Marine emergency plan planning method and system based on block chain

Abstract

The invention relates to the technical field of emergency communication, in particular to an ocean emergency plan planning method and system based on a block chain, and the method comprises the following steps: receiving air pressure, temperature and wind speed data based on a target ocean monitoring region, collecting the water velocity and direction data, extracting the geographic position and course data of a ship, and carrying out the data processing; and performing timestamp alignment and data fusion processing on the data to obtain a marine environment condition data set. According to the invention, the block chain technology is applied to ocean emergency plan planning, the transparency and traceability of data are improved, the probability and potential influence of disasters are predicted through time sequence analysis, early warning signals are sent to associated nodes through a network, and the health condition and communication load of each node in the network are monitored in real time. And the data flow and the bandwidth are dynamically adjusted, so that the response speed and the efficiency of the network are improved, rescue resources can be quickly and effectively deployed in an emergency, and the accident influence is reduced to the greatest extent.

Description

Technical Field

[0001] The present invention relates to the field of emergency communication technology, and in particular to a method and system for marine emergency plan planning based on blockchain. Background Art

[0002] The field of emergency communication technology involves technologies and methods to ensure information exchange in emergencies or crisis situations. The core goal of this field is to ensure the stability and reliability of communication networks in natural disasters, man-made accidents or other emergency situations. Emergency communication technologies include satellite communications, mobile communications, radio frequency communications and network data transmission. The technology supports rapid deployment, high flexibility and a wide coverage area to meet different emergency response needs. On this basis, the development of corresponding communication protocols and standards is the key to ensure effective interconnection between various devices and systems. In addition, emergency communications also need to pay attention to information security and privacy protection to ensure the security of sensitive data during transmission.

[0003] Among them, the marine emergency plan planning method refers to planning plans to deal with possible risks and damages in the face of marine-related emergencies, such as ship accidents, marine oil pollution or natural disasters. The core of this topic is to quickly and effectively integrate and dispatch resources through advanced communication technologies and coordination mechanisms to respond to accidents and recover from disasters. Using this method, relevant organizations can develop specific operational procedures and communication strategies to ensure effective information transmission and rescue operation initiation in the first time, minimize the impact of accidents, and protect the marine environment and public safety.

[0004] Traditional planning methods still have certain limitations in data management, security, and real-time performance. Current technologies generally lack sufficient data fusion processing capabilities, making it difficult to ensure data consistency and real-time updates in a multi-source data environment. Traditional methods have shortcomings in data security and privacy protection, especially in large-scale rescue operations involving cross-regional and multi-agency collaboration, where data is vulnerable to unauthorized access and tampering. Traditional methods fail to effectively integrate and dispatch resources, which usually leads to untimely deployment of rescue resources and inability to meet rapidly changing emergency response needs. This is particularly evident when dealing with large-scale natural disasters or man-made accidents, which can lead to delays in rescue operations, increase casualties and property losses, and affect the overall efficiency of disaster recovery. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and propose a blockchain-based marine emergency plan planning method and system.

[0006] In order to achieve the above purpose, the present invention adopts the following technical solution: a method for planning marine emergency plans based on blockchain, comprising the following steps:

[0007] S1: Based on the target ocean monitoring area, receive air pressure, temperature and wind speed data, collect water flow speed and direction data, extract the geographic location and heading data of the ship, align the data with the timestamp and perform data fusion processing to obtain the ocean environment status data set;

[0008] S2: Based on the marine environment status data set, the probability and potential impact of the disaster are evaluated, and compared with the preset risk threshold to determine whether there is an abnormal risk and obtain risk assessment information;

[0009] S3: Based on the risk assessment information, when an abnormal risk is detected, an early warning signal is automatically sent to the associated nodes through the network, and the data flow and bandwidth are dynamically adjusted. A fault recovery mechanism is adopted to automatically reconstruct the network path when a node fails, and an emergency notification result is obtained;

[0010] S4: Based on the emergency notification result, according to the availability of each emergency rescue vessel, the functional status of the life-saving equipment, the current risk disaster type and resource demand, resource matching and scheduling are performed to obtain a resource allocation log;

[0011] S5: Based on the resource allocation log, record the data of each rescue operation, encrypt the data and store it on the blockchain, optimize the traceability of the operation and data security, and obtain emergency plan record information.

[0012] As a further solution of the present invention, the marine environmental condition data set includes temperature, air pressure, wind speed, wind direction, current speed, current direction and ship position information; the risk assessment information includes disaster type, probability of occurrence, expected impact range and emergency response level; the emergency notification result includes warning time, warning level and target receiving group; the resource allocation log includes resource type, allocation target information and allocation time; the emergency plan record information includes rescue mission number, roles and responsibilities of personnel involved and resource usage list.

