Marine emergency commanding and dispatching method and system based on data processing

Abstract

The invention relates to the technical field of ocean emergency management, in particular to an ocean emergency commanding and dispatching method and system based on data processing, and the method comprises the following steps: collecting data streams of an ocean monitoring station and a meteorological station, integrating the collected wind speed, wave height and ship position information, recognizing data points which are not consistent with a conventional mode, analyzing the data points, and carrying out the analysis of the data points. And judging whether the event is an abnormal event to obtain an ocean data set. According to the method, data are analyzed through a time sequence, the standard deviation and the mean value are obtained through calculation, recognition of abnormal fluctuation is more accurate, the detection capacity of key events is enhanced through refined data processing, the timeliness and accuracy of resource scheduling are further improved through matching analysis of real-time resources and demands, and the method is suitable for large-scale popularization and application. The emergency response is more targeted and effective, the simulation comparison of the performance and the analysis of the response efficiency ensure the optimization of the command and dispatch scheme in the actual execution, and the overall efficiency and accuracy of the ocean emergency management are significantly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of marine emergency management, and in particular to a marine emergency command and dispatch method and system based on data processing. Background Art

[0002] The field of marine emergency management technology includes the comprehensive management of the response, control and recovery process of marine emergencies. This technical field focuses on effectively responding to various emergencies such as marine oil spills, ship collisions, and marine search and rescue through various management measures and technical means. The core content of marine emergency management includes event warning, emergency response, resource scheduling and command and coordination, aiming to minimize the impact of accidents on the marine environment and human activities. This technical field requires the comprehensive use of multidisciplinary knowledge such as information technology, communication technology and management to build a system that can quickly respond to and effectively handle marine emergencies.

[0003] Among them, the marine emergency command and dispatch method of data processing refers to the process of using data processing technology to optimize marine emergency response and resource allocation, which mainly involves collecting data information of relevant sea areas, using data analysis and processing technology to conduct real-time assessment of the situation, and making command decisions accordingly. The technical matters covered include data collection, processing and analysis, as well as decision-making information based on the analysis results, mainly through computer systems and software to achieve rapid data processing and generation of response instructions, and improve the efficiency and accuracy of marine emergency command and dispatch.

[0004] Although existing technologies in maritime emergency management cover incident warning and emergency response, there are limitations in data processing speed and efficiency in actual operation. Conventional technologies cannot perform real-time data analysis and processing of maritime emergencies, resulting in delayed response. This delay increases the risk to the environment and personnel safety in emergency situations. The accuracy and timeliness of resource scheduling are insufficient, and resource allocation is not timely and does not meet actual needs due to the lack of an effective data support system. For activities such as offshore oil pollution treatment or maritime search and rescue, if resource allocation is delayed or inaccurate, it will cause pollution to spread or search and rescue opportunities to be lost, affecting the effectiveness and efficiency of emergency response. Summary of the invention

[0005] In order to solve the limitations of data processing speed and efficiency in the prior art, conventional technology cannot perform real-time data analysis and processing of marine emergencies, resulting in response delays. This delay leads to increased risks to the environment and personnel safety in emergency situations. The accuracy and timeliness of resource scheduling are insufficient, and the lack of an effective data support system leads to insufficient resource allocation and failure to meet actual needs. For activities such as offshore oil pollution treatment or maritime search and rescue, if resource allocation is delayed or inaccurate, it will cause pollution to spread or search and rescue opportunities to be lost, affecting the effectiveness and efficiency of emergency treatment. The embodiment of the present invention provides a marine emergency command and dispatch method and system based on data processing. The technical solution is as follows:

[0006] On the one hand, a marine emergency command and dispatch method based on data processing is provided, the method comprising:

[0007] S1: Collect data streams from offshore monitoring stations and meteorological stations, integrate the collected wind speed, wave height and ship position information, identify data points that do not conform to the normal pattern, analyze the data points, determine whether they are abnormal events, and obtain the ocean data set;

[0008] S2: Perform time series analysis on the ocean data set, perform data processing, calculate standard deviation and mean, identify abnormal fluctuations in the data, identify the type of events, including sudden ocean storms and sudden changes in ship speed, and set corresponding alarm levels to obtain key event detection results;

[0009] S3: Using the key event detection results, perform matching analysis between real-time resources and marine emergency needs, and obtain a resource allocation plan by evaluating the spatial and temporal relationship between the location and status of resources and emergency events;

[0010] S4: According to the resource allocation scheme, simulate differentiated marine emergency response situations, evaluate the efficiency and response time of the resource allocation scheme, compare performance, optimize the command and dispatch of marine emergency, and obtain response efficiency analysis results;

[0011] S5: Using the response efficiency analysis results, conduct marine emergency command and dispatch and real-time resource adjustment, adjust the priority of task allocation and resource utilization efficiency, respond to the rescue needs of risk areas, and obtain marine emergency command and dispatch instructions.

[0012] As a further solution of the present invention, the ocean data set includes integrated wind speed data, wave height measurements, and real-time positions of ships; the key event detection results include identified sudden ocean storm events, abnormal ship speed events, and corresponding alarm levels; the resource allocation plan includes the location of rescue ships, the status of rescue equipment, and emergency response time analysis; the response efficiency analysis results include comparisons of differentiated emergency response plans in terms of response time, resource utilization, and expected effects; the ocean emergency command and dispatch instructions include resource allocation in emergency situations, priority definitions, and rescue operations in risk areas.

