Safety management method and system for offshore operation personnel

Abstract

The invention discloses an offshore operation personnel safety management method and system, and the method comprises the steps: generating a positioning code containing positioning information for a preset position in an offshore operation scene, enabling an offshore operation personnel to use a mobile terminal to scan the positioning code of each preset position, and recording the position change of the offshore operation personnel in the whole offshore operation process in detail. And the cloud management platform receives the scanning record of the offshore operation personnel sent by the mobile terminal, analyzes the dynamic change of the offshore operation personnel in real time through the scanning record, and determines a movement track diagram. Meanwhile, the cloud management platform accurately predicts potential dangers in the offshore operation process according to the environment monitoring data, and immediately generates abnormal information and early warning information when the abnormity of the offshore operation personnel is detected through the movement track diagram and the existence of the potential dangers is monitored according to the environment monitoring data; and related personnel and management departments are notified in various modes, so that the safety of the offshore operation personnel is effectively protected.

Description

Technical Field

[0001] The present application relates to the technical field of safety management, and in particular to a method and system for safety management of offshore workers. Background Art

[0002] The safety management of offshore workers has attracted widespread attention. With the rapid development of offshore wind power and other marine projects, higher requirements have been placed on the safety management of seafarers. Traditional safety management methods, such as manual records and post-analysis, can no longer meet the real-time and accurate requirements of modern marine engineering for personnel safety monitoring.

[0003] Some related methods for the safety management of offshore workers rely on physical sign-in systems, such as using magnetic cards and IC cards as a medium for identity recognition. This method requires personnel to go to a designated location to punch in when going out to sea and returning to land, and record the time of going out to sea and returning to land. However, this method has problems such as poor real-time performance, incomplete data recording, and easy forgery, and cannot accurately reflect the real-time location and dynamic changes of offshore workers.

[0004] In other related methods of marine personnel safety management, GPS positioning or other wireless communication technologies are used to track and monitor the location of personnel. However, these technologies have certain limitations in practical applications, such as limited signal coverage, low positioning accuracy, and expensive equipment costs.

[0005] In addition, relevant technologies rely on manual review and judgment and lack intelligent analysis and early warning functions, making it difficult to detect potential safety hazards and risks in a timely manner and unable to respond quickly. Summary of the invention

[0006] In view of this, the present application provides a method and system for the safety management of offshore workers. The cloud management platform receives and analyzes the scanning records of offshore workers sent by mobile terminals. When abnormalities of offshore workers and potential dangerous situations are detected, relevant personnel and management departments are immediately notified in various ways to effectively protect the safety of offshore workers.

[0007] According to one aspect of the present application, a method for safety management of offshore workers is provided, which is applied to a cloud management platform, and the cloud management platform can be communicatively connected with a mobile terminal, and the method includes: receiving an encrypted scanning record sent by the mobile terminal; decrypting the scanning record, and determining a movement trajectory map of the offshore worker corresponding to the user information in the scanning record based on the decrypted scanning record; determining abnormal information of the offshore worker based on the movement trajectory map; obtaining environmental monitoring data fed back by the offshore worker, inputting the environmental monitoring data into a risk prediction model, and determining early warning information of the environment in which the offshore worker is located, wherein the risk prediction model is trained based on historical environmental monitoring data, and the environmental monitoring data at least includes meteorological data and sea traffic data; displaying the abnormal information or the early warning information, and sending the abnormal information or the early warning information to a terminal associated with the offshore worker corresponding to the abnormal information or the early warning information.

[0008] According to another aspect of the present application, a method for safety management of offshore workers is provided, which is applied to a mobile terminal, and the method includes: scanning a positioning code located at a preset position to identify the positioning information in the positioning code, and recording the scanning time and the user information of the mobile terminal logged in during the scanning; determining the scanning record according to the scanning time, the positioning information and the user information; encrypting the scanning record, and sending the encrypted scanning record to a cloud management platform, so that the cloud management platform determines the abnormal information or warning information of the offshore worker corresponding to the user information in the scanning record according to the scanning record, displays the abnormal information or the warning information, and sends the abnormal information or the warning information to a terminal associated with the offshore worker corresponding to the abnormal information or the warning information.

[0009] According to another aspect of the present application, a safety management system for offshore workers is provided, including: a cloud management platform for receiving the encrypted scan record sent by the mobile terminal; decrypting the scan record, and determining a movement trajectory map of the offshore worker corresponding to the user information in the scan record based on the decrypted scan record; determining abnormal information of the offshore worker based on the movement trajectory map; obtaining environmental monitoring data fed back by the offshore worker, inputting the environmental monitoring data into a risk prediction model, and determining early warning information of the environment in which the offshore worker is located, wherein the risk prediction model is trained based on historical environmental monitoring data, and the monitoring data at least includes meteorological data and sea traffic data; displaying the abnormal information or the early warning information, and displaying the abnormal information or the early warning information. The warning information is sent to the terminal associated with the offshore operator corresponding to the abnormal information or the warning information; the mobile terminal is used to scan the positioning code located at a preset position to identify the positioning information in the positioning code, and record the scanning time and the user information logged in to the mobile terminal when scanning; determine the scanning record according to the scanning time, the positioning information and the user information; encrypt the scanning record, and send the encrypted scanning record to the cloud management platform, so that the cloud management platform determines the abnormal information or the warning information of the offshore operator corresponding to the user information in the scanning record according to the scanning record, displays the abnormal information or the warning information, and sends the abnormal information or the warning information to the terminal associated with the offshore operator corresponding to the abnormal information or the warning information.

