Information protection-oriented intelligent computing transmission method and system

Abstract

The invention belongs to the technical field of wireless communication, and discloses an information protection-oriented intelligent computing transmission method and system, and the method comprises the steps: comprehensively deploying communication nodes based on the terrain and range distribution of a mine region; establishing a wireless communication network between the communication nodes, and calibrating the sensor and the data acquisition equipment; environment parameters in a mine area are monitored in real time through the communication nodes, and node state information is updated; based on a dynamic scheduling mechanism, the working state of each communication node is monitored and diagnosed in combination with environmental parameters and node state information, and an information transmission strategy is adjusted according to a state diagnosis result. According to the method, three types of calculation sensing stages are designed, and the three types of nodes form a safety monitoring network covering the whole mine area, so that the comprehensiveness of environment monitoring is ensured, and the safety and stability in the information monitoring and transmission process are improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to an intelligent computing transmission method and system for information protection. Background Art

[0002] As an important base for industrial production, safety monitoring of mines is particularly important. The mine environment is complex and changeable, often accompanied by dangerous factors such as flammable and explosive gases, high temperature, and high pressure, and the operation of large-scale mechanical equipment also increases the risk of accidents. Therefore, it is necessary to configure a corresponding safety monitoring system to monitor and manage these risks, ensure the safety of miners and the normal operation of equipment, and reduce the possibility of accidents.

[0003] Mine safety monitoring is an important system to ensure the safety of workers and equipment during mine operations. Its necessity is mainly reflected in the complex environment, high operating risks, dense personnel, and the serious consequences that mine accidents may bring. The safety monitoring system uses advanced technical means, such as sensor nodes and network communication technology, to monitor the environmental conditions, equipment status and personnel activities of each key point in the mine in real time, so as to timely warn and prevent potential safety risks.

[0004] The safety monitoring system involves a variety of technical means, among which the key ones are node technology and network technology. Node technology includes various sensor nodes, such as temperature sensors, humidity sensors, gas concentration sensors, etc. These nodes can collect data on various environmental parameters in the mine in real time. These data are transmitted to the central control system through network technologies, such as wireless sensor networks (WSN) and Internet of Things (IoT) technologies, to ensure the real-time and reliability of the data.

[0005] In traditional mine safety monitoring solutions, a branch node may lose connection with the central node. At this time, it is usually impossible to quickly determine whether the damage to the branch node is caused by the link, the branch node itself, or environmental damage. Further research is needed on how to quickly identify the cause of the loss of connection when the branch node loses connection with the central node, and to promptly detect abnormalities in the detection environment and report them effectively.

[0006] Therefore, how to provide an intelligent computing transmission method and system for information protection is a problem that needs to be solved urgently. Summary of the invention

[0007] The embodiments of the present invention provide an intelligent computing transmission method and system for information protection to solve the above problems existing in the prior art.

[0008] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended to be a general review, nor is it intended to identify key / important components or to delineate the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0009] According to a first aspect of an embodiment of the present invention, an intelligent computing transmission method for information protection is provided.

[0010] In one embodiment, the intelligent computing transmission method for information protection includes:

[0011] Comprehensively deploy communication nodes based on the terrain and range distribution of the mining area;

[0012] Establish wireless communication networks between communication nodes and calibrate sensors and data acquisition equipment;

[0013] Real-time monitoring of environmental parameters in the mining area through communication nodes, and updating of node status information;

[0014] Based on the dynamic scheduling mechanism, combined with environmental parameters and node status information, the working status of each communication node is monitored and diagnosed, and the information transmission strategy is adjusted according to the status diagnosis results.

[0015] In one embodiment, based on the topography and range distribution of the mining area, the comprehensive deployment of communication nodes includes:

[0016] Use geographic information system tools to analyze the topography of the mining area, draw a topographic map of the mining area, set the boundaries of the mining area, and divide different functional areas according to the type of operation;

[0017] Corresponding communication nodes are deployed according to the distribution of the functional areas and the types of operations.

[0018] In one embodiment, the communication node includes a central node, fixed branches and mobile branch nodes; the central node is deployed in a functional area located at the core of a mine, the fixed branch nodes are deployed in a functional area for construction operations, and the mobile branch nodes are deployed in a movable device.

[0019] In one embodiment, the steps of establishing a wireless communication network between communication nodes and calibrating sensors and data acquisition equipment include:

[0020] Establishing communication connections between various communication nodes based on a wireless communication network;

[0021] According to the trust levels pre-divided by the communication nodes, different data access permissions and decryption capabilities are set, and communication nodes of different levels use different reconfigurable encryption methods, and high-level communication nodes can decrypt the encrypted information of low-level communication nodes;

[0022] After the communication node is connected to the wireless communication network, the sensor and data acquisition device where the communication node is driven are calibrated for accuracy.

[0023] In one embodiment, the dynamic scheduling mechanism is used to monitor and diagnose the working status of each communication node in combination with environmental parameters and node status information, and the information transmission strategy is adjusted according to the status diagnosis result, including:

[0024] Real-time detection of the connection status between communication nodes, when the target fixed branch node is interrupted, the scheduling instructions of the mobile branch node are assigned according to the pre-defined mobile branch node scheduling strategy;

[0025] After the mobile branch node moves to the connection interruption position, it establishes data transmission with the central node, and analyzes the fault type of the connection interruption phenomenon of the target fixed branch node through the central node;

[0026] Based on the historical information and current node status information of the communication node, the confidence probability of the working status and environmental parameters of the communication node is evaluated, and the decision framework of the communication node is defined to adjust the information transmission strategy.

[0027] In one embodiment, the real-time detection of the connection status between the communication nodes, when the target fixed branch node is interrupted, assigning the scheduling instruction of the mobile branch node according to the predefined mobile branch node scheduling strategy includes:

[0028] Detect the connection status between the central node and the fixed branch node in real time, and when the target fixed branch node is disconnected, try to communicate with other fixed branch nodes connected to the target fixed branch node. If the other connected fixed branch nodes can normally obtain the information of the target fixed branch node, it is determined that the connection between the central node and the target fixed branch node is disconnected, and marked as disconnected;

[0029] If the other connected fixed branch nodes cannot obtain the information of the target fixed branch node, it is determined that there is a connection abnormality and the scheduling function of the mobile branch node is started;

[0030] According to the scheduling strategy of the mobile branch node, the central node is used to calculate the priority, distance, time and optimal path from the mobile branch node to the target fixed branch node, and the scheduling instruction is issued after the calculation is completed;

[0031] The mobile branch node moves to the target fixed branch node whose connection is interrupted according to the scheduling instruction, establishes a connection with the sensor and the acquisition device, and repairs the target fixed branch node to work normally.