[0013] As a further solution of the present invention, the steps of collecting data streams from offshore monitoring stations and meteorological stations, integrating the collected wind speed, wave height and ship position information, identifying data points that do not conform to the normal pattern, analyzing the data points, and determining whether they are abnormal events, and obtaining the ocean data set are specifically as follows:

[0014] S101: collect data streams from offshore monitoring stations and meteorological stations, including wind speed, wave height and ship position information, transmit them in real time through the communication network, update the data in real time, and obtain the original data set;

[0015] S102: extract key information from the original data set, identify data points that deviate from the normal range, analyze abnormal fluctuations and trends that do not conform to the normal pattern, and obtain deviation analysis results;

[0016] S103: According to the deviation analysis result, the influencing factors of the data point deviation are evaluated, including weather changes, abnormal ocean currents and human activities, to obtain an ocean data set.

[0017] As a further solution of the present invention, the steps of performing time series analysis on the ocean data set, performing data processing, calculating the standard deviation and mean, identifying abnormal fluctuations in the data, identifying the types of events, including sudden ocean storms and sudden changes in ship speed, and setting corresponding alarm levels to obtain key event detection results are specifically as follows:

[0018] S201: performing time series analysis on the ocean data set, extracting data points to form a continuous timeline, performing data fluctuation analysis, arranging the data in chronological order, and marking the timestamps of the data points to obtain time-stamped data;

[0019] S202: Based on the time-stamped data, calculate the standard deviation and mean of the data points, identify the data points whose fluctuations exceed the normal range by comparing the deviations between the real-time values ​​of the data points and the statistical mean, capture the data peaks and abnormal decreases, and obtain the abnormal fluctuation data points;

[0020] S203: Using the abnormal fluctuation data points, identify the event types of sudden ocean storms and ship speed changes, calculate the abnormal score value based on the fluctuation characteristics and fluctuation trends of the abnormal data points, set the corresponding event alarm level, and obtain the key event detection result.

[0021] As a further solution of the present invention, the formula for calculating the abnormality score value is:

[0022]

[0023] Among them, A t represents the abnormal score value at time t, D t-1 , D t-2 and D t-3 They represent the marine environment monitoring data points at time t-1, t-2 and t-3 respectively, and w1, w2 and w3 are weight coefficients.

[0024] As a further solution of the present invention, the key event detection results are used to perform matching analysis between real-time resources and marine emergency needs, and the steps of obtaining a resource allocation plan by evaluating the spatial and temporal relationship between the location and status of resources and the emergency events are specifically as follows:

[0025] S301: Using the key event detection results, extract key event information, including event type, time and location, perform initial resource matching demand analysis, and obtain event and resource matching records;

[0026] S302: Evaluate the location and status of available marine emergency resources through the event and resource matching record, including the real-time location and response status of rescue vessels, helicopters and rescue equipment, compare with the event location and time in the event and resource matching record, analyze the arrival time of resources and the urgency of the event, and obtain resource allocation analysis results;

[0027] S303: According to the resource allocation analysis results, referring to the real-time scheduling probability of multiple types of resources and the response efficiency to emergency events, marine emergency manpower mobilization and resource scheduling are carried out to obtain a resource allocation plan.

[0028] As a further solution of the present invention, according to the resource allocation scheme, the differentiated marine emergency response situations are simulated, the efficiency and response time of the resource allocation scheme are evaluated, the performance is compared, the command and dispatch of the marine emergency are optimized, and the steps of obtaining the response efficiency analysis results are specifically as follows:

[0029] S401: Based on the resource allocation scheme, construct differentiated marine emergency response simulation scenarios, allocate differentiated resources to each scenario, simulate the target type of marine emergency event and respond to it, and obtain a simulated response situation;

[0030] S402: evaluating the response time and efficiency in differentiated scenarios through the simulated response situation, calculating the weighted average response time, identifying the key factors causing the response delay, and obtaining a performance comparison result;

[0031] S403: According to the performance comparison results, adjust and optimize the marine emergency command and dispatch, reconfigure resources to avoid response time and optimize marine emergency handling efficiency, optimize the layout of dispatch commands, personnel and equipment, and obtain response efficiency analysis results.

[0032] As a further solution of the present invention, the formula for calculating the weighted average response time is:

[0033]

[0034] Among them, BR is the weighted average response time, N represents the number of simulations, and x i represents the randomly generated scene parameters in the i-th simulation, f(x i ) is the response time of the scenario, T represents the operation time, k represents the adjustment coefficient, a and b represent the key parameters of the resource allocation plan, and e is the base of the natural logarithm.

[0035] As a further solution of the present invention, the response efficiency analysis result is used to perform marine emergency command and dispatch and real-time resource adjustment, adjust the priority of task allocation and resource utilization efficiency, respond to the rescue needs of risk areas, and obtain the marine emergency command and dispatch instructions in the following steps:

[0036] S501: Based on the response efficiency analysis results, evaluate and adjust the use of multiple resources and task allocation in the marine emergency response, analyze efficiency bottlenecks and time delays, optimize task priorities, and obtain priority ranking records;

[0037] S502: Using the priority ranking records, real-time monitoring of marine emergency command and dispatch, including dispatch of ships, rescue personnel and rescue equipment, allocating resources according to real-time marine conditions and changes in risk areas, and obtaining real-time resource adjustment records;

[0038] S503: Through the real-time resource adjustment record, when facing sudden marine incidents, key rescue operations and resource dispatch are carried out to respond to and avoid losses and risks, and obtain marine emergency command and dispatch instructions.

