Ship safety lifesaving emergency equipment maintenance AI intelligent management platform

Abstract

The invention relates to an AI intelligent management platform for maintenance of ship safety lifesaving emergency equipment. The AI intelligent management platform comprises a front-end function system and a rear-end storage system. The front-end function system comprises a sailor training module, an intelligent inspection module, a third-party maintenance supervision module and the like. Wherein the sailor training module adopts a panoramic VR camera to carry out live-action shooting on a scene on a ship, a virtual reality (VR) technology is applied to provide real scene boarding experience, sailors are helped to remotely realize immersive ship visiting, and a real ship environment is comprehensively understood; through the combination of videos and characters, skill training of sailors before on-ship work is provided. The sailors can remotely realize immersive ship visiting through the sailors training module, comprehensively understand the actual ship environment and remarkably improve the practical operation skills of the sailors; the personalized training path system customizes an exclusive training plan for each sailor through AI algorithm intelligent analysis according to the post demand, experience level and skill weakness of the sailor, and achieves the precision and high efficiency of training.

Description

Technical Field

[0001] The present invention relates to the technical field of shipping industry safety management and digital transformation, and specifically to an AI intelligent management platform for the maintenance of ship safety life-saving emergency equipment. Background Art

[0002] As the main means of transportation in international trade, the safety and reliability of ships are directly related to the stability and development of the global economy. With the continuous growth of global trade volume and the continuous progress of ship technology, the importance of ship safety emergency life-saving equipment has become increasingly prominent. These equipment include, but are not limited to, fixed fire extinguishing systems, lifeboats (boat davits), inflatable life rafts, GMDSS (Global Maritime Distress and Safety System), and emergency generators, etc., which together constitute the last line of defense for ships to cope with emergencies.

[0003] However, there are many challenges in the management of traditional ship safety emergency life-saving equipment. First of all, the familiarity of crew members with various safety life-saving equipment on board directly affects the emergency response ability of the ship. Traditional pre-job familiarization training is often limited by time and location, and the training content is disjointed from actual operation, resulting in crew members being unable to operate the equipment quickly and accurately in case of emergency. Secondly, as an important means of accident prevention, the effectiveness of ship safety inspections depends to a large extent on the personal qualities and experience of crew members. The traditional manual inspection method is not only inefficient, but also prone to omissions and misjudgments due to human factors, posing potential threats to ship safety. In addition, third-party maintenance agencies also play an important role in the periodic inspection and supervision of ship safety life-saving equipment, but their service quality is uneven, and problems such as data fraud and false reports occur from time to time, seriously threatening the safe operation of ships.

[0004] In order to address the above challenges, in recent years, with the rapid development of advanced technologies such as the Internet of Things (IOT), big data analysis, machine learning algorithms, and virtual reality (VR), augmented reality (AR), etc., an AI intelligent management platform for the maintenance of ship safety life-saving emergency equipment has emerged as the times require. The platform aims to achieve visual management of the maintenance of ship safety life-saving equipment through functions such as an integrated online learning module, an intelligent inspection system, a third-party maintenance supervision mechanism, and a business integrated digital archive, improve the safety of ship navigation, and promote the digital transformation of ship management and inspection.

[0005] Specifically, through an integrated online learning module and using VR real-scene immersive ship visiting technology, the platform makes the training content more intuitive and easy to understand, thus improving the learning efficiency and practical operation ability of seafarers. The intelligent inspection system uses image recognition and Internet of Things technologies to automatically identify the status of ship safety equipment, assisting seafarers in conducting accurate inspections and reducing human errors and omissions. The third-party maintenance supervision mechanism records the entire process of inspection and testing through an intelligent supervision system, ensuring the compliance and effectiveness of maintenance activities. At the same time, the establishment of a business integrated digital archive enables the effective management of electronic archives throughout the life cycle of ship safety equipment, facilitating traceability and query.

[0006] In summary, the development and application of the AI intelligent management platform for the maintenance of ship safety emergency rescue equipment not only solve many problems existing in traditional ship safety management, but also promote the transformation and upgrading of the ship shipping industry through technological innovation, providing strong support for building a safe, efficient and green shipping system. Therefore, the research and development of this platform has important practical significance and broad application prospects. Summary of the Invention

[0007] To solve the problems of the prior art, the present invention provides an AI intelligent management platform for the maintenance of ship safety rescue emergency equipment. It aims to comprehensively integrate functions such as seafarer training, intelligent inspection, third-party maintenance supervision, file management and data analysis through intelligent technical means, improve the maintenance management level of ship safety emergency rescue equipment, reduce the probability of accidents, and ensure the life safety of seafarers and the safe operation of ships.

[0008] To solve the above technical problems, the present invention is realized through the following technical solutions: In the first aspect, the AI intelligent management platform for the maintenance of ship safety rescue emergency equipment includes a front-end function system and a back-end storage system:

[0009] The front-end function system includes:

[0010] A seafarer training module that uses a panoramic VR camera to take real-scene photos of the shipboard scene, applies virtual reality (VR) technology to provide a real-scene ship boarding experience, helps seafarers remotely achieve immersive ship visiting, and comprehensively understand the real ship environment; provides skill training for seafarers before taking up their posts on board in the form of a combination of video and text, including but not limited to personal survival skills, fire fighting, emergency and rescue content;

[0011] An intelligent inspection module that uses image recognition and Internet of Things technologies to automatically identify the status of ship safety equipment through seafarers' handheld terminals and / or 5G explosion-proof AR helmets, assisting seafarers in conducting accurate inspections and reducing human errors and omissions;

[0012] This module utilizes image recognition and Internet of Things technologies to automatically identify the status of ship safety equipment through crew handheld terminals and / or 5G explosion-proof AR helmets. The handheld terminals and / or 5G explosion-proof AR helmets are equipped with camera devices. When the crew approaches the equipment, the image recognition function will be automatically activated to take pictures of the equipment and identify its status (such as whether it is damaged, whether it has expired, etc.). At the same time, the Internet of Things technology can monitor the operating data of the equipment in real time, such as temperature, pressure, etc., to further ensure the normal operation of the equipment.

