and control parameters as dependent variables into the value domain, thereby constructing a mapping relationship between the production information and the updated prevention and control parameters. Among them, the mapping relationship is a discrete relationship, and the independent variables correspond to the dependent variables one by one. The updated prevention and control parameters refer to the effective prevention and control parameters after the update.

[0169] In some embodiments, for each effective control parameter, the management cloud platform updates the effective control parameter in a variety of ways. For example, the management cloud platform updates the security control level in the effective control parameter based on the proportion of the warning volume corresponding to the effective control parameter to obtain an updated control parameter. For example, the higher the proportion of the warning volume, the higher the updated security control level.

[0170] In some embodiments, the management cloud platform further determines a mapping relationship based on a mapping model.

[0171] The mapping model refers to a model used to update effective prevention and control parameters. In some embodiments, the mapping model is a machine learning model. The management cloud platform trains the mapping model by gradient descent method and other methods based on sample production information and actual updated prevention and control parameters.

[0172] In some embodiments, the sample production information is obtained based on historical data. The management cloud platform determines the historical production process corresponding to the sample production information based on the sample production information and historical data, and determines the effective prevention and control parameters in the historical production process, and obtains the actual updated prevention and control parameters corresponding to the sample production information through the above-mentioned method for updating the effective prevention and control parameters.

[0173] The training process of the mapping model is similar to that of the accident model. For details, please refer to the training process of the accident model.

[0174] In some embodiments, the management cloud platform obtains management perception information from the Industrial Internet of Things perception control platform through the Industrial Internet of Things management platform and the Industrial Internet of Things sensor network platform; and updates the mapping relationship based on the management perception information.

[0175] For instructions on managing perception information, see Figure 2 and its related description.

[0176] In some embodiments, the operating equipment is equipped with a camera, which is used to identify the operating equipment and operating personnel that interfere with the operating equipment. The operating equipment automatically determines whether its own actions are interfered with, and issues an alarm after receiving interference, and uploads the operating equipment and operating personnel that interfere with it as perception management information to the industrial Internet of Things perception control platform. The interference of the operation of the operating equipment includes obstacles on the route, etc.

[0177] In some embodiments, the operating equipment adjusts the intensity of the alarm based on the alarm level. The higher the alarm level, the higher the intensity of the alarm issued by the operating equipment. The intensity of the alarm is characterized by loudness, etc. The alarm level can be pre-set by the technician based on the actual situation.

[0178] In some embodiments, the management cloud platform updates the mapping relationship based on the management perception information. For example, the management cloud platform counts the number of management perception information related to the security control area, adds the number of security warning signals in the warning volume ratio to the number of management perception information to obtain a new warning volume ratio, and if the new warning volume ratio exceeds the preset ratio threshold, the management cloud platform updates the security control parameters corresponding to the security control area through the above-mentioned method of updating effective control parameters. The management cloud platform uses the updated security control parameters as the new dependent variable of the production information in the mapping relationship.

[0179] For example, the management cloud platform retrains the mapping model based on production information and updated safety control parameters.

[0180] In some embodiments of the present specification, by updating the mapping relationship, the accuracy of the mapping relationship can be improved, thereby improving the accuracy of subsequent determination of security control parameters.

[0181] In some embodiments, the management cloud platform matches the current production information with the independent variables in the definition domain, and uses the dependent variables mapped by the matched independent variables as security control parameters.

[0182] In some embodiments, the management cloud platform inputs the current production information into the mapping model, and confirms the updated control parameters output by the mapping model as security control parameters.

[0183] In some embodiments of this specification, the safety control parameters can be quickly determined through mapping relationships and production information, thereby improving the efficiency of determining the safety control parameters.

[0184] Step 330: Send the security control parameters to the industrial Internet of Things management platform. The industrial Internet of Things management platform determines the security control area of ​​at least one production line based on the security control parameters.

[0185] In some embodiments, the industrial Internet of Things management platform identifies a processing procedure whose safety control level in the safety control parameters is greater than a preset level threshold as a target control process, wherein the preset level threshold is pre-set based on historical experience.

[0186] In some embodiments, the preset level threshold is set based on the processor performance of the industrial Internet of Things management platform (for example, the maximum operating frequency of the processor, etc.). The stronger the processor performance, the lower the preset level threshold.

[0187] In some embodiments, for a target prevention and control process, the security control area of ​​the target prevention and control process is determined by the above method for determining the security control area based on the associated time period and the associated area. For more information about the associated time period and the associated area, see Figure 2 Related description.

[0188] Step 340: Obtain the security control area through the industrial Internet of Things management platform.

[0189] For more information about this section, see Figure 2 and its related description.

[0190] In some embodiments of the present specification, full use is made of the big data learning, processing capabilities and data sharing characteristics of the management cloud platform, statistical analysis is performed on the production information of multiple production lines to obtain safety control parameters, and safety control areas are determined based on the safety control parameters, which is beneficial to improving the efficiency and accuracy of determining safety control areas.