[0039] On the other hand, an electric vehicle state monitoring system is provided, wherein the electric vehicle state monitoring system is used to execute the above electric vehicle state monitoring method, and the system comprises:

[0040] The data recording module collects data streams from offshore monitoring stations and weather stations, records wind speed, wave height, and ship location information, and analyzes the data to determine whether it is an abnormal event, thereby obtaining an ocean data set;

[0041] The data analysis module performs time series analysis based on the ocean data set, calculates the standard deviation and mean, identifies event types through anomaly detection, including sudden ocean storms and sudden changes in ship speed, sets alarm levels, and obtains key event detection results;

[0042] The resource matching module performs real-time matching analysis between resources and needs based on the key event detection results, evaluates resource location and status, analyzes the relationship with emergency events, and obtains a resource allocation plan;

[0043] The emergency response module adopts the resource allocation scheme to simulate differentiated emergency response situations, evaluate the response time and efficiency of the resource allocation scheme, optimize the command and dispatch process, and obtain response efficiency analysis results;

[0044] The command and dispatch module uses the response efficiency analysis results to adjust command and dispatch and resource utilization, assign task priorities, respond to the needs of risk areas, and obtain marine emergency command and dispatch instructions.

[0045] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0046] By integrating the data streams of offshore monitoring and meteorological stations, optimizing the identification and response process of emergencies, and conducting real-time analysis of data streams, especially comprehensive evaluation of wind speed, wave height and ship position, it is helpful to quickly identify abnormal events that do not conform to normal patterns and achieve early warning of events. By analyzing the data through time series, the standard deviation and mean are calculated, making the identification of abnormal fluctuations more accurate. This refined data processing enhances the detection capability of key events. Real-time matching analysis of resources and needs further improves the timeliness and accuracy of resource scheduling, making emergency response more targeted and effective. The simulation comparison of performance and analysis of response efficiency ensure the optimization of command and dispatch plans in actual implementation, significantly improving the overall efficiency and accuracy of marine emergency management. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0048] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0049] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0050] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0051] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0052] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0053] Figure 7 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0054] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0055] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0056] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0057] See also Figure 1 The embodiment of the present invention provides a marine emergency command and dispatch method based on data processing. The processing flow of the method may include the following steps:

[0058] S1: Collect data streams from offshore monitoring stations and meteorological stations, integrate the collected wind speed, wave height and ship position information, identify data points that do not conform to the normal pattern, analyze the data points, determine whether they are abnormal events, and obtain the ocean data set;

[0059] S2: Perform time series analysis on the ocean data set, perform data processing, calculate standard deviation and mean, identify abnormal fluctuations in the data, identify the type of events, including sudden ocean storms and sudden changes in ship speed, and set corresponding alarm levels to obtain key event detection results;

[0060] S3: Using the key event detection results, we conduct a matching analysis between real-time resources and marine emergency needs, and obtain a resource allocation plan by evaluating the spatial and temporal relationship between the location and status of resources and emergency events;

[0061] S4: According to the resource allocation plan, simulate the differentiated marine emergency response situation, evaluate the efficiency and response time of the resource allocation plan, compare the performance, optimize the command and dispatch of the marine emergency, and obtain the response efficiency analysis results;

[0062] S5: Use the response efficiency analysis results to conduct marine emergency command and dispatch and real-time resource adjustment, adjust the priority of task allocation and resource utilization efficiency, respond to rescue needs in risk areas, and obtain marine emergency command and dispatch instructions.

[0063] The ocean data set includes integrated wind speed data, wave height measurements, and real-time locations of ships. Key event detection results include identified sudden ocean storm events, abnormal ship speed events, and corresponding alarm levels. Resource allocation plans include the locations of rescue ships, the status of rescue equipment, and emergency response time analysis. Response efficiency analysis results include comparisons of differentiated emergency response plans in terms of response time, resource utilization, and expected effects. Ocean emergency command and dispatch instructions include resource allocation in emergency situations, priority definitions, and rescue operations in risk areas.

[0064] See also Figure 2 , collect data streams from offshore monitoring stations and weather stations, integrate the collected wind speed, wave height and ship position information, identify data points that do not conform to the normal pattern, analyze the data points, and determine whether they are abnormal events. The specific steps to obtain the ocean data set are:

[0065] S101: Collect data streams from offshore monitoring stations and weather stations, including wind speed, wave height and ship position information, transmit them in real time through the communication network, and update the data in real time to obtain the original data set. The execution process is as follows;

[0066] Data from offshore monitoring stations and meteorological stations, including wind speed, wave height, ship location and other information, are collected and transmitted in real time through high-frequency communication networks. Encryption technology is used during data transmission to ensure information security. At the same time, data collectors deployed at each node of the network preliminarily screen the information and remove data points with obvious errors, such as abnormal data where the wave height suddenly jumps from 2 meters to 20 meters. This data is caused by sensor failure or data transmission error. In this way, preliminary quality control can be performed before the data reaches the server to ensure that the incoming data has a certain degree of reliability. The data set received by the server is the original data set. This efficient data processing mechanism ensures the timeliness and accuracy of monitoring data, providing a reliable data basis for maritime safety and climate research. This process is crucial for subsequent data analysis and decision-making, because only high-quality data can ensure the accuracy of analysis results and the effectiveness of application, and obtain the original data set.