[0010] By means of the above technical scheme, the present application provides a method and system for the safety management of sea workers, which generates a positioning code containing positioning information for a preset position in a sea operation scene, so that sea workers can use a mobile terminal to scan the positioning code of each preset position, and record in detail the position changes of sea workers during the entire sea operation process. The cloud management platform receives the scanning records of sea workers sent by the mobile terminal, and analyzes the dynamic changes of sea workers in real time through the scanning records to determine the movement trajectory map. At the same time, the cloud management platform accurately predicts the potential dangers in the sea operation process based on environmental monitoring data. When abnormalities of sea workers are detected through the movement trajectory map, and potential dangers are detected based on environmental monitoring data, abnormal information and early warning information are immediately generated, and relevant personnel and management departments are notified in various ways, which helps managers to make decisions quickly and take corresponding preventive measures to effectively protect the safety of sea workers.

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0013] Figure 1 A schematic diagram of a process flow of a method for safety management of offshore workers provided in an embodiment of the present application is shown;

[0014] Figure 2 A structural block diagram of a safety management system for offshore workers provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0015] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0016] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be interpreted as limiting the present application.

[0017] Those skilled in the art will appreciate that, unless expressly stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, or there may be intermediate elements. In addition, the "connection" or "connection" used herein may include wireless connection or wireless fusion. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0018] Now, exemplary embodiments according to the present application will be described in more detail with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in a variety of different forms and should not be interpreted as being limited to the embodiments set forth herein. It should be understood that these embodiments are provided to make the disclosure of the present application thorough and complete, and to fully convey the concepts of these exemplary embodiments to those of ordinary skill in the art.

[0019] The safety management of offshore workers has attracted widespread attention. With the rapid development of offshore wind power and other marine projects, higher requirements have been placed on the safety management of seafarers. Traditional safety management methods, such as manual records and post-analysis, can no longer meet the real-time and accurate requirements of modern marine engineering for personnel safety monitoring.

[0020] Traditional safety management of seafarers relies on physical sign-in and punch-in systems, such as using magnetic cards and IC cards as media for identity identification. This method requires personnel to punch in at designated locations when going out to sea and returning to land, and record the time of going out to sea and returning to land. However, this method has problems such as poor real-time performance, incomplete data recording, and easy forgery, and cannot accurately reflect the real-time location and dynamic changes of seafarers. For example, the sign-in and punch-in system can usually only record the entry and exit time of personnel, but cannot record in detail the key information such as the position changes, work content, and work environment of personnel during the entire sea operation process. In some personnel safety management methods based on information technology, RFID technology, GPS positioning or other wireless communication technologies are usually used to track and monitor the location of personnel. However, these technologies have certain limitations in practical applications, such as limited signal coverage, low positioning accuracy, and expensive equipment costs. For example, some systems use RFID (radio frequency identification) technology to track the location of seafarers, but these systems usually have the following shortcomings: the cost of RFID tags and readers is high, and corresponding hardware facilities need to be deployed at each operation point. RFID technology is easily interfered by environmental factors such as seawater and metal, which affects the stability and accuracy of the signal. RFID technology may cause operators to worry about privacy violations, especially without clear notification and consent. In addition, GPS positioning systems and RFID technology require personnel to carry additional equipment, which not only increases the workload, but may also affect the accuracy and completeness of data records due to equipment failure, loss or power exhaustion. At the same time, the lack of effective data sharing and intercommunication mechanisms between different systems or platforms has led to serious data island phenomena. This makes it difficult for managers to fully and accurately grasp the overall situation of offshore operators, affecting the scientificity and effectiveness of safety management decisions.

[0021] like Figure 1As shown, in this embodiment, a method for safety management of offshore workers is provided, which can be applied to a cloud management platform and a mobile terminal, wherein the cloud management platform can be connected to the mobile terminal for communication. This embodiment is described by taking the method applied to the cloud management platform and the mobile terminal as an example, and the method includes:

[0022] Step 101: The mobile terminal scans a positioning code at a preset position to identify positioning information in the positioning code, and records the scanning time and the user information of the mobile terminal logged in during the scanning.

[0023] Step 102: The mobile terminal determines the scanning record according to the scanning time, positioning information and user information.

[0024] Step 103: The mobile terminal encrypts the scan record and sends the encrypted scan record to the cloud management platform.

[0025] In this embodiment, a unique QR code containing positioning information, safety instructions and other data is generated in advance for key locations in the offshore operation scene, and the QR code is used as the positioning code of the key location, so that when offshore workers move to these locations, they can use the mobile terminal they carry with them to scan the positioning code, and send the scanning record to the cloud management platform through the mobile terminal, so that the cloud management platform can realize actual monitoring of personnel activities based on the scanning record, thereby improving the reliability of safety management.

