An AI-based intelligent ship fire fighting and evacuation system and control method

Abstract

The present invention discloses an AI-based intelligent ship fire fighting and evacuation system, which comprises a control module for performing AI analysis on data of a detection module and controlling a drone for auxiliary fire extinguishing, an identification module for identifying and judging the type of fire based on the data of a secondary analysis of the control module, an alarm for timely sounding an alarm when a fire is detected, a detection module for fire detection, an identification module for targeted fire extinguishing according to the identified fire type, and a evacuation module for providing a safe escape route for users based on the positioning of a mobile communication device and an internal 3D channel structure model of the ship; the system of the present invention can automatically detect and identify the type of fire source, automatically give an alarm prompt, and control the identification module for targeted fire extinguishing, thereby improving the efficiency of fire extinguishing and reducing the possibility of flash fire; at the end of fire extinguishing, the thermal imaging instrument will continuously scan the fire scene, search for potential hot spots, and perform secondary fire extinguishing, thereby greatly improving safety and reducing property losses.

Description

Technical Field

[0001] The present invention relates to the field of ship fire fighting technology, and in particular to an AI-based intelligent ship fire fighting and evacuation system and a control method. Background Art

[0002] In recent years, countries around the world have attached more and more importance to the development of the marine economy, and the shipping industry is the first to bear the brunt. In the context of the global village, material transportation is extremely important. Among all means of transportation, ships are more economical than others. Therefore, the shipping industry will pay more and more attention in the coming years. While developing, many problems have also emerged. The problem of fire accidents ranks first. Because ships are far away from land, enclosed spaces and multi-layer structures, as well as the presence of flammable items, even a slight improper handling will result in serious consequences such as ship destruction and death. Even if the fire can be extinguished, it will cause extremely serious casualties and economic losses. Therefore, solving the problem of ship fire accidents is imminent.

[0003] The traditional ship fire emergency system is too simple, the monitoring system is not perfect, and the fire extinguishing system lacks targeted fire extinguishing. When a fire occurs, it is not detected in time and the fire is extinguished before it takes shape, missing the best fire extinguishing period. The extension of the fire extinguishing time will increase the corresponding economic and personnel losses, and there is also the possibility of flashover and re-ignition. At the same time, the traditional ship fire emergency fire extinguishing system still adopts the method of extinguishing with water. Although this fire extinguishing method is relatively economical, it does not effectively extinguish the fire. Current ship equipment is getting closer and closer to electronic fire. Once a fire occurs, water extinguishing cannot be used. Targeted fire extinguishing is performed for specific fires, which not only reduces the fire extinguishing time but also avoids some unnecessary losses. In addition, the internal passage structure of the cabin is very complicated. Unfamiliar crew members or tourists often flee randomly due to nervousness when escaping from a fire, resulting in an inability to escape smoothly and safely. Therefore, the present invention proposes an intelligent ship fire fighting system and control method to solve the problems existing in the prior art. Summary of the invention

[0004] In view of the above problems, the purpose of the present invention is to propose an AI-based intelligent ship fire fighting and evacuation system and control method, which can automatically detect and identify the type of fire source, automatically alarm and prompt, and control the identification module to perform targeted fire extinguishing, thereby improving the fire extinguishing efficiency and reducing the possibility of flash fire; at the end of the fire extinguishing, the thermal imaging instrument will continue to scan the fire scene, looking for potential hot spots, and perform secondary fire extinguishing, which greatly improves safety, protects the lives of crew members, and reduces property losses. At the same time, the system can automatically locate the mobile communication devices of all users on the ship and the point where the fire occurs, and automatically generate recommended escape routes, increasing the safe escape rate of crew members and tourists.

[0005] To achieve the purpose of the present invention, the present invention is implemented through the following technical solutions: an AI-based intelligent ship fire fighting and evacuation system, including a control module, a detection module, an identification module and a evacuation module, the control module includes a data storage unit and an alarm, the data storage unit is used for data transmission and storage and auxiliary fire extinguishing through AI analysis and control of drones, the alarm is used to promptly issue an alarm when a fire is detected, the detection module performs fire detection based on heat detectors, smoke detectors, gas detectors and thermal imaging instruments, the identification module performs targeted fire extinguishing based on water sprinkler fire extinguishers, dry powder fire extinguishers, foam fire extinguishers and carbon dioxide fire extinguishers according to the identified fire types, and the evacuation module provides users with a safe escape route based on the positioning of mobile communication equipment and the internal 3D channel structure model of the ship.