[0013] As a further solution of the present invention, based on the target ocean monitoring area, receiving air pressure, temperature and wind speed data, collecting water flow speed and direction data, extracting the geographic location and heading data of the ship, performing timestamp alignment and data fusion processing on the data, and obtaining the marine environment status data set are specifically as follows:

[0014] S101: Based on the target ocean monitoring area, receive real-time data on air pressure, temperature and wind speed, obtain data on water flow speed and direction from the ocean current monitoring station, collect the geographic location and heading information of the ship through the satellite navigation system, add a timestamp to each data point, and obtain the basic data set;

[0015] S102: Based on the basic data set, perform data format standardization and cleaning processing, including deleting damaged data records and correcting data with inconsistent formats, optimizing data quality, and performing consistency and integrity checks on the data to obtain a processed data set;

[0016] S103: Based on the processed data set, data fusion processing is performed to integrate multiple sources into the same time frame by aligning data timestamps to obtain a marine environment status data set.

[0017] As a further solution of the present invention, based on the marine environment status data set, the probability and potential impact of disaster occurrence are evaluated, and compared with the preset risk threshold to determine whether there is an abnormal risk. The steps of obtaining risk assessment information are specifically as follows:

[0018] S201: Based on the marine environment status data set, time series analysis is performed, the data set is divided into multiple time periods using time segmentation technology, the data pattern and trend in each time period are identified, and the change of the data pattern over time is analyzed to obtain the time-dependent analysis result;

[0019] S202: Based on the time-dependent analysis result, a risk assessment is performed, by comparing with a preset risk threshold, identifying abnormal data patterns, marking time periods and regions with high-risk events, and obtaining risk identification information;

[0020] S203: Based on the risk identification information, evaluate the probability and impact of disasters, analyze the probability of disaster occurrence and the expected impact range, and quantitatively evaluate the impact of disasters to obtain risk assessment information.

[0021] As a further solution of the present invention, the formula for quantitatively evaluating the impact of disasters is:

[0022]

[0023] Among them, R represents the disaster risk index, P represents the probability of a disaster, I represents the expected impact of the disaster, S represents the effectiveness of existing safety measures, C represents the coverage rate of safety measures, and D represents the dispersion of disaster-related data.

[0024] As a further solution of the present invention, based on the risk assessment information, when an abnormal risk is detected, an early warning signal is automatically sent to the associated node through the network, and the data flow and bandwidth are dynamically adjusted. A fault recovery mechanism is adopted to automatically reconstruct the network path when a node fails. The specific steps of obtaining the emergency notification result are:

[0025] S301: Based on the risk assessment information, an abnormal risk warning signal is sent to the associated nodes, and each node receives the alarm information in time to obtain a warning signal transmission record;

[0026] S302: Based on the early warning signal transmission record, the communication load and health status of each node are monitored in real time, the data flow and bandwidth allocation are adjusted, the efficiency and response speed of the network under high load conditions are optimized, and a network performance adjustment log is obtained;

[0027] S303: Based on the network performance adjustment log, evaluate the faulty nodes in the network, automatically start the fault recovery mechanism, reconstruct the network path, bypass the affected nodes, optimize the continuity and stability of communication, and obtain the emergency notification result.

[0028] As a further solution of the present invention, the formula for adjusting data flow and bandwidth allocation is:

[0029]

[0030] Among them, BW new BW is the adjusted bandwidth allocation value. old represents the original bandwidth of the current node, ΔL represents the load change from the previous measurement interval, and L max represents the maximum load capacity, H represents the health index of the current node, and H max Represents the maximum ideal value of the health index.

[0031] As a further solution of the present invention, based on the emergency notification result, according to the availability of each emergency rescue vessel, the functional status of the life-saving equipment, the current risk disaster type and resource demand, resource matching and scheduling are performed, and the steps of obtaining the resource allocation log are specifically as follows:

[0032] S401: Based on the emergency notification result, analyze the current position, operation status and life-saving equipment function status of each emergency rescue ship, evaluate the response capability and rescue preparation time of each ship, and obtain rescue ship status information;

[0033] S402: Based on the rescue vessel status information, according to the type and urgency of the current disaster, identify matching vessels and rescue teams, optimize resource allocation and time response, and obtain rescue resource scheduling information;

[0034] S403: Based on the rescue resource scheduling information, record the participants and the rescue equipment used in each rescue operation to obtain a resource allocation log.

[0035] As a further solution of the present invention, based on the resource allocation log, the data of each rescue operation is recorded, the data is encrypted and stored on the blockchain, the traceability of the operation and the data security are optimized, and the steps of obtaining the emergency plan record information are specifically as follows:

[0036] S501: Based on the resource allocation log, the time and location of each rescue operation are collected, and the identity authentication information of the participants and the specifications of the resources used are extracted to obtain a rescue operation record;

[0037] S502: Based on the rescue operation record, encrypt the data using a data encryption protocol to optimize the confidentiality and security of the information, and obtain encrypted rescue data;

[0038] S503: Based on the encrypted rescue data, data is stored and the encrypted data is uploaded to the blockchain platform to optimize the traceability and security of the data and obtain emergency plan record information.

