Emergency response strategy determination method and device, storage medium, program product and processor

Abstract

The invention discloses an emergency response strategy determination method and device, a storage medium, a program product and a processor. The method comprises the steps that a monitoring data set of a coal mine is collected, and monitoring data in the monitoring data set is at least used for representing the environment state of the coal mine and / or the operation state of equipment in the coal mine; in response to abnormal monitoring data existing in the monitoring data set, the probability of occurrence of a target event in the coal mine is determined, and the hazard of the target event to the coal mine is greater than a hazard threshold; in response to the fact that the probability is larger than a probability threshold value, a multi-dimensional data model corresponding to the coal mine is called, the monitoring data is simulated, development trend information of the target event is obtained, the multi-dimensional data model is used for simulating the environment in the coal mine, and the development trend information is used for representing the change condition of the environment under the condition that the target event occurs; and determining an emergency response strategy matched with the development trend information. The technical problem that the efficiency of determining the coal mine emergency response strategy is low is solved.

Description

Technical Field

[0001] The present application relates to the field of coal mines, and in particular, to a method, device, storage medium, program product and processor for determining an emergency response strategy. Background Art

[0002] At present, emergency management for coal mine accidents usually relies on traditional means such as manual monitoring, telephone or radio communication. Although the above methods can help accident emergency management to a certain extent, the above methods are inefficient, information transmission is lagging, and the emergency decision-making process usually relies on experience and lacks scientific basis. In addition, when a coal mine accident occurs, the underground environment is complex, and the existing monitoring methods cannot provide detailed and accurate disaster information in a timely manner, resulting in the technical problem of low efficiency in determining the coal mine emergency response strategy.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a method, device, storage medium, program product and processor for determining an emergency response strategy, so as to at least solve the technical problem of low efficiency in determining coal mine emergency response strategies.

[0005] According to one aspect of an embodiment of the present application, a method for determining an emergency response strategy is provided, which may include: collecting a monitoring data set of a coal mine, wherein the monitoring data in the monitoring data set is used to at least characterize the environmental status of the coal mine and / or the operating status of equipment in the coal mine; in response to the presence of abnormal monitoring data in the monitoring data set, determining the probability of a target event occurring in the coal mine, wherein the hazard of the target event to the coal mine is greater than a hazard threshold; in response to the probability being greater than the probability threshold, calling a multidimensional data model corresponding to the coal mine, simulating the monitoring data, and obtaining development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; and determining an emergency response strategy that matches the development trend information.

[0006] Optionally, in response to the presence of abnormal monitoring data in the monitoring data set, determining the probability of a target event occurring in the coal mine includes: in response to the presence of abnormal monitoring data in the monitoring data set, fusing other monitoring data in the monitoring data set except the abnormal monitoring data to obtain fused data; and determining the probability based on the fused data.

[0007] Optionally, determining an emergency response strategy that matches the development trend information includes: obtaining location information of a target object in the coal mine; and determining the emergency response strategy according to the location information and the development trend information.

[0008] Optionally, the method may further include: in response to a change in the location information, updating the emergency response strategy based on the changed location information.

[0009] Optionally, the method may further include: acquiring historical accident data of the coal mine and environmental data of the coal mine; and constructing a multidimensional data model based on the historical accident data and environmental data.

[0010] Optionally, the monitoring data set includes at least environmental data of the coal mine and status data of equipment in the coal mine, and collecting the monitoring data set of the coal mine includes: controlling sensors in the coal mine underground to collect environmental data and status data; the method also includes: transmitting the environmental data and status data to the control unit through a wireless sensor network.

[0011] According to another aspect of an embodiment of the present application, a device for determining an emergency response strategy is also provided, and the device may include: a collection unit, used to collect a monitoring data set of a coal mine, wherein the monitoring data in the monitoring data set is used to at least characterize the environmental state of the coal mine and / or the operating state of the equipment in the coal mine; a first determination unit, used to determine the probability of a target event occurring in the coal mine in response to the presence of abnormal monitoring data in the monitoring data set, wherein the hazard of the target event to the coal mine is greater than a hazard threshold; a processing unit, used to call a multidimensional data model corresponding to the coal mine in response to the probability being greater than the probability threshold, simulate the monitoring data, and obtain development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; a second determination unit, used to determine an emergency response strategy that matches the development trend information.

[0012] According to another aspect of an embodiment of the present application, a computer-readable storage medium is also provided, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the method for determining the emergency response strategy of the embodiment of the present application.

[0013] According to another aspect of an embodiment of the present application, a processor is further provided, the processor being used to run a program, wherein when the program is run by the processor, the method for determining the emergency response strategy of an embodiment of the present application is executed.

[0014] According to another aspect of an embodiment of the present application, a computer program product is further provided. The computer program product includes computer instructions, wherein the computer instructions, when executed by a processor, implement the method for determining the emergency response strategy of the embodiment of the present application.

[0015] In an embodiment of the present application, a monitoring data set of a coal mine is collected, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental state of the coal mine and / or the operating state of the equipment in the coal mine; in response to the presence of abnormal monitoring data in the monitoring data set, the probability of a target event occurring in the coal mine is determined, wherein the harm of the target event to the coal mine is greater than the harm threshold; in response to the probability being greater than the probability threshold, a multidimensional data model corresponding to the coal mine is called to simulate the monitoring data to obtain development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize the changes in the environment when the target event occurs; and an emergency response strategy matching the development trend information is determined. That is, in an embodiment of the present application, a monitoring data set of a coal mine is collected, and if there is abnormal monitoring data in the monitoring data set, based on the abnormal monitoring data, the probability of a target event (i.e., an abnormal event) occurring in the coal mine can be determined. If the probability is greater than the probability threshold, the multidimensional data model can be called to simulate the monitoring data to obtain the development trend information of the target event. Based on the development trend information, the corresponding emergency response strategy can be determined, thereby solving the technical problem of low efficiency in determining the coal mine emergency response strategy and achieving the technical effect of improving the efficiency of determining the coal mine emergency response strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 is a flow chart of a method for determining an emergency response strategy according to an embodiment of the present application;

[0018] Figure 2 is a schematic diagram of a coal mine accident emergency response management system according to an embodiment of the present application;

[0019] Figure 3 is a flow chart of a coal mine accident emergency response management method according to an embodiment of the present application;

[0020] Figure 4 is a schematic diagram of a device for determining an emergency response strategy according to an embodiment of the present application;

[0021] Figure 5 is a structural block diagram of a computer terminal according to an embodiment of the present application;

[0022] Figure 6 It is a block diagram of an electronic device according to a method for determining an emergency response strategy according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] According to an embodiment of the present application, an embodiment of a method for determining an emergency response strategy is provided. The steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] In this embodiment, a method for determining an emergency response strategy is proposed. The method can collect a monitoring data set of a coal mine. If there is abnormal monitoring data in the monitoring data set, the probability of a target event (i.e., an abnormal event) occurring in the coal mine can be determined based on the abnormal monitoring data. If the probability is greater than a probability threshold, a multidimensional data model can be called to simulate the monitoring data to obtain development trend information of the target event. Based on the development trend information, a corresponding emergency response strategy can be determined, thereby solving the technical problem of low efficiency in determining the emergency response strategy of a coal mine and achieving the technical effect of improving the efficiency of determining the emergency response strategy of a coal mine.