[0032] In one embodiment, after the mobile branch node moves to the connection interruption position, data transmission is established with the central node, and the central node analyzes the fault type of the connection interruption phenomenon of the target fixed branch node, including:

[0033] The mobile branch nodes use sensors and acquisition equipment to collect field data and send it to the central node;

[0034] The central node pre-processes the field data and checks for abnormal values ​​in the field data;

[0035] Analyze the node status information of the mobile branch node and the target fixed branch node, and compare the historical data and field data of the target fixed branch node in a normal state to identify the fault characteristics;

[0036] After completing the fault diagnosis, a diagnostic report is generated through the central node and a treatment plan is formulated.

[0037] In one embodiment, the process of evaluating the working status of the communication node and the confidence probability of the environmental parameters based on the historical information of the communication node and the current node status information, defining the decision framework of the communication node, and adjusting the information transmission strategy includes:

[0038] The central node obtains the environmental parameters, node status information and historical information of each fixed branch node, and then performs preprocessing to extract node features;

[0039] Based on the extracted node features, a probability model is constructed using Bayesian to represent the relationship between node status and environmental parameters, and the confidence probability between the working status and environmental parameters is calculated;

[0040] According to the combined results of confidence probabilities, it is determined whether there is any abnormality in the working status of the fixed branch node, and a decision-making framework is built using different working statuses and response capabilities. After identifying the abnormal working status, the response decision is automatically matched and the information transmission decision between the communication nodes is adjusted.

[0041] In one embodiment, the relationship between the working state and the environmental parameters includes normal working state and normal environmental parameters, normal working state and abnormal environment, abnormal working state and normal environment, and abnormal working state and abnormal environment.

[0042] According to a second aspect of an embodiment of the present invention, an intelligent computing transmission system for information protection is provided.

[0043] In one embodiment, the intelligent computing transmission system for information protection includes:

[0044] Node deployment module, used to comprehensively deploy communication nodes based on the topography and range distribution of the mining area;

[0045] A communication connection module is used to establish a wireless communication network between communication nodes and calibrate sensors and data acquisition equipment;

[0046] The monitoring and updating module is used to monitor the environmental parameters in the mining area in real time through the communication nodes and update the node status information;

[0047] The scheduling calculation module is used to monitor and diagnose the working status of each communication node based on the dynamic scheduling mechanism, combined with environmental parameters and node status information, and adjust the information transmission strategy according to the status diagnosis results.

[0048] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0049] In some embodiments, the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0050] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0051] In one embodiment, the computer-readable storage medium stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0052] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0053] 1. By designing three types of computing perception stages, the first type of node is the central node, which stores all the information of the mine and makes decisions, and is the core of the local area network; the second type of node is a fixed branch node, which has data connection with the central node and between branch nodes, and has the ability to collect information on vision, sound, vibration, temperature, humidity, and magnetic field in the regional scope; the third type of node is a flexible and movable branch node, which moves by aerodynamics, i.e., drones, hot air balloons, etc., liquid dynamics, i.e., unmanned ships, friction, i.e., unmanned vehicles, unmanned robots, etc., and also has the ability to collect information on vision, sound, vibration, temperature, humidity, and magnetic field in the regional scope, and has the ability to detect the working status of branch nodes; the three types of nodes form a safety monitoring network covering the entire mining area, thereby ensuring the comprehensiveness of environmental monitoring and improving the safety and stability of information monitoring and transmission.

[0054] 2. The information of traditional intelligent decision-making system is divided into multiple trust levels according to the degree of authorization. High-level trust can receive and analyze low-level trust data, but not vice versa. Different levels of trust data use different reconfigurable encryption and decryption methods, combined with the sudden cross-level scheduling mode, that is, when a preset fault occurs in the system, no matter how trustworthy the current node is, it can use the highest level of trust mode for communication and data scheduling. In this way, dynamic real-time reconfigurable encrypted intelligent information transmission is realized to ensure the safe circulation of information.

[0055] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0057] Figure 1 is a flow chart of an intelligent computing transmission method for information protection according to an exemplary embodiment;

[0058] Figure 2 is a structural diagram of an intelligent computing transmission system for information protection according to an exemplary embodiment;

[0059] Figure 3 is a schematic diagram of a working mechanism of an intelligent computing transmission system for information protection according to an exemplary embodiment;

[0060] Figure 4 The figure is a schematic diagram showing the structure of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0061] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0062] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0063] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0064] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0065] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0066] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0067] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above modules.

[0068] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0069] Figure 1 An embodiment of an intelligent computing transmission method for information protection of the present invention is shown.

[0070] In this optional embodiment, the intelligent computing transmission method for information protection includes:

[0071] Step S101: comprehensively deploy communication nodes based on the topography and range distribution of the mining area;

[0072] Step S103: establishing a wireless communication network between communication nodes, and calibrating sensors and data acquisition equipment;

[0073] Step S105: monitor the environmental parameters in the mining area in real time through the communication nodes, and update the node status information;

[0074] Step S107: Based on the dynamic scheduling mechanism, combined with environmental parameters and node status information, monitor and diagnose the working status of each communication node, and adjust the information transmission strategy according to the status diagnosis result.

[0075] In this optional embodiment, when comprehensively deploying communication nodes based on the topography and range distribution of the mining area, geographic information system tools can be used to analyze the topography of the mining area, draw a mining topographic map, set the boundary range of the mining area, and divide different functional areas according to the operation type; deploy corresponding communication nodes according to the distribution of the functional areas and the operation type.

[0076] In this optional embodiment, the communication nodes include a central node, fixed branches and mobile branch nodes; the central node is deployed in a functional area located at the core of the mine, the fixed branch nodes are deployed in a functional area for construction operations, and the mobile branch nodes are deployed in a movable device.

[0077] In this optional embodiment, when establishing a wireless communication network between communication nodes and calibrating sensors and data acquisition equipment, a communication connection between each communication node can be established based on the wireless communication network; different data access rights and decryption capabilities are set according to the trust levels pre-divided by the communication nodes, and communication nodes of different levels use different reconfigurable encryption methods, and high-level communication nodes can decrypt encrypted information of low-level communication nodes; after the communication nodes are connected to the wireless communication network, the sensors and data acquisition equipment where the communication nodes are driven are calibrated for accuracy.

[0078] In this optional embodiment, based on the dynamic scheduling mechanism, combined with environmental parameters and node status information, the working status of each communication node is monitored and diagnosed, and the information transmission strategy is adjusted according to the status diagnosis results. The connection status between the communication nodes can be detected in real time. When an interruption occurs at the target fixed branch node, the scheduling instructions of the mobile branch node are allocated according to the pre-defined mobile branch node scheduling strategy; after the mobile branch node moves to the connection interruption position, data transmission is established with the central node, and the fault type of the target fixed branch node connection interruption phenomenon is analyzed through the central node; based on the historical information of the communication node and the current node status information, the confidence probability of the working status of the communication node and the environmental parameters is evaluated, and the decision framework of the communication node is defined to adjust the information transmission strategy.