[0013] Third-party maintenance supervision module. This module conducts qualification review and online certification of third-party maintenance agencies to ensure that the qualifications of third-party personnel and companies are compliant, true, and valid. The entire process of inspection and testing is recorded through multi-source sensing terminals, data transmission networks, and AI processing devices.

[0014] This module conducts qualification review and online certification of third-party maintenance agencies to ensure that the qualifications of third-party personnel and companies are compliant, true, and valid. At the same time, through multi-source sensing terminals, data transmission networks, and AI processing devices, the entire process of inspection and testing is recorded. These records include videos, pictures, data, etc., and can be uploaded to the platform backend in real time for storage and analysis.

[0015] The backend storage system includes:

[0016] File management and evidence retention module. This module establishes an electronic file for the entire life cycle of ship safety equipment; an independent electronic file is established for each equipment to ensure the integrity and accuracy of the information, and the file is updated and maintained regularly to ensure the timeliness of the information.

[0017] Report maintenance and data analysis module. This module supports the custom generation of various reports according to requirements; this module supports the custom generation of various reports according to requirements, such as equipment inspection reports, maintenance record reports, etc. These reports display data in the form of charts, tables, etc., facilitating users to intuitively understand the operating status and maintenance situation of the equipment. At the same time, the module also has a data analysis function, which can deeply mine and analyze the collected data to provide strong support for decision-making.

[0018] In this aspect, through intelligent inspection and maintenance management, potential faults in ship safety emergency rescue equipment can be discovered and handled in a timely manner, thus greatly reducing the probability of accidents. This not only ensures the safety of crew members but also improves the overall safety performance of the ship; the equipped handheld terminals and / or 5G explosion-proof AR helmets and the application of the intelligent inspection module enable crew members to complete inspection tasks more quickly and accurately. The handheld terminals and / or 5G explosion-proof AR helmets can automatically identify the equipment status, reduce the error of human judgment, and improve the efficiency and accuracy of inspection; the management platform records and supervises the whole maintenance process of the third-party maintenance agency to ensure the quality and effect of the maintenance work. At the same time, based on the comprehensive evaluation mechanism of AI analysis and user feedback, the maintenance quality and service level can be continuously optimized, further improving the reliability of ship safety emergency rescue equipment; through the file management and data analysis module, an electronic file of the whole life cycle of ship safety emergency rescue equipment is established, and evidence materials such as pictures and videos during inspection and maintenance are automatically collected. This not only facilitates supervision and audit but also provides a rich data source for data analysis. Using the data analysis function in the management platform, the equipment failure law can be deeply explored, future trends can be predicted, and a more scientific decision-making basis can be provided for ship safety management; the application of the crew training module and virtual reality (VR) technology enables crew members to receive more comprehensive and systematic training, improving their professional skills and emergency handling abilities. This helps crew members to respond quickly and accurately in case of emergencies, further ensuring the safety of the ship and crew members.

[0019] In a specific implementation manner, the crew training module further includes training process management, which can formulate a training ship catalog and provide a VR immersive ship visit function, including panoramic views, side views, 45° bow photos, 45° stern photos, perspective structure diagrams, and key area identification points, enabling crew members to comprehensively understand the ship layout and equipment locations;

[0020] The crew training module also includes training courses and materials, providing teaching videos including but not limited to the inspection, operation, and detection of fixed CO2 fire extinguishing systems, operation guidance videos for daily maintenance, drawing materials including but not limited to ship fire control plans and CO2 system schematic diagrams, as well as detailed information and photos of key equipment and equipment components for crew members to study and understand in depth.

[0021] In a specific implementation manner, the intelligent inspection module automatically generates inspection tasks according to the preset inspection plan and equipment maintenance cycle and pushes them to relevant personnel to ensure that the inspection work is completed on time and with quality. The inspection data is uploaded to the cloud in real time, and the AI algorithm immediately analyzes the equipment health status, predicts potential faults, issues early warnings, and realizes real-time guidance and collaboration between experts and front-line personnel through high-definition video calls and remote desktop sharing functions;

[0022] The detection process of the third - party maintenance supervision module includes on - site personnel qualifications, detection content, and detection results, realizing cloud storage of maintenance and detection content, socialized supervision, comprehensively evaluating the maintenance effect based on AI analysis and user feedback, and continuously optimizing the maintenance quality and service level.

[0023] In a specific implementation, the electronic files of the file management and evidence retention module include learning records, equipment information, inspection records, and maintenance activities, which are convenient for traceability and query, and automatically collect picture and video evidence materials during inspection and maintenance to ensure operation compliance and facilitate supervision and auditing.

[0024] The reports generated by the report maintenance and data analysis module include, but are not limited to, training and assessment records, inspection reports, maintenance statistics, and fault analysis. It uses AI algorithms to deeply mine massive data, analyze equipment fault patterns, predict future trends, and provide a scientific basis for ship safety management.

[0025] In a specific implementation, the handheld terminal and / or the 5G explosion - proof AR helmet have an operating system, memory, CPU, graphics card, screen, and keyboard / touch screen, with data acquisition, communication, GPS / Beidou satellite positioning, photo and video recording, data processing, application software installation, and security protection functions, used to automatically identify the status of ship safety equipment, assist crew members in precise inspections, and upload inspection data to the cloud processor for analysis and processing in real - time.