[0039] A marine emergency plan planning system based on blockchain, the marine emergency plan planning system based on blockchain is used to execute the above-mentioned marine emergency plan planning method based on blockchain, and the system includes:

[0040] The ocean data collation module receives air pressure, temperature and wind speed data based on the target ocean monitoring area, collects water flow speed and direction data, extracts the geographic location and heading data of the ship, performs timestamp alignment and data fusion processing on the data, and obtains the ocean environment status data set;

[0041] The risk analysis module evaluates the probability and potential impact of disasters based on the marine environmental status data set, determines whether there are abnormal risks, and obtains risk assessment information;

[0042] Based on the risk assessment information, the emergency notification module sends an early warning signal to the associated nodes through the network when an abnormal risk is detected, and dynamically adjusts the data flow and bandwidth to optimize the network load balancing, and automatically reconstructs the network path when a node fails, optimizes the continuity and stability of communication, and obtains the emergency notification result;

[0043] The rescue resource scheduling module performs resource matching and scheduling based on the emergency notification result, the availability of each emergency rescue vessel, the functional status of the life-saving equipment, the current risk disaster type and resource demand, and obtains a resource allocation log;

[0044] The operation record archiving module records the data of each rescue operation based on the resource allocation log, encrypts the data and stores it on the blockchain, optimizes the traceability of the operation and data security, and obtains emergency plan record information.

[0045] Compared with the prior art, the advantages and positive effects of the present invention are:

[0046] In the present invention, by applying blockchain technology to marine emergency plan planning, the transparency and traceability of data are improved, data is collected from multiple sources and timestamp alignment and data fusion processing are performed to ensure the integrity and timeliness of the data, and the operation data is encrypted and stored in the blockchain to enhance data security and tamper-proof capabilities. The probability and potential impact of disasters are predicted through time series analysis, and compared with preset risk thresholds, abnormal risks are judged to provide decision makers with an intuitive data-based basis. Early warning signals are sent to associated nodes through the network, and the health status and communication load of each node in the network are monitored in real time, as well as the data flow and bandwidth are dynamically adjusted, thereby improving the response speed and efficiency of the network, ensuring that rescue resources can be deployed quickly and effectively in emergency situations, and minimizing the impact of accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0049] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0050] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0051] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0052] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0053] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0054] Figure 7 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0055] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0056] 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.

[0057] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0058] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0059] 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.

[0060] See also Figure 1 The present invention provides a technical solution: a method for planning marine emergency plans based on blockchain, comprising the following steps:

[0061] S1: Based on the target ocean monitoring area, it receives air pressure, temperature and wind speed data from meteorological satellites, collects water flow speed and direction data from ocean current monitoring stations, extracts the geographic location and heading data of the ship through satellite navigation, performs timestamp alignment and data fusion processing on the data, and obtains the ocean environment status data set;

[0062] S2: Based on the marine environmental status data set, the probability and potential impact of disasters are evaluated through time series analysis, and compared with the preset risk threshold to determine whether there is abnormal risk and obtain risk assessment information;

[0063] S3: Based on risk assessment information, when abnormal risks are detected, early warning signals are automatically sent to related nodes through the network. By real-time monitoring of the health status and communication load of each node in the network, data flow and bandwidth are dynamically adjusted to optimize network load balancing. A fault recovery mechanism is used to automatically reconstruct network paths when nodes fail, optimize the continuity and stability of communications, and obtain emergency notification results.

[0064] S4: Based on the emergency notification results, according to the availability of each emergency rescue vessel, the functional status of life-saving equipment, the current risk disaster type and resource requirements, resource matching and scheduling are carried out to obtain a resource allocation log;

[0065] S5: Based on the resource allocation log, the data of each rescue operation is recorded, including the time when the operation was initiated, the geographical coordinates of the emergency rescue location, the identity verification information of the participants, and the specifications of the resources used. The data is encrypted and stored on the blockchain to optimize the traceability of the operation and data security, and obtain the emergency plan record information.

[0066] The marine environment status data set includes temperature, air pressure, wind speed, wind direction, current speed, current direction and ship position information; risk assessment information includes disaster type, probability of occurrence, expected impact range and emergency response level; emergency notification results include warning time, warning level and target recipient group; resource allocation log includes resource type, allocation target information and allocation time; emergency plan record information includes rescue mission number, roles and responsibilities of personnel involved and resource usage list;

[0067] See also Figure 2 Based on the target ocean monitoring area, the air pressure, temperature and wind speed data from the meteorological satellite are received, and the water flow speed and direction data from the ocean current monitoring station are collected. The geographic location and heading data of the ship are extracted through satellite navigation, and the data are timestamped and fused. The specific steps to obtain the marine environment status data set are as follows:

[0068] S101: Based on the target ocean monitoring area, receive real-time data on air pressure, temperature and wind speed, obtain data on water flow speed and direction from the ocean current monitoring station, collect the geographic location and heading information of the ship through the satellite navigation system, add a timestamp to each data point, and obtain the basic data set;

[0069] Based on the marine environment monitoring needs of the target marine monitoring area, real-time data is received, involving the monitoring of air pressure, temperature and wind speed. The data is obtained through meteorological instruments installed at the monitoring station. For example, the barometer is used to measure the atmospheric pressure, the temperature sensor is used to record the water temperature and air temperature of the current sea area, and the anemometer is used to capture the wind speed and direction. During data collection, each data point must be timestamped to ensure the time accuracy of the data. The timestamp is automatically added through the system clock synchronized with the global time standard, providing an accurate time reference for subsequent data processing. The data also includes the water flow speed and direction obtained from the ocean current monitoring station, which is usually completed through a current meter installed on the seabed. It can measure the pressure changes caused by the water flow on the sensor to infer the water flow speed and direction. The satellite navigation system is used to collect the geographic location and heading information of the ship. Usually, this data is achieved through a global positioning system receiver installed on the ship.