[0027] Figure 1 FIG. 1 is a flow chart of a method for determining an emergency response strategy according to an embodiment of the present application. Figure 1 As shown, the method may include the following steps:

[0028] Step S102: collecting a monitoring data set of the coal mine, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental state of the coal mine and / or the operating state of the equipment in the coal mine.

[0029] In the technical solution provided in the above step S102 of the present application, the above monitoring data set may include monitoring data, and may include environmental data and status data. The above monitoring data may be real-time monitoring data, which may at least be used to characterize the environmental status of a coal mine and / or the operating status of equipment in a coal mine. The above equipment may be equipment directly related to coal mine safety and production, and may include ventilation equipment, transportation equipment, power equipment, and communication equipment, etc. The above operating status may include information such as the ventilation effect of fans and ventilation ducts, the operating status of drainage equipment, and the location of transportation equipment. It should be noted that this is only for example, and no specific limitation is imposed on the type of operating status.

[0030] Optionally, by real-time monitoring of the status of the above-mentioned key equipment, potential problems can be discovered in time before an accident occurs and preventive measures can be taken; when an accident occurs, the problematic equipment can be quickly located, the dispatch of rescue resources can be optimized, and the consequences of the accident can be reduced.

[0031] For example, the real-time multi-source data acquisition and fusion module can be used to monitor the environment and equipment status of the coal mine in real time to obtain a monitoring data set, which can include the collected multi-source data. The monitoring data set can be transmitted to the central control room in real time for data fusion and processing. It should be noted that this is only an example, and there is no specific limitation on the device for collecting the monitoring data set.

[0032] Optionally, the real-time multi-source data acquisition and fusion module uses a variety of sensors to monitor the environment and equipment status of the coal mine in real time to obtain multi-source monitoring data, which may include multi-source data collected by sensors such as gas concentration sensors, temperature sensors, pressure sensors, dust sensors, and vibration sensors. Furthermore, the above sensors can collect multi-source data such as gas leakage, fire, and explosion in coal mines. After the monitoring data set is collected, the collected monitoring data set can be transmitted to the central control room in real time through a wireless sensor network for data fusion and processing, so that when an accident occurs, the dangerous environment can be automatically identified and reported in a timely manner.

[0033] Step S104, in response to the presence of abnormal monitoring data in the monitoring data set, determining the probability of a target event occurring in the coal mine based on the abnormal monitoring data, wherein the harm of the target event to the coal mine is greater than a harm threshold.

[0034] In the technical solution provided in the above step S104 of the present application, the above target event may be an accident underground in a coal mine, that is, the target event may be an event whose harm to the coal mine is greater than a harm threshold, and may be various events that may occur during the operation of the coal mine and endanger the safety of the coal mine, the safety of personnel lives, the safety of equipment and the continuity of production, for example, may be a gas explosion accident, a mine fire accident, a mine flooding accident, a landslide accident, a dust explosion accident, etc. It should be noted that this is only an example, and there is no specific restriction on the type of target event.

[0035] Optionally, if there is abnormal monitoring data in the monitoring data set, it can be determined that there is a possibility of the target event occurring in the coal mine. Therefore, the probability of the target event occurring in the coal mine can be determined based on the abnormal monitoring data.

[0036] Step S106, in response to the probability being greater than the probability threshold, calling the multidimensional data model corresponding to the coal mine, simulating the monitoring data, and obtaining the development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize the changes in the environment when the target event occurs.

[0037] In the technical solution provided in the above step S106 of the present application, the above probability threshold may be a preset value. The above multidimensional data model may be a pre-built model, which may be used to simulate the environment in a coal mine. The above development trend information may be used to characterize changes in the environment when a target event occurs, for example, the diffusion range of gas leakage in a coal mine, the possibility of a coal mine collapse, etc. It should be noted that this is only for illustration, and there is no specific limitation on the type of development trend information.

[0038] Optionally, this embodiment can integrate multiple dimensions of monitoring data such as environmental monitoring, equipment status, personnel location, historical accident data, etc. in the coal mine by using a multidimensional data model to form a comprehensive data view, which helps to fully understand the operating status of the coal mine and timely discover potential safety hazards. By using a multidimensional data model, various complex data can be deeply analyzed. By analyzing the correlation between data of different dimensions, the development trend of the accident can be accurately predicted, such as the diffusion range of gas leakage, the possibility of collapse, etc., to provide a scientific basis for emergency response. Further, based on the multidimensional data model, a variety of accident scenarios can be simulated to analyze the possible effects of different emergency plans. Through AI and machine learning algorithms, various factors such as resource availability, safety of evacuation paths, efficiency of rescue operations, etc. can be weighed to recommend the optimal emergency response strategy. Therefore, after determining that the probability of a target event occurring in a coal mine is greater than a probability threshold, a multidimensional data model can be called to simulate the monitoring data to determine the development trend information of the target event in the coal mine. Using this development trend information, information such as the leakage of gas in the coal mine and the leakage speed can be determined.

[0039] Optionally, by utilizing intelligent decision support and accident simulation modules, a multidimensional data model of coal mine accidents can be established. When an accident occurs, the multidimensional data model can be used to simulate the development trend of the accident (i.e., the target event) to predict changes in the disaster situation (i.e., changes in the environment). Based on the development trend information, it can help commanders formulate scientific rescue plans.

[0040] Step S108, determining an emergency response strategy that matches the development trend information.

[0041] In the technical solution provided in the above step S108 of the present application, the above emergency response strategy can be used to locate and evacuate personnel, and may include emergency response strategies for gas explosion accidents, emergency response strategies for landslide accidents, and emergency response strategies for high temperature or fire accidents, etc. For example, it may include real-time warning information, and recommend the best emergency action plan based on the explosion range and time, such as shutting down the gas source, starting the ventilation system to reduce the gas concentration, and can be used to dynamically adjust the positions of rescue equipment (such as ventilation fans, gas extraction equipment) and rescue personnel, and may include the optimal evacuation route, etc. It should be noted that this is only an example, and there is no specific restriction on the type of emergency response strategy.