[0026] The handheld terminal and / or the 5G explosion - proof AR helmet is a portable device integrating a variety of advanced technologies, designed specifically for the inspection and maintenance of ship safety equipment. It is equipped with powerful hardware and rich software functions, capable of automatically identifying the status of ship safety equipment, assisting crew members in precise inspections, and uploading inspection data to the cloud processor for analysis and processing in real - time.

[0027] The handheld terminal and / or the 5G explosion - proof AR helmet uses image recognition technology to automatically identify the status of ship safety equipment, such as the integrity of fire - fighting equipment and the smoothness of the release mechanism of lifeboats; through screen display and voice prompts, the handheld terminal and / or the 5G explosion - proof AR helmet can assist crew members in precise inspections, reducing human errors and omissions; during the inspection process, the handheld terminal and / or the 5G explosion - proof AR helmet uploads the collected data and images to the cloud processor in real - time to ensure the timeliness and accuracy of the data; the cloud processor deeply analyzes and processes the uploaded data, generates inspection reports and warning information, providing strong support for the safe operation of the ship.

[0028] In a specific implementation, the crew training module further includes a personalized training path system. This system intelligently analyzes multi-dimensional data such as the crew's job requirements, personal experience level, identified skill deficiencies, and historical learning performance through AI algorithms and customizes an exclusive training plan for each crew member.

[0029] The specific implementation method of the personalized training path system is as follows:

[0030] Step 1: Multi-dimensional data collection,

[0031] Including job information: Collect information such as the crew's job type and scope of responsibilities;

[0032] Experience level: Evaluate the crew's work experience, time on board, tasks participated in, etc.;

[0033] Skill deficiencies: Identify in which aspects the crew has skill deficiencies through examinations, practical assessments, questionnaires, etc.;

[0034] Historical learning performance: Record the learning progress, grades, and feedback of the crew's previous training;

[0035] Step 2: AI algorithm analysis: Use machine learning algorithms to deeply analyze the collected multi-dimensional data, identify the crew's training needs and potential learning difficulties; generate personalized training plans and learning paths for each crew member according to the analysis results.

[0036] Step 3: Training plan customization, including:

[0037] Basic safety knowledge and equipment familiarity training: For newly recruited crew members, focus on arranging basic safety knowledge training, including personal safety and social responsibility, first aid at sea, fire fighting, lifeboat raft operation, emergency evacuation, etc.; provide training on ship equipment familiarity, and use VR panoramic technology to simulate the ship environment to enable the crew to comprehensively understand the ship layout and equipment locations.

[0038] Advanced course push: For experienced crew members who are lacking in new technology applications, targetedly push advanced courses such as intelligent ship system operation and automated control system maintenance; provide interactive learning methods such as case analysis and practical simulation to help the crew master new technologies and advanced equipment operation skills.

[0039] In a specific implementation, the crew training module further includes a VR intelligent training and collaboration system, which includes:

[0040] Interactive VR operation and emergency training module: Use VR technology to reproduce the ship environment, simulate the operation of safety and rescue equipment and emergency response, and improve the crew's practical and emergency response capabilities;

[0041] This module uses precise VR modeling technology to reproduce the internal structure and external environment of the ship, enabling crew members to simulate the operation of various safety and rescue equipment in a virtual environment, such as lifeboat release, fire hose use, familiarization with emergency escape routes, etc., enhancing the crew's practical operation ability. At the same time, a variety of emergency situations are designed for simulation, such as fires, abandoning ship, collisions, etc. Crew members are required to make quick judgments and execute correct emergency procedures in the simulated environment to improve their response ability in real emergency situations.

[0042] The implementation methods of interactive VR operation drills and emergency handling training include:

[0043] 1. VR Modeling and Scene Reproduction: Using advanced VR modeling technology, a highly realistic virtual ship environment is constructed according to the actual structure and layout of the ship. Ensure that the equipment, layout, and details in the virtual environment are consistent with the real ship, so that crew members can conduct realistic operation drills in the virtual environment.

[0044] 2. Simulation Operation of Safety and Rescue Equipment: Simulate the operation of various safety and rescue equipment in the virtual environment, such as the release of lifeboats, the use of fire hoses, and the familiarization with emergency escape routes. Through the interactive interface in the virtual environment, crew members can simulate the operation of these equipment and receive operation feedback to enhance their practical operation ability.

[0045] 3. Emergency Situation Simulation: Design a variety of emergency situation simulations, such as fires, abandoning ship, collisions, etc. Use VR technology to simulate the occurrence and evolution process of these emergency situations, and require crew members to make quick judgments and execute correct emergency procedures in the simulated environment.

[0046] Dynamic Sudden Situation Simulation Module: Incorporate unpredictable dynamic changes, including but not limited to fire escalation, equipment failures, to test the crew's instant decision-making and response abilities, and provide instant feedback and improvement suggestions;

[0047] Integrate dynamic and unpredictable sudden situations into VR training, such as simulating a sudden intensification of the fire, life-saving equipment failures, or adverse weather conditions, to test the crew's instant decision-making and response abilities. The system gives instant scores and detailed feedback reports based on the crew's reaction speed, operation accuracy, and teamwork in the simulated scenario, pointing out the deficiencies in the operation and providing improvement suggestions to promote the continuous improvement of the crew's skills.

