CN112380678A - Intelligent auxiliary decision-making platform and decision-making method for emergency evacuation of large passenger ship - Google Patents
Intelligent auxiliary decision-making platform and decision-making method for emergency evacuation of large passenger ship Download PDFInfo
- Publication number
- CN112380678A CN112380678A CN202011203656.5A CN202011203656A CN112380678A CN 112380678 A CN112380678 A CN 112380678A CN 202011203656 A CN202011203656 A CN 202011203656A CN 112380678 A CN112380678 A CN 112380678A
- Authority
- CN
- China
- Prior art keywords
- intelligent
- module
- platform
- simulation
- fire
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000004088 simulation Methods 0.000 claims abstract description 58
- 230000003993 interaction Effects 0.000 claims abstract description 29
- 239000000779 smoke Substances 0.000 claims abstract description 29
- 238000005516 engineering process Methods 0.000 claims abstract description 24
- 238000012937 correction Methods 0.000 claims abstract description 14
- 238000004891 communication Methods 0.000 claims abstract description 9
- 230000008859 change Effects 0.000 claims abstract description 8
- 238000005094 computer simulation Methods 0.000 claims abstract description 8
- 238000005457 optimization Methods 0.000 claims abstract description 7
- 239000002341 toxic gas Substances 0.000 claims abstract description 7
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 5
- 230000005540 biological transmission Effects 0.000 claims abstract description 4
- 239000007921 spray Substances 0.000 claims description 11
- 238000009792 diffusion process Methods 0.000 claims description 10
- 230000007613 environmental effect Effects 0.000 claims description 9
- 239000007789 gas Substances 0.000 claims description 7
- 230000007774 longterm Effects 0.000 claims description 6
- 238000012986 modification Methods 0.000 claims description 4
- 230000004048 modification Effects 0.000 claims description 4
- 230000007480 spreading Effects 0.000 claims description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 4
- 239000013307 optical fiber Substances 0.000 claims description 3
- 238000002922 simulated annealing Methods 0.000 claims description 3
- 238000012790 confirmation Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000004888 barrier function Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000005507 spraying Methods 0.000 description 2
- 238000009423 ventilation Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 1
- DMBHHRLKUKUOEG-UHFFFAOYSA-N diphenylamine Chemical compound C=1C=CC=CC=1NC1=CC=CC=C1 DMBHHRLKUKUOEG-UHFFFAOYSA-N 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/06—Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Emergency Management (AREA)
- Chemical & Material Sciences (AREA)
- Business, Economics & Management (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Analytical Chemistry (AREA)
- Alarm Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides an intelligent auxiliary decision-making platform for emergency evacuation of a large passenger ship, which comprises a data attribute collection module, a machine-machine data interaction module and an emergency plan virtual simulation platform, wherein the emergency plan virtual simulation platform comprises a virtual mapping module, a fire/smoke dynamic simulation module, a machine-machine interaction correction module and an intelligent decision-making output module, and the decision-making method comprises the following steps: the collection and transmission of attribute data are realized through the technology of Internet of things and/or 5G communication; simulating the dynamic change trend of fire, smoke and toxic gas by CFD simulation software; manually confirming the simulation result through VR simulation; outputting an intelligent emergency evacuation scheme of multi-objective optimization by combining a GIS technology and a system engineering theory; the invention combines artificial intelligence, virtual simulation, digital twin, 5G communication and Internet of things technology, so that the system has the functions of remote identification, intelligent simulation, multiple control and intelligent decision.
Description
Technical Field
The invention relates to the technical field of emergency management, in particular to an intelligent auxiliary decision-making platform and a decision-making method for emergency evacuation of a large passenger ship.
Background
The passenger ship tourism industry is a new industry with huge development potential, the market share is increased year by year, and the whole development level far higher than the international tourism industry is presented, however, passenger ship accidents frequently occur in recent years, the development of the industry is seriously hindered, and particularly after the research and discovery of many water accidents in recent years, the site order, the personnel psychology and the external guidance are the keys of emergency evacuation, so that whether the passengers can be correctly evacuated in the face of emergencies or not at the present stage, the occurrence of secondary accidents is prevented, the emergency evacuation efficiency is provided, and the passenger ship tourism industry becomes an important research subject for providing the safety and the emergency capacity of the passenger ship.
The invention patent 201910751569.4 provides a method for atmospheric diffusion prediction based on CFD simulation technology, but does not answer emergency evacuation plans; the invention patent 201911021687.6 provides an emergency evacuation method based on a digital twinning technology, but the method only builds a three-dimensional model through CAD drawing and GIS technology, detects the physical world through video monitoring, cannot identify the physical world in real time in a smog diffused space, and does not consider the influence of external factors on evacuation; the invention patent 201711392966.4 discloses emergency evacuation scheme which is based on data acquisition of behavior of a tested person in VR space, but the emergency evacuation scheme cannot deal with evacuation in real time under the environment with real-time change.