[0042] For example, the evacuation route of personnel can be determined based on the speed and scope of gas leakage. Or if the system detects abnormal pressure on the coal mine working face or tunnel roof and predicts the risk of landslide, the development trend information of the landslide can be determined, and based on the development trend information, the possibility and potential impact range of the landslide can be evaluated. Based on the possibility and potential impact range of the landslide, an emergency response strategy can be generated, which may include: sending early warning information to the central control room and generating safe evacuation routes to guide underground personnel to evacuate quickly to a safe area. At the same time, dynamically adjust the position of rescue equipment (such as support equipment, tunneling machines) and rescue teams to ensure timely response to landslides and reduce losses. If it is determined that a target event of high temperature or fire will occur in a coal mine, the location of the fire can be quickly identified and located, and the development trend information of the fire can be determined. Based on the location information and development trend information, the corresponding emergency response strategy can be determined. The emergency response strategy may include: activating nearby fire-fighting facilities (such as fire extinguishers, fire hoses), notifying the central control room to activate a more comprehensive fire-fighting plan, and according to the development trend of the fire, the system generates a safe evacuation route, guides personnel to evacuate through the communication system, and dynamically adjusts the deployment of fire-fighting resources according to the real-time situation at the fire scene. It should be noted that the types of target events, the content of emergency response strategies, and the content of development trend information are only examples and are not specifically limited here.

[0043] In this embodiment, historical accident data, real-time monitoring data and accident simulation results can be combined, and AI and machine learning technology can be used to analyze multiple possible emergency response plans and recommend the optimal plan (ie, emergency response strategy).

[0044] Optionally, a dynamic rescue resource scheduling and optimization module can be used to track the location of rescue equipment and personnel in real time through positioning technology (such as GPS, RFID), and the emergency response strategy can be updated in real time based on the location of rescue equipment and personnel.

[0045] Optionally, multiple parties can collaborate through real-time communication and collaboration platforms, so that the commander can exchange information with underground personnel in real time, view video surveillance and sensor data at the accident site, and update emergency rescue plans in real time; support multi-user collaboration to ensure information synchronization among rescue teams. Furthermore, the underground personnel positioning and evacuation system can equip underground workers with RFID tags or other positioning devices to monitor the specific location of underground personnel in real time.

[0046] In this embodiment, multi-source data can be collected in real time to obtain a monitoring data set, and the monitoring data set can be transmitted to the central control room in real time to use the central control room for data fusion and processing. A multi-dimensional data model of coal mine accidents can be established in advance. When an accident (that is, a target event) occurs, the development trend of the accident can be simulated, and the change of the disaster situation can be predicted to obtain development trend information. Based on the development trend information, a variety of possible emergency response plans (that is, emergency response strategies) can be determined, which can be selected by the user, or based on historical experience, the optimal plan among multiple emergency response strategies can be determined and recommended. According to the optimal plan, the commander can interact with the underground personnel in real time and update the emergency rescue plan in real time. Further, the specific location of the underground personnel can be monitored in real time. When an accident occurs, the system intelligence can generate the optimal personnel evacuation route to ensure that the personnel can evacuate to a safe place safely and quickly.

[0047] Through the above steps S102 and S108 of the present application, a monitoring data set of a coal mine is collected, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental state of the coal mine and / or the operating state of the equipment in the coal mine; in response to the presence of abnormal monitoring data in the monitoring data set, the probability of a target event occurring in the coal mine is determined, wherein the harm of the target event to the coal mine is greater than the harm threshold; in response to the probability being greater than the probability threshold, a multidimensional data model corresponding to the coal mine is called to simulate the monitoring data to obtain development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize the changes in the environment when the target event occurs; and an emergency response strategy matching the development trend information is determined. That is, in an embodiment of the present application, a monitoring data set of a coal mine is collected, and if there is abnormal monitoring data in the monitoring data set, based on the abnormal monitoring data, the probability of a target event (i.e., an abnormal event) occurring in the coal mine can be determined. If the probability is greater than the probability threshold, the multidimensional data model can be called to simulate the monitoring data to obtain the development trend information of the target event. Based on the development trend information, the corresponding emergency response strategy can be determined, thereby solving the technical problem of low efficiency in determining the coal mine emergency response strategy and achieving the technical effect of improving the efficiency of determining the coal mine emergency response strategy.

[0048] The above method of this embodiment is further introduced below.

[0049] As an optional implementation, step S104, in response to the presence of abnormal monitoring data in the monitoring data set, determines the probability of a target event occurring in a coal mine, including: in response to the presence of abnormal monitoring data in the monitoring data set, fuses other monitoring data in the monitoring data set except the abnormal monitoring data to obtain fused data; and determines the probability based on the fused data.

[0050] In this embodiment, if there is an abnormal monitoring data set in the monitoring data set, the monitoring data other than the abnormal monitoring data in the monitoring data set can be fused to obtain fused data, and the probability of occurrence of the target event can be determined by analyzing the monitoring data set.

[0051] Optionally, if there is abnormal monitoring data in the monitoring data set, it can be determined that there is a possibility of the target event occurring in the coal mine, and the probability of the target event occurring needs to be determined. The relevant data of the target event can be captured through the multi-source data acquisition module to obtain the monitoring data set. Further, the monitoring data can be fused and processed to generate a preliminary risk assessment, which can be used to determine the probability of the target event occurring. Then, the intelligent decision support module can combine the real-time monitoring data and the historical accident model to generate and recommend the optimal emergency response plan. The rescue resource scheduling module can be used to adjust the deployment of equipment and personnel through the positioning system to optimize the rescue path. The real-time communication platform ensures seamless communication between the command center and the underground personnel, and the personnel positioning and evacuation system guides the underground personnel to evacuate safely. The entire system works together to ensure rapid, accurate and efficient accident response.

[0052] As an optional implementation, step S108, determining an emergency response strategy that matches the development trend information, includes: obtaining location information of the target object in the coal mine; and determining the emergency response strategy according to the location information and the development trend information.

[0053] In this embodiment, the location information of the target object can be obtained, and the location information can be used to characterize the location of the target object in the coal mine, and can be a spatial location coordinate. It should be noted that this is only an example, and the type of location information is not specifically limited. The target object can be a worker underground.

[0054] Optionally, the underground personnel positioning and evacuation system can be used to equip underground workers with RFID tags or other positioning devices, and monitor the specific location of underground personnel in real time. When an accident occurs, the system can immediately display the distribution of personnel in various areas underground to help command personnel formulate evacuation plans. Based on real-time environmental data and accident simulation results, the system intelligently generates the optimal evacuation route to avoid dangerous areas and ensure that personnel can evacuate to a safe place safely and quickly.