[0070] S102: Based on the basic data set, perform data format standardization and cleaning, including deleting damaged data records and correcting inconsistent data formats, optimizing data quality, and performing consistency and integrity checks on the data to obtain a processed data set;

[0071] Based on the basic data set, format standardization involves unifying the data formats of various data sources for subsequent processing, such as unifying the timestamps into the international standard time format and the temperature data into degrees Celsius. The standardization process is executed on the data processing server by writing data processing scripts. Data cleaning includes deleting damaged data records and correcting data with inconsistent formats. For example, abnormal temperature records are automatically detected by algorithms and removed from the data set. At the same time, the integrity of the data is checked, such as ensuring that each data record has complete timestamp and geographic location information. While optimizing data quality, the data is checked for consistency and integrity to ensure that the data meets the predetermined quality standards before being uploaded to the database, thus obtaining the processed data set.

[0072] S103: Based on the processed data set, data fusion processing is performed to integrate multiple sources into the same time frame by aligning data timestamps to obtain a marine environment status data set;

[0073] Based on the processed data set, multi-source data are integrated into the same time frame. By aligning the data timestamps, the temporal consistency of data from different sources is ensured. For example, meteorological data, ocean current data, and ship position data are aligned according to the recorded timestamps. This is usually implemented in the database through programming. During the data fusion process, it is necessary to ensure that the errors of all data timestamps are within the allowable range. Through data fusion, a marine environmental status data set is obtained. This data set integrates information from different data sources and provides a comprehensive perspective for monitoring and analysis of the marine environment.

[0074] See also Figure 3 Based on the marine environment status dataset, the probability and potential impact of disasters are evaluated through time series analysis, and compared with the preset risk threshold to determine whether there is an abnormal risk. The specific steps for obtaining risk assessment information are as follows:

[0075] S201: Based on the marine environment status data set, time series analysis is performed. The data set is divided into multiple time periods using time segmentation technology. The data patterns and trends in each time period are identified. The changes in data patterns over time are analyzed to obtain time-dependent analysis results.

[0076] Based on the marine environmental status data set, the time segmentation technology is used to operate the marine environmental status data set, and the data set is divided into multiple time periods. Each time period contains a set of data points. Each data point includes information such as timestamp, location, air pressure, temperature, wind speed, water flow speed and direction. By clustering the data in each time period, the main meteorological and oceanic condition patterns in the time period can be identified. For example, the data points in the time period can be divided into several categories through the K-means clustering algorithm. Each category represents a specific environmental condition pattern. Through time series prediction models, such as the autoregressive moving average model, the changing trend of the pattern over time is analyzed, and the meteorological and oceanic conditions that may occur in a certain time period in the future are calculated, and finally the time-dependent analysis results are obtained.

[0077] S202: Based on the time-dependent analysis results, risk assessment is performed, by comparing with the preset risk threshold, identifying abnormal data patterns, marking time periods and areas with high-risk events, and obtaining risk identification information;

[0078] Based on the results of time-dependent analysis, it is necessary to set a preset risk threshold, which is determined based on historical data statistics and expert experience and represents the highest acceptable risk level. Data analysis tools are used to compare whether the data patterns identified in each time period exceed this threshold. In specific implementation, anomaly detection algorithms, such as isolation forests, can be used to identify patterns that are significantly different from most data, that is, abnormal data patterns, mark the time periods and regions where the patterns are located, calculate the anomaly score for each data point, and those with scores higher than a certain threshold are considered anomalies. All time periods and regions identified as high-risk are integrated to form risk identification information.

[0079] S203: Based on the risk identification information, evaluate the probability and impact of disasters, analyze the probability of disasters and the expected impact range, quantitatively evaluate the impact of disasters, and obtain risk assessment information;

[0080] The formula for quantitatively assessing the impact of disasters is:

[0081]

[0082] Among them, R represents the disaster risk index, P represents the probability of a disaster, I represents the expected impact of the disaster, S represents the effectiveness of existing safety measures, C represents the coverage rate of safety measures, and D represents the dispersion of disaster-related data.

[0083] The meaning and acquisition method of parameters:

[0084] P represents the probability of a disaster occurring, which is usually derived from historical disaster data through statistical analysis, taking into account the frequency of similar disasters occurring within a specific period of time.

[0085] I represents the expected impact of the disaster, which is quantified based on historical disaster impact data and expert assessments, such as economic losses, casualties, etc.

[0086] S represents the effectiveness of existing safety measures, which is evaluated through safety audits and effectiveness tests, and reflects the ability of safety measures to reduce the impact of disasters.