[0048] The implementation methods of sudden situation scenario simulation and instant feedback include:

[0049] 1. Dynamic Changes and Unpredictability: Integrate dynamic and unpredictable sudden situations into VR training, such as simulating a sudden intensification of the fire, life-saving equipment failures, or adverse weather conditions. These sudden situations should be random and unpredictable to test the crew's instant decision-making and response abilities.

[0050] 2. Instant Scoring and Feedback Report: The system should be able to record the reaction speed, operation accuracy, and teamwork of crew members in simulated scenarios. Based on this information, the system should be able to give instant scores and detailed feedback reports, pointing out the deficiencies in operations and providing improvement suggestions.

[0051] Multi - person VR Collaborative Training Module: Support multi - user simultaneous participation, simulate cross - departmental collaboration, strengthen communication and collaboration capabilities among crew members, and improve the overall emergency response efficiency;

[0052] Develop a VR collaborative training function that supports multi - user simultaneous participation, allowing crew members with different functions to collaborate in the same virtual environment, simulating cross - departmental collaboration in daily ship operations and emergency situations. By simulating complex tasks such as emergency evacuation, cargo securing, and maritime search and rescue, strengthen the communication and collaboration capabilities among crew members, ensure that an effective emergency response team can be quickly formed in real events, and improve the overall emergency response efficiency.

[0053] The implementation methods of the multi - person VR collaborative training mode include:

[0054] 1. Multi - user simultaneous participation: Develop a VR collaborative training function that supports multi - user simultaneous participation. Allow crew members with different functions to collaborate in the same virtual environment, simulating cross - departmental collaboration in daily ship operations and emergency situations.

[0055] 2. Complex task simulation: By simulating complex tasks such as emergency evacuation, cargo securing, and maritime search and rescue, strengthen the communication and collaboration capabilities among crew members. These tasks should be realistic and challenging to test the teamwork and emergency response capabilities of crew members.

[0056] In the second aspect, the construction equipment of the AI intelligent management platform for the maintenance of ship safety and life - saving emergency equipment includes:

[0057] A processor for executing program instructions stored in the memory to implement the functions of the AI intelligent management platform for the maintenance of ship safety and emergency life - saving equipment, including operations of the crew training, intelligent inspection, third - party maintenance supervision, file management, and data analysis modules;

[0058] A memory for storing program instructions and data. The program instructions include codes for implementing the functions of the crew training module, intelligent inspection module, third - party maintenance supervision module, file management, and data analysis module. The data includes but is not limited to crew training records, inspection data, maintenance records, and equipment information;

[0059] A communication interface for data exchange and communication with ship safety and emergency life - saving equipment, handheld terminals, and / or 5G explosion - proof AR helmets, and external equipment of third - party maintenance agencies;

[0060] An input / output device for receiving operation instructions input by a user and displaying processing results, including but not limited to a keyboard, a mouse, a touch screen, and a display.

[0061] In a third aspect, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the functions of the AI intelligent management platform for the maintenance of ship safety emergency rescue equipment are realized.

[0062] In a fourth aspect, a computer program product includes a computer-readable storage medium, and a computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the functions of the AI intelligent management platform for the maintenance of ship safety emergency rescue equipment are realized.

[0063] The beneficial effects of the present invention are as follows:

[0064] 1. Through the crew training module, especially the application of panoramic VR camera live shooting and virtual reality (VR) technology, crew members can remotely achieve immersive ship visits, comprehensively understand the actual ship environment, and significantly improve their safety awareness and practical skills before taking up their posts on board. The personalized training path system, through intelligent analysis by AI algorithms based on the crew's post requirements, experience level, and skill deficiencies, customizes an exclusive training plan for each crew member, achieving precision and efficiency in training. The VR intelligent training and collaboration system not only provides interactive operations and emergency training but also incorporates dynamic emergency situation simulations and multi-person collaborative training, greatly enhancing the crew's emergency response ability and teamwork ability.

[0065] 2. The intelligent inspection module uses image recognition and Internet of Things technologies to automatically identify the status of ship safety equipment, reduce errors caused by human judgment, and improve the accuracy and efficiency of inspections. The provision of handheld terminals and / or 5G explosion-proof AR helmets enables crew members to complete inspection tasks more quickly and conveniently. At the same time, inspection data is uploaded to the cloud in real time, facilitating managers to promptly understand and master the equipment status.

[0066] 3. The present invention conducts qualification audits and online certifications for third-party maintenance agencies to ensure that the qualifications of third-party personnel and companies are compliant, true, and valid, guaranteeing the quality of maintenance work from the source. Through multi-source perception terminals, a data transmission network, and AI processing devices, the entire process of the inspection and testing process is recorded to ensure the transparency and traceability of the maintenance process. Based on a comprehensive evaluation mechanism of AI analysis and user feedback, the maintenance quality and service level can be continuously optimized, further enhancing the reliability of ship safety emergency rescue equipment.

[0067] 4. The file management and evidence retention module creates independent electronic files for each device to ensure the integrity and accuracy of information, facilitating traceability and query. The report maintenance and data analysis module supports custom generation of various reports, and deeply mines and analyzes massive data through AI algorithms to identify equipment failure patterns, predict future trends, and provide a more scientific decision-making basis for ship safety management;

[0068] 5. Through intelligent inspection and maintenance management, the present invention can promptly detect and handle potential faults in ship safety emergency rescue equipment, reduce the probability of accidents, and ensure the life safety of crew members and the overall safety performance of the ship. The comprehensive integration and collaborative effect of the platform make the maintenance management work of ship safety emergency rescue equipment more efficient and convenient, improving the overall safety management level. Brief Description of the Drawings

[0069] Figure 1 is a schematic diagram of the system structure of the present invention.

[0070] Figure 2 is a schematic diagram of the crew training process of the present invention.