[0055] For example, when an accident occurs, the system can simulate the development trend of the accident in real time, including the impact range of gas explosion, fire spread or landslide. Based on the simulation results, a variety of emergency response plans can be automatically generated, covering resource scheduling, evacuation routes, equipment use, etc. The algorithm can analyze the pros and cons of these plans and recommend the best plan to the commander, so that he can quickly formulate a scientific rescue plan.

[0056] As an optional implementation, the method may further include: in response to a change in the location information, updating the emergency response strategy based on the changed location information.

[0057] In this embodiment, if the location information of personnel in the coal mine changes, the emergency response strategy can be updated based on the changed location information.

[0058] Optionally, using the dynamic rescue resource scheduling and optimization module, the location of rescue equipment and personnel can be tracked in real time through positioning technology (such as GPS, RFID) to ensure that rescue materials and personnel can be quickly dispatched to their locations. According to the real-time situation of the accident, the deployment location of rescue equipment and personnel can be dynamically adjusted to optimize the rescue path and reduce the response time. The optimization algorithm of resource scheduling can ensure the optimal configuration of resources and realize fast and efficient rescue operations.

[0059] For example, through positioning technologies such as GPS and RFID, the location of rescue equipment and personnel can be tracked in real time. Each rescue equipment and personnel is equipped with a positioning device, and the system can accurately obtain their real-time location. When an accident occurs, the deployment location of rescue equipment and personnel can be dynamically adjusted according to the development trend of the accident. The optimization algorithm combines the type of rescue equipment, the situation at the accident site, and the road traffic conditions to optimize the rescue path in real time and reduce the rescue time. The system automatically updates the rescue plan to ensure that rescue resources can reach the designated location in time and improve rescue efficiency.

[0060] Optionally, the Internet of Things (IoT), 5G communications, and dedicated wireless networks for underground coal mines can be integrated to ensure real-time transmission of information between underground personnel, sensor nodes, and the ground command center. The platform supports multi-party collaboration, and the command center can view underground sensor data and video surveillance images in real time through an efficient communication network, and communicate with underground personnel by voice or text. The platform can be designed for multiple users, supporting information synchronization and task allocation between rescue team groups to ensure the accuracy and efficiency of command and dispatch.

[0061] Optionally, each underground worker can be equipped with an RFID tag or other positioning device, and the system can monitor the distribution of personnel in each area underground in real time. When an accident occurs, the optimal evacuation route can be automatically generated by combining real-time environmental data and accident simulation results. This route avoids dangerous areas (such as fire or gas leakage areas) to ensure that underground personnel can quickly evacuate to a safe place through safe passages. The evacuation route can also be updated in real time to respond to dynamic changes in accidents and maximize the safety of underground personnel. Among them, the above-mentioned emergency response strategy may include a planned evacuation route.

[0062] As an optional implementation, the method may further include: acquiring historical accident data of the coal mine and environmental data of the coal mine; and constructing a multidimensional data model based on the historical accident data and environmental data.

[0063] In this embodiment, historical accident data of the coal mine and environmental data of the coal mine may be obtained, and a multidimensional data model may be constructed based on the historical accident data and environmental data.

[0064] Optionally, a multi-dimensional data model of coal mine accidents can be constructed through historical accident data, real-time monitoring data, artificial intelligence (AI) and machine learning algorithms.

[0065] For example, various types of data can be collected from underground coal mines, including but not limited to environmental monitoring data (such as gas concentration, temperature, humidity, pressure, etc.), equipment operation status data, personnel location data, historical accident data, geological structure data, ventilation system data, etc. These data can be obtained in real time through sensor networks installed underground, equipment status monitoring systems, personnel positioning systems, etc. The collected raw data may contain noise, outliers, or missing values. The collected data can be preprocessed, and the preprocessing methods may include data cleaning, format conversion, and anomaly detection. The purpose of preprocessing is to ensure data quality and facilitate subsequent analysis and modeling. Furthermore, data from different sources can be fused to build a unified data framework. For example, gas concentration can be associated with ventilation system data to understand the impact of ventilation effect on gas concentration; personnel location data can be fused with equipment status data to determine whether equipment failure affects personnel safety. Data fusion helps to reveal the inherent connection between data and provide more comprehensive information for subsequent intelligent decision-making. Based on the preprocessed data, features related to coal mine safety are extracted, such as equipment failure rate, personnel distribution density, and gas concentration fluctuation frequency. You can choose a suitable machine learning or deep learning model, such as decision tree, neural network, support vector machine, etc. Use historical data and feature engineering data sets to train the model so that it can identify patterns, predict accident trends, or optimize decisions. Verify the model with a test data set to evaluate its prediction accuracy and stability. Based on the verification results, tune the model, such as adjusting parameters, adding data, or improving the algorithm, to improve the performance of the model. The trained model can be integrated into the coal mine accident emergency response management system to process and analyze the collected monitoring data set in real time. The model can be used in application scenarios such as accident warning, rescue resource scheduling, and personnel evacuation path planning, and the response efficiency and safety of the system can be improved through intelligent decision support.

[0066] It should be noted that the above is only an example and does not impose any specific limitation on the method of constructing a multidimensional data model.

[0067] Optionally, an intelligent decision support and accident simulation module is used to establish a multi-dimensional data model of the accident through AI and machine learning technology, combined with historical accident data and real-time monitoring data. When an accident occurs or is about to occur, the constructed multi-dimensional data model can be used to simulate the development trend of the accident, such as the impact range of gas explosions and landslides, and predict changes in the disaster situation. The above-mentioned intelligent decision support and accident simulation module can provide intelligent decision support, analyze a variety of emergency response plans, and recommend the best rescue plan to help commanders reasonably dispatch resources and guide personnel to evacuate or conduct effective rescue. At the same time, the above-mentioned module can also continuously update the rescue plan (that is, the emergency response strategy) to ensure that the commander can make a scientific response according to the real-time changes of the accident.

[0068] As an optional implementation, step S102, the monitoring data set includes at least environmental data of the coal mine and status data of equipment in the coal mine, and collecting the monitoring data set of the coal mine includes: controlling sensors in the coal mine underground to collect environmental data and status data; the method also includes: transmitting the environmental data and status data to the control unit through a wireless sensor network.

[0069] In this embodiment, the sensors in the coal mine can be controlled to collect environmental data and status data, and transmit the data to the control unit through the wireless sensor network. The control unit can be a central control room.