Therefore, regarding emergency evacuation of a large passenger ship, it is necessary to provide a solution that can recognize changes in the physical world in real time and can respond to multiple emergency evacuation schemes quickly, and the solution has been selected, and meanwhile, uncontrollable factors caused by too long time are considered while emergency evacuation is performed, so that external assistance needs to be sought, economic loss and casualties need to be evaluated quickly, whether fire fighting configuration can be optimized, whether space layout can be optimized, and the like, and the above problems still need to be solved urgently at present.
Disclosure of Invention
The invention aims to provide an intelligent auxiliary decision-making platform and a decision-making method for emergency evacuation of a large passenger ship.
In order to achieve the purpose, the technical scheme of the invention is as follows:
an intelligent aid decision-making platform for emergency evacuation of a large passenger ship is characterized by comprising a data attribute collection module, a machine-machine data interaction module and an emergency plan virtual simulation platform, wherein the emergency plan virtual simulation platform comprises a virtual mapping module, a fire/smoke dynamic simulation module, a machine-machine interaction correction module and an intelligent decision-making output module.
Furthermore, the fire/smoke dynamic simulation module comprises a CFD simulation platform, the intelligent decision output module comprises an intelligent auxiliary decision platform, and data interaction is carried out between the CFD simulation platform and the intelligent auxiliary decision platform through a machine-computer data interaction module.
Further, the virtual mapping module comprises a VR device, and the VR device acquires a simulation result of the CFD simulation platform through the machine-machine data interaction module.
An intelligent aid decision-making method for emergency evacuation of a large passenger ship is characterized by comprising the following steps:
step 1) realizing collection and transmission of attribute data through Internet of things technology and/or 5G communication;
step 2) simulating the dynamic change trend of fire, smoke and toxic gas through CFD simulation software;
step 3) manually confirming the simulation result through VR simulation;
and 4) combining the GIS technology and the system engineering theory to output an intelligent emergency evacuation scheme of multi-objective optimization.
Further, the step 1 comprises:
identifying and positioning information of a space position, positions of a gas sensor and a smoke sensor, a vent position, a window area and a position, a spray head position and water spray quantity, a door area and a position by an infrared scanner, and transmitting the information identified and positioned by the infrared scanner to a data attribute collection module by 5G communication and optical fibers;
the data attribute collection module converts the information into binary signals through the Internet of things technology and then remotely transmits the binary signals to the emergency plan virtual simulation platform.
Further, the step 2 and the step 3 comprise simulating the diffusion and spreading change trend of fire, smoke and toxic gas in the virtual space through a CFD simulation platform;
optimizing the diffusion of fire/smoke according to different environmental conditions by combining the GIS technology and the artificial intelligence technology with data attributes;
and displaying the simulation result of the CFD simulation platform in a three-dimensional virtual space through the VR device.
Further, the environmental conditions include whether the window is opened, whether ventilation exists, whether personnel and personnel positions exist, whether barriers exist, whether the fire fighting system works normally and the like, and the environmental conditions are transmitted in real time through the internet of things technology and are measured in hours.
Further, the step 3 includes judging whether the simulation result displayed by the VR device is feasible or not through the human-computer interaction correction module, interactively transmitting the modification suggestion through the human-computer data module back to the CFD simulation platform for correction until the human-computer interaction correction module confirms that the scheme is feasible, and then transmitting the simulation result of the CFD simulation platform to the intelligent decision output module.
Further, the step 4 includes that the intelligent assistant decision platform acquires a simulation result of the CFD simulation platform through machine-computer data interaction, performs multi-objective optimization based on a simulated annealing method and a system engineering theory of parallel computing and distributed computing, makes short, medium and long-term intelligent assistant emergency evacuation schemes, and outputs the result.
Further, the short-term intelligent auxiliary emergency evacuation scheme comprises the steps of judging whether fire disasters can be eliminated under the condition of pure fire spraying; if the local personnel evacuation is feasible, only a local personnel evacuation scheme needs to be formulated; if not, making an evacuation scheme for all people on the premise of fire alarm;
the middle-term intelligent auxiliary emergency evacuation scheme comprises the steps of evaluating casualties and economic losses on the basis of a personnel evacuation scheme, identifying whether nearby ships exist through a Beidou satellite positioning system so as to transmit emergency rescue signals, or identifying whether the ships can return to nearby ports through the Beidou satellite positioning system;
the scheme for the long-term intelligent auxiliary emergency evacuation comprises the steps of carrying out space layout and optimal configuration of fire fighting positions, fire fighting amount and the like through short-term and medium-term output results.