[0006] Further improvements are: the control module also includes a first safety switch, a second safety switch, an AI sub-module and a drone sub-module, the first safety switch and the second safety switch are both in a normally closed state, the AI ​​sub-module is based on a model trained on historical ship fire data, so that it can make early warning judgments when abnormal data (such as a sharp increase in temperature, changes in gas concentration, etc.) occurs, and the drone sub-module reaches the fire source area based on a data collection and storage unit, and transmits back high-definition images, videos and thermal imaging data to help identify the fire level, spread trend and potential danger.

[0007] A further improvement is that the heat detector, smoke detector, gas detector and thermal imaging instrument are all connected to the controller module via a first safety switch, and a power amplifier module is also connected between the first safety switch and the controller module.

[0008] A further improvement is that the sprinkler fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and carbon dioxide fire extinguisher are all connected to the controller module through a second safety switch, and the identification module is arranged between the second safety switch and the sprinkler fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and carbon dioxide fire extinguisher.

[0009] A further improvement is that the guidance module includes multiple communication protocol sub-modules and an escape route generation sub-module. The multiple communication protocol sub-modules select the current best signal source based on the real-time fire data in the control module to perform real-time positioning of the fire occurrence point and the user's location. The escape route generation sub-module is based on the internal 3D channel structure model of the ship, and uses a dynamic path planning algorithm combined with real-time data obtained by the multiple communication protocol sub-modules to generate an automatically updated guidance route and send it to the user's mobile communication device.

[0010] A control method for an AI-based intelligent ship fire fighting and evacuation system comprises the following steps: Step 1: First, the thermal detector and thermal imaging instrument of the detection module collect heat signals, the smoke detector collects smoke signals, and the gas detector collects gas signals. The heat signals, smoke signals and / or gas signals are amplified by the power amplifier module and transmitted to the control module for storage, and synchronously transmitted to the AI ​​submodule, the drone submodule and the grooming module; Step 2: The drone submodule then arrives at the fire source area based on real-time positioning data, and wirelessly transmits high-definition images, videos, and thermal imaging data to the AI ​​submodule, which makes early warning judgments based on the AI ​​prediction algorithm; Step 3: When the AI ​​submodule detects a high-risk fire signal, the controller module will immediately send an alarm command to the alarm to give an alarm prompt, transmit the real-time fire data to the control center and the guidance module, and transmit the heat signal, smoke signal and / or gas signal to the recognition module for recognition and processing; Step 4: The final recognition module identifies the types of the heat signal, smoke signal and / or gas signal received, and activates the water fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and / or carbon dioxide fire extinguisher for targeted fire extinguishing. At the same time, the guidance module generates an escape route based on the location information of the fire occurrence point and sends it to the user's mobile communication device to guide escape; Finally, the thermal imaging instrument will continue to scan the fire scene, monitor residual hot spots and collect thermal signals, amplify the thermal signals through the power amplifier module and transmit them to the controller module for secondary alarm and fire extinguishing.

[0011] A further improvement is that the drone hardware deployment of the drone submodule in step 2 is to install drone base stations on the ship deck and key cabin locations, and equip them with small drones suitable for use in small spaces. When a fire occurs, the drone can take off automatically and go to the fire source for investigation.

[0012] The beneficial effects of the present invention are as follows: the system of the present invention can automatically detect and identify the type of fire source, automatically give an alarm, and control the identification module to perform targeted fire extinguishing, thereby improving the fire extinguishing efficiency and reducing the possibility of flash fire; at the end of the fire extinguishing, the thermal imaging instrument will continue to scan the fire scene, looking for potential hot spots, and perform secondary fire extinguishing, which greatly improves safety and protects the lives of crew members and reduces property losses. At the same time, the system can automatically locate the mobile communication devices of all users on the ship and the point where the fire occurs, and automatically generate recommended escape routes, thereby increasing the safe escape rate of crew members and tourists. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flowchart of the fire protection system of the present invention.

[0014] Figure 2 This is a diagram of the fire protection system control module architecture of the present invention.