[0070] In this embodiment, multiple sensor nodes can be installed in advance in the coal mine, and sensors can be deployed in the sensor nodes. The deployed sensors may include gas concentration sensors, temperature sensors, pressure sensors, dust sensors, vibration sensors, etc. The above sensors can be used to monitor the environmental status and equipment operation status of the mine. Each sensor node can be equipped with a data acquisition module, which can collect potential dangerous data such as gas leakage, fire, explosion, etc. in real time. The sensor node can transmit the collected data (for example, environmental data and status data) to the central control room through a wireless sensor network (such as LoRa, Zigbee or Wi-Fi), and the central control system fuses the multi-source data to eliminate redundant information and noise. The fused data is provided to other modules for analysis, decision-making and response. It should be noted that this is only an example, and there is no specific restriction on the type of sensor and the deployment method of the sensor.

[0071] At present, the coal mine accident emergency management system mainly relies on traditional means such as manual monitoring, telephone or radio communication. Although the above methods can help accident emergency management to a certain extent, there are many shortcomings. For example, in coal mine accident emergency management, the traditional emergency response system usually relies on manual command and traditional communication equipment (such as walkie-talkies, telephones) to coordinate rescue. The above method is inefficient, information transmission has a lag, and the emergency decision-making process often relies on experience and lacks scientific basis. In addition, when a coal mine accident occurs, the underground environment is complex, and the existing monitoring methods cannot provide detailed and accurate disaster information in a timely manner, resulting in increased difficulty in rescue, delayed response speed, and low efficiency in personnel evacuation and equipment rescue. As a result, there is a technical problem of low efficiency in determining coal mine emergency response strategies.

[0072] To solve the above problems, in this embodiment, a coal mine accident emergency response management system and method are disclosed. Figure 2 is a schematic diagram of a coal mine accident emergency response management system according to an embodiment of the present application, such as Figure 2 As shown, the system may include: a real-time multi-source data acquisition and fusion module 201, an intelligent decision support and accident simulation module 202, a real-time communication and collaboration platform 203, an underground personnel positioning and evacuation system 204 and a dynamic rescue resource scheduling and optimization module 205.

[0073] Optionally, the above modules can transmit data through the central control room 206. The above real-time multi-source data acquisition and fusion module 201 can include a gas concentration sensor 2011, a temperature sensor 2012, a pressure sensor 2013, a dust sensor 2014 and a vibration sensor 2015.

[0074] Optionally, the real-time multi-source data collection and fusion module 201 can collect multi-source data (ie, monitoring data) and transmit the multi-source data to the central control room 206 in real time for data fusion and processing.

[0075] Optionally, the intelligent decision support and accident simulation module 202 may be used to simulate accident scenarios to provide intelligent decision support for the target time.

[0076] Optionally, the dynamic rescue resource scheduling and optimization module 205 can track the location of rescue equipment and personnel, and can also dynamically adjust the deployment location of rescue equipment and personnel according to the real-time situation of the accident to optimize the rescue path.

[0077] Optionally, the above-mentioned real-time communication and collaboration platform 203 can integrate the Internet of Things, 5G communication and underground dedicated wireless network to ensure real-time communication underground and on the ground.

[0078] Optionally, the underground personnel positioning and evacuation system 204 can monitor the specific positions of the underground personnel in real time, and intelligently generate the optimal personnel evacuation route based on the real-time environmental data and accident simulation results.

[0079] In this embodiment, the above modules are used to improve the efficiency of emergency response, reduce casualties and property losses in coal mine production accidents, and have significant safety and economic benefits. It should be noted that the data processing modules here are only used as examples and are not specifically limited here.

[0080] In summary, the coal mine accident emergency response management system proposed in this embodiment ensures that emergency handling can be carried out quickly and accurately when an accident occurs through the collaborative work of multiple modules such as multi-source data collection, intelligent decision-making, dynamic scheduling, real-time communication, and personnel positioning and evacuation.

[0081] Optionally, through the real-time multi-source data acquisition and fusion module, a variety of sensors (such as gas concentration sensors, temperature sensors, pressure sensors, dust sensors, etc.) can be used to monitor the environment and equipment status of coal mines, and collect multi-source data of potential dangers such as gas leakage, fire, explosion, etc. in real time. The collected monitoring data can be transmitted to the central control room through the wireless sensor network. The central control room can automatically integrate and process these data, identify dangerous environments, and report to the command center in a timely manner.

[0082] Optionally, the above-mentioned dynamic rescue resource scheduling and optimization module can track the location of rescue equipment and personnel in real time through positioning technologies such as GPS and RFID, ensuring that rescue materials and personnel can be quickly deployed in place according to the real-time situation. The system's optimization algorithm analyzes the accident situation in real time, dynamically adjusts the deployment location of rescue equipment and personnel, optimizes the rescue path, and reduces the response time. The resource scheduling algorithm ensures the optimal allocation of resources, thereby achieving fast and efficient rescue, improving the efficiency and accuracy of emergency response, and minimizing casualties and equipment losses.

[0083] Optionally, the above-mentioned real-time communication and collaboration platform can ensure unimpeded communication between underground personnel, sensor nodes and the ground command center. The platform supports multi-party collaboration by integrating the Internet of Things (IoT), 5G communications and underground dedicated wireless networks. Commanders can interact with underground personnel in real time through the platform and view sensor data and on-site videos. The real-time location of underground personnel is also displayed through the underground personnel positioning and evacuation system. The system generates the optimal evacuation route based on the accident simulation results and real-time data to avoid dangerous areas and ensure that underground personnel can be quickly evacuated to a safe place. This collaborative working mechanism greatly improves the efficiency and safety of emergency rescue.

[0084] Figure 3is a flow chart of a coal mine accident emergency response management method according to an embodiment of the present application, such as Figure 3 As shown, the method may include the following steps:

[0085] Step S302: collect multi-source data in real time.

[0086] In this embodiment, multi-source data can be collected in real time, and the collected multi-source data can be transmitted to the central control room in real time for data fusion and processing.

[0087] Step S304: Process the multi-source data using a multi-dimensional data model to determine development trend information.

[0088] In this embodiment, a multi-dimensional data model of coal mine accidents can be established in advance. When an accident occurs, the model can be used to simulate the development trend of the accident and predict changes in the disaster situation.

[0089] Step S306, determining an emergency response strategy that matches the development trend information.

[0090] In this embodiment, multiple emergency response plans applicable to the current development trend information can be determined, and the best plan can be selected and recommended.

[0091] Step S308: Update the emergency response strategy.

[0092] In this embodiment, the command personnel can exchange information with the underground personnel in real time and update the emergency rescue plan (ie, the emergency response strategy) in real time.

[0093] Optionally, the specific location of underground personnel is monitored in real time. When an accident occurs, the system intelligently generates the best evacuation route to ensure that personnel can be evacuated to a safe place safely and quickly.