[0026] For example, the key positions can be determined according to the characteristics of the actual offshore operation scene, for example, the positioning code can be deployed at prominent locations such as ship entrances and exits, booster station entrances, docks and construction platforms. Furthermore, offshore workers do not need to be equipped with additional equipment, and can use their own mobile terminals with QR code scanning functions, such as smart phones, to reduce the workload and enterprise costs, and improve the popularity and ease of use of safety management. At the same time, offshore workers log in to their exclusive user information in the mobile terminal, and scan the positioning code at the key position when moving to the key position, so that the mobile terminal can identify the positioning information in the positioning code. The mobile terminal records the time of each scan and the user information logged in at each scan, and uses the positioning information, scanning time and user information identified by each scan as a scan record, and uses encryption technology to ensure the security and uniqueness of the scan record, so that the encrypted scan record is sent to the cloud management platform, so that the cloud management platform can monitor the offshore workers in real time according to the scan record to ensure the safety of the offshore workers.

[0027] Among them, real-time data transmission between mobile scanning terminals and cloud servers is achieved through modern communication technologies (such as 4G / 5G, WiFi, etc.), ensuring that the dynamic location and time information of offshore workers can be uploaded to the cloud management platform in real time, which is convenient for managers to monitor in real time.

[0028] In this embodiment, through the QR code scanning technology, the key data such as the identity information, time of going to sea and returning to land, and location changes of the offshore workers are fully recorded, providing rich data support for safety management, so that managers can have a more comprehensive understanding of the offshore operations. In addition, the positioning information in the scanned record is carefully encoded and encrypted, with high accuracy and reliability. Compared with other positioning methods, it may be affected by factors such as signal interference and error accumulation, resulting in inaccurate location information. The scanning record of the QR code can serve as strong evidence that the offshore workers have arrived at a specific location, improving the credibility of the data.

[0029] It is worth mentioning that the mobile terminal has an offline scanning function, which can ensure that data can be recorded even without a network, and automatically synchronized to the cloud management platform after the network is restored. In addition, the mobile terminal supports offline data caching and breakpoint resume functions to ensure the timeliness and reliability of data.

[0030] Step 104: the cloud management platform receives the encrypted scanning record sent by the mobile terminal.

[0031] Step 105 , the cloud management platform decrypts the scan record, and determines the movement trajectory of the offshore operator corresponding to the user information in the scan record based on the decrypted scan record.

[0032] In this embodiment, the cloud management platform performs real-time analysis of the movement trajectory of offshore workers based on the received scanning records, accurately analyzes the dynamic changes in the positions of offshore workers during sea operations, and provides data support for subsequent safety management.

[0033] Further, as a refinement and extension of the specific implementation methods of the above-mentioned embodiment, in order to fully illustrate the specific implementation process of this embodiment, the step of determining the movement trajectory map of the offshore workers corresponding to the user information in the scanning record based on the decrypted scanning record specifically includes: determining the scanning record whose positioning information in the decrypted scanning record conforms to the preset sea position as the starting record; determining the user information in the starting record as the target user information, and determining the scanning record associated with the target user information as the monitoring record; using geographic information system technology to determine the positioning point corresponding to the positioning information in the monitoring record on the preset map; in the preset map, connecting the positioning points according to the scanning time of the positioning information in the monitoring record, and determining the movement trajectory map of the target worker, wherein the target worker is the offshore worker corresponding to the target user information; and displaying the movement trajectory map.

[0034] In this embodiment, the cloud management platform receives the encrypted scan records from the mobile terminal, decrypts the scan records, and cleans, verifies and integrates the decrypted scan records to reduce data redundancy and improve data consistency. Furthermore, the cloud management platform associates different scan records of the same person based on the user information in the pre-processed scan records, draws the movement trajectory map of different offshore workers, thereby achieving real-time monitoring of multiple different offshore workers, meeting the diversity of offshore operations, and improving the comprehensiveness of safety management.

[0035] Exemplarily, for any scanning record associated with user information, the cloud management platform detects whether there is positioning information that meets the preset sea position. If so, it means that the sea workers corresponding to the user information have started to work at sea. The scanning record whose positioning information meets the preset sea position is determined as the starting record, and the user information is determined as the target user information. The scanning record associated with the target user information is determined as the monitoring record, so that the sea workers can be continuously detected through the monitoring records.

[0036] Furthermore, using Geographic Information System (GIS) technology, the positioning information in the monitoring records is mapped onto a preset map to determine the positioning points corresponding to each positioning information. And according to the scanning time of the positioning information in the monitoring records, each positioning point is connected in chronological order to form a movement trajectory map, which is then visualized.

[0037] It is worth mentioning that the corresponding time information can be marked on or next to the movement trajectory map so that managers can intuitively understand the location of offshore workers at different time points.

[0038] In one embodiment, the offshore worker safety management method further includes: a cloud management platform determines the target worker's time to go to sea based on the scanning time in the start record and the current time; if the time to go to sea is greater than the preset time, the cloud management platform determines the target worker's timeout information based on the time to go to sea greater than the preset time; the cloud management platform displays the timeout information and sends the timeout information to a terminal associated with the target worker.

[0039] In this embodiment, the cloud management platform automatically identifies abnormal behavior of offshore workers, such as failure to return to land after the time limit, by analyzing the scanning records of offshore workers, and promptly sends the detected timeout information to the terminal associated with the overdue offshore workers through various means (such as SMS, email, APP push, etc.), so that relevant personnel and management departments can take corresponding measures in a timely manner.