[0087] C represents the coverage rate of security measures, which is calculated based on the distribution of security facilities and the proportion of protected people or assets.

[0088] D represents the dispersion of disaster-related data, which is calculated from the standard deviation of disaster-related data and is used to assess the variability and uncertainty of the data.

[0089] Calculation example:

[0090] The following parameters are set: P = 0.20 (a probability of 20% indicates that such a disaster may occur within a given time frame), I = 70 (an impact level of 70 units, which may indicate the expected financial losses or casualties), S = 0.80 (an effectiveness of 80% safety measures indicates that current measures can reduce 80% of potential losses), C = 0.50 (a coverage rate of 50% indicates that safety measures cover half of the potentially affected areas or populations), and D = 16 (the dispersion is 16, which is the square of the standard deviation calculated from the relevant disaster data).

[0091] Calculation process:

[0092]

[0093] The calculation result R = 3.4 means that under the given safety measures and coverage, considering the probability and expected impact of disasters, the disaster risk assessment result of the area is 3.4. This value can be used to compare the risk levels in different regions or at different times, helping decision makers to develop more effective preventive measures or emergency response strategies. The lower value indicates that the current safety measures are effective, but we still need to be vigilant about potential high-impact disasters.

[0094] See also Figure 4 Based on the risk assessment information, when an abnormal risk is detected, an early warning signal is automatically sent to the associated nodes through the network, and the health status and communication load of each node in the network are monitored in real time to dynamically adjust the data flow and bandwidth, optimize the network load balancing, and adopt a fault recovery mechanism to automatically reconstruct the network path when a node fails, optimize the continuity and stability of communication, and obtain the emergency notification results. The specific steps are as follows:

[0095] S301: Based on the risk assessment information, an abnormal risk warning signal is sent to the associated nodes, and each node receives the alarm information in time to obtain a warning signal transmission record;

[0096] Based on the risk assessment information, according to the risk area, identify which related nodes need to receive alarms. The nodes include but are not limited to ocean monitoring stations, related ships and coastal base stations. The alarm signal is sent by the central monitoring platform and encrypted transmission is used to ensure information security. The receiving device of each node is set to automatically confirm receipt of the alarm and record the reception time and status. The records are stored in the central database to form early warning signal transmission records. The recorded data includes timestamp, node identification, alarm type and reception status.

[0097] S302: Based on the early warning signal transmission record, the communication load and health status of each node are monitored in real time, the data flow and bandwidth allocation are adjusted, the efficiency and response speed of the network under high load conditions are optimized, and a network performance adjustment log is obtained;

[0098] The formula for adjusting data flow and bandwidth allocation is:

[0099]

[0100] Among them, BW new BW is the adjusted bandwidth allocation value. old represents the original bandwidth of the current node, ΔL represents the load change compared with the previous measurement interval, and L max represents the maximum load capacity, H represents the health index of the current node, and H max Represents the maximum ideal value of the health index.

[0101] The meaning and acquisition method of parameters:

[0102] BW old : The original bandwidth of the current node, usually obtained directly from the network management system, which records the bandwidth configuration value of the node before any adjustment.

[0103] ΔL: The load change from the last measurement interval, which is calculated by comparing the current network load with the last recorded load data. The specific calculation method is to subtract the last recorded load value from the current load.

[0104] L max :The maximum data flow that can be carried. This value is usually determined by the design parameters of the network and can be obtained from the network configuration file or system specification document.

[0105] H: The health index of the current node, which is obtained by analyzing multiple indicators such as the node's error log, response time, and failure rate. A low health index indicates that the node may have performance degradation or may fail in the near future.

[0106] H max: The optimal health index of a node under ideal conditions. This is a theoretical value, usually set to 100%, indicating that the node is completely fault-free and operates optimally.

[0107] Calculation example:

[0108] Set the following parameters: BW old =100Mbps (megabits per second), ΔL = 10Mbps (the current load has increased by 10Mbps compared to the last time), L max =200Mbps (maximum node load capacity), H = 80 (current health index, which may be slightly reduced due to minor failures or response delays), H max =100 (ideal health index of the node).

[0109] Calculation process:

[0110]

[0111]

[0112] The results show that after taking into account the slight decline in node health and the increase in load, the ideal bandwidth of the node should be adjusted to 25Mbps to maintain network stability and responsiveness. This adjustment helps network administrators understand the actual operating bandwidth of the current node under non-ideal conditions, which is an important step in ensuring network quality and efficiency.

[0113] S303: Based on the network performance adjustment log, evaluate the faulty nodes in the network, automatically start the fault recovery mechanism, reconstruct the network path, bypass the affected nodes, optimize the continuity and stability of communication, and obtain the emergency notification result.

[0114] Based on the network performance adjustment log, nodes with abnormally increased communication delays or frequent data loss are identified. Once diagnosed as a faulty node, the fault recovery mechanism is immediately activated, including automatic rerouting of data streams to bypass affected nodes and reconstructing network paths within seconds to ensure the continuity and stability of communications. All operation processes and their results are recorded in the emergency notification results, including the time when the fault occurred, the affected nodes, the recovery measures taken, and the network status after recovery. This information is of great value for subsequent network maintenance and upgrades.