[0067] S102: Extract key information from the original data set, identify data points that deviate from the normal range, analyze abnormal fluctuations and trends that do not conform to the normal pattern, and obtain the execution process of the deviation analysis results as follows;

[0068] Extract key information from the original data set and identify data points that deviate from the normal range according to the formula:

[0069]

[0070] In the formula, σ represents the standard deviation, x c represents each data point, μ represents the average value of data point c, and Z represents the total number of data points;

[0071] Calculate the mean μ of the data points, which is obtained by summing all data points and dividing by the number of data points N;

[0072] Set the data points of wind speed to 10, 12, 9, 11, 10 m / s, then μ = (10 + 12 + 9 + 11 + 10) / 5 = 10.4 m / s;

[0073] Sum the squares of the differences between each data point and the mean, and divide by the number of data points Z to get the variance;

[0074] Taking the square root of the variance gives the standard deviation σ. This step is used to identify data points that deviate too much from the mean. Wave heights or wind speeds that exceed twice the standard deviation are considered abnormal. This statistical analysis method is very suitable for anomaly detection in a big data environment, with high reliability and ease of real-time monitoring and early warning.

[0075] S103: Based on the deviation analysis results, the influencing factors of the data point deviation are evaluated, including weather changes, abnormal ocean currents and human activities, and the execution process of the ocean data set is as follows;

[0076] Evaluate the influencing factors of data point deviations, including weather changes, abnormal ocean currents, human activities, etc., and conduct in-depth correlation analysis of factors through data mining technology. For example, use decision tree algorithms to classify influencing factors, and find out the interactions between different factors through association rule mining, which can help determine the main driving factors of specific deviations. For example, it is found that the abnormal ocean current speed in a specific area is related to the excessive concentration of nearby ships. Through analysis, it can provide data support for marine management departments, help formulate policies and response measures more effectively, better manage and protect marine resources, and provide important references for subsequent research. This process not only improves the application value of data, but also enhances the adaptability and response speed to changes in the marine environment, laying a solid foundation for marine scientific research and practical applications, and obtaining marine data sets.

[0077] See also Figure 3 , perform time series analysis on the ocean data set, perform data processing, calculate standard deviation and mean, identify abnormal fluctuations in the data, identify the type of event, including sudden ocean storms and sudden changes in ship speed, and set corresponding alarm levels. The specific steps to obtain key event detection results are as follows:

[0078] S201: Perform time series analysis on the ocean data set, extract data points to form a continuous timeline, perform data fluctuation analysis, arrange the data in chronological order, and mark the timestamps of the data points. The execution process of obtaining time-stamped data is as follows;

[0079] When processing ocean data sets, time series analysis is performed, which is done by extracting data points and forming a continuous timeline. This process involves arranging the data points in the order of their occurrence and marking each data point with a timestamp. The key to this step is to ensure the timing and integrity of the data to facilitate subsequent analysis of fluctuations and trends. Data fluctuation analysis relies on such time-stamped data, through which changes in ocean environmental parameters such as temperature, salinity, wave height, etc. over time can be observed. The timestamps of marked data points are the basis for analyzing how data changes over time, allowing researchers to track the specific time of occurrence of each data point, analyze the periodicity and anomalies of data fluctuations, and obtain time-stamped data.

[0080] S202: Based on the time-stamped data, the standard deviation and mean of the data points are calculated, and by comparing the deviation between the real-time value of the data point and the statistical mean, the data points with fluctuations beyond the normal range are identified, and the data peaks and abnormal reductions are captured. The execution process of obtaining the abnormal fluctuation data points is as follows;

[0081] Calculating the standard deviation and mean of data points is a common step in statistical analysis. By calculating statistics, the degree of deviation of the real-time value of the data point from the statistical mean can be compared. This analysis helps identify data points that fluctuate beyond the normal range, that is, points that appear as data peaks or abnormal decreases. Identifying abnormal data points is the key to understanding and dealing with potential problems in marine data sets. It can reveal signals of potential environmental changes or equipment failures. It involves complex data processing techniques, such as moving averages or exponential smoothing, which help smooth time series data and more clearly identify true outliers, resulting in abnormally fluctuating data points.