[0071] Figure 3 is a schematic diagram of the perspective structure of the present invention.

[0072] Figure 4 is a schematic diagram of the key area identification points of the present invention.

[0073] Figure 5 is a schematic diagram of the training course page of the present invention.

[0074] Figure 6 is a schematic diagram of the equipment component page of the C02 compartment facilities of the present invention.

[0075] Figure 7 is a schematic diagram of the equipment parameter page of the C02 compartment facilities of the present invention.

[0076] Figure 8 is a schematic diagram of the equipment photo page of the C02 compartment facilities of the present invention.

[0077] Figure 9 is a schematic diagram of the convention information page of the C02 compartment facilities of the present invention.

[0078] Figure 10 is a schematic diagram of the inspection requirements page of the C02 compartment facilities of the present invention.

[0079] Figure 11 is a schematic diagram of the common problem page of the C02 compartment facilities of the present invention.

[0080] Figure 12 is a schematic diagram of the equipment test page of the C02 compartment facilities of the present invention.

[0081] Figure 13 It is a schematic diagram of the intelligent inspection process of the present invention.

[0082] Figure 14 It is a first - perspective schematic diagram of the handheld terminal and / or the 5G explosion - proof AR helmet of the present invention.

[0083] Figure 15 It is a schematic diagram of the third - party maintenance and supervision process of the present invention.

[0084] Figure 16 It is a schematic diagram of the backend storage structure of the present invention. Specific embodiments

[0085] Next, in combination with the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0086] Embodiment 1: An AI intelligent management platform for the maintenance of ship safety and rescue equipment.

[0087] Platform composition and overall functions

[0088] Platform composition: The platform consists of two core parts, namely the front - end function system and the backend storage system.

[0089] Front - end function system:

[0090] Reference Figure 1 、 Figure 2 、 Figure 3 、 Figure 4 、 Figure 5 、 Figure 6 、 Figure 7 、 Figure 8 、 Figure 9 、 Figure 10 、 Figure 11 And Figure 12 As shown, the crew training module:

[0091] Function: Using panoramic VR technology and combined with on - ship real - scene shooting, it provides an immersive safety training experience for crew members.

[0092] Implementation method: By using a panoramic VR camera to capture key areas inside and outside the ship, a virtual ship environment is constructed in combination with virtual reality technology. The virtual reality (VR) technology is used to provide a boarding experience in a real scenario, helping crew members remotely achieve an immersive ship visit and comprehensively understand the actual ship environment; in the form of a combination of video and text, skill training is provided for crew members before they take up their posts on the ship, including but not limited to personal survival skills, fire fighting, emergency response and life-saving content.

[0093] Reference Figure 1 、 Figure 13 And Figure 14 As shown, intelligent inspection module:

[0094] Function: By using image recognition and Internet of Things technologies, automatic identification and status monitoring of ship safety equipment are realized.

[0095] Implementation method: The crew holds a terminal or wears a 5G explosion-proof AR helmet, captures images of ship safety equipment through the camera on the device, uses AI algorithms for image recognition and analysis, and real-time feedback the device status. At the same time, in combination with Internet of Things sensors, the working parameters of the equipment are monitored to achieve precise inspection.

[0096] Third-party maintenance supervision module:

[0097] Function: Conduct qualification review and online certification of third-party maintenance agencies, and record and supervise their overhaul and testing processes.

[0098] Implementation method: Establish a database of third-party maintenance agencies, and conduct online review and certification of their qualifications. During the maintenance process, information such as the operation logs of maintenance personnel and equipment detection data are recorded through the platform to ensure the transparency and standardization of maintenance work.

[0099] Backend storage system:

[0100] File management and evidence retention module:

[0101] Function: Establish an electronic file for the entire life cycle of ship safety equipment to ensure the integrity and accuracy of information.

[0102] Implementation method: Enter the entire life cycle information of ship safety equipment such as procurement, installation, commissioning, inspection, and maintenance into the platform to form an electronic file. At the same time, encrypt and store key operation records to ensure the security and traceability of information.

[0103] Report maintenance and data analysis module:

[0104] Function: Support the custom generation of various reports, provide data analysis functions, and provide strong support for decision-making.

[0105] Implementation method: The platform provides a rich set of report templates, and users can customize the report content according to their needs. At the same time, using big data analysis technology, the platform data is deeply mined and analyzed to provide a scientific basis for ship safety management.

[0106] Overall process

[0107] Platform initialization:

[0108] Establish a platform database and enter the basic information of ship safety equipment.

[0109] Configure the interfaces and permissions between the front-end function system and the back-end storage system.

[0110] Crew training:

[0111] The crew logs in to the platform and selects the crew training module.

[0112] According to the training needs, select the corresponding VR scenario for learning.

[0113] After completing the learning, participate in an online assessment to test the learning results.

[0114] Intelligent inspection:

[0115] The crew holds a handheld terminal or wears an AR helmet and enters the intelligent inspection module.

[0116] Capture images of ship safety equipment and use AI algorithms for identification and analysis.

[0117] According to the analysis results, record the equipment status and generate an inspection report.

[0118] Reference Figure 1 And Figure 15 As shown in, Third-party maintenance supervision:

[0119] The maintenance agency logs in to the platform and submits an application for qualification review.

[0120] After the platform approves, the maintenance agency conducts maintenance operations.

[0121] During the maintenance process, record the operation logs and equipment inspection data.

[0122] The platform supervises the maintenance process to ensure the maintenance quality.

[0123] Reference Figure 1 And Figure 8 As shown in, Archive management and data analysis:

[0124] The platform automatically collects and organizes the full life cycle information of ship safety equipment.