[0115] See also Figure 5 ,Based on the emergency notification results, according to the availability of each emergency rescue ship, the functional status of life-saving equipment, the current risk disaster type and resource requirements, resource matching and scheduling are carried out, and the steps to obtain the resource allocation log are as follows:

[0116] S401: Based on the emergency notification result, analyze the current position, operation status and life-saving equipment function status of each emergency rescue ship, evaluate the response capability and rescue preparation time of each ship, and obtain the rescue ship status information;

[0117] Based on the results of the emergency notification, the integrated ship monitoring data is used to regularly receive status information from each ship. This status information is sent through the satellite communication system, including GPS location data, engine operating parameters and test results of life-saving equipment. The data is analyzed and processed to evaluate the response capability of each ship, including the time required to arrive at the disaster site and the ability to prepare for rescue operations. The functional status of the life-saving equipment is checked through automatic diagnosis to ensure that all equipment can work properly in an emergency. For example, the launch mechanism of the lifeboat and the supply status of life jackets are checked and recorded. The information is summarized to form the rescue ship status information, which provides a basis for decision-making on subsequent rescue operations.

[0118] S402: Based on the rescue vessel status information, according to the type and urgency of the current disaster, identify matching vessels and rescue teams, optimize resource allocation and time response, and obtain rescue resource scheduling information;

[0119] Based on the rescue vessel status information, the most suitable vessel and rescue team are matched according to the type of current disaster such as tsunami, tanker leak or marine fire and the degree of urgency. Factors taken into consideration include the location, speed and type of rescue equipment of the vessel, as well as the professional skills and previous response performance of the rescue team. Resource allocation optimization aims to reduce response time and improve rescue efficiency. Methods to achieve this include adjusting vessel routes, reallocating rescue tasks and pre-deploying rescue equipment. Decisions will be recorded in the rescue resource scheduling information, which provides data support for real-time monitoring of rescue operations.

[0120] S403: Based on the rescue resource scheduling information, record the participants and the rescue equipment used in each rescue operation to obtain a resource allocation log.

[0121] Based on the rescue resource dispatch information, the use of rescue resources will be recorded in the resource allocation log before each rescue operation begins, including the list of personnel involved in the rescue, the rescue equipment used and the specific details of the operation. The data is automatically collected and updated by the rescue command center through the rescue operation management system. The use of rescue equipment includes the distribution of consumables such as medical kits, food and water, and the use of technical equipment such as diving equipment and fire fighting tools.

[0122] See also Figure 6,Based on the resource allocation log, the data of each rescue operation is recorded, including the time when the operation was initiated, the geographical coordinates of the emergency rescue location, the identity verification information of the participants and the specifications of the resources used. The data is encrypted and stored on the blockchain to optimize the traceability of the operation and data security. The specific steps to obtain the emergency plan record information are as follows:

[0123] S501: Based on the resource allocation log, the time and location of each rescue operation are collected, and the identity authentication information of the participants and the specifications of the resources used are extracted to obtain the rescue operation record;

[0124] Based on the resource allocation log, the specific information of each rescue operation is recorded. The information includes the time and location of the initiation of the rescue operation, which is automatically collected through the recording system of the on-site command center. The data of the operation time and location are synchronized through the GPS system and the rescue event log. The identity authentication information of the participants is obtained through the identity management data of the rescue team. Each participant must be identified through biometrics or digital ID to ensure that all operations are performed by authorized personnel. The specifications of the resources used, such as lifeboats, medical equipment and other rescue tools, are recorded by the resource management system, including model, quantity and functional status. The integrated processing of the data obtains the rescue operation record. The record is not only used to audit and evaluate the rescue effect, but also provides a basis for legal review or subsequent training.

[0125] S502: Based on the rescue operation record, encrypt the data using a data encryption protocol to optimize the confidentiality and security of the information, and obtain encrypted rescue data;

[0126] Based on the rescue operation records, encryption processing is performed to ensure the confidentiality and security of information. The data encryption protocols used include public key infrastructure and symmetric encryption technology to ensure the security of data during transmission and storage. The encryption operation is performed by a dedicated security management system to generate and manage encryption keys. At the same time, data access activities are monitored to ensure that only authorized users can access sensitive information. The encrypted rescue data is stored in a secure central database, and backup copies are stored in multiple geographically dispersed locations to prevent data loss or destruction. The encryption and data processing processes strictly follow international security standards and regulatory requirements to maximize the protection of data confidentiality and integrity.

[0127] S503: Based on the encrypted rescue data, data is stored and the encrypted data is uploaded to the blockchain platform to optimize the traceability and security of the data and obtain emergency plan record information.