[0082] S203: Using abnormal fluctuation data points, identify the event types of sudden ocean storms and ship speed changes, calculate the abnormal score value based on the fluctuation characteristics and fluctuation trends of the abnormal data points, and set the corresponding event alarm level. The execution process of obtaining the key event detection results is as follows;

[0083] The formula for calculating the anomaly score value is:

[0084]

[0085] Among them, A t represents the abnormal score value at time t, D t-1 , D t-2 and D t-3represent the marine environment monitoring data points at time t-1, t-2 and t-3 respectively, w1, w2 and w3 are weight coefficients;

[0086] Parameter meaning and setting value:

[0087] A t is the abnormal score value at time t, indicating the probability of emergencies in the marine environment;

[0088] D t-1 ,D t-2 ,D t-3 For monitoring data at three consecutive time points, such as wind speed or wave height, the monitoring data is collected directly from ocean sensors. Set D t-1 =15m / s, D t-2 =17m / s, D t-3 =13m / s;

[0089] w1, w2 and w3 are weight coefficients, which are determined based on the correlation analysis of historical data. Let w1 = 0.5, w2 = 0.3, w3 = 0.2, which reflects D t-1 A t The impact of is the greatest, and as time goes by, the impact of the data point gradually decreases;

[0090] Substitute the parameters into the formula for calculation:

[0091]

[0092] The results show that the environmental status at the current time t has higher abnormal activity relative to the previous three data points. Based on this score value, an early warning can be issued and appropriate response measures can be activated to ensure maritime safety.

[0093] See also Figure 4 ,Using the key event detection results, we conduct a matching analysis between real-time resources and marine emergency needs. By evaluating the spatial and temporal relationship between the location and status of resources and emergency events, the steps to obtain the resource allocation plan are as follows:

[0094] S301: Using the key event detection results, extract the key event information, including the type, time and location of the event, and perform an initial resource matching demand analysis to obtain the event and resource matching record. The execution process is as follows;

[0095] Extract information about key events, including determining the type, time and location of the event. Through the information, perform an initial resource matching demand analysis. This process uses advanced data analysis technology to classify and label event information. The system compares event characteristics with resource records in the database and selects qualified rescue units and equipment, such as maritime rescue ships, helicopters and medical equipment. The matching process takes into account the availability, response time and geographical location of each resource to ensure that the selected resources best match the needs of the event. After a successful match, the allocation of each resource and the estimated investment time are listed in detail. As part of the response plan, it is crucial to respond quickly and effectively to emergencies at sea, ensure the optimal allocation of resources and rapid response, and obtain event and resource matching records.

[0096] S302: Through the event and resource matching records, the location and status of available marine emergency resources are evaluated, including the real-time location and response status of rescue vessels, helicopters and rescue equipment, and compared with the event location and time in the event and resource matching records, and the arrival time of resources and the urgency of the event are analyzed to obtain the execution process of the resource allocation analysis results as follows;

[0097] Assess the location and status of available marine emergency resources according to the formula:

[0098]

[0099] In the formula, J arrival represents the resource arrival time, J event represents the time when the event occurs, S represents the distance of the resource from the event location, and V represents the speed of resource movement;

[0100] Get the event occurrence time from the event and resource matching record event and the current location of the resource. Assume that a rescue ship is located 100 km north of the incident site, and the average moving speed of the ship is 30 km / h. The incident time is 08:00. Then the distance between the resource and the incident site is D = 100 km, and the moving speed of the resource is V = 30 km / h.

[0101] Substitute the values ​​into the formula to calculate:

[0102]

[0103] This calculation method provides scientific time estimates for emergency response, ensuring that resources can arrive at the scene in the shortest possible time.

[0104] S303: According to the resource allocation analysis results, referring to the real-time dispatch probability of multiple types of resources and the response efficiency to emergency events, marine emergency manpower mobilization and resource dispatch are carried out, and the execution process of the resource allocation plan is obtained as follows;

[0105] The system evaluates the scheduling priority of various resources, the availability of human resources and skill matching. It predicts the response efficiency of different resource combinations through algorithm models and selects the optimal plan for scheduling, including how to choose helicopters or rescue ships for initial rapid response, while considering the mobilization of subsequent medical and technical support teams. Decisions are based on complex algorithms and historical data analysis to ensure that a quick and accurate response can be made in the face of multiple estimated emergency situations. The specific scheduling time and location of various resources are specified in detail, providing a detailed execution blueprint for actual operations, which not only improves rescue efficiency, but also significantly reduces potential risks and costs.

[0106] See also Figure 5 According to the resource allocation scheme, the differentiated marine emergency response situations are simulated, the efficiency and response time of the resource allocation scheme are evaluated, the performance is compared, and the command and dispatch of marine emergency are optimized. The specific steps to obtain the response efficiency analysis results are as follows:

[0107] S401: Based on the resource allocation scheme, differentiated marine emergency response simulation scenarios are constructed, differentiated resources are allocated to each scenario, and responses are performed when simulating target type marine emergency events. The execution process of the simulated response situation is as follows;

[0108] Carry out differentiated marine emergency response simulations. This process involves building multiple simulation scenarios, each of which allocates corresponding resources according to its specific needs. The simulation scenarios are designed to simulate different types of marine emergencies, such as ship sinking, offshore oil spills, or natural disasters. Through simulation, the actual effect of various resource allocations on emergency response can be tested and evaluated. During the simulation, the deployment of various resources such as rescue ships, helicopters, and rescue equipment are carried out according to the preset plan, while recording the response time and processing efficiency. The data will be used to evaluate the effectiveness of the simulation and provide a basis for improvement of the actual emergency response, which will help identify the strengths and weaknesses of resource allocation, make necessary adjustments and optimizations, and obtain simulated response situations.