[0125] Users customize and generate reports according to their needs.

[0126] Using big data analysis technology, deeply mine and analyze the platform data.

[0127] According to the analysis results, formulate ship safety management strategies and decisions.

[0128] Through the implementation of this platform, the maintenance management of ship safety emergency rescue equipment has achieved intelligence and high efficiency, effectively reducing the probability of accidents and improving the overall safety performance of ships.

[0129] Example 2: In the shipping industry, the professional skills and safety awareness of crew members are directly related to the operational safety and efficiency of ships. Traditional crew training methods often adopt a "one-size-fits-all" teaching model, ignoring the differences in crew job requirements, personal experience levels, and skill deficiencies, resulting in uneven training effects. To improve the effectiveness of crew training, the present invention introduces a personalized training path system in the crew training module, aiming to customize exclusive training plans for crew members according to their actual situations, so as to achieve precise training and improve the skill levels and safety awareness of crew members.

[0130] System composition and implementation method

[0131] System composition:

[0132] Multi-dimensional data collection module: Responsible for collecting relevant information of crew members, including job information, experience level, skill deficiencies, and historical learning performance, etc.

[0133] AI algorithm analysis module: Use machine learning algorithms to deeply analyze the collected data and identify the training needs and potential learning difficulties of crew members.

[0134] Training plan customization module: Customize personalized training plans for crew members according to the analysis results of the AI algorithm.

[0135] Implementation method:

[0136] Multi-dimensional data collection:

[0137] Job information: Imported through the crew registration or management system to collect information such as the job type and scope of responsibilities of crew members.

[0138] Experience level: Evaluate the experience level of crew members according to their onboard time, work experience, and obtained qualification certificates, etc.

[0139] Skill deficiencies: Identify the skill deficiencies of crew members through online exams, practical assessments, or colleague / superior evaluations, etc.

[0140] Historical learning performance: Record the learning progress, grades, and feedback of crew members' previous participation in training as a reference for subsequent training plans.

[0141] AI Algorithm Analysis:

[0142] Use machine learning algorithms (such as decision trees, random forests, neural networks, etc.) to conduct in-depth analysis on the multi-dimensional data collected.

[0143] Based on the job requirements, experience levels, and skill deficiencies of the crew members, identify their training needs and potential learning difficulties.

[0144] Consider the learning habits and preferences of the crew members to generate personalized training suggestions for each crew member.

[0145] Training Plan Customization:

[0146] Basic Safety Knowledge and Equipment Familiarization Training: For newly recruited crew members or those with job changes, focus on arranging basic safety knowledge training and providing training on ship equipment familiarity to ensure that their basic safety skills meet the standards.

[0147] Push Advanced Courses: For experienced crew members who are lacking in the application of new technologies, according to their job requirements and skill deficiencies, push advanced courses such as intelligent ship system operation and new energy ship technology.

[0148] Personalized Learning Path: Based on the analysis results of the AI algorithm, customize a personalized learning path for each crew member, including the learning sequence, course difficulty, learning resources, etc.

[0149] Overall Process

[0150] Data Collection and Preprocessing: After the crew members register or log in to the platform, the system automatically collects their job information, experience levels, etc. data and conducts preprocessing.

[0151] Identify Skill Deficiencies: Through online exams, practical assessments, etc., identify the skill deficiencies of the crew members and record their historical learning performance.

[0152] AI Algorithm Analysis: Use machine learning algorithms to conduct in-depth analysis on the multi-dimensional data collected to identify the training needs and potential learning difficulties of the crew members.

[0153] Training Plan Customization: According to the analysis results of the AI algorithm, customize a personalized training plan for the crew members, including basic safety knowledge training, pushing advanced courses, and personalized learning paths, etc.

[0154] Training Implementation and Monitoring: The crew members study according to the personalized training plan, and the platform monitors the learning progress and grades in real time, providing learning reminders and feedback.

[0155] Training Effect Evaluation: After the training is completed, evaluate the learning effect of the crew members through online exams, practical assessments, etc., and adjust the subsequent training plan according to the evaluation results.

[0156] Implementation Effect

[0157] By introducing a personalized training path system, crew training has become more accurate and efficient. The crew's skill level has been significantly improved, providing a strong guarantee for the safe operation of the ship. At the same time, the personalized training plan has also stimulated the crew's enthusiasm and initiative in learning, and improved their satisfaction and participation in training.

[0158] Example 3: In ship operations, the practical skills and emergency response capabilities of the crew are directly related to the safety and efficiency of the ship. Traditional training methods are limited by factors such as venues and equipment, and it is difficult to provide a highly simulated operating environment and emergency scenarios. In order to further improve the practical and emergency capabilities of the crew, the present invention introduces a VR intelligent training and collaboration system in the crew training module, and uses virtual reality (VR) technology to simulate operations and emergency training, aiming to improve the practical skills, emergency response capabilities and teamwork capabilities of the crew through a highly simulated virtual environment.

[0159] System composition and implementation

[0160] System composition:

[0161] Interactive VR operation and emergency training module:

[0162] VR technology is used to recreate the internal and external environment of the ship, including key areas such as the wheelhouse, engine room, and deck.

[0163] Build highly simulated virtual ship equipment, such as fire-fighting equipment, lifeboats, life rafts, etc., for crew members to perform simulated operations.

[0164] Design a variety of emergency situation simulations, such as fire, collision, abandonment of ship, etc., to conduct emergency response training.

[0165] Dynamic emergency simulation module:

[0166] Incorporate dynamically changing and unpredictable emergencies into VR training, such as simulating sudden intensification of fire, failure of life-saving equipment, and ship tilting.