[0128] Based on the encrypted rescue data, the encrypted rescue data is then uploaded to the blockchain platform, using the immutable and distributed characteristics of blockchain technology to improve data traceability and security. Each rescue data is regarded as an independent transaction record on the blockchain, including the time, location, participants and resource usage of the data. The blockchain's consensus mechanism ensures that all records are verified by network nodes and added to the blockchain. Once the record is added, it cannot be changed or deleted, enhancing the trust and transparency of the record. The data on the blockchain can be used to audit the compliance of rescue activities, evaluate the efficiency of the use of rescue resources, and serve as a reference for improving rescue strategies in the future. The information ultimately forms emergency plan record information, providing strong information support and decision-making basis for rescue operations and resource management.

[0129] See also Figure 7 , A marine emergency plan planning system based on blockchain, a marine emergency plan planning system based on blockchain is used to execute the above-mentioned marine emergency plan planning method based on blockchain, and the system includes:

[0130] The ocean data collation module receives air pressure, temperature and wind speed data based on the target ocean monitoring area, collects water flow speed and direction data, extracts the geographic location and heading data of the ship, performs timestamp alignment and data fusion processing on the data, and obtains the ocean environment status data set;

[0131] The risk analysis module evaluates the probability and potential impact of disasters based on the marine environmental status data set, determines whether there are abnormal risks, and obtains risk assessment information;

[0132] Based on the risk assessment information, the emergency notification module sends warning signals to related nodes through the network when abnormal risks are detected, and dynamically adjusts the data flow and bandwidth to optimize network load balancing. It also automatically reconstructs the network path when a node fails, optimizes the continuity and stability of communication, and obtains emergency notification results.

[0133] The rescue resource scheduling module matches and schedules resources based on the emergency notification results, the availability of each emergency rescue vessel, the functional status of life-saving equipment, the current risk disaster type and resource requirements, and obtains a resource allocation log;

[0134] The operation record archiving module records the data of each rescue operation based on the resource allocation log, encrypts the data and stores it on the blockchain, optimizes the traceability of the operation and data security, and obtains emergency plan record information.

[0135] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0136] In the present invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0137] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0138] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0139] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0140] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, 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 devices or units, which can be electrical, mechanical or other forms.

[0141] 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 on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0142] In addition, each functional unit in each embodiment of the present invention 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.

[0143] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0144] 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 method for planning marine emergency plans based on blockchain, characterized in that: The following steps are involved: S1: Based on the target ocean monitoring area, receive air pressure, temperature and wind speed data, collect water flow speed and direction data, extract the geographic location and heading data of the ship, align the data with the timestamp and perform data fusion processing to obtain the ocean environment status data set; S2: Based on the marine environment status data set, the probability and potential impact of the disaster are evaluated, and compared with the preset risk threshold to determine whether there is an abnormal risk and obtain risk assessment information; S3: Based on the risk assessment information, when an abnormal risk is detected, an early warning signal is automatically sent to the associated nodes through the network, and the data flow and bandwidth are dynamically adjusted. A fault recovery mechanism is adopted to automatically reconstruct the network path when a node fails, and an emergency notification result is obtained; S4: Based on the emergency notification result, according to the availability of each emergency rescue vessel, the functional status of the life-saving equipment, the current risk disaster type and resource demand, resource matching and scheduling are performed to obtain a resource allocation log; S5: Based on the resource allocation log, record the data of each rescue operation, encrypt the data and store it on the blockchain, optimize the traceability of the operation and data security, and obtain emergency plan record information.

2. The method for planning marine emergency plans based on blockchain according to claim 1 is characterized in that: The marine environment status data set includes temperature, air pressure, wind speed, wind direction, current speed, current direction and ship position information; the risk assessment information includes disaster type, probability of occurrence, expected impact range and emergency response level; the emergency notification results include warning time, warning level and target receiving group; the resource allocation log includes resource type, allocation target information and allocation time; the emergency plan record information includes rescue mission number, roles and responsibilities of the personnel involved and resource usage list.

3. The method for planning marine emergency plans based on blockchain according to claim 1 is characterized in that: Based on the target ocean monitoring area, the air pressure, temperature and wind speed data are received, and the water flow speed and direction data are collected. The geographic location and heading data of the ship are extracted, and the data are timestamped and fused. The specific steps to obtain the ocean environment status data set are as follows: S101: Based on the target ocean monitoring area, receive real-time data on air pressure, temperature and wind speed, obtain data on water flow speed and direction from the ocean current monitoring station, collect the geographic location and heading information of the ship through the satellite navigation system, add a timestamp to each data point, and obtain the basic data set; S102: Based on the basic data set, perform data format standardization and cleaning processing, including deleting damaged data records and correcting data with inconsistent formats, optimizing data quality, and performing consistency and integrity checks on the data to obtain a processed data set; S103: Based on the processed data set, data fusion processing is performed to integrate multiple sources into the same time frame by aligning data timestamps to obtain a marine environment status data set.