[0109] S402: By simulating response situations, evaluating response time and efficiency in differentiated scenarios, calculating weighted average response time, identifying key factors causing response delays, and obtaining performance comparison results, the execution process is as follows;

[0110] The formula for calculating the weighted average response time is:

[0111]

[0112] Among them, BR is the weighted average response time, N represents the number of simulations, and x i represents the randomly generated scene parameters in the i-th simulation, f(x i) is the response time of the scenario, T represents the operation time, k represents the adjustment coefficient, a and b represent the key parameters of the resource allocation scheme, and e is the base of the natural logarithm;

[0113] Parameter meaning and setting value:

[0114] N is the number of simulations, and the operation frequency within one year is obtained from the data monitoring system and is set to 10000, reflecting the frequency of the operation;

[0115] x i The randomly generated scenario parameters come from the actual operation data set and reflect different operation environments;

[0116] f(x i ) is the response time for a specific scenario, which is established based on historical performance data;

[0117] T is the operation time, the average operation time from the system log, and the set value is 300 seconds, indicating the duration of the operation;

[0118] k is the adjustment coefficient, which is set to 0.05 based on the system adjustment history of the past year, expressing the sensitivity of time extension to system performance;

[0119] a and b are key parameters of the resource configuration scheme, which are obtained from the system configuration log. a is 500GB and b is 450GB, showing the storage capacity of different resource configurations.

[0120] Substitute the parameters into the formula for calculation:

[0121] Calculate |ab|, the result is 50GB, the square root is about 7.07, and the reciprocal is about 0.141;

[0122] Calculate e using e k×T , given k = 0.05 and T = 300, the result is about 164;

[0123] set up To simulate the total response time, set the value to 2000000 milliseconds and substitute it into the formula:

[0124]

[0125] The results show that the weighted average response time obtained by Monte Carlo algorithm simulation is 4619.66 milliseconds, which shows the estimated performance of the system under the current resource configuration and operating conditions. This result reflects the understanding of how the adjustment coefficient and configuration differences work together to affect the system performance, and provides a basis for further optimizing the configuration.

[0126] S403: According to the performance comparison results, adjust and optimize the marine emergency command and dispatch, reconfigure resources to avoid response time and optimize the efficiency of marine emergency handling, optimize the layout of dispatch commands, personnel and equipment, and obtain the execution process of the response efficiency analysis results as follows;

[0127] Adjust and optimize the marine emergency command and dispatch, which includes reconfiguring resources to avoid unnecessary response time and improve the overall efficiency of marine emergency handling. During the adjustment process, not only the quantity and type of resources are considered, but also the optimization of dispatch orders, the rearrangement of personnel layout, and the optimal deployment of rescue equipment. Through optimization measures, it is aimed to reduce the start-up time of rescue operations, improve rescue efficiency, and ensure that when facing actual marine emergencies, a quick and effective response can be carried out, which will directly affect the handling strategy and success rate of future marine emergency events, and obtain the response efficiency analysis results.

[0128] See also Figure 6 , using the response efficiency analysis results, conduct marine emergency command and dispatch and real-time resource adjustment, adjust the priority of task allocation and resource utilization efficiency, respond to the rescue needs of risk areas, and obtain the specific steps of marine emergency command and dispatch instructions:

[0129] S501: Based on the response efficiency analysis results, evaluate and adjust the use of multiple resources and task allocation in marine emergency response, analyze efficiency bottlenecks and time delays, optimize task priorities, and obtain the execution process of priority ranking records as follows;

[0130] Evaluate and adjust the use of multiple resources and task allocation in marine emergency response. This process involves in-depth analysis of the utilization efficiency of existing resources, identifying efficiency bottlenecks and the main causes of time delays, such as unreasonable routes of rescue ships, insufficient rescue personnel or outdated rescue equipment. In response to the problems, re-optimize the priority of tasks, use advanced algorithm models for simulation and prediction, ensure that the most urgent and most influential events are handled first, and list the priority of each rescue task in detail. The priority is determined based on the urgency of the task, the scope of impact and the status of available resources, ensuring that limited resources can be used most effectively in a changing marine environment. This not only improves rescue efficiency, but also significantly reduces estimated losses and risks, and obtains priority ranking records.

[0131] S502: Using the priority sorting records, real-time monitoring of marine emergency command and dispatch, including dispatch of ships, rescue personnel and rescue equipment, and allocation of resources according to the real-time marine conditions and changes in risk areas, the execution process of obtaining real-time resource adjustment records is as follows;

[0132] Real-time monitoring of marine emergency command and dispatch, including the dispatch of ships, rescue personnel and rescue equipment. During this process, the command center uses the latest communication technology and geographic information systems to dynamically allocate resources according to real-time marine conditions and changes in risk areas. For example, after receiving a new marine incident report, it quickly adjusts the deployment of rescue ships and helicopters, giving priority to incidents in high-risk areas. Updated risk assessment reports will be used to guide the use of rescue equipment and the dispatch of personnel. This highly dynamic and responsive resource adjustment can greatly improve the timeliness and effectiveness of rescue operations, record the decision and implementation details of each resource adjustment in detail, provide data support and decision-making basis for subsequent estimated adjustments, and obtain real-time resource adjustment records.