[0040] Exemplarily, the cloud management platform determines the time for the target operator to go to sea in the monitoring record based on the difference between the scanning time in the start record and the current time. If the time to go to sea is greater than the preset prescribed time, the cloud management platform immediately generates timeout information, for example, calculates the specific duration of the timeout, or, based on the duration of the timeout, constructs detailed timeout information, such as the number of hours and minutes of the timeout. The timeout information is thus generated in an appropriate format (such as text, warning or notification) and displayed in the cloud management platform. The cloud management platform sends the timeout information to the terminal of the target operator in a variety of ways to ensure timely reminders, so as to accurately track and remind the operator of the timeout situation and enhance the safety management effect.

[0041] If the time of going out to sea is less than or equal to the preset time, the cloud management platform will detect whether there is positioning information that meets the preset return location in the monitoring record to determine whether the target operator has returned to land. If the time of going out to sea is less than or equal to the preset time, and there is positioning information that meets the preset return location in the monitoring record, the cloud management platform will determine the scanning record whose positioning information in the monitoring record meets the preset return location as the end record, and determine the time of going out to sea of ​​the target operator based on the scanning time in the end record and the start record, and end the monitoring of the target operator at the same time.

[0042] Step 106, the cloud management platform determines abnormal information of the offshore workers based on the movement trajectory map.

[0043] Step 107: The cloud management platform displays the abnormal information and sends the abnormal information to the terminal associated with the offshore operator corresponding to the abnormal information.

[0044] In this embodiment, the cloud management platform reduces the workload of manual monitoring and improves the response speed and accuracy of security management through automated detection and push of abnormal information.

[0045] Furthermore, as a refinement and expansion of the specific implementation methods of the above-mentioned embodiment, in order to fully illustrate the specific implementation process of this embodiment, the steps of determining the abnormal information of the offshore workers according to the movement trajectory map specifically include: determining the movement speed and activity range of the offshore workers according to the movement trajectory map; obtaining the sea going plan information of the offshore workers; if the movement speed or activity range does not meet the preset conditions in the sea going plan information, determining the abnormal information according to the movement speed or activity range that does not meet the sea going plan information.

[0046] In this embodiment, the cloud management platform analyzes the activity range and movement patterns of offshore workers by drawing a mobile trajectory map, thereby evaluating whether the offshore workers have followed the established work plans and safety regulations, and immediately triggers an alarm when abnormal behavior is detected to remind managers to pay attention and take corresponding measures.

[0047] Further, as a refinement and expansion of the specific implementation methods of the above-mentioned embodiment, in order to fully illustrate the specific implementation process of this embodiment, the steps of determining the moving speed of the offshore workers according to the moving trajectory map specifically include: converting the positioning information corresponding to the adjacent points in the moving trajectory map into radians, and determining the radian information of the adjacent points; determining the first radian difference and the second radian difference between the adjacent points according to the radian information; determining the actual distance between the adjacent points according to the first radian difference, the second radian difference and the preset earth radius; determining the time interval between the adjacent points according to the scanning time corresponding to the adjacent points; and determining the moving speed of the offshore workers according to the actual distance and the time interval.

[0048] The moving trajectory diagram includes positioning points and scanning times corresponding to the positioning points. The positioning points are determined according to the positioning information in the scanning record, and the adjacent points are positioning points corresponding to adjacent scanning times.

[0049] In this embodiment, based on the time series analysis method and combined with the geographical characteristics that the earth is an irregular sphere or ellipsoid, the geographic distance calculation formula (Haversine formula) is used to more accurately calculate the actual spherical distance between adjacent points in the movement trajectory diagram, thereby calculating a more accurate movement speed based on the actual distance.

[0050] For example, taking two adjacent positioning points in scanning time as adjacent points, the longitude and latitude of the two adjacent points can be obtained through the positioning information of the adjacent points in the moving trajectory diagram, and the longitude and latitude of the two adjacent points can be converted into radians to meet the calculation requirements of trigonometric functions in the geographic distance calculation formula.

[0051] Furthermore, the actual distance d between adjacent points is calculated according to the following formula:

[0052]

[0053] in, are the radians converted from the latitudes of two adjacent points, is the difference between the latitudes of two adjacent points converted into radians, Δλ is the difference between the longitudes of two adjacent points converted into radians, and R is the radius of the earth, which can be taken as an average of approximately 6371 kilometers.

[0054] Therefore, the moving speed of the offshore workers can be calculated based on the actual distance and the interval between the scanning times of adjacent points.

[0055] It is worth mentioning that the movement speed of offshore workers can be statistically analyzed, such as calculating the average speed, maximum speed, standard deviation of speed, etc. The calculated movement speed or a quantity related to the movement speed is compared with the established allowable speed range. If it exceeds the allowable range, it is marked as abnormal behavior.