[0167] The system dynamically adjusts emergency situations in simulated scenarios based on preset algorithms or random generation mechanisms, testing the crew's immediate decision-making and response capabilities.

[0168] Provide instant scoring and feedback reports to evaluate the crew's performance in simulation scenarios, and point out existing problems and areas for improvement.

[0169] Multiplayer VR Collaboration Training Module:

[0170] Develop VR collaborative training functions that support simultaneous multi-user participation, allowing crew members with different functions to work together in the same virtual environment.

[0171] Simulate cross - departmental collaboration scenarios, such as fire brigades, lifeboat teams, cabin crews, etc., to enhance the communication and collaboration capabilities among crew members.

[0172] Provide functions such as role assignment, task assignment, progress monitoring, etc., to ensure the orderly progress of collaborative training.

[0173] Implementation method:

[0174] Utilize VR hardware (such as head - mounted displays, controllers, etc.) and software (such as VR development platforms, game engines, etc.) to construct a virtual ship environment.

[0175] Create ship equipment models and scene models through 3D modeling technology to ensure high - fidelity simulation.

[0176] Use a physics engine to simulate the physical processes of equipment operation and emergency response, improving the authenticity of the simulation.

[0177] Develop a dynamic emergency situation generation algorithm to achieve the dynamic change and unpredictability of the simulation scenario.

[0178] Design a multi - person collaborative training mechanism, including functions such as role assignment, task assignment, progress monitoring, etc., to ensure the effectiveness of collaborative training.

[0179] Overall process

[0180] System initialization and configuration:

[0181] Install and configure VR hardware and software to ensure the normal operation of the system.

[0182] Import ship equipment models and scene models to construct a virtual ship environment.

[0183] Set the dynamic emergency situation generation algorithm and the multi - person collaborative training mechanism.

[0184] Crew training and assessment:

[0185] Crew members wear VR hardware and enter the virtual ship environment.

[0186] According to the job requirements and training objectives, select the corresponding operation and emergency training modules.

[0187] Simulate operating ship equipment in the virtual environment and conduct emergency response training.

[0188] The system gives instant scores and feedback reports based on the crew members' performance in the simulation scenario.

[0189] For multi - person collaborative training, the system assigns roles and tasks, and crew members work collaboratively in the same virtual environment.

[0190] Training and assessment evaluation:

[0191] Analyze the instant scoring and feedback report to evaluate the practical skills, emergency response capabilities, and teamwork capabilities of the crew members.

[0192] According to the evaluation results, adjust the training plan and training content to ensure the training effect.

[0193] For crew members with excellent performance, give rewards and recognition; for crew members with poor performance, provide additional training and guidance.

[0194] Continuous optimization and improvement:

[0195] Collect the feedback from the crew members on the VR intelligent training and collaboration system, and continuously optimize the system functions and user experience.

[0196] According to the development trend of the shipping industry and the application of new technologies, update the training content and simulation scenarios to ensure the timeliness and practicality of the training.

[0197] Implementation effect

[0198] Through the VR intelligent training and collaboration system, the practical and emergency capabilities of the crew members have been significantly improved, and the communication and collaboration capabilities among the crew members have also been strengthened. The system provides a highly simulated virtual environment and dynamically changing emergencies, enabling the crew members to train in an environment close to the real situation, improving the effectiveness and pertinence of the training. At the same time, the multi-person collaborative training function enhances the communication and collaboration capabilities among the crew members, providing a more solid guarantee for the safe operation of the ship.

[0199] Example 4: Figures 1 to 16 Overall system construction and software and hardware support

[0200] Specific construction process:

[0201] Integrate the functions of the above four modules to construct a complete AI intelligent management system for the maintenance of ship safety emergency rescue equipment.

[0202] Develop the system platform to achieve data interaction and sharing among various modules.

[0203] Select and install the required hardware devices, including servers, handheld terminals, and / or 5G explosion-proof AR helmets, etc.

[0204] Software and hardware support:

[0205] Hardware: Servers, storage devices, handheld terminals, and / or 5G explosion-proof AR helmets, intelligent rescue equipment, etc.

[0206] Software: System platform software, data collection and analysis software, file management software, etc.

[0207] Implementation process flow:

[0208] Complete the development and testing of the system platform.

[0209] Purchase and install the required hardware devices.

[0210] Integrate the functions of each module into the system platform.

[0211] Provide system usage training for the crew.

[0212] Officially go online and run, and conduct continuous optimization and upgrading.

[0213] The above five embodiments elaborate in detail the specific construction process of each module, the required software and hardware support, and the specific implementation process flow. These embodiments together constitute a complete solution for the AI intelligent management system for the maintenance of ship safety emergency rescue equipment.

[0214] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A ship safety emergency life-saving equipment maintenance AI intelligent management platform, characterized in that: Including front-end functional system and back-end storage system: The front-end functional system includes: Crew training module, which uses a panoramic VR camera to shoot real scenes on board, and uses virtual reality (VR) technology to provide a real-life onboard experience, helping crew members to remotely visit the ship immersively and fully understand the real ship environment; through a combination of video and text, it provides skills training for crew members before they take up their posts on board, including but not limited to personal survival skills, firefighting, emergency response and lifesaving content; Intelligent inspection module, which uses image recognition and IoT technology to automatically identify the status of ship safety equipment through crew handheld terminals and / or 5G explosion-proof AR helmets, assisting crew members in conducting accurate inspections and reducing human errors and omissions; The third-party maintenance supervision module conducts qualification review and online certification of third-party maintenance agencies to ensure that the qualifications of third-party personnel and companies are compliant, authentic and valid. The module records the entire maintenance and inspection process through multi-source sensing terminals, data transmission networks, and AI processing equipment. The back-end storage system includes: Archives management and evidence retention module, which establishes electronic archives of the entire life cycle of ship safety equipment; Report maintenance and data analysis module, which supports the generation of various reports according to customized requirements.