[0015] Figure 3 This is the architecture diagram of the fire protection system drainage module of the present invention. DETAILED DESCRIPTION

[0016] In order to deepen the understanding of the present invention, the present invention will be further described in detail below in conjunction with examples. The examples are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention. Example

[0017] according to Figure 1 , Figure 2 and Figure 3 As shown, this embodiment provides an AI-based intelligent ship fire fighting and evacuation system, including a control module, a detection module, an identification module and a evacuation module. The control module includes a controller module, an identification module and an alarm. The controller module is used to control the identification module to perform targeted fire extinguishing. The controller module adopts an S7-200PLC controller. The identification module is used to identify and determine the fire type based on the detection data of the detection module. The alarm is used to issue an alarm in time when a fire is detected. The detection module performs fire detection based on heat detectors, smoke detectors, gas detectors and thermal imaging instruments. The identification module performs targeted fire extinguishing based on a water sprinkler fire extinguisher, a dry powder fire extinguisher, a foam fire extinguisher and a carbon dioxide fire extinguisher according to the identified fire type. The evacuation module provides users with a safe escape route based on the positioning of mobile communication devices.

[0018] Regarding heat detectors, fixed-temperature heat detectors are used in areas of the ship where the temperature changes dramatically and the high-temperature environment is located, such as the ship's engine room, boiler room and kitchen, while differential-temperature heat detectors are used in areas where the temperature changes less but a quick response to fire is required, such as cabins, living areas and warehouses.

[0019] The control module also includes a first safety switch, a second safety switch, an AI sub-module and a drone sub-module. The first safety switch and the second safety switch are both in a normally closed state (i.e., the switches are closed and turned on), so that the intelligent fire-fighting system is in real-time working state. The AI ​​sub-module is based on the ship's historical fire data training model, so that it can make early warning judgments when abnormal data (such as a sharp increase in temperature, changes in gas concentration, etc.) appears. The drone sub-module reaches the fire source area based on the data collection and storage unit, and transmits back high-definition images, videos and thermal imaging data to help identify the fire level, spread trend and potential danger.

[0020] The heat detector, smoke detector, gas detector and thermal imaging instrument are all connected to the controller module through the first safety switch, and a power amplifier module is also connected between the first safety switch and the controller module.

[0021] The sprinkler fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and carbon dioxide fire extinguisher are all connected to the controller module through the second safety switch, and the identification module is arranged between the second safety switch and the sprinkler fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and carbon dioxide fire extinguisher.

[0022] The guidance module includes multiple communication protocol sub-modules and escape route generation sub-modules. The multiple communication protocol sub-modules select the current best signal source based on the real-time fire data in the control module to perform real-time positioning of the fire occurrence point and the user's location. The escape route generation sub-module is based on the internal 3D channel structure model of the ship, and uses a dynamic path planning algorithm combined with real-time data obtained by multiple communication protocol sub-modules to generate an automatically updated guidance route and send it to the user's mobile communication device.

[0023] In this embodiment, in order to prevent the detector transmission line of the detection module from being damaged by fire, IoT technology is used to connect the detector and identification module with the controller module wirelessly. Example

[0024] This embodiment provides a control method for an AI-based intelligent ship fire fighting and evacuation system, comprising the following steps: Step 1: First, the thermal detector and thermal imaging instrument of the detection module collect heat signals, the smoke detector collects smoke signals, and the gas detector collects gas signals. The heat signals, smoke signals and / or gas signals are amplified by the power amplifier module and transmitted to the control module for storage, and synchronously transmitted to the AI ​​submodule, the drone submodule and the grooming module; Step 2: The drone submodule then arrives at the fire source area based on real-time positioning data, and wirelessly transmits high-definition images, videos, and thermal imaging data to the AI ​​submodule, which makes early warning judgments based on the AI ​​prediction algorithm; The drone hardware deployment of the drone sub-module is to install drone base stations on the ship deck and key cabin locations, and equip them with small drones suitable for use in small spaces. When a fire occurs, the drone can take off automatically and go to the fire source for investigation.

[0025] Step 3: When the AI ​​submodule detects a high-risk fire signal, the controller module will immediately send an alarm command to the alarm to give an alarm prompt, transmit the real-time fire data to the control center and the guidance module, and transmit the heat signal, smoke signal and / or gas signal to the recognition module for recognition and processing; Step 4: The final recognition module identifies the types of the heat signal, smoke signal and / or gas signal received, and activates the water fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and / or carbon dioxide fire extinguisher for targeted fire extinguishing. At the same time, the guidance module generates an escape route based on the location information of the fire occurrence point and sends it to the user's mobile communication device to guide escape; Finally, the thermal imaging instrument will continue to scan the fire scene, monitor residual hot spots and collect thermal signals, amplify the thermal signals through the power amplifier module and transmit them to the controller module for secondary alarm and fire extinguishing.