The invention combines artificial intelligence, virtual simulation, digital twin, 5G communication and Internet of things technology, so that the system has the functions of remote identification, intelligent simulation, multiple control and intelligent decision;
all functions are integrated into the virtual simulation platform of the emergency plan, so that the effects of second-level fire judgment, minute-level evacuation scheme output, hour-level emergency rescue and the like can be achieved;
the intelligent evacuation system has the functions of intelligent output and intelligent management, can make an emergency evacuation scheme, can estimate economy and casualties, can optimize and improve the existing space fire fighting access and fire fighting measures, and has good industrial application prospect.
Drawings
FIG. 1 is a schematic view of the working procedure of embodiment 1 of the present invention;
fig. 2 is a schematic workflow diagram of embodiments 2, 3, and 4 of the present invention.
Reference numerals:
1 data attribute collection module 2 virtual mapping module 3 fire/smoke dynamic simulation module
4 a man-machine interaction correction module 5, an intelligent decision output module 6 and a machine-machine data interaction module.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention discloses an intelligent auxiliary decision-making platform for emergency evacuation of a large passenger ship, which comprises a data attribute collection module 1, a machine-machine data interaction module 6 and an emergency plan virtual simulation platform as shown in figure 1, wherein the emergency plan virtual simulation platform comprises a virtual mapping module 2, a fire/smoke dynamic simulation module 3, a human-machine interaction correction module 4 and an intelligent decision-making output module 5.
The fire/smoke dynamic simulation module 3 comprises a CFD simulation platform, the intelligent decision output module 5 comprises an intelligent auxiliary decision platform, and data interaction is carried out between the CFD simulation platform and the intelligent auxiliary decision platform through a machine-computer data interaction module 6.
The virtual mapping module 2 comprises a VR device, and the VR device acquires a simulation result of the CFD simulation platform through the machine-machine data interaction module 6.
An intelligent aid decision-making method for emergency evacuation of a large passenger ship comprises the following steps:
step 1) realizing collection and transmission of attribute data through Internet of things technology and/or 5G communication;
step 2) simulating the dynamic change trend of fire, smoke and toxic gas through CFD simulation software;
step 3) manually confirming the simulation result through VR simulation;
and 4) combining the GIS technology and the system engineering theory to output an intelligent emergency evacuation scheme of multi-objective optimization.
The step 1 comprises the following steps:
identifying and positioning information of a space position, positions of a gas sensor and a smoke sensor, a vent position, a window area and a position, a spray head position and water spray quantity, a door area and a position by an infrared scanner, and transmitting the information identified and positioned by the infrared scanner to a data attribute collection module 1 by 5G communication and optical fibers;
the data attribute collection module 1 converts information into binary signals through the internet of things technology and remotely transmits the binary signals to the emergency plan virtual simulation platform.
The step 2 and the step 3 comprise simulating the diffusion, spreading and change trend of fire, smoke and toxic gas in the virtual space through a CFD simulation platform;
optimizing the diffusion of fire/smoke according to different environmental conditions by combining the GIS technology and the artificial intelligence technology with data attributes;
and displaying the simulation result of the CFD simulation platform in a three-dimensional virtual space through the VR device.
The environmental conditions comprise whether windows are opened or not, whether ventilation exists or not, whether personnel and personnel positions exist or not, whether barriers exist or not, whether the fire fighting system works normally or not and the like, and the environmental conditions are transmitted in real time through the Internet of things technology and are measured in hours.
And the step 3 comprises the steps of judging whether the simulation result displayed by the VR device is feasible or not through the human-computer interaction correction module 4, interactively transmitting the modification suggestion back to the CFD simulation platform through the human-computer data module for correction until the human-computer interaction correction module 4 confirms that the scheme is feasible, and then transmitting the simulation result of the CFD simulation platform to the intelligent decision output module 5.
And 4, the intelligent auxiliary decision platform acquires a simulation result of the CFD simulation platform through machine-computer data interaction, performs multi-objective optimization based on a simulated annealing method and a system engineering theory of parallel computing and distributed computing, and makes short, medium and long-term intelligent auxiliary emergency evacuation schemes and outputs the result.