[0094] The above method is further explained below by taking a coal mine gas leakage accident emergency response system based on multi-source data.

[0095] Optionally, gas leakage is a common dangerous situation in coal mines. To deal with the above situation, the following steps can be performed: a variety of sensor nodes are arranged in the coal mine, including gas concentration sensors, temperature sensors and pressure sensors. When the gas concentration in a certain area reaches the warning value, the gas sensor will immediately collect data and send the data to the central control room through the wireless sensor network. After receiving the gas concentration data, the system in the central control room combines other sensor data in the mine (such as temperature changes and pressure fluctuations) through data fusion technology to further analyze the environmental changes in the area and confirm the severity of the gas leakage. Based on historical data and current gas leakage trends, the system simulates possible accident development scenarios, such as the scope and speed of gas diffusion. The simulation results show that there is a risk of gas spreading rapidly to other operating areas, so the system immediately recommends to the commander to evacuate the underground workers and automatically activate the emergency ventilation system. Furthermore, through the real-time communication platform provided by the system, the command center can communicate with the underground personnel in real time and command the evacuation. Through the personnel positioning system, the system automatically plans the safest evacuation route to avoid high-concentration gas areas. The system uses positioning technology to track the location of rescue personnel and equipment in real time to ensure efficient evacuation and rescue work.

[0096] Optionally, through the above steps, the gas leak is detected and handled in time, avoiding a catastrophic explosion. Through intelligent evacuation route planning, personnel can evacuate quickly and safely. Rescue resources are quickly deployed to the gas leak area through dynamic scheduling and optimization of the system, ensuring the efficiency of emergency response.

[0097] The above method is further explained below by taking the coal mine collapse accident emergency response system.

[0098] Alternatively, in underground coal mines, collapse is another serious accident. To deal with the above situation, the following steps can be performed: The system arranges vibration sensors, stress sensors and displacement sensors underground to monitor the stress changes and vibration conditions of coal mine structures in real time. When the vibration sensors and stress sensors in a certain mining area detect abnormal fluctuations at the same time, the system immediately collects the vibration data and stress data of the area and uploads them to the central control room through a wireless network. The central control system combines historical data and current data to predict the probability of collapse through big data analysis and machine learning models. The system simulates the possible scope and impact area of ​​collapse and finds that multiple operating areas may be involved. The system automatically generates the best emergency response plan for collapse, recommends immediate evacuation of personnel in the area affected by the collapse, and dispatches rescue equipment (such as support equipment and rescue tools) to the dangerous area to prevent further collapse. Through GPS and RFID technology, the system tracks the location of rescue equipment and personnel in real time. The command center can adjust the deployment position of equipment and personnel at any time through the system to ensure efficient and orderly rescue work. At the same time, the system automatically generates the optimal evacuation route to guide underground personnel to a safe area.

[0099] Through the above methods, the risk of landslides was predicted in advance, avoiding catastrophic consequences. Through real-time monitoring and simulation, the system can quickly formulate rescue plans and reduce rescue time. Personnel positioning and intelligent evacuation route planning ensure that personnel can evacuate safely before landslides occur, minimizing the risk of casualties.

[0100] It should be noted that the embodiments of the present application can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. A person of ordinary skill in the art will appreciate that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present application can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0101] The above are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed in the present application and within the spirit and principles of the present application should be covered within the protection scope of the present application.

[0102] In this embodiment, through a multi-level communication network, real-time information interaction between the underground and the ground is guaranteed, the problem of information transmission lag in the traditional emergency response system is solved, and the response time is shortened. The dynamic rescue resource scheduling function combines real-time data analysis and decision support systems to ensure that rescue resources can quickly reach the accident site, significantly improving the rescue efficiency. Through accident scene simulation and AI decision support, the development trend of the accident can be accurately predicted, scientific rescue plans can be provided, and commanders can be helped to make the best decisions. The above method can also perform real-time personnel positioning and intelligent evacuation route planning to ensure that underground workers can be evacuated quickly and safely when an accident occurs, reducing the risk of casualties. By improving the rescue response speed, optimizing resource scheduling, and improving the scientific nature of decision-making, not only the efficiency of accident emergency response is improved, but also casualties and property losses in coal mine production accidents are reduced, with significant safety and economic benefits.

[0103] The coal mine accident emergency response management system in this embodiment solves the key problems in the existing system by integrating technologies such as multi-source data collection, intelligent decision support, dynamic rescue resource scheduling, real-time communication, and underground personnel positioning. The system uses a variety of sensors to monitor the coal mine environment and equipment status in real time to ensure that comprehensive and accurate data can be obtained when an accident occurs. The intelligent decision support module combines AI and machine learning technologies to simulate and analyze accident scenarios in real time to help commanders develop the best emergency response plan. The dynamic resource scheduling module uses GPS, RFID and other technologies to track equipment and personnel in real time, optimize rescue routes, and reduce response time. In addition, the system integrates the Internet of Things and 5G communication technologies to ensure seamless communication between underground and ground command centers, and improve the collaborative efficiency of emergency response.

[0104] The system of this application has achieved significant technological progress in many aspects. First, the multi-source data acquisition module provides comprehensive monitoring of the underground environment and equipment status of coal mines, improving the timeliness of accident detection. Secondly, the intelligent decision support and accident simulation functions enable the system to predict the development of accidents and help commanders formulate scientific rescue plans at an early stage. Third, the dynamic rescue resource scheduling and optimization module effectively reduces the rescue response time and improves the rescue efficiency. Finally, the application of 5G communication and the Internet of Things ensures stable and efficient communication in the complex environment of the mine, ensuring the smoothness of information in accident handling.

[0105] Through this application, the efficiency and safety of emergency management of coal mine accidents have been greatly improved. The combination of real-time monitoring and intelligent decision-making reduces the reaction time after an accident. Intelligent evacuation route generation and optimized resource scheduling improve the accuracy of rescue operations, and the casualty rate and equipment loss rate are significantly reduced. Because the system relies on highly automated and intelligent technical means, it also reduces the need for human intervention, significantly improves the overall safety production level of coal mines, reduces operating costs, and increases social and economic benefits.

[0106] In the embodiment of the present application, a monitoring data set of a coal mine is collected. If there is abnormal monitoring data in the monitoring data set, the probability of a target event (i.e., an abnormal event) occurring in the coal mine can be determined based on the abnormal monitoring data. If the probability is greater than the probability threshold, a multidimensional data model can be called to simulate the monitoring data to obtain the development trend information of the target event. Based on the development trend information, the corresponding emergency response strategy can be determined, thereby solving the technical problem of low efficiency in determining the emergency response strategy of the coal mine and achieving the technical effect of improving the efficiency of determining the emergency response strategy of the coal mine.