[0056] Further, as a refinement and extension of the specific implementation method of the above embodiment, in order to fully illustrate the specific implementation process of this embodiment, the activity range of the offshore workers is determined according to the mobile trajectory map, specifically including: obtaining the distance threshold and the minimum number of samples of the positioning point; determining the neighborhood of the positioning point with the positioning point as the center and the distance threshold as the radius; marking the positioning point as an unvisited state; determining the positioning point whose number of positioning points in the neighborhood is greater than or equal to the minimum number of samples as a core point; randomly determining an unvisited positioning point as a target point; if the target point is a core point, marking all positioning points in the neighborhood of the target point as visited, and creating a new cluster, and adding all positioning points in the neighborhood of the target point to the cluster; if the target point is a core point and the number of positioning points in the neighborhood of the target point is greater than or equal to the minimum number of samples, then the positioning point is marked as a core point; If there are core points other than the target point, the core points other than the target point in the neighborhood of the target point are determined as extension points, and the neighborhood of the target point is updated according to the neighborhood of the extension point, and all the positioning points in the neighborhood of the extension point are added to the cluster until there are no extension points in the neighborhood of the target point, and a positioning point in an unvisited state is randomly determined as the target point; the positioning points belonging to multiple clusters are determined as merged points, and the multiple clusters to which the merged points belong are merged into one cluster; if the target point is not a core point, the target point is marked as visited, and a positioning point in an unvisited state is randomly re-determined as the target point until there are no positioning points in an unvisited state; if there are no positioning points in an unvisited state, the activity range of the offshore workers is determined according to the clusters.

[0057] The moving trajectory diagram includes positioning points and scanning times corresponding to the positioning points, and the positioning points are determined according to the positioning information in the scanning record.

[0058] In this embodiment, the clustering algorithm DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is used to cluster the various positioning points in the movement trajectory map, and the density of the positioning points is used to determine which positioning points belong to the same cluster, and to identify noise points. Therefore, regardless of the number of clusters preset, the positioning points within a certain distance range are classified into one cluster, and the clustering results can be used to obtain the activity range with irregular shapes and different densities, which is in line with the actual working scenarios of seafarers.

[0059] Specifically, the core idea of ​​this embodiment is "extension", that is, starting from a core point, the range of the cluster is continuously expanded in a density-reachable manner. Specifically, first select an unvisited point p. If the point is a core point (that is, there are enough points in its neighborhood), create a new cluster C and add the points in its neighborhood to cluster C. Then, traverse all the positioning points in cluster C. For each positioning point q in cluster C, if q is also a core point, the points in the neighborhood of q are also added to cluster C, and so on, until cluster C is no longer expanded. Next, the next unvisited point will be selected, and the above process will be repeated until all points have been visited.

[0060] It should be noted that the neighborhood is determined by the distance threshold, which defines the neighborhood range of the positioning point, and the minimum number of samples MinPts determines whether a positioning point is a core point. If there are at least MinPts positioning points (including the positioning point itself) in the neighborhood of a positioning point, the positioning point is considered to be a core point.

[0061] Exemplarily, the geographic distance calculation formula involved in the above embodiment can continue to be used to calculate the spherical distance between each positioning point in the movement trajectory map, and determine whether each positioning point is within the neighborhood of other positioning points based on the spherical distance between each positioning point.

[0062] Furthermore, three lists can be created first, namely, the unvisited point list (unvisited), the visited point list (visited), and the cluster list (clusters). Next, the unvisited point list is initialized, and all the anchor points in the moving trajectory map are added to the unvisited point list, so that all the anchor points in the moving trajectory map are in an unvisited state. The visited point list and the cluster list clusters are initialized to be empty. Then, a anchor point p is taken out from the unvisited point list, marked as visited, and added to the visited point list visited. Check whether the anchor point p is a core point (that is, whether there are at least MinPts anchor points in its neighborhood). If the anchor point p is not a core point, the anchor point p is marked as visited, added to the visited point list visited, and the next anchor point is taken out from the unvisited point list unvisited for processing. If the anchor point p is a core point, a new cluster C is created, added to the cluster list clusters, and all anchor points q in the neighborhood of the anchor point p are traversed. If the positioning point q is in an unvisited state, it is marked as a visited state and added to the list visited and cluster C. If the positioning point q is in a visited state and belongs to an existing cluster C' (that is, q is in the neighborhood of C'), cluster C' is merged with cluster C until there are no positioning points that can be expanded. Then, the next positioning point is taken out from the unvisited point list for processing, and the above process is repeated until unvisited is empty, that is, all positioning points have been visited, and multiple clusters are obtained. Therefore, the multiple activity ranges of offshore workers in the movement trajectory map are determined based on the areas formed by the multiple clusters obtained by clustering.

[0063] In one embodiment, the method for safety management of offshore workers also includes: sorting the positioning points in each cluster according to the scanning time to determine the point order; determining the stay time of the activity range corresponding to each cluster according to the difference in the scanning time corresponding to the first and last positioning points in the point order; if the stay time does not meet the specified time in the sea going plan information, determining abnormal behavior information according to the stay time that does not meet the sea going plan information; displaying the abnormal behavior information, and sending the abnormal behavior information to the terminal associated with the offshore worker corresponding to the abnormal behavior information.

[0064] In this embodiment, for each activity range, the residence time is determined by counting the time span of the positioning points in the activity range, and the calculated residence time is compared with the established residence time limit. If the residence time exceeds the specified limit, it is marked as abnormal behavior and an early warning is issued in time.

[0065] It is worth mentioning that for each activity range, it is also possible to determine whether the activity range conforms to the operating area in the sea departure plan information. If the activity range does not conform to the operating area, the established stay time will be reduced so that when the offshore operators stay in the non-operating area for too long, abnormal information will be generated in time to allow relevant personnel to pay attention to any abnormal behavior in time.