[0191] It should be noted that the above description of process 300 is only for example and illustration, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to process 300 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0192] Figure 4 It is a schematic diagram of the structure of the risk identification model shown in some embodiments of this specification.

[0193] In some embodiments, Figure 4 As shown, the management cloud platform can determine security risk data 450 through a risk identification model 430 based on security monitoring information 410 and security prevention and control parameters 420. For a description of security monitoring information, security risk data and security prevention and control parameters, see Figure 2 and Figure 3 and its related description.

[0194] In some embodiments, the risk identification model refers to a model used to determine security risk data. In some embodiments, the risk identification model is a machine learning model.

[0195] In some embodiments, the risk identification model includes a feature layer 431 and an identification layer 432. In some embodiments, the feature layer 431 may be a convolutional neural network (CNN). The identification layer 432 may be a deep-learning neural network (DNN).

[0196] In some embodiments, the input of the feature layer includes security monitoring information 410, and the output includes monitoring features 440. In some embodiments, the input of the identification layer includes security control parameters 420 and monitoring features 440, and the output includes security risk data 450.

[0197] Monitoring characteristics are used to reflect the characteristics of security monitoring information.

[0198] In some embodiments, the management cloud platform jointly trains the feature layer and the recognition layer based on the training set. The training set includes a large number of labeled training samples. The training samples include sample safety monitoring information and sample safety monitoring parameters. The labels include actual safety risk data. In some embodiments, the training samples and labels are determined based on historical data.

[0199] In some embodiments, the management cloud platform can use the historical security monitoring information in the historical monitoring database and the historical security prevention and control parameters corresponding to the historical security monitoring information as training samples, and determine the historical security risk data corresponding to the historical security prevention and control parameters in the historical data as labels. Figure 3 The method in is determined.

[0200] In some embodiments, the risk identification model can be trained in the following manner: input multiple sample safety monitoring information into the initial feature layer, obtain the sample monitoring features output by the initial feature layer, input the sample monitoring features and the sample safety monitoring parameters into the initial recognition layer, construct a loss function through the label and the prediction result of the initial recognition layer, update the initial feature layer and the initial recognition layer based on the iteration of the loss function, and complete the risk identification model training when the loss function of the initial recognition layer meets the preset conditions. For the preset conditions, see step 320 and its related description.

[0201] In some embodiments, in response to an update of the mapping relationship, the management cloud platform constructs an updated training set based on the management perception information.

[0202] For instructions on updating the mapping relationship, see Figure 3 Related description.

[0203] The updated training set refers to the updated training set.

[0204] In some embodiments, the management cloud platform determines the accident level according to the alarm level of the operating equipment that issues an alarm in the management perception information, takes the operating equipment that issues an alarm as the target monitoring object, and constructs new safety risk data as a new label based on the target monitoring object and the accident level of the target monitoring object. The management cloud platform determines the operating equipment and / or operating personnel that interfere with the operating equipment based on the management perception information, and takes the safety monitoring information corresponding to such operating equipment and / or operating personnel as new sample safety monitoring information.

[0205] The management cloud platform incorporates the new labels and sample safety monitoring information into the training set to obtain an updated training data set.

[0206] For more information about alarm levels, incident levels, and target monitoring objects, see Figure 2 and Figure 3 Related description.

[0207] In some embodiments of the present specification, by updating the training set, the accuracy and versatility of the risk identification model can be improved, thereby improving the accuracy of the predicted security risk data.

[0208] In some embodiments of this specification, a risk identification model is used to predict security risk data, and the self-learning ability of a machine learning model can be used to effectively predict the security risk data.

[0209] Some embodiments of the present specification also provide a computer-readable storage medium, which stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the industrial Internet of Things security management method based on a management cloud platform as described in any of the above embodiments.

[0210] Furthermore, certain features, structures or characteristics in one or more embodiments of this specification may be appropriately combined.

[0211] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining the digits. Although the numerical domains and parameters used to confirm the breadth of the range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0212] If there is any inconsistency or conflict between the descriptions, definitions, and / or usage of terms in the materials cited in this specification and the contents described in this specification, the descriptions, definitions, and / or usage of terms in this specification shall prevail.