[0107] According to an embodiment of the present application, a device for determining an emergency response strategy is also provided. It should be noted that the device for determining an emergency response strategy of this embodiment can be used to execute the method for determining an emergency response strategy of the above embodiment of the present application.

[0108] Figure 4 is a schematic diagram of a device for determining an emergency response strategy according to an embodiment of the present application. Figure 4 As shown, the emergency response strategy determination device 40 may include: a collection unit 402 , a first determination unit 404 , a processing unit 406 and a second determination unit 408 .

[0109] The collection unit 402 is used to collect a monitoring data set of a coal mine, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental status of the coal mine and / or the operating status of the equipment in the coal mine.

[0110] The first determination unit 404 is configured to determine the probability of a target event occurring in the coal mine in response to the presence of abnormal monitoring data in the monitoring data set, wherein the harm of the target event to the coal mine is greater than a harm threshold.

[0111] Processing unit 406 is used to call the multidimensional data model corresponding to the coal mine in response to the probability being greater than the probability threshold, simulate the monitoring data, and obtain the development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize the changes in the environment when the target event occurs.

[0112] The second determining unit 408 is used to determine an emergency response strategy that matches the development trend information.

[0113] The device for determining the emergency response strategy of this embodiment collects a monitoring data set of a coal mine through a collection unit, wherein the monitoring data in the monitoring data set is used to at least characterize the environmental status of the coal mine and / or the operating status of the equipment in the coal mine; determines the probability of a target event occurring in the coal mine in response to the presence of abnormal monitoring data in the monitoring data set through a first determination unit, wherein the hazard of the target event to the coal mine is greater than a hazard threshold; calls a multidimensional data model corresponding to the coal mine through a processing unit in response to the probability being greater than the probability threshold, simulates the monitoring data, and obtains development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; determines an emergency response strategy matching the development trend information through a second determination unit, thereby solving the technical problem of low efficiency in determining the emergency response strategy of the coal mine and achieving the technical effect of improving the efficiency of determining the emergency response strategy of the coal mine.

[0114] The embodiment of the present application may provide a computer terminal, which may be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal may also be replaced by a terminal device such as a mobile terminal.

[0115] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0116] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the method for determining the emergency response strategy: collecting a monitoring data set of the coal mine, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental status of the coal mine and / or the operating status of the equipment in the coal mine; in response to the presence of abnormal monitoring data in the monitoring data set, determining the probability of a target event occurring in the coal mine, wherein the hazard of the target event to the coal mine is greater than the hazard threshold; in response to the probability being greater than the probability threshold, calling the multidimensional data model corresponding to the coal mine, simulating the monitoring data, and obtaining development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; determining an emergency response strategy that matches the development trend information.

[0117] Optionally, Figure 5 is a structural block diagram of a computer terminal according to an embodiment of the present application, such as Figure 5 As shown, the computer terminal 508 may include: one or more (only one is shown in the figure) processors 502 , a memory 504 and a transmission device 506 .

[0118] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the method and device for determining the emergency response strategy in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the method for determining the emergency response strategy described above is realized. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal 508 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0119] The processor can call the information and application programs stored in the memory through the transmission device to perform the following steps: collect a monitoring data set of the coal mine, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental status of the coal mine and / or the operating status of the equipment in the coal mine; in response to the presence of abnormal monitoring data in the monitoring data set, determine the probability of a target event occurring in the coal mine, wherein the hazard of the target event to the coal mine is greater than the hazard threshold; in response to the probability being greater than the probability threshold, call the multidimensional data model corresponding to the coal mine, simulate the monitoring data, and obtain development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; determine an emergency response strategy that matches the development trend information.

[0120] It can be understood by those skilled in the art that Figure 5 The structure shown is for illustration only, and the computer terminal 508 may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, referred to as MID), a PAD, or other terminal devices. Figure 5 The structure of the computer terminal 508 is not limited. For example, the computer terminal 508 may also include Figure 5 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 5 Different configurations are shown.

[0121] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0122] According to an embodiment of the present application, a computer-readable storage medium is also provided, which includes a stored program, wherein the program executes the method for determining the emergency response strategy in the above embodiment.

[0123] Optionally, in this embodiment, the computer-readable storage medium may be located in any one of the computer terminals in a computer terminal group in a computer network, or in any one of the mobile terminals in a mobile terminal group.

[0124] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: collecting a monitoring data set of a coal mine, wherein the monitoring data in the monitoring data set is used to at least characterize the environmental status of the coal mine and / or the operating status of equipment in the coal mine; in response to the presence of abnormal monitoring data in the monitoring data set, determining the probability of a target event occurring in the coal mine, wherein the hazard of the target event to the coal mine is greater than a hazard threshold; in response to the probability being greater than the probability threshold, calling a multidimensional data model corresponding to the coal mine, simulating the monitoring data, and obtaining development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; and determining an emergency response strategy that matches the development trend information.

[0125] Optionally, the computer-readable storage medium may also execute program code for the following steps: in response to the presence of abnormal monitoring data in the monitoring data set, fuse other monitoring data in the monitoring data set except the abnormal monitoring data to obtain fused data; and determine the probability based on the fused data.

[0126] Optionally, the computer-readable storage medium may also execute program codes of the following steps: obtaining location information of a target object in a coal mine; and determining an emergency response strategy according to the location information and development trend information.

[0127] Optionally, the computer-readable storage medium may also execute program code for the following steps: in response to a change in the location information, updating an emergency response strategy based on the changed location information.

[0128] Optionally, the computer-readable storage medium may also execute program codes of the following steps: obtaining historical accident data of the coal mine and environmental data of the coal mine; and constructing a multidimensional data model based on the historical accident data and environmental data.

[0129] Optionally, the computer-readable storage medium may also execute program codes for the following steps: controlling sensors in the coal mine to collect environmental data and status data; the method also includes: transmitting the environmental data and status data to the control unit via a wireless sensor network.

[0130] In this embodiment, a monitoring data set of a coal mine is collected. If there is abnormal monitoring data in the monitoring data set, the probability of a target event (i.e., an abnormal event) occurring in the coal mine can be determined based on the abnormal monitoring data. If the probability is greater than a probability threshold, a multidimensional data model can be called to simulate the monitoring data to obtain development trend information of the target event. Based on the development trend information, a corresponding emergency response strategy can be determined, thereby solving the technical problem of low efficiency in determining the emergency response strategy of the coal mine and achieving the technical effect of improving the efficiency of determining the emergency response strategy of the coal mine.

[0131] According to an embodiment of the present application, a processor is also provided, which is used to run a program, wherein when the program is run by the processor, the method for determining the emergency response strategy in the above embodiment is executed.