[0066] In addition, the analysis results of movement speed, activity range and stay time can be integrated to comprehensively judge whether the offshore workers have followed the operation plan and safety regulations. An evaluation report is generated based on the analysis results, which includes the statistical information of the movement speed, stay time, and specific description of abnormal behavior of the offshore workers. At the same time, the evaluation results can also be fed back to the offshore workers to remind them to comply with the operation plan and safety regulations.

[0067] Step 108, the cloud management platform obtains the environmental monitoring data fed back by the offshore workers, inputs the environmental monitoring data into the risk prediction model, and determines the early warning information of the environment in which the offshore workers are located.

[0068] Among them, the risk prediction model is trained based on historical environmental monitoring data, and the environmental monitoring data at least includes meteorological data and sea traffic data.

[0069] Step 109, displaying the warning information, and sending the warning information to the terminal associated with the offshore operator corresponding to the warning information.

[0070] In this embodiment, the cloud management platform accurately predicts and manages the operational risks of offshore workers, fully reveals the dynamic and coupling relationships between complex risk factors, and accurately predicts potential dangerous situations. Once a potential dangerous situation is predicted, the cloud management platform will immediately generate early warning information and notify relevant personnel and management departments in various ways to improve the comprehensiveness of safety protection.

[0071] In one embodiment, the method for safety management of offshore workers also includes: preprocessing historical environmental monitoring data and extracting feature vectors from the preprocessed historical environmental monitoring data; determining initial parameters of the logistic regression model by maximum likelihood estimation; training the logistic regression model with initial parameters according to the feature vector, and updating the parameters in the logistic regression model using the gradient descent method until the loss function of the logistic regression module converges or reaches the maximum number of iterations; determining a risk prediction model based on the logistic regression model whose loss function converges or reaches the maximum number of iterations, so that the risk prediction model can output the probability of danger based on the environmental monitoring data.

[0072] In this embodiment, the risk prediction model adopts a logistic regression model, which takes advantage of the simplicity and intuitiveness of logistic regression, adapts to the requirements of higher interpretability in offshore operation scenarios, and can focus on the orderly occurrence of multiple events or the hierarchical superposition of potential factors, revealing the dynamics and coupling relationships between various risk factors in complex offshore operation scenarios.

[0073] Exemplarily, historical environmental monitoring data is preprocessed. For example, for meteorological data such as wind speed and wave height, a reasonable range can be set according to its physical characteristics to identify outliers. For maritime traffic data such as the number of nearby ships, if there are obviously unreasonable high or low values, they can also be judged as outliers and processed. For missing values ​​in meteorological conditions and maritime traffic data, interpolation can be performed based on the correlation of the time series, or the mean, median, etc. of the feature can be used for filling.

[0074] Next, feature vectors are extracted from the preprocessed historical environmental monitoring data. For meteorological feature vectors such as wind speed and temperature, Z-score normalization can be used to make their mean 0 and standard deviation 1. For maritime traffic feature vectors such as the number of nearby ships, Min-Max normalization can be used to map them to the [0,1] interval.

[0075] Furthermore, the probability model of logistic regression is defined as:

[0076]

[0077] Where X = (X1, X2, ..., X n ) is the feature vector obtained after the above processing, Y∈{0,1} is the label, β0,β1,...,β n is the model parameter.

[0078] Next, the model parameters are estimated by the maximum likelihood estimation method, the loss function of the logistic regression uses the logarithmic loss function, and the parameters in the logistic regression model are updated using the gradient descent method until the loss function of the logistic regression module converges or reaches the maximum number of iterations. The training is completed and the risk prediction model is obtained so that the risk prediction model can output the hazard probability based on the environmental monitoring data.

[0079] Furthermore, as a refinement and expansion of the specific implementation methods of the above-mentioned embodiment, in order to fully illustrate the specific implementation process of this embodiment, the environmental monitoring data is input into the risk prediction model, and the steps of determining the early warning information of offshore workers specifically include: if the probability of danger is greater than a preset threshold, the early warning information is determined based on the environmental monitoring data corresponding to the probability of danger greater than the preset threshold.

[0080] In this embodiment, the risk probability at the output of the risk prediction model and the preset threshold are used to achieve an effective early warning function, avoid excessive or insufficient warnings, optimize the decision-making process, and provide dynamic adaptation capabilities. Reasonable threshold settings can not only improve the accuracy of early warnings, but also ensure that necessary response measures are taken in a timely manner when risks occur, thereby ensuring the safety of offshore workers.

[0081] For example, early warning information usually includes key information such as the type of hazard, expected time of occurrence, scope of impact, and recommended response measures, which helps managers make decisions quickly and take appropriate preventive measures.

[0082] It is worth mentioning that the risk prediction model has a dynamic adjustment function. With the continuous addition of new data and the continuous optimization of the model, the risk prediction model can continuously improve the prediction accuracy and adaptability. At the same time, by collecting user feedback on warning information, the risk prediction model can further optimize the prediction algorithm and warning strategy to ensure the continuous improvement and enhancement of the risk prediction model.