[0133] S503: Through real-time resource adjustment records, when facing sudden marine incidents, key rescue operations and resource dispatch are carried out to respond to and avoid losses and risks, and the execution process of obtaining marine emergency command and dispatch instructions is as follows;

[0134] When faced with sudden marine incidents, key rescue operations and resource dispatch are carried out according to the formula:

[0135]

[0136] In the formula, GR represents resource scheduling efficiency, P o Represents the priority coefficient of each resource, A o represents the availability of resources, Q represents the total response time, and n is the number of resources o;

[0137] Obtain the priority coefficient and availability of each resource from the real-time resource adjustment record. For example, the priority coefficient of the rescue vessel is 0.8 and the availability is 1 (fully available);

[0138] The helicopter has a priority factor of 0.9, an availability of 0.9 (partially available), and a total response time of 1 hour;

[0139] Substituting the values ​​into the formula:

[0140]

[0141] This calculation method provides a quantitative way to evaluate the overall efficiency of rescue operations, ensuring that key resources are optimally used when they are most needed. The resulting marine emergency command and dispatch instructions can accurately guide field operations and ensure the success of rescue operations.

[0142] On the other hand, an electric vehicle state monitoring system is provided, wherein the electric vehicle state monitoring system is used to execute the above electric vehicle state monitoring method, and the system comprises:

[0143] The data recording module collects data streams from offshore monitoring stations and weather stations, records wind speed, wave height, and ship location information, and analyzes the data to determine whether it is an abnormal event, thereby obtaining an ocean data set;

[0144] The data analysis module performs time series analysis based on the ocean data set, calculates the standard deviation and mean, identifies event types through anomaly detection, including sudden ocean storms and sudden changes in ship speed, sets alarm levels, and obtains key event detection results;

[0145] The resource matching module uses key event detection results to conduct real-time matching analysis between resources and needs, evaluate resource location and status, analyze the relationship with emergency events, and obtain resource allocation plans;

[0146] The emergency response module adopts resource allocation schemes to simulate differentiated emergency response situations, evaluate the response time and efficiency of resource allocation schemes, optimize the command and dispatch process, and obtain response efficiency analysis results;

[0147] The command and dispatch module uses the response efficiency analysis results to adjust command and dispatch and resource utilization, assign task priorities, respond to the needs of risk areas, and obtain marine emergency command and dispatch instructions.

[0148] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A marine emergency command and dispatch method based on data processing, characterized in that: The following steps are involved: S1: Collect data streams from offshore monitoring stations and meteorological stations, integrate the collected wind speed, wave height and ship position information, identify data points that do not conform to the normal pattern, analyze the data points, determine whether they are abnormal events, and obtain the ocean data set; S2: Perform time series analysis on the ocean data set, perform data processing, calculate standard deviation and mean, identify abnormal fluctuations in the data, identify the type of events, including sudden ocean storms and sudden changes in ship speed, and set corresponding alarm levels to obtain key event detection results; S3: Using the key event detection results, perform matching analysis between real-time resources and marine emergency needs, and obtain a resource allocation plan by evaluating the spatial and temporal relationship between the location and status of resources and emergency events; S4: According to the resource allocation scheme, simulate differentiated marine emergency response situations, evaluate the efficiency and response time of the resource allocation scheme, compare performance, optimize the command and dispatch of marine emergency, and obtain response efficiency analysis results; S5: Using the response efficiency analysis results, conduct marine emergency command and dispatch and real-time resource adjustment, adjust the priority of task allocation and resource utilization efficiency, respond to the rescue needs of risk areas, and obtain marine emergency command and dispatch instructions.

2. The marine emergency command and dispatch method based on data processing according to claim 1 is characterized in that: The ocean data set includes integrated wind speed data, wave height measurements, and real-time locations of ships. The key event detection results include identified sudden ocean storm events, abnormal ship speed events, and corresponding alarm levels. The resource allocation plan includes the location of rescue ships, the status of rescue equipment, and emergency response time analysis. The response efficiency analysis results include comparisons of differentiated emergency response plans' response time, resource utilization, and expected effects. The ocean emergency command and dispatch instructions include resource allocation in emergency situations, priority definitions, and rescue operations in risk areas.

3. The marine emergency command and dispatch method based on data processing according to claim 1 is characterized in that: Collect data streams from offshore monitoring stations and weather stations, integrate the collected wind speed, wave height, and ship position information, identify data points that do not conform to the normal pattern, analyze the data points, and determine whether they are abnormal events. The specific steps to obtain the ocean data set are: S101: collect data streams from offshore monitoring stations and meteorological stations, including wind speed, wave height and ship position information, transmit them in real time through the communication network, update the data in real time, and obtain the original data set; S102: extract key information from the original data set, identify data points that deviate from the normal range, analyze abnormal fluctuations and trends that do not conform to the normal pattern, and obtain deviation analysis results; S103: According to the deviation analysis result, the influencing factors of the data point deviation are evaluated, including weather changes, abnormal ocean currents and human activities, to obtain an ocean data set.

4. The marine emergency command and dispatch method based on data processing according to claim 1 is characterized in that: The steps of performing time series analysis on the ocean data set, performing data processing, calculating the standard deviation and mean, identifying abnormal fluctuations in the data, identifying the types of events, including sudden ocean storms and sudden changes in ship speed, and setting corresponding alarm levels to obtain key event detection results are as follows: S201: performing time series analysis on the ocean data set, extracting data points to form a continuous timeline, performing data fluctuation analysis, arranging the data in chronological order, and marking the timestamps of the data points to obtain time-stamped data; S202: Based on the time-stamped data, calculate the standard deviation and mean of the data points, identify the data points whose fluctuations exceed the normal range by comparing the deviations between the real-time values ​​of the data points and the statistical mean, capture the data peaks and abnormal decreases, and obtain the abnormal fluctuation data points; S203: Using the abnormal fluctuation data points, identify the event types of sudden ocean storms and ship speed changes, calculate the abnormal score value based on the fluctuation characteristics and fluctuation trends of the abnormal data points, set the corresponding event alarm level, and obtain the key event detection result.