[0079] In this optional embodiment, when the connection status between communication nodes is detected in real time, when the target fixed branch node is interrupted, according to the predefined mobile branch node scheduling policy, when the scheduling instructions of the mobile branch node are allocated, the connection status between the central node and the fixed branch node can be detected in real time, and when the target fixed branch node is disconnected, the central node attempts to communicate with other fixed branch nodes connected to the target fixed branch node. If the other connected fixed branch nodes can normally obtain the information of the target fixed branch node, it is determined that the connection between the central node and the target fixed branch node is interrupted, and marked as a connection interruption; if the other connected fixed branch nodes cannot obtain the information of the target fixed branch node, it is determined that there is a connection abnormality, and the scheduling function of the mobile branch node is started; according to the scheduling policy of the mobile branch node, the central node is used to calculate the priority, distance, time and optimal path from the mobile branch node to the target fixed branch node, and a scheduling instruction is issued after the calculation is completed; the mobile branch node moves to the target fixed branch node with the interrupted connection according to the scheduling instruction, establishes a connection with the sensor and the acquisition device, and repairs the target fixed branch node to work normally.

[0080] In this optional embodiment, after the mobile branch node moves to the connection interruption position, it establishes data transmission with the central node, and when the fault type of the connection interruption phenomenon of the target fixed branch node is analyzed through the central node, the mobile branch node uses sensors and collection equipment to collect field data and sends it to the central node; the central node pre-processes the field data and checks the abnormal values ​​in the field data; analyzes the node status information of the mobile branch node and the target fixed branch node, and compares the historical data and field data of the target fixed branch node under normal conditions to identify fault characteristics; after completing the fault diagnosis, a diagnostic report is generated through the central node, and a processing plan is formulated.

[0081] In this optional embodiment, based on the historical information of the communication node and the current node status information, the confidence probability of the working status and environmental parameters of the communication node is evaluated, and the decision framework of the communication node is defined to adjust the information transmission strategy. The central node can obtain the environmental parameters, node status information and historical information of each fixed branch node, and then perform preprocessing to extract node features; based on the extracted node features, a probability model is constructed using Bayesian to represent the relationship between the node status and the environmental parameters, and the confidence probability between the working status and the environmental parameters is calculated; based on the combined results of the confidence probabilities, it is determined whether there is an abnormality in the working status of the fixed branch node, and a decision framework is constructed using different working statuses and response capabilities. After identifying the abnormality in the working status, the response decision is automatically matched to adjust the information transmission decision between the communication nodes.

[0082] In this optional embodiment, the relationship between the working state and the environmental parameters includes normal working state and normal environmental parameters, normal working state and abnormal environment, abnormal working state and normal environment, and abnormal working state and abnormal environment.

[0083] Figure 2 An embodiment of an intelligent computing transmission system for information protection according to the present invention is shown.

[0084] In this optional embodiment, the information protection-oriented intelligent computing transmission system includes:

[0085] The node deployment module 201 is used to comprehensively deploy communication nodes based on the topography and range distribution of the mining area;

[0086] The communication connection module 203 is used to establish a wireless communication network between communication nodes and calibrate sensors and data acquisition equipment;

[0087] Monitoring and updating module 205, used to monitor environmental parameters in the mine area in real time through communication nodes and update node status information;

[0088] The scheduling calculation module 207 is used to monitor and diagnose the working status of each communication node based on the dynamic scheduling mechanism, combined with environmental parameters and node status information, and adjust the information transmission strategy according to the status diagnosis result.

[0089] In view of the traditional mine safety monitoring scheme, when the connection between a branch node and the central node is interrupted, the present invention formulates a series of optimization schemes to quickly identify the cause of the loss of connection, and promptly detect the abnormality of the detection environment and conduct effective reporting and processing.

[0090] The present invention proposes an intelligent computing transmission system for information protection. Specifically, the information of the traditional intelligent decision-making system is divided into multiple trust levels according to the degree of authorization. The high-level trust can receive and parse the low-level trust data, but not vice versa. Different levels of trusted data use different reconfigurable encryption and decryption methods. The reconfigurable encryption method uses a same encryption code to encrypt the information transmission itself, and the decryption information obtained by nodes of different levels is different, which further leads to the highest trust level node can obtain all information, the lowest trust level node can obtain the least information, and so on in between. Furthermore, this system sets a sudden cross-level scheduling mode, that is, when a preset major accident occurs in the system, regardless of the current node's trust level, it can use the highest level of trust mode for communication and data scheduling. In this way, an intelligent computing transmission system for information protection is constructed to ensure the safe circulation of information.

[0091] Different levels of trusted data use different reconfigurable encryption and decryption methods. This design is intended to ensure the security and effectiveness of information. The following is a detailed description of this mechanism:

[0092] 1. Basic principles of encryption mechanism

[0093] Reconfigurable encryption uses the same encryption code (key) to encrypt information. The basic idea of ​​this method is to ensure that the information remains confidential during transmission, and at the same time, through different decryption algorithms or strategies, nodes at different levels can obtain different levels of information when decrypting.

[0094] 2. Classification of Trust Levels

[0095] The system manages data access permissions by classifying nodes into different trust levels (e.g., high trust, medium trust, and low trust). Nodes at each level have different access to information and decryption capabilities based on their trust level: 2.1. High trust level nodes can obtain and decrypt all information. These nodes have the highest authority and can access complete, uncensored data, suitable for decision makers or important system administrators. 2.2. Medium trust level nodes can access partial information, usually data related to their duties. These nodes can decrypt information related to their work, but cannot access sensitive or highly confidential data. 2.3. Low trust level nodes can only obtain minimal information, usually filtered or processed data to prevent the leakage of sensitive information. The decryption capabilities of these nodes are strictly limited to ensure information security.

[0096] 3. Reconfigurable decryption method

[0097] The reconfigurability of the decryption method is reflected in the following aspects: 3.1. Dynamic permission control, which can dynamically adjust the decryption capability of the node according to the trust level of the node. When the trust level of the node changes, the system can update its decryption permission in real time. 3.2. Information security: Even if the attacker obtains the encrypted data, due to the different levels of decryption strategies, the low-trust nodes cannot obtain complete information, which effectively reduces the risk of information leakage. 3.3. Flexibility and adaptability: In actual applications, the system can adjust the decryption methods of nodes at different levels according to specific needs or environmental changes, providing a more flexible information management strategy.