[0026] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An AI-based intelligent ship fire fighting and evacuation system, characterized by: It includes a control module, a detection module, an identification module and a guidance module. The control module includes a data storage unit and an alarm. The data storage unit is used to store and analyze detection data. The identification module is used to identify and determine the fire type based on the data analyzed by the control module. The alarm is used to promptly issue an alarm when a fire is detected. The detection module performs fire detection based on heat detectors, smoke detectors, gas detectors and thermal imaging instruments. The identification module performs targeted fire extinguishing based on water sprinkler fire extinguishers, dry powder fire extinguishers, foam fire extinguishers and carbon dioxide fire extinguishers according to the identified fire type. The guidance module provides users with a safe escape route based on the positioning of mobile communication equipment and the internal 3D channel structure model of the ship.

2. According to claim 1, an AI-based intelligent ship fire fighting and evacuation system is characterized by: The control module also includes a first safety switch and a second safety switch, both of which are in a normally closed state. The data storage unit includes an AI submodule and a drone submodule. The AI ​​submodule makes an early warning judgment when abnormal data appears based on a training model based on historical ship fire data. The drone submodule reaches the fire source area based on the data collection and storage unit, and transmits back high-definition images, videos and thermal imaging data.

3. The AI-based intelligent ship fire fighting and evacuation system according to claim 2 is characterized in that: The heat detector, smoke detector, gas detector and thermal imaging instrument are all connected to the controller module via a first safety switch, and a power amplifier is also connected between the first safety switch and the controller module.

4. According to claim 2, an AI-based intelligent ship fire fighting and evacuation system is characterized by: The sprinkler fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and carbon dioxide fire extinguisher are all connected to the controller module through a second safety switch, and the identification module is arranged between the second safety switch and the sprinkler fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and carbon dioxide fire extinguisher.

5. According to claim 1, the AI-based intelligent ship fire fighting and evacuation system is characterized by: The guidance module includes multiple communication protocol submodules and an escape route generation submodule. The multiple communication protocol submodules select the current best signal source based on the real-time fire data in the control module to locate the fire occurrence point and the user's location in real time. The escape route generation submodule is based on the internal 3D channel structure model of the ship and uses a dynamic path planning algorithm combined with the real-time data obtained by the multiple communication protocol submodules to generate an automatically updated guidance route and send it to the user's mobile communication device.

6. A control method for an AI-based intelligent ship fire fighting and evacuation system, characterized in that: The following steps are involved: Step 1: First, the thermal detector and thermal imaging instrument of the detection module collect heat signals, the smoke detector collects smoke signals, and the gas detector collects gas signals. The heat signal, smoke signal, and gas signal are amplified by the power amplifier module and transmitted to the control module for storage, and synchronously transmitted to the AI ​​submodule, the drone submodule, and the guidance module; Step 2: The drone submodule then arrives at the fire source area based on real-time positioning data, and wirelessly transmits high-definition images, videos, and thermal imaging data to the AI ​​submodule, which makes early warning judgments based on the AI ​​prediction algorithm; Step 3: When the AI ​​submodule detects a high-risk fire signal, the controller module will immediately send an alarm command to the alarm to give an alarm prompt, transmit the real-time fire data to the control center and the guidance module, and transmit the heat signal, smoke signal, and gas signal to the recognition module for recognition and processing; Step 4: Finally, the recognition module identifies the type of signal according to the received heat signal, smoke signal and gas signal, and activates the water fire extinguisher, dry powder fire extinguisher, foam fire extinguisher and carbon dioxide fire extinguisher for targeted fire extinguishing. At the same time, the guidance module generates an escape path based on the location information of the fire occurrence point and sends it to the user's mobile communication device to guide escape; Finally, the thermal imaging instrument will continue to scan the fire scene, monitor residual hot spots and collect thermal signals, amplify the thermal signals through the power amplifier module and transmit them to the controller module for secondary alarm and fire extinguishing.

7. The control method of the AI-based intelligent ship fire fighting and evacuation system according to claim 6 is characterized in that: The drone hardware deployment of the drone submodule in step 2 specifically involves installing drone base stations on the ship deck and key cabin locations, and equipping them with small drones suitable for use in small spaces.

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