5. The marine emergency command and dispatch method based on data processing according to claim 4 is characterized in that: The formula for calculating the abnormal score value is: Among them, A t represents the abnormal score value at time t, D t-1 , D t-2 and D t-3 They represent the marine environment monitoring data points at time t-1, t-2 and t-3 respectively, and w1, w2 and w3 are weight coefficients.

6. The marine emergency command and dispatch method based on data processing according to claim 1 is characterized in that: Using the key event detection results, the matching analysis of real-time resources and marine emergency needs is carried out, and the steps of obtaining the resource allocation plan are specifically as follows by evaluating the spatial and temporal relationship between the location and status of resources and the emergency events: S301: Using the key event detection results, extract key event information, including event type, time and location, perform initial resource matching demand analysis, and obtain event and resource matching records; S302: Evaluate the location and status of available marine emergency resources through the event and resource matching record, including the real-time location and response status of rescue vessels, helicopters and rescue equipment, compare with the event location and time in the event and resource matching record, analyze the arrival time of resources and the urgency of the event, and obtain resource allocation analysis results; S303: According to the resource allocation analysis results, referring to the real-time scheduling probability of multiple types of resources and the response efficiency to emergency events, marine emergency manpower mobilization and resource scheduling are carried out to obtain a resource allocation plan.

7. The marine emergency command and dispatch method based on data processing according to claim 1 is characterized in that: According to the resource allocation scheme, the differentiated marine emergency response situations are simulated, the efficiency and response time of the resource allocation scheme are evaluated, the performance is compared, the command and dispatch of the marine emergency is optimized, and the steps for obtaining the response efficiency analysis results are as follows: S401: Based on the resource allocation scheme, construct differentiated marine emergency response simulation scenarios, allocate differentiated resources to each scenario, simulate the target type of marine emergency event and respond to it, and obtain a simulated response situation; S402: evaluating the response time and efficiency in differentiated scenarios through the simulated response situation, calculating the weighted average response time, identifying the key factors causing the response delay, and obtaining a performance comparison result; S403: According to the performance comparison results, adjust and optimize the marine emergency command and dispatch, reconfigure resources to avoid response time and optimize marine emergency handling efficiency, optimize the layout of dispatch commands, personnel and equipment, and obtain response efficiency analysis results.

8. The marine emergency command and dispatch method based on data processing according to claim 7 is characterized in that: The formula for calculating the weighted average response time is: Among them, BR is the weighted average response time, N represents the number of simulations, and x i represents the randomly generated scene parameters in the i-th simulation, f(x i ) is the response time of the scenario, T represents the operation time, k represents the adjustment coefficient, a and b represent the key parameters of the resource allocation plan, and e is the base of the natural logarithm.

9. The marine emergency command and dispatch method based on data processing according to claim 1 is characterized in that: The response efficiency analysis results are used to conduct marine emergency command and dispatch and real-time resource adjustment, adjust the priority of task allocation and resource utilization efficiency, respond to the rescue needs of risk areas, and obtain marine emergency command and dispatch instructions in the following steps: S501: Based on the response efficiency analysis results, evaluate and adjust the use of multiple resources and task allocation in the marine emergency response, analyze efficiency bottlenecks and time delays, optimize task priorities, and obtain priority ranking records; S502: Using the priority ranking records, real-time monitoring of marine emergency command and dispatch, including dispatch of ships, rescue personnel and rescue equipment, allocating resources according to real-time marine conditions and changes in risk areas, and obtaining real-time resource adjustment records; S503: Through the real-time resource adjustment record, when facing sudden marine incidents, key rescue operations and resource dispatch are carried out to respond to and avoid losses and risks, and obtain marine emergency command and dispatch instructions.

10. The marine emergency command and dispatch system based on data processing is characterized by: According to the marine emergency command and dispatch method based on data processing according to any one of claims 1 to 9, the system comprises: The data recording module collects data streams from offshore monitoring stations and weather stations, records wind speed, wave height, and ship location information, and analyzes the data to determine whether it is an abnormal event, thereby obtaining an ocean data set; The data analysis module performs time series analysis based on the ocean data set, calculates the standard deviation and mean, identifies event types through anomaly detection, including sudden ocean storms and sudden changes in ship speed, sets alarm levels, and obtains key event detection results; The resource matching module performs real-time matching analysis between resources and needs based on the key event detection results, evaluates resource location and status, analyzes the relationship with emergency events, and obtains a resource allocation plan; The emergency response module adopts the resource allocation scheme to simulate differentiated emergency response situations, evaluate the response time and efficiency of the resource allocation scheme, optimize the command and dispatch process, and obtain response efficiency analysis results; The command and dispatch module uses the response efficiency analysis results to adjust command and dispatch and resource utilization, assign task priorities, respond to the needs of risk areas, and obtain marine emergency command and dispatch instructions.

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