The short-term intelligent auxiliary emergency evacuation scheme comprises the steps of judging whether fire disasters can be eliminated under the condition of pure fire spraying; if the local personnel evacuation is feasible, only a local personnel evacuation scheme needs to be formulated; if not, making an evacuation scheme for all people on the premise of fire alarm;
the middle-term intelligent auxiliary emergency evacuation scheme comprises the steps of evaluating casualties and economic losses on the basis of a personnel evacuation scheme, identifying whether nearby ships exist through a Beidou satellite positioning system so as to transmit emergency rescue signals, or identifying whether the ships can return to nearby ports through the Beidou satellite positioning system;
the scheme for the long-term intelligent auxiliary emergency evacuation comprises the steps of carrying out space layout and optimal configuration of fire fighting positions, fire fighting amount and the like through short-term and medium-term output results.
Example one
As shown in fig. 1, when the emergency plan virtual simulation platform recognizes that a large passenger ship has a gas sensor and/or a smoke sensor to send out an alarm signal, the fire source and the fire situation are recognized through data uploaded by the remote infrared scanner, smoke diffusion simulation is performed through the CFD simulation platform in the emergency plan virtual simulation platform, manual confirmation is performed through the VR platform, if the system is identified as fire extinguishing spray, the fire can be eliminated, only the evacuation scheme of partial region personnel is output, and casualties and economic losses are evaluated.
Example two
As shown in fig. 2, when the emergency plan virtual simulation platform recognizes that a large passenger ship has a gas sensor and/or a smoke sensor to send out an alarm signal, the fire source and the fire situation are recognized through data uploaded by a remote infrared scanner, smoke diffusion simulation is performed through a CFD simulation platform in the emergency plan virtual simulation platform, manual confirmation is performed through a VR platform, if the system is identified as that the fire cannot be eliminated under the condition of pure fire spray, an evacuation scheme of all personnel needs to be formulated, casualties and economic losses of the personnel are evaluated, meanwhile, whether the ship is near or not is recognized through a Beidou satellite positioning system, and if the ship is near, an emergency rescue signal is transmitted to wait for rescue; and an intelligent auxiliary decision-making platform built in the emergency plan virtual simulation platform outputs an optimized configuration scheme of spatial layout, fire fighting position, usage amount and the like.
EXAMPLE III
As shown in fig. 2, when the emergency plan virtual simulation platform recognizes that a large passenger ship has a gas sensor and/or a smoke sensor to send out an alarm signal, the fire source and the fire situation are recognized through data uploaded by a remote infrared scanner, smoke diffusion simulation is performed through a CFD simulation platform in the emergency plan virtual simulation platform, manual confirmation is performed through a VR platform, if the system is identified as that the fire cannot be eliminated under the condition of pure fire spray, an evacuation scheme of all personnel needs to be formulated, casualties and economic losses are evaluated, meanwhile, a big dipper satellite positioning system is used to recognize whether a ship is near, if the system is not capable of returning to a near port, if the system is capable of returning to the near port, a return path is output through an intelligent auxiliary decision making platform built in the emergency plan virtual simulation platform, and space layout, fire fighting position and dosage and the like.
Example four
As shown in fig. 2, when the emergency plan virtual simulation platform recognizes that a large passenger ship has a gas sensor and/or a smoke sensor to send out an alarm signal, the fire source and the fire condition are identified through the data uploaded by the remote infrared scanner, the smoke diffusion simulation is carried out through a CFD simulation platform in the emergency plan virtual simulation platform, and the artificial confirmation is carried out through the VR platform, if the system is identified as the fire-fighting spray, the fire can not be eliminated, then the evacuation scheme of all the people needs to be formulated, casualties and economic losses are evaluated, meanwhile, the Beidou satellite positioning system is used for identifying whether nearby ships exist or not, if not, and continuously identifying whether the vehicle has the ability to return to the nearby port through the Beidou satellite positioning system, and if not, outputting an optimal configuration scheme of space layout, fire fighting position, usage amount and the like while waiting for air rescue.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An intelligent aid decision-making platform for emergency evacuation of a large passenger ship is characterized by comprising a data attribute collection module, a machine-machine data interaction module and an emergency plan virtual simulation platform, wherein the emergency plan virtual simulation platform comprises a virtual mapping module, a fire/smoke dynamic simulation module, a machine-machine interaction correction module and an intelligent decision-making output module.
2. The intelligent aid decision platform for emergency evacuation of large passenger ships according to claim 1, wherein the fire/smoke dynamic simulation module comprises a CFD simulation platform, the intelligent decision output module comprises an intelligent aid decision platform, and data interaction is performed between the CFD simulation platform and the intelligent aid decision platform through a machine-computer data interaction module.
3. The platform of claim 2, wherein the virtual mapping