[0098] The emergency cross-level dispatch mode is designed to ensure that when a major accident or emergency occurs in the system, all nodes can quickly and effectively communicate and dispatch data, regardless of their original trustworthiness. Through this mechanism, the system can achieve rapid information flow and efficient response in crisis situations.

[0099] In addition, for the emergency cross-level dispatching mode set in the present invention, when a preset major accident occurs in the system, the following definition can be made:

[0100] 1. Definition of emergencies: emergencies are usually unforeseen emergencies that require immediate response, such as natural disasters, cyber attacks or system failures. Such events are high risk and high urgency, and the system has the ability to quickly adapt and provide reliable information support.

[0101] 2. Implementation mechanism of burst cross-level scheduling mode

[0102] The implementation of this model mainly includes the following aspects:

[0103] 2.1. Privilege escalation: When an emergency occurs, the access rights of all nodes will be instantly upgraded to the highest level. This means that complete information can be obtained regardless of the original trust level of the node. This design ensures that all personnel involved in the response have equal access to necessary information to facilitate collaborative work. 2.2 Priority of information flow: In emergencies, the rate of information transmission is critical. The system sets priorities to ensure that critical data can be quickly transmitted to relevant nodes to avoid negative consequences caused by delays. 2.3 Dynamic scheduling mechanism: The system has the ability of real-time monitoring and dynamic scheduling, and can adjust the information transmission strategy in a timely manner according to the nature and development of the emergency to ensure that information can arrive quickly when needed.

[0104] When the connection between the first branch node and the central node is interrupted, the central node first inquires about the status of the node through the second branch node connected to the branch node. If it is found that the node is still working normally and is connected to the second branch node normally, it is determined that only the information transmission link between the central node and the first branch node is interrupted. No further processing is required. Only the first link is marked as interrupted and repaired at an appropriate time. When the second branch node cannot obtain the information of the first branch node, the central node dispatches the third flexible and movable branch node to go to the first branch node to collect information on the vision, sound, vibration, temperature, humidity, and magnetic field in the area, and detects the working status of the branch node, and transmits the above information to the branch node.

[0105] Furthermore, the present invention also proposes a definition of confidence probability, which evaluates four states of each branch node, namely, normal working state and normal environmental parameters, normal working state and abnormal environment, abnormal working state and normal environment, and abnormal working state and abnormal environment. The acquisition method is to use the Bayesian function to evaluate its possible results based on the historical information and current state information of the branch node. At the same time, when the connection between the first branch node and the central node is interrupted, the central node informs the operator of the confidence probability of the state information for the operator to evaluate.

[0106] The overall process of the present invention can be summarized in the following four aspects:

[0107] 1. Planning and layout: Determine the terrain, scope and key areas of the mining area, including the location layout of the central node, fixed branch nodes, and the areas that need to be covered. Determine the type and number of flexible and movable branch nodes, and plan their deployment strategy according to the characteristics and needs of the mine. Install and configure the hardware and software equipment of the central node and fixed branch nodes. Deploy flexible and movable branch nodes to ensure that they have functions such as information collection, mobility and data transmission. 2. Network connection and calibration: Establish data connections between nodes to ensure smooth communication and information transmission between nodes. Calibrate sensors and data acquisition equipment to ensure their accuracy and reliability. 3. Monitoring and data acquisition: Each node begins to monitor and collect regional information, including visual, sound, vibration, temperature, humidity and magnetic field data. The central node stores and analyzes this data and continuously updates the status information and status of each node. 4. Connection interruption processing: When the central node is disconnected from a fixed branch node, it first communicates with other branch nodes connected to the branch node to determine the specific situation of the connection interruption. If the second branch node can obtain the information of the first branch node, it determines that the connection interruption is a link interruption, marks and records the connection problem, and prepares to repair it. If the second branch node is also unable to obtain information, the central node will dispatch a flexible and movable branch node to the location of the first branch node, and collect and detect the regional information and node status to obtain detailed information on the connection interruption.

[0108] Embodiment 1

[0109] For the mine area layout and node deployment planning (including the following six aspects)

[0110] 1. Determine the topography, scope and key areas of the mining area

[0111] Geographic Information System (GIS) tools are needed to conduct terrain analysis of the mine area and draw detailed topographic maps. Determine the boundary of the mine, including the mining area, transportation channel, spoil dump, etc. Key area identification: The central node is located in the core management area of ​​the mine, usually close to the mine office or command center, for centralized data management and monitoring. Fixed branch nodes are distributed in the key operating areas of the mine (such as mining area, processing area, transportation area) for real-time monitoring and data collection.

[0112] 2. Node location layout

[0113] 2.1. The location of the central node is the geographical center of the mine, ensuring that all fixed branch nodes can be covered. The fixed branch node layout is based on the operation process of the mine, and the location of the fixed branch nodes is reasonably arranged to ensure that each node can cover the required data collection area. 2.2. Example layout: Mine command center (GPS coordinates); fixed branch node 1: mining area (GPS coordinates); fixed branch node 2: transportation channel (GPS coordinates); fixed branch node 3: processing area (GPS coordinates).

[0114] 3. Types and quantities of flexible and movable branch nodes

[0115] 3.1. Mobile branch node types include: Unmanned aerial vehicles (UAVs), which are used for aerial monitoring and data collection and are suitable for large-scale monitoring. Mobile monitoring vehicles, which can be flexibly moved within the mine and are equipped with a variety of sensors for environmental monitoring. Wearable devices provide real-time data collection and monitoring for on-site staff to facilitate personal safety management. 3.2. Mobile branch node type quantity planning: Determine the number of flexible and movable branch nodes based on the scale of the mine and operational requirements. For example, UAVs: 2-3; Mobile monitoring vehicles: 1-2; Wearable devices: 1 for each key employee.

[0116] 4. Deployment strategy: The deployment strategy of flexible and movable branch nodes needs to formulate flexible scheduling strategies according to the operation requirements and the dynamic changes of the mine to ensure that each area can obtain the necessary data in a timely manner. Regularly check and maintain mobile nodes to ensure their normal operation and data transmission capabilities.

[0117] 5. Install and configure the hardware and software equipment of the central node and fixed branch nodes

[0118] The central node includes servers, which provide high-performance computing capabilities and support data processing and storage; as well as network equipment to ensure stable communication between the central node and all branch nodes. Fixed branch nodes include data acquisition equipment, such as sensors, cameras, etc., to ensure real-time monitoring; as well as computing equipment, local data processing and transmission functions. The software aspect requires a data management system for collecting, storing and analyzing data. There is also a communication protocol to ensure the security and efficiency of data transmission between the central node and each branch node.