[0083] Furthermore, if Figure 2 As shown, as a specific implementation of the above-mentioned offshore worker safety management method, an embodiment of the present application provides a offshore worker safety management system 200, and the offshore worker safety management system 200 includes: a cloud management platform 201 and a mobile terminal 202.

[0084] Among them, the cloud management platform 201 is used to receive the encrypted scanning record sent by the mobile terminal; decrypt the scanning record, and determine the movement trajectory map of the offshore workers corresponding to the user information in the scanning record according to the decrypted scanning record; determine the abnormal information of the offshore workers according to the movement trajectory map; obtain the environmental monitoring data fed back by the offshore workers, input the environmental monitoring data into the risk prediction model, and determine the early warning information of the environment in which the offshore workers are located, wherein the risk prediction model is trained based on historical environmental monitoring data, and the monitoring data at least includes meteorological data and sea traffic data; display abnormal information or early warning information, and send the abnormal information or early warning information to the terminal associated with the offshore workers corresponding to the abnormal information or early warning information;

[0085] The mobile terminal 202 is used to scan the positioning code at a preset position to identify the positioning information in the positioning code, and record the scanning time and the user information of the mobile terminal logged in when scanning; determine the scanning record according to the scanning time, positioning information and user information; encrypt the scanning record, and send the encrypted scanning record to the cloud management platform, so that the cloud management platform can determine the abnormal information or warning information of the offshore operator corresponding to the user information in the scanning record according to the scanning record, display the abnormal information or warning information, and send the abnormal information or warning information to the terminal associated with the offshore operator corresponding to the abnormal information or warning information.

[0086] For the specific definition of the offshore worker safety management system, please refer to the definition of the offshore worker safety management method above, which will not be repeated here. Each module in the above-mentioned offshore worker safety management system can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0087] Those skilled in the art will appreciate that the accompanying drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily necessary for implementing the present application. Those skilled in the art will appreciate that the modules in the devices in the implementation scenario can be distributed in the devices of the implementation scenario according to the description of the implementation scenario, or can be changed accordingly and located in one or more devices different from the present implementation scenario. The modules of the above-mentioned implementation scenario can be combined into one module, or can be further split into multiple submodules.

[0088] The above serial numbers of this application are only for description and do not represent the advantages and disadvantages of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of this application, but this application is not limited to them, and any changes that can be thought of by technicians in this field should fall within the scope of protection of this application.

Claims

1. A method for safety management of offshore workers, applied to a cloud management platform, wherein the cloud management platform can be connected to a mobile terminal for communication, and is characterized in that: The method comprises: Receiving the encrypted scanning record sent by the mobile terminal; Decrypting the scan record, and determining a movement trajectory of the offshore worker corresponding to the user information in the scan record according to the decrypted scan record; Determining abnormal information of the offshore operator according to the movement trajectory diagram; Obtaining environmental monitoring data fed back by the offshore workers, inputting the environmental monitoring data into a risk prediction model, and determining early warning information of the environment in which the offshore workers are located, wherein the risk prediction model is trained based on historical environmental monitoring data, and the environmental monitoring data includes at least meteorological data and sea traffic data; The abnormal information or the warning information is displayed, and the abnormal information or the warning information is sent to a terminal associated with the offshore operator corresponding to the abnormal information or the warning information.

2. The offshore worker safety management method according to claim 1, characterized in that: Determining the movement trajectory of the offshore worker corresponding to the user information in the scan record according to the decrypted scan record specifically includes: Determine the scanning record whose positioning information in the decrypted scanning record matches the preset seagoing position as the starting record; Determine the user information in the starting record as the target user information, and determine the scanning record associated with the target user information as the monitoring record; Using geographic information system technology, determine the positioning point corresponding to the positioning information in the monitoring record on a preset map; In the preset map, the positioning points are connected according to the scanning time of the positioning information in the monitoring record to determine the movement trajectory map of the target operator, wherein the target operator is the offshore operator corresponding to the target user information; The moving trajectory diagram is displayed.

3. The offshore worker safety management method according to claim 2, characterized in that: The method further comprises: Determine the departure time of the target operator according to the scanning time and the current time in the starting record; If the time to go out to sea is greater than the preset time, determining the timeout information of the target operator according to the time to go out to sea that is greater than the preset time; The timeout information is displayed and sent to a terminal associated with the target operator.

4. The offshore worker safety management method according to claim 1, characterized in that: Determining the abnormal information of the offshore operator according to the movement trajectory diagram specifically includes: Determining the moving speed and activity range of the offshore workers according to the moving trajectory diagram; Obtaining the sea-going plan information of the offshore workers; If the moving speed or the activity range does not meet the preset conditions in the sea going plan information, the abnormal information is determined according to the moving speed or the activity range that does not meet the sea going plan information.

5. The offshore worker safety management method according to claim 4, characterized in that: The movement trajectory diagram includes a positioning point and a scanning time corresponding to the positioning point, the positioning point is determined according to the positioning information in the scanning record, and the moving speed of the offshore operator is determined according to the movement trajectory diagram, specifically including: Convert the positioning information corresponding to the adjacent points in the movement trajectory diagram into radians, and determine the radian information of the adjacent points, wherein the adjacent points are the positioning points corresponding to the adjacent scanning times; Determine a first radian difference and a second radian difference between the adjacent points according to the radian information; Determining the actual distance between the adjacent points according to the first arc difference, the second arc difference and a preset earth radius; Determine the time interval between the adjacent points according to the scanning times corresponding to the adjacent points; The moving speed of the offshore worker is determined according to the actual distance and the time interval.