4. The method for planning marine emergency plans based on blockchain according to claim 1 is characterized in that: Based on the marine environment status data set, the probability and potential impact of disasters are assessed, and compared with the preset risk threshold to determine whether there is an abnormal risk. The steps for obtaining risk assessment information are as follows: S201: Based on the marine environment status data set, time series analysis is performed, the data set is divided into multiple time periods using time segmentation technology, the data pattern and trend in each time period are identified, and the change of the data pattern over time is analyzed to obtain the time-dependent analysis result; S202: Based on the time-dependent analysis result, a risk assessment is performed, by comparing with a preset risk threshold, identifying abnormal data patterns, marking time periods and regions with high-risk events, and obtaining risk identification information; S203: Based on the risk identification information, evaluate the probability and impact of disasters, analyze the probability of disaster occurrence and the expected impact range, and quantitatively evaluate the impact of disasters to obtain risk assessment information.

5. The method for planning marine emergency plans based on blockchain according to claim 4 is characterized in that: The formula for quantitatively assessing the impact of disasters is: Among them, R represents the disaster risk index, P represents the probability of a disaster, I represents the expected impact of the disaster, S represents the effectiveness of existing safety measures, C represents the coverage rate of safety measures, and D represents the dispersion of disaster-related data.

6. The method for planning marine emergency plans based on blockchain according to claim 1 is characterized in that: Based on the risk assessment information, when an abnormal risk is detected, an early warning signal is automatically sent to the associated node through the network, and the data flow and bandwidth are dynamically adjusted. A fault recovery mechanism is adopted to automatically reconstruct the network path when a node fails. The specific steps for obtaining the emergency notification result are: S301: Based on the risk assessment information, an abnormal risk warning signal is sent to the associated nodes, and each node receives the alarm information in time to obtain a warning signal transmission record; S302: Based on the early warning signal transmission record, the communication load and health status of each node are monitored in real time, the data flow and bandwidth allocation are adjusted, the efficiency and response speed of the network under high load conditions are optimized, and a network performance adjustment log is obtained; S303: Based on the network performance adjustment log, evaluate the faulty nodes in the network, automatically start the fault recovery mechanism, reconstruct the network path, bypass the affected nodes, optimize the continuity and stability of communication, and obtain the emergency notification result.

7. The method for planning marine emergency plans based on blockchain according to claim 6 is characterized in that: The formula for adjusting data flow and bandwidth allocation is: Among them, BW new BW is the adjusted bandwidth allocation value. old represents the original bandwidth of the current node, ΔL represents the load change from the previous measurement interval, and L max represents the maximum load capacity, H represents the health index of the current node, and H max Represents the maximum ideal value of the health index.

8. The method for planning marine emergency plans based on blockchain according to claim 1 is characterized in that: Based on the emergency notification result, according to the availability of each emergency rescue vessel, the functional status of the life-saving equipment, the current risk disaster type and resource demand, the steps of matching and scheduling resources to obtain the resource allocation log are as follows: S401: Based on the emergency notification result, analyze the current position, operation status and life-saving equipment function status of each emergency rescue ship, evaluate the response capability and rescue preparation time of each ship, and obtain rescue ship status information; S402: Based on the rescue vessel status information, according to the type and urgency of the current disaster, identify matching vessels and rescue teams, optimize resource allocation and time response, and obtain rescue resource scheduling information; S403: Based on the rescue resource scheduling information, record the participants and the rescue equipment used in each rescue operation to obtain a resource allocation log.

9. The method for planning marine emergency plans based on blockchain according to claim 1 is characterized in that: Based on the resource allocation log, the data of each rescue operation is recorded, the data is encrypted and stored on the blockchain, the traceability of the operation and data security are optimized, and the steps for obtaining the emergency plan record information are as follows: S501: Based on the resource allocation log, the time and location of each rescue operation are collected, and the identity authentication information of the participants and the specifications of the resources used are extracted to obtain a rescue operation record; S502: Based on the rescue operation record, encrypt the data using a data encryption protocol to optimize the confidentiality and security of the information, and obtain encrypted rescue data; S503: Based on the encrypted rescue data, data is stored and the encrypted data is uploaded to the blockchain platform to optimize the traceability and security of the data and obtain emergency plan record information.

10. The marine emergency plan planning system based on blockchain is characterized by: According to the method for planning marine emergency plans based on blockchain according to any one of claims 1 to 9, the system comprises: The ocean data sorting module receives air pressure, temperature and wind speed data based on the target ocean monitoring area, collects water flow speed and direction data, extracts the geographic location and heading data of the ship, performs timestamp alignment and data fusion processing on the data, and obtains the ocean environment status data set; The risk analysis module evaluates the probability and potential impact of disasters based on the marine environmental status data set, determines whether there are abnormal risks, and obtains risk assessment information; Based on the risk assessment information, the emergency notification module sends an early warning signal to the associated nodes through the network when an abnormal risk is detected, and dynamically adjusts the data flow and bandwidth to optimize the network load balancing, and automatically reconstructs the network path when a node fails, optimizes the continuity and stability of communication, and obtains the emergency notification result; The rescue resource scheduling module performs resource matching and scheduling based on the emergency notification result, the availability of each emergency rescue vessel, the functional status of the life-saving equipment, the current risk disaster type and resource demand, and obtains a resource allocation log; The operation record archiving module records the data of each rescue operation based on the resource allocation log, encrypts the data and stores it on the blockchain, optimizes the traceability of the operation and data security, and obtains emergency plan record information.

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