[0119] 6. Deploy flexible and movable branch nodes

[0120] 6.1. Deployment steps: Installation and testing, deploy flexible and movable branch nodes in the actual operating environment to ensure that their information collection, mobility and data transmission functions are normal. Train operators to make them familiar with equipment operation and data collection processes. After the initial deployment, continuously monitor the operation of the nodes and make adjustments and optimizations according to actual needs. 6.2. Connection interruption detection: When the system detects that the connection between the central node and a fixed branch node is interrupted, the system immediately starts the connection interruption handler. 6.3. Communication confirmation: The central node will try to communicate with other connected fixed branch nodes to determine whether it is a problem with a single node or a connection problem across the entire area. If the other connected branch nodes can normally obtain the information of the disconnected node, the system preliminarily determines that the connection between the central node and the specific branch node is interrupted. 6.4. Link interruption judgment: If the other connected nodes can obtain the information of the disconnected node, it means that the branch node is in normal working condition, but the information transmission link between the central node and the node is interrupted. In this case, the system will mark the connection interruption, but there is no need to intervene in the node itself. 6.5. Information acquisition and processing: If other connected nodes are also unable to obtain the information of the disconnected node, the system determines that there is a more complex connection problem. The central node will start the scheduling process of the flexible and movable branch nodes. 6.6. Mobile branch node scheduling: The central node selects the most suitable flexible and movable branch node according to the pre-set scheduling strategy, and sends instructions to it to go to the location of the fixed branch node where the connection is interrupted. The scheduling of mobile branch nodes is a dynamic and intelligent process involving real-time data analysis, policy decision-making and efficient execution. When the central node faces the situation of disconnection of the fixed branch node, it needs to select the most suitable movable branch node according to the preset scheduling strategy to ensure that the flow of information is not affected.

[0121] According to the above deployment and distribution methods, communication nodes can be fully deployed in the mining area to build a complete three-type node system, such as Figure 3 shown.

[0122] Embodiment 2

[0123] After the intelligent computing transmission system is built, it is necessary to realize information transmission and intelligent decision-making through communication and scheduling between nodes. Therefore, the overall scheduling process can be summarized as follows.

[0124] 1. Design of Scheduling Strategy

[0125] The scheduling strategy is the core of the scheduling process and usually includes the following aspects:

[0126] 1.1. Priority assessment: Evaluate the nodes that need to be prioritized based on the importance of the fixed branch nodes and the current situation. For example, if a fixed branch node involves critical safety monitoring, its priority will be higher than other nodes. 1.2. Distance and time calculation: The central node needs to calculate the distance and estimated time required for the movable branch node to reach the target fixed branch node in real time. Use map information and real-time traffic data for dynamic calculations to determine the optimal path. 1.3. Node status monitoring: Monitor the status of the movable branch nodes, including power, fault conditions, current tasks, etc., to ensure that the selected nodes can complete the scheduling tasks.

[0127] 2. Decision-making process of the central node

[0128] When the fixed branch node connection is interrupted, the central node will make a decision according to the following steps:

[0129] 2.1. Detect interruption: Through the real-time monitoring system, timely detect the connection interruption of the fixed branch node, and confirm the nature and scope of the interruption. 2.2. Data analysis: Analyze the impact of the interruption on the overall operation process, and perform priority assessment to determine the fixed branch nodes that need to be scheduled. 2.3. Movable node selection: Based on distance, status, time and task urgency, select the most suitable node from the movable branch node library. Ensure that the selected node has good mobility and stable data transmission function. 2.4. Send scheduling instructions: Send scheduling instructions to the selected movable branch node, including target location, task requirements and expected arrival time.

[0130] 3. Execution process of moving branch nodes

[0131] After receiving the dispatch instruction, the movable branch node will perform the following steps:

[0132] 3.1. Confirm the task: After receiving the dispatch instruction, confirm the target location and task requirements, and make necessary preparations. 3.2. Path planning: Based on the current location information and the target location, perform path planning and select the best route. Real-time traffic, terrain changes, and possible obstacles need to be considered. 3.3. Movement and monitoring: Start moving to the target location while monitoring the path to ensure safety and smoothness along the way. During the movement, continue to communicate with the central node to transmit location information and status updates to ensure the transparency and real-time nature of the dispatch process. 3.4. Arrive at the target location: After arriving at the fixed branch node where the connection is interrupted, immediately connect the device and collect data. Ensure that the fixed branch node resumes normal operation and transmits the collected information back to the central node in real time.

[0133] 4. Recovery and Adjustment

[0134] After successful connection and data collection, the central node needs to perform subsequent recovery and adjustment:

[0135] 4.1. Data integration and analysis: Integrate and analyze the collected data to evaluate the cause and impact of the connection interruption. 4.2. Performance evaluation: Evaluate the scheduling process of the mobile branch node and identify the advantages and disadvantages in the scheduling strategy for subsequent optimization. 4.3. Update the scheduling strategy: According to the evaluation results, adjust and optimize the scheduling strategy to improve the response speed and accuracy in the future. 4.4. Information collection and status detection: Once the mobile branch node reaches the target location, it begins to collect visual, sound, vibration, temperature, humidity, magnetic field and other information in the surrounding area. At the same time, the mobile branch node detects the working status of the fixed branch node with interrupted connection to ensure whether the node itself has a fault. 4.5. Information transmission and diagnosis: The information collected by the mobile branch node is sent to the central node through data transmission. The central node analyzes and diagnoses the collected information to understand the specific cause of the connection interruption: whether it is caused by node failure, communication link failure, or environmental abnormality.

[0136] Embodiment 3

[0137] Information transmission and diagnosis are important links to ensure the safety and efficiency of mine operations, especially when the connection of fixed branch nodes is interrupted. The timely response and data transmission capabilities of mobile branch nodes can provide key information to the central node for fault diagnosis.

[0138] The following is a detailed explanation of the process.

[0139] 1. Information collection and data transmission

[0140] 1.1. Information collection: Mobile branch nodes use various sensors (such as temperature, pressure, humidity sensors), cameras and other monitoring equipment on site to collect real-time data on site. This data may include: 1.2. Equipment status: Monitor the operating status of the equipment in use, including temperature, vibration, pressure, etc.

[0141] 1.3. Environmental parameters: Collect meteorological data of the surrounding environment, such as wind speed, rainfall, temperature, etc. 1.4. Personnel safety data: Collect physiological data (such as heart rate, body temperature, etc.) of on-site staff through wearable devices. 1.5. Data transmission: Once the necessary information is collected, the mobile branch node will use wireless communication technology (such as 5G, LTE, Wi-Fi, etc.) to transmit the data to the central node in real time. To ensure the integrity and security of the data, data encryption and error checking mechanisms are usually adopted. Packet fragmentation and retransmission functions can be used to prevent data from being lost or damaged during transmission.