2. According to claim 1, a ship safety emergency life-saving equipment maintenance AI intelligent management platform is characterized by: The crew training module also includes training process management, the ability to develop a training ship catalog, and provides a VR immersive ship visit function, including panoramic views, side views, 45° bow photos, 45° stern photos, perspective structural diagrams, and key area marking points, so that crew members can fully understand the ship layout and equipment locations; The crew training module also includes training courses and materials, including but not limited to fixed CO2 fire extinguishing system inspection, operation, and detection teaching videos, daily maintenance and operation guidance videos, and drawings and materials including but not limited to ship fire control diagrams, CO2 system schematics, and detailed information and photos of key equipment and equipment components for in-depth learning and understanding by crew members.

3. According to claim 1, a ship safety emergency life-saving equipment maintenance AI intelligent management platform is characterized by: The intelligent inspection module automatically generates inspection tasks and pushes them to relevant personnel according to the preset inspection plan and equipment maintenance cycle, ensuring that the inspection work is completed on time and with quality. The inspection data is uploaded to the cloud in real time, and the AI ​​algorithm instantly analyzes the health status of the equipment, predicts potential failures, and provides early warnings. It also enables experts to provide real-time guidance and collaboration to front-line personnel through high-definition video calls and remote desktop sharing functions. The inspection process of the third-party maintenance supervision module includes on-site personnel qualifications, inspection content and inspection results, realizes cloud storage of maintenance and inspection content, socializes supervision, conducts comprehensive evaluation of maintenance effects based on AI analysis and user feedback, and continuously optimizes maintenance quality and service levels.

4. According to claim 1, a ship safety emergency life-saving equipment maintenance AI intelligent management platform is characterized by: The electronic archives of the archive management and evidence retention module include learning records, equipment information, inspection records, and maintenance activities, which are easy to trace and query, and automatically collect pictures and video evidence materials during the inspection and maintenance process to ensure compliance with operations and facilitate supervision and review; The reports generated by the report maintenance and data analysis module include but are not limited to training and assessment records, inspection reports, maintenance statistics and fault analysis. It also uses AI algorithms to conduct in-depth mining of massive data, analyze equipment failure patterns, predict future trends, and provide a scientific basis for ship safety management.

5. According to claim 1, a ship safety emergency life-saving equipment maintenance AI intelligent management platform is characterized by: The handheld terminal and / or 5G explosion-proof AR helmet are equipped with an operating system, memory, CPU, graphics card, screen and keyboard / touch screen, and have data collection, communication, GPS / Beidou satellite positioning, photo and video recording, data processing, application software installation, and security protection functions. They are used to automatically identify the status of ship safety equipment, assist crew members in conducting accurate inspections, and upload inspection data to the cloud processor in real time for analysis and processing.

6. According to claim 1, a ship safety emergency life-saving equipment maintenance AI intelligent management platform is characterized by: The crew training module further includes a personalized training path system, which uses AI algorithms to intelligently analyze and customize a unique training plan for each crew member based on the crew member's job requirements, personal experience level, identified skill shortcomings, and historical learning performance multi-dimensional data; The personalized training path system is specifically implemented as follows: Step 1: Multi-dimensional data collection, including job information, experience level, skill gaps and historical learning performance; Step 2: AI algorithm analysis; Step 3: Customize the training plan, including basic safety knowledge and equipment familiarity training and advanced course delivery.

7. According to claim 1, a ship safety emergency life-saving equipment maintenance AI intelligent management platform is characterized by: The crew training module further includes a VR intelligent training and collaboration system, which includes: Interactive VR operation and emergency training module: Use VR technology to reproduce the ship environment, simulate the operation of safety and life-saving equipment and emergency response, and improve the crew's practical operation and emergency response capabilities. Dynamic emergency simulation module: Incorporates unpredictable dynamic changes, including but not limited to fire escalation and equipment failure, tests the crew's immediate decision-making and response capabilities, and provides immediate feedback and improvement suggestions. Multi-person VR collaborative training module: supports simultaneous participation of multiple users, simulates cross-departmental collaboration, strengthens communication and collaboration capabilities among crew members, and improves overall emergency response efficiency.

8. A device for constructing an AI intelligent management platform for ship safety emergency life-saving equipment maintenance, characterized in that: include: A processor, used to execute program instructions stored in the memory to realize the functions of the AI ​​intelligent management platform for ship safety emergency life-saving equipment maintenance, including the operation of crew training, intelligent inspection, third-party maintenance supervision, file management and data analysis modules; A storage device for storing program instructions and data, wherein the program instructions include codes for implementing the functions of the crew training module, intelligent inspection module, third-party maintenance supervision module, and file management and data analysis module, and the data include but are not limited to crew training records, inspection data, maintenance records, and equipment information; Communication interface, used for data exchange and communication with ship safety emergency life-saving equipment, handheld terminals and / or 5G explosion-proof AR helmets, and external equipment of third-party maintenance agencies; Input / output devices are used to receive user input operation instructions and display processing results, including but not limited to keyboards, mice, touch screens and displays.

9. A computer-readable storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a processor, the functions of the ship safety emergency life-saving equipment maintenance AI intelligent management platform as described in any one of claims 1 to 7 are realized.

10. A computer program product, characterized in that It includes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the function of the ship safety emergency life-saving equipment maintenance AI intelligent management platform is realized as described in any one of claims 1 to 7.

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