[0132] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0133] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the method for determining the emergency response strategy: collecting a monitoring data set of the coal mine, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental status of the coal mine and / or the operating status of the equipment in the coal mine; in response to the presence of abnormal monitoring data in the monitoring data set, determining the probability of a target event occurring in the coal mine, wherein the hazard of the target event to the coal mine is greater than the hazard threshold; in response to the probability being greater than the probability threshold, calling the multidimensional data model corresponding to the coal mine, simulating the monitoring data, and obtaining development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; determining an emergency response strategy that matches the development trend information.

[0134] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the method and device for determining the emergency response strategy in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the method for determining the emergency response strategy described above is realized. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0135] The processor can call the information and application programs stored in the memory through the transmission device to perform the following steps: collect a monitoring data set of the coal mine, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental status of the coal mine and / or the operating status of the equipment in the coal mine; in response to the presence of abnormal monitoring data in the monitoring data set, determine the probability of a target event occurring in the coal mine, wherein the hazard of the target event to the coal mine is greater than the hazard threshold; in response to the probability being greater than the probability threshold, call the multidimensional data model corresponding to the coal mine, simulate the monitoring data, and obtain development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; determine an emergency response strategy that matches the development trend information.

[0136] Optionally, the processor may also execute program codes of the following steps: in response to the presence of abnormal monitoring data in the monitoring data set, fusing other monitoring data in the monitoring data set except the abnormal monitoring data to obtain fused data; and determining the probability based on the fused data.

[0137] Optionally, the processor may also execute program codes of the following steps: obtaining location information of a target object in a coal mine; and determining an emergency response strategy according to the location information and development trend information.

[0138] Optionally, the processor may also execute program code of the following steps: in response to a change in the location information, updating an emergency response strategy based on the changed location information.

[0139] Optionally, the processor may also execute program codes of the following steps: obtaining historical accident data of the coal mine and environmental data of the coal mine; and constructing a multidimensional data model based on the historical accident data and environmental data.

[0140] Optionally, the processor may also execute program codes of the following steps: controlling sensors in the coal mine to collect environmental data and status data; the method also includes: transmitting the environmental data and status data to the control unit via a wireless sensor network.

[0141] By adopting the embodiment of the present application, the monitoring data set of the coal mine is collected. If there is abnormal monitoring data in the monitoring data set, the probability of the target event (that is, the abnormal event) occurring in the coal mine can be determined based on the abnormal monitoring data. If the probability is greater than the probability threshold, the multidimensional data model can be called to simulate the monitoring data to obtain the development trend information of the target event. Based on the development trend information, the corresponding emergency response strategy can be determined, thereby solving the technical problem of low efficiency in determining the emergency response strategy of the coal mine, and achieving the technical effect of improving the efficiency of determining the emergency response strategy of the coal mine.

[0142] According to an embodiment of the present application, a computer program product is also provided. The computer program product includes computer instructions, wherein when the computer instructions are executed by a processor, the method for determining the emergency response strategy in the above embodiment is implemented.

[0143] An embodiment of the present application may provide an electronic device, which may include a memory and a processor.

[0144] Figure 6 It is a block diagram of an electronic device according to a method for determining an emergency response strategy according to an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0145] like Figure 6 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 to a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0146] A number of components in the device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0147] The computing unit 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as a verification method for data. For example, in some embodiments, the verification method for data may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the data verification method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the data verification method in any other appropriate manner (e.g., by means of firmware).

[0148] According to an embodiment of the present application, a method for determining an emergency response strategy is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0149] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor that may be a dedicated or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0150] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0151] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0152] To provide interaction with a user, the systems and techniques described herein may be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or an LCD (liquid crystal display, monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a path ball) through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0153] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a Local Area Network (LAN), a Wide Area Network (WAN), and the Internet.

[0154] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0155] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0156] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0157] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0158] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0159] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0160] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0161] The above are only preferred implementations of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining an emergency response strategy, characterized in that: include: Collecting a monitoring data set of a coal mine, wherein the monitoring data in the monitoring data set is at least used to characterize the environmental state of the coal mine and / or the operating state of equipment in the coal mine; In response to the presence of abnormal monitoring data in the monitoring data set, determining a probability of a target event occurring in the coal mine based on the abnormal monitoring data, wherein the harm of the target event to the coal mine is greater than a harm threshold; In response to the probability being greater than a probability threshold, calling a multidimensional data model corresponding to the coal mine, simulating the monitoring data, and obtaining development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; Determine an emergency response strategy that matches the trend information.

2. The method according to claim 1, characterized in that In response to the presence of abnormal monitoring data in the monitoring data set, determining the probability of a target event occurring in the coal mine includes: In response to the presence of the abnormal monitoring data in the monitoring data set, fusing the other monitoring data in the monitoring data set except the abnormal monitoring data to obtain fused data; Based on the fused data, the probability is determined.

3. The method according to claim 1, characterized in that The determining of an emergency response strategy matching the development trend information includes: Acquiring location information of a target object in the coal mine; Determine the emergency response strategy according to the location information and the development trend information.

4. The method according to claim 3, characterized in that The method further comprises: In response to a change in the location information, the emergency response strategy is updated based on the changed location information.

5. The method according to claim 1, characterized in that: The method further comprises: Obtaining historical accident data of the coal mine and environmental data of the coal mine; The multidimensional data model is constructed based on the historical accident data and the environmental data.

6. The method according to claim 1, characterized in that The monitoring data set includes at least environmental data of the coal mine and status data of equipment in the coal mine. The monitoring data set collected from the coal mine includes: Controlling the sensors in the coal mine to collect the environmental data and the status data; The method further comprises: transmitting the environmental data and the status data to a control unit via a wireless sensor network.

7. A device for determining an emergency response strategy, characterized in that: include: A collection unit, used for collecting a monitoring data set of a coal mine, wherein the monitoring data in the monitoring data set is used at least to characterize the environmental state of the coal mine and / or the operating state of equipment in the coal mine; a first determining unit, configured to determine, in response to the presence of abnormal monitoring data in the monitoring data set, a probability of a target event occurring in the coal mine, wherein the harm of the target event to the coal mine is greater than a harm threshold; a processing unit, configured to, in response to the probability being greater than a probability threshold, call a multidimensional data model corresponding to the coal mine, simulate the monitoring data, and obtain development trend information of the target event, wherein the multidimensional data model is used to simulate the environment in the coal mine, and the development trend information is used to characterize changes in the environment when the target event occurs; The second determining unit is used to determine an emergency response strategy that matches the development trend information.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 6.

9. A computer program product, characterized in that The method comprises computer instructions, which implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A processor, characterized in that: The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 6 when run by the processor.

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