[0142] 2. Data analysis and diagnosis of central nodes

[0143] Once the central node receives the data transmitted by the mobile branch node, it will immediately start analysis and diagnosis. This process usually includes the following steps:

[0144] 2.1. Data collation and preprocessing: The central node will collate the received data, remove redundant information, ensure the data format is uniform, and prepare for subsequent analysis. 2.2. Real-time monitoring and anomaly detection: Using the real-time monitoring system, the central node will check whether there are abnormal values ​​in the data, such as sensor data outside the normal working range. These anomalies may be early warning signs of potential failures.

[0145] 3. Fault diagnosis process

[0146] During the data analysis process, the central node will determine the specific cause of the connection interruption through the following methods:

[0147] 3.1. Status check: Analyze the status information of the mobile branch node and the target fixed branch node to determine whether there is a device failure or limited function. This includes battery power, whether the sensor function is normal, whether the hardware is damaged, etc. 3.2. Data comparison: Identify the fault characteristics by comparing the historical data under normal status with the current data. For example, if the temperature reading of the sensor is far below or above the normal range, it may indicate a device failure. 3.3. Signal strength monitoring: Check the signal strength and stability of the communication link. If the signal is lost or the strength drops below the threshold, there may be a problem with the communication link. In this case, check the base station, network equipment, etc. 3.4. Delay and packet loss rate: Analyze the delay and packet loss rate of data transmission. If the packet loss rate is high, it may indicate network instability or device failure. 3.5. Environmental data analysis: By analyzing the on-site environmental data, such as the impact of extreme weather (storms, low temperatures, etc.), determine whether it is the cause of the connection interruption. For example, extreme weather may cause equipment failure or communication interruption. 3.6. Historical data comparison: Compare the current environmental data with the historical data to identify possible abnormalities.

[0148] 4. Feedback and handling measures

[0149] Once the diagnosis is complete, the central node will perform the following steps:

[0150] 4.1. Generate diagnostic report: Summarize the cause of the failure and generate a detailed diagnostic report to provide to relevant technical personnel and management. 4.2. Develop treatment plan: According to the diagnosis results, develop corresponding treatment plan, including repair, replacement of equipment, optimization of communication links or taking countermeasures to ensure operation safety. 4.3. Implementation and monitoring: After the treatment measures are implemented, continue to monitor the system status to ensure that the problem is resolved and prevent it from happening again.

[0151] 5. Confidence probability evaluation: Based on the historical information and current status information of the branch nodes, the Bayesian function is used to evaluate the confidence probability of the working status and environmental conditions of each node. When a connection interruption occurs, the central node provides the confidence probability of these status information to the operator for evaluation.

[0152] The following is the detailed confidence probability assessment process:

[0153] 5.1. Data collection: First, the central node continuously collects data from each branch node, including working status data (e.g., whether the node is operating normally), environmental parameter data (e.g., temperature, humidity, vibration, magnetic field, etc.), and historical information (previous operating status and environmental data). 5.2. Data preprocessing: Data preprocessing includes data cleaning, denoising, and calibration. Ensure the quality and accuracy of the data to reduce potential errors. 5.3. Feature extraction: Extract features from the collected data, which are used to evaluate the status of the node. For example, features may include the mean and variance of environmental parameters, the working time of the node, the frequency of abnormal events, etc. 5.4. Bayesian network model: Based on the collected data and features, a Bayesian network or other suitable probability model is used to establish a probability model to represent the relationship between the node status and environmental parameters. Bayesian networks are able to consider the relationship between different features and estimate the probability of different states through probability distribution. Common types of Bayesian networks: Naive Bayesian network: Naive Bayesian is the simplest Bayesian network and is usually used for classification problems. It assumes that the features are independent of each other under a given category, which simplifies the estimation of conditional probabilities.

[0154] Bayesian Network Example

[0155] 1) Overview of probability model: Probabilistic models, such as Bayesian networks, are directed graph models used to represent random variables and their conditional dependencies. In mine operations, this model can be used to describe the relationship between node status (such as equipment status, communication status, etc.) and environmental parameters (such as temperature, humidity, air pressure, etc.). The model can help identify the impact of environmental changes on node performance, and then perform fault diagnosis and prevention.

[0156] 2) Node status and environmental parameters

[0157] Node status: Device status, such as normal, faulty, or waiting for repair. Communication status, such as good, weak signal, or disconnected. Battery status, such as full, low battery, or waiting for charging.

[0158] Environmental parameters: Temperature. Ambient temperature changes may affect the operating performance of the device. Humidity. High humidity may cause device failure or signal attenuation. Air pressure. Low air pressure may affect the sensor accuracy of the device. Wind speed. High wind speed may affect the stability of the mobile branch node.

[0159] 3) Example: Bayesian network construction

[0160] 3.1) Variable Definition

[0161] Node status: DD, device status (normal / faulty); CC, communication status (good / weak signal / disconnected). Environmental parameters: T, temperature (low / normal / high); HH, humidity (low / normal / high); PP, air pressure (low / normal / high); WW, wind speed (low / normal / high).

[0162] 3.2) Bayesian network structure, in a Bayesian network, conditional dependencies can be represented by directed edges. For example, the device state DD may depend on the temperature T and humidity HH. The communication state CC may depend on the temperature T, humidity HH, air pressure PP and wind speed WW.

[0163] 3.3.) Conditional Probability Table (CPT): Each node has a conditional probability table, which represents the probability distribution of the node given the conditions of its parent node. For example: Conditional probability table of device state DD: P(D|T, H): The probability of the device being normal or faulty, depending on different combinations of temperature and humidity. Conditional probability table of communication state CC: P(C|T, H, P, W): The probability of the communication state, depending on different combinations of temperature, humidity, air pressure and wind speed.

[0164] 3.4) Example data: Assume that in a certain environment, the following data is collected: T = High; H = High; P = Normal; W = Normal. According to these environmental parameters, the conditional probability table can be consulted to obtain the probability of device failure P (D = Failure | T = High, H = High) and the communication status P (C | T = High, H = High, P = Normal, W = Normal).

[0165] 4) Reasoning and Application

[0166] Through Bayesian networks, reasoning can be performed. Fault prediction, if the model outputs a high probability of device failure, maintenance or replacement measures can be taken. Environmental impact assessment, analyze the performance of equipment and communications under different environmental conditions, and formulate corresponding strategies to reduce the risk of failure. Model parameter learning: Model parameters may need to be learned based on historical data. This includes learning the probability distribution of different states and the conditional probability relationship between features. After establishing a Bayesian network or other probabilistic model, model parameter learning is a crucial step. Through historical data, learning the probability distribution of different states and the conditional probability relationship between features can improve the accuracy and prediction performance of the model. The following explains the composition of model parameters and how to learn these probability distributions and conditional probability relationships.

[0167] Embodiment 4

[0168] 1. Composition of model parameters

[0169] Model parameters usually include the following:

[0170] Prior probability: For each variable (such as device state D, environmental parameter T, humidity H, etc.), its prior probability distribution P(D), P(T), etc. needs to be learned. This is the overall distribution of these variables without any other information. Conditional probability: The conditional probability table (CPT) is used to represent the probability distribution of each variable given its parent node (i.e., conditional variable). For example, the probability of device state D given temperature T and humidity H is P(D|T, H).

[0171] 2. Learn the relationship between probability distribution and conditional probability

[0172] There are two main methods for learning model parameters: Maximum Likelihood Estimation (MLE) and Bayesian Estimation. The following are the specific steps and methods:

[0173] 2.1 Maximum Likelihood Estimation (MLE)

[0174] Steps: Collect historical data sets and record the values ​​of each variable.

[0175] Compute the prior probability for each variable.

[0176] Example: If there are 100 samples and the device state D = Normal is 70 times, then: P(D = Normal) = 0.7. Then, if there are 40 samples where Temperature = High T = High and the device state D = Fault D = Fault occur simultaneously 20 times: P(D = Fault | = High) = 2040 = 0.5 P(D = Fault | T = High) = 4020 = 0.5.

[0177] 2.2. Bayesian estimation: Bayesian estimation takes into account prior information and posterior information and is suitable for situations where the amount of data is small. Unlike MLE, Bayesian estimation combines a prior distribution. Steps: Select a prior distribution (such as Beta distribution, Dirichlet distribution, etc.) as the prior probability. Collect historical data and calculate the posterior probability: Example: If Beta distribution is selected as the prior, the parameters can be updated after combining the data to obtain the posterior distribution, and then the conditional probability is calculated.

[0178] 2.3. EM algorithm: For cases with missing data or hidden variables, the EM (Expectation Maximization) algorithm is often used: E step: Calculate the expectation of the hidden variable under the current model parameters. M step: Use the expected value of the E step to re-estimate the model parameters.

[0179] 3. Implementation of the learning process

[0180] 3.1. Data collection: Collect historical data about equipment status and environmental parameters. 3.2. Preprocessing: Clean data, remove outliers, and handle missing values. 3.3. Parameter learning: Use MLE or Bayesian methods to learn parameters and build conditional probability tables. 3.4. Model validation: Verify the learned model performance through methods such as cross-validation, and adjust parameter settings to improve accuracy. 3.5. Iterative update: As more data is collected, model parameters are updated regularly to improve the accuracy of predictions. 3.6. State evaluation: Once the model is established and parameter learning is completed, the system can use this model to evaluate the state of each branch node. For each node, the system will calculate the probability of each state (normal operation / abnormal operation, normal environment / abnormal environment) based on the current data and model.

[0181] 4. Confidence probability calculation: Through the probability model, the system calculates the probability of each state, that is, the probability of normal working state and normal environmental parameters, normal working state and abnormal environment, abnormal working state and normal environment, and abnormal working state and abnormal environment. These probabilities can be expressed in the form of percentages or fractions to reflect the relative likelihood of each state.

[0182] Embodiment 5

[0183] In the probability model, the confidence probability (or confidence level) can be used to express the relationship between the working state and the environmental parameters. By calculating the probability of different combinations of working state and environmental parameters, the system can be analyzed under various conditions.

[0184] 1. Define state and environment parameters

[0185] Assume the following states and environmental parameters: Working state DD: Normal; Abnormal. Environmental parameter EE: Normal; Abnormal. We will focus on the confidence probabilities of four combinations: P(D = Normal, E = Normal); P(D = Normal, E = Abnormal); P(D = Abnormal, E = Normal); P(D = Abnormal, E = Abnormal).

[0186] 2. Steps to calculate confidence probability

[0187] 2.1. Calculate prior probability

[0188] First, calculate the prior probabilities of the working state and environmental parameters: P(D=normal) and P(D=abnormal); P(E=normal) and P(E=abnormal). These probabilities can be obtained through historical data statistics.

[0189] 2.2. Calculate conditional probability

[0190] Next, the conditional probabilities are calculated to indicate the probability of the working state under given environmental parameters: P(D=normal|E=normal), P(D=normal|E=abnormal); P(D=abnormal|E=normal), P(D=abnormal|E=abnormal). These conditional probabilities can be obtained through data analysis.

[0191] 2.3 Calculation of confidence probability

[0192] According to the total probability formula, the confidence probability of each combination can be calculated:

[0193] The working status is normal and the environmental parameters are normal: P(D=normal, E=normal)=P(E=normal)·P(D=normal|E=normal); the working status is normal and the environmental parameters are abnormal: P(D=normal, E=abnormal)=P(E=abnormal)·P(D=normal|E=abnormal); the working status is abnormal and the environmental parameters are normal: P(D=abnormal, E=normal)=P(E=normal)·P(D=abnormal|E=normal); the working status is abnormal and the environmental parameters are abnormal: P(D=abnormal, E=abnormal)=P(E=abnormal)·P(D=abnormal|E=normal).

[0194] 3. Correlation between confidence probability and working status

[0195] The confidence probability reflects the likelihood of a working state under certain environmental conditions. For example, if it is calculated that:

[0196] A high P(D=normal, E=abnormal) may indicate that the device can still work normally under abnormal environmental conditions. Conversely, if P(D=abnormal, E=abnormal) is high, it indicates that the probability of device abnormality also increases under abnormal environmental conditions. Through these combined probabilities, a decision framework can be constructed for real-time monitoring and diagnosis. For example, when a specific environmental parameter is detected as abnormal, the system can automatically adjust the device monitoring to enhance the warning and response capabilities to potential failures.

[0197] 4. Specific Examples

[0198] Assumption data: From historical data, it is calculated that: P(D=normal)=0.8; P(D=abnormal)=0.2; P(E=normal)=0.7; P(E=abnormal)=0.3.

[0199] Conditional probability: P(D=normal|E=normal)=0.9; P(D=normal|E=abnormal)=0.5; P(D=abnormal|E=normal)=0.1; P(D=abnormal|E=abnormal)=0.5.

[0200] Calculate the confidence probability: working status is normal and environmental parameters are normal: P (D = normal, E = normal)

[0201] =0.7·0.9=0.63; The working status is normal and the environmental parameters are abnormal: P(D=normal, E=abnormal)=0.3·0.5=0.15; The working status is abnormal and the environmental parameters are normal: P(D=abnormal, E=normal)=0.7·0.1=0.07; The working status is abnormal and the environmental parameters are abnormal: P(D=abnormal, E=abnormal)=0.3·0.5=0.15.

[0202] Through the above calculations, the confidence probabilities of the four states are obtained. These probability values ​​can help evaluate the stability and safety of the working state under different environmental conditions.

[0203] Notify operators: The central node communicates the calculated confidence probabilities to operators so that they can understand the status assessment of each node. This probabilistic information helps operators better understand the status of the nodes so that they can take appropriate decisions and actions, especially during connection interruption processing.

[0204] 5. Maintenance and repair: Take appropriate measures to repair the connection interruption problem based on the collected information and confidence probability assessment. Perform maintenance and repair work for the failure of the central node, fixed branch node or mobile branch node to ensure the normal operation of the system.

[0205] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0206] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0207] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0208] In addition, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0209] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0210] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. An intelligent computing transmission method for information protection, characterized in that: include: Comprehensively deploy communication nodes based on the terrain and range distribution of the mining area; Establish wireless communication networks between communication nodes and calibrate sensors and data acquisition equipment; Real-time monitoring of environmental parameters in the mining area through communication nodes, and updating of node status information; Based on the dynamic scheduling mechanism, combined with environmental parameters and node status information, the working status of each communication node is monitored and diagnosed, and the information transmission strategy is adjusted according to the status diagnosis results.

2. The intelligent computing transmission method for information protection according to claim 1, characterized in that: Based on the topography and distribution of the mining area, the communication nodes are fully deployed including: Use geographic information system tools to analyze the topography of the mining area, draw a topographic map of the mining area, set the boundaries of the mining area, and divide different functional areas according to the type of operation; Corresponding communication nodes are deployed according to the distribution of the functional areas and the types of operations.

3. The intelligent computing transmission method for information protection according to claim 2, characterized in that: The communication nodes include a central node, fixed branches and mobile branch nodes; the central node is deployed in a functional area located at the core of a mine, the fixed branch nodes are deployed in a functional area for construction operations, and the mobile branch nodes are deployed in a movable device.

4. The intelligent computing transmission method for information protection according to claim 3 is characterized in that: The step of establishing a wireless communication network between communication nodes and calibrating sensors and data acquisition equipment includes: Establishing communication connections between various communication nodes based on a wireless communication network; According to the trust levels pre-divided by the communication nodes, different data access permissions and decryption capabilities are set, and communication nodes of different levels use different reconfigurable encryption methods, and high-level communication nodes can decrypt the encrypted information of low-level communication nodes; After the communication node is connected to the wireless communication network, the sensor and data acquisition device where the communication node is driven are calibrated for accuracy.

5. The intelligent computing transmission method for information protection according to claim 3 is characterized in that: The dynamic scheduling mechanism is based on combining environmental parameters and node status information to monitor and diagnose the working status of each communication node, and adjust the information transmission strategy according to the status diagnosis result, including: Real-time detection of the connection status between communication nodes, when the target fixed branch node is interrupted, the scheduling instructions of the mobile branch node are assigned according to the pre-defined mobile branch node scheduling strategy; After the mobile branch node moves to the connection interruption position, it establishes data transmission with the central node, and analyzes the fault type of the connection interruption phenomenon of the target fixed branch node through the central node; Based on the historical information and current node status information of the communication node, the confidence probability of the working status and environmental parameters of the communication node is evaluated, and the decision framework of the communication node is defined to adjust the information transmission strategy.

6. The intelligent computing transmission method for information protection according to claim 5, characterized in that: The real-time detection of the connection status between the communication nodes and the allocation of the scheduling instructions of the mobile branch nodes according to the predefined mobile branch node scheduling strategy when the target fixed branch node is interrupted include: Detect the connection status between the central node and the fixed branch node in real time, and when the target fixed branch node is disconnected, try to communicate with other fixed branch nodes connected to the target fixed branch node. If the other connected fixed branch nodes can normally obtain the information of the target fixed branch node, it is determined that the connection between the central node and the target fixed branch node is disconnected, and marked as disconnected; If the other connected fixed branch nodes cannot obtain the information of the target fixed branch node, it is determined that there is a connection abnormality and the scheduling function of the mobile branch node is started; According to the scheduling strategy of the mobile branch node, the central node is used to calculate the priority, distance, time and optimal path from the mobile branch node to the target fixed branch node, and the scheduling instruction is issued after the calculation is completed; The mobile branch node moves to the target fixed branch node whose connection is interrupted according to the scheduling instruction, establishes a connection with the sensor and the acquisition device, and repairs the target fixed branch node to work normally.

7. The intelligent computing transmission method for information protection according to claim 5, characterized in that: After the mobile branch node moves to the connection interruption position, data transmission is established with the central node, and the central node analyzes the target fixed branch node connection interruption phenomenon through the central node. The fault type includes: The mobile branch nodes use sensors and acquisition equipment to collect field data and send it to the central node; The central node pre-processes the field data and checks for abnormal values ​​in the field data; Analyze the node status information of the mobile branch node and the target fixed branch node, and compare the historical data and field data of the target fixed branch node in a normal state to identify the fault characteristics; After completing the fault diagnosis, a diagnostic report is generated through the central node and a treatment plan is formulated.

8. The intelligent computing transmission method for information protection according to claim 2, characterized in that: The method of evaluating the working status of the communication node and the confidence probability of the environmental parameters based on the historical information of the communication node and the current node status information, defining the decision framework of the communication node, and adjusting the information transmission strategy includes: The central node obtains the environmental parameters, node status information and historical information of each fixed branch node, and then performs preprocessing to extract node features; Based on the extracted node features, a probability model is constructed using Bayesian to represent the relationship between node status and environmental parameters, and the confidence probability between the working status and environmental parameters is calculated; According to the combined results of confidence probabilities, it is determined whether there is any abnormality in the working status of the fixed branch node, and a decision-making framework is built using different working statuses and response capabilities. After identifying the abnormal working status, the response decision is automatically matched and the information transmission decision between the communication nodes is adjusted.

9. The intelligent computing transmission method for information protection according to claim 8, characterized in that: The relationship between the working state and the environmental parameters includes a normal working state and a normal environmental parameter, a normal working state and an abnormal environment, an abnormal working state and a normal environment, and an abnormal working state and an abnormal environment.

10. An intelligent computing transmission system for information protection, characterized in that: include: Node deployment module, used to comprehensively deploy communication nodes based on the topography and range distribution of the mining area; A communication connection module is used to establish a wireless communication network between communication nodes and calibrate sensors and data acquisition equipment; The monitoring and updating module is used to monitor the environmental parameters in the mining area in real time through the communication nodes and update the node status information; The scheduling calculation module is used to monitor and diagnose the working status of each communication node based on the dynamic scheduling mechanism, combined with environmental parameters and node status information, and adjust the information transmission strategy according to the status diagnosis results.

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