Claims

1. An industrial Internet of Things security management method based on a management cloud platform, characterized in that: The method is executed by a management cloud platform of an industrial Internet of Things security management system based on a management cloud platform, and the method includes: Obtaining the safety control area of ​​at least one production line through the industrial Internet of Things management platform corresponding to the at least one production line, including: Acquire the production information of the at least one production line and the security control area in multiple time periods through the industrial Internet of Things management platform; The security control areas of the multiple time periods are determined by the industrial Internet of Things management platform corresponding to the at least one production line; and Determine, by means of the industrial Internet of Things management platform, a security control node based on the production information, and determine, based on the security control node, the security control areas in the multiple time periods; Determining the safety monitoring parameters of the safety control area; Based on the safety monitoring parameters, a safety monitoring instruction is generated and sent to the safety monitoring device of the industrial Internet of Things perception control platform through the industrial Internet of Things management platform; Acquiring safety monitoring information collected by the safety monitoring device based on the safety monitoring parameters; Based on the security monitoring information, generate security management parameters for the security control area, the security management parameters including security warning parameters and / or production scheduling parameters, and send the security management parameters to the industrial Internet of Things management platform; In response to receiving confirmation information sent by the industrial Internet of Things management platform, generating a security management instruction based on the confirmation information; The safety management instruction is sent to the industrial Internet of Things perception control platform through the industrial Internet of Things management platform, and the industrial Internet of Things perception control platform includes an early warning platform and an operation platform. The early warning platform controls the early warning device to send a safety early warning signal based on the safety early warning parameter, and / or the operation platform updates the operation parameters of the at least one production line based on the production scheduling parameter; and Obtain the execution result of the early warning platform based on the security management instruction, and adjust the security monitoring parameter based on the execution result.

2. The method according to claim 1, characterized in that The step of obtaining the safety control area of ​​at least one production line through the industrial Internet of Things management platform corresponding to the at least one production line further includes: Acquire the production information of the at least one production line through the industrial Internet of Things management platform; Based on the production information, determining safety control parameters of the at least one production line; Sending the safety control parameters to the industrial Internet of Things management platform, and the industrial Internet of Things management platform determining the safety control area of ​​the at least one production line based on the safety control parameters; and The security control area is obtained through the industrial Internet of Things management platform.

3. The method according to claim 1, characterized in that The generating of the security management parameters of the security control area based on the security monitoring information, wherein the security management parameters include security warning parameters and production scheduling parameters, and sending the security management parameters to the industrial Internet of Things management platform includes: Determining safety risk data of the at least one production line based on the safety monitoring information; and Based on the security risk data, the security management parameter is determined.

4. The method according to claim 3, characterized in that: The determining the security management parameter based on the security risk data includes: Based on the security risk data, determining controllable data and uncontrollable data; Based on the controllable data, determining the safety warning parameter; and The production scheduling parameters are determined based on the uncontrollable data and the production information of the at least one production line.

5. An industrial Internet of Things security management system based on a management cloud platform, characterized in that: The system includes a management cloud platform and at least one subsystem, wherein the at least one subsystem includes a subsystem corresponding to at least one production line, wherein each subsystem in the at least one subsystem includes an industrial Internet of Things user platform, an industrial Internet of Things service platform, an industrial Internet of Things management platform, an industrial Internet of Things sensor network platform and an industrial Internet of Things perception control platform, and the management cloud platform is configured as follows: Obtaining the safety control area of ​​the at least one production line through the industrial Internet of Things management platform corresponding to the at least one production line, including: Acquire the production information of the at least one production line and the security control area in multiple time periods through the industrial Internet of Things management platform; The security control areas of the multiple time periods are determined by the industrial Internet of Things management platform corresponding to the at least one production line; and Determine, by means of the industrial Internet of Things management platform, a security control node based on the production information, and determine, based on the security control node, the security control areas in the multiple time periods; Determining the safety monitoring parameters of the safety control area; Based on the safety monitoring parameters, a safety monitoring instruction is generated and sent to the safety monitoring device of the industrial Internet of Things perception control platform through the industrial Internet of Things management platform; Acquiring safety monitoring information collected by the safety monitoring device based on the safety monitoring parameters; Based on the security monitoring information, generate security management parameters for the security control area, the security management parameters including security warning parameters and / or production scheduling parameters, and send the security management parameters to the industrial Internet of Things management platform; In response to receiving confirmation information sent by the industrial Internet of Things management platform, generating a security management instruction based on the confirmation information; The safety management instruction is sent to the industrial Internet of Things perception control platform through the industrial Internet of Things management platform, and the industrial Internet of Things perception control platform includes an early warning platform and an operation platform. The early warning platform controls the early warning device to send a safety early warning signal based on the safety early warning parameter, and / or the operation platform updates the operation parameters of the at least one production line based on the production scheduling parameter; and Obtain the execution result of the early warning platform based on the security management instruction, and adjust the security monitoring parameter based on the execution result.

6. The system according to claim 5, characterized in that The management cloud platform is further configured as follows: Acquire the production information of the at least one production line through the industrial Internet of Things management platform; Based on the production information, determining safety control parameters of the at least one production line; Sending the safety control parameters to the industrial Internet of Things management platform, and the industrial Internet of Things management platform determining the safety control area of ​​the at least one production line based on the safety control parameters; as well as The security control area is obtained through the industrial Internet of Things management platform.

7. The system according to claim 5, characterized in that The management cloud platform is further configured as follows: Determining safety risk data of the at least one production line based on the safety monitoring information; and Based on the security risk data, the security management parameter is determined.

8. A computer-readable storage medium, characterized in that: The storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the method as claimed in claim 1.

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