6. The offshore worker safety management method according to claim 4, characterized in that: The movement trajectory diagram includes a positioning point and a scanning time corresponding to the positioning point, the positioning point is determined according to the positioning information in the scanning record, and the determining the activity range of the offshore operator according to the movement trajectory diagram specifically includes: Obtaining the distance threshold and minimum number of samples of the positioning point; Taking the positioning point as the center and the distance threshold as the radius, determine the neighborhood of the positioning point; Marking the positioning point as unvisited; Determine the positioning points in the neighborhood whose number of positioning points is greater than or equal to the minimum sample number as core points; Randomly determine a positioning point that is in an unvisited state as a target point; If the target point is the core point, all the positioning points in the neighborhood of the target point are marked as visited, and a new cluster is created, and all the positioning points in the neighborhood of the target point are added to the cluster; If the target point is the core point, and there are core points other than the target point in the neighborhood of the target point, the core points other than the target point in the neighborhood of the target point are determined as extension points, and the neighborhood of the target point is updated according to the neighborhood of the extension point, and all the positioning points in the neighborhood of the extension point are added to the clusters until there is no extension point in the neighborhood of the target point, and a positioning point that is not visited is randomly determined as the target point; Determine the positioning points belonging to the plurality of clusters as merging points, and merge the plurality of clusters to which the merging points belong into clusters; If the target point is not the core point, the target point is marked as a visited state, and a positioning point that is in an unvisited state is randomly re-determined as the target point until there is no positioning point in an unvisited state; If there is no positioning point in an unvisited state, the activity range of the offshore operator is determined according to the clusters.

7. The offshore worker safety management method according to claim 6, characterized in that: The method further comprises: According to the scanning time, the positioning points in the clusters are sorted to determine the point order; Determine the residence time of the activity range corresponding to each cluster according to the difference in scanning time corresponding to the first and last positioning points in the point sequence; If the stay time does not conform to the specified time in the sea-going plan information, determine abnormal behavior information according to the stay time that does not conform to the sea-going plan information; The abnormal behavior information is displayed, and the abnormal behavior information is sent to a terminal associated with the offshore operator corresponding to the abnormal behavior information.

8. The offshore worker safety management method according to claim 1, characterized in that: The method further comprises: Preprocessing the historical environmental monitoring data, and extracting feature vectors from the preprocessed historical environmental monitoring data; The initial parameters of the logistic regression model were determined by maximum likelihood estimation; Training the logistic regression model with the initial parameters according to the feature vector, and updating the parameters in the logistic regression model using a gradient descent method until the loss function of the logistic regression module converges or reaches a maximum number of iterations; Determining the risk prediction model according to the logistic regression model in which the loss function converges or reaches the maximum number of iterations, so that the risk prediction model can output a hazard probability according to the environmental monitoring data; The inputting of the environmental monitoring data into the risk prediction model to determine the early warning information of the offshore workers specifically includes: If the danger probability is greater than a preset threshold, early warning information is determined according to the environmental monitoring data corresponding to the danger probability greater than the preset threshold.

9. A method for safety management of offshore workers, applied to a mobile terminal, characterized in that: The method comprises: Scanning a positioning code at a preset location to identify positioning information in the positioning code, and recording the scanning time and user information of the mobile terminal logged in during the scanning; Determine a scanning record according to the scanning time, the positioning information and the user information; The scanning record is encrypted and sent to a cloud management platform, so that the cloud management platform can determine the abnormal information or warning information of the offshore operator corresponding to the user information in the scanning record based on the scanning record, display the abnormal information or the warning information, and send the abnormal information or the warning information to a terminal associated with the offshore operator corresponding to the abnormal information or the warning information.

10. A safety management system for offshore workers, characterized in that: The system comprises: A cloud management platform is used to receive the encrypted scan record sent by the mobile terminal; decrypt the scan record, and determine the movement trajectory map of the offshore operator corresponding to the user information in the scan record based on the decrypted scan record; determine the abnormal information of the offshore operator based on the movement trajectory map; obtain the environmental monitoring data fed back by the offshore operator, input the environmental monitoring data into the risk prediction model, and determine the early warning information of the environment in which the offshore operator is located, wherein the risk prediction model is trained based on historical environmental monitoring data, and the monitoring data at least includes meteorological data and sea traffic data; display the abnormal information or the early warning information, and send the abnormal information or the early warning information to the terminal associated with the offshore operator corresponding to the abnormal information or the early warning information; A mobile terminal is used to scan a positioning code located at a preset position to identify the positioning information in the positioning code, and record the scanning time and the user information of the mobile terminal logged in during the scanning; determine the scanning record according to the scanning time, the positioning information and the user information; encrypt the scanning record, and send the encrypted scanning record to a cloud management platform, so that the cloud management platform determines the abnormal information or warning information of the offshore operator corresponding to the user information in the scanning record according to the scanning record, displays the abnormal information or the warning information, and sends the abnormal information or the warning information to a terminal associated with the offshore operator corresponding to the abnormal information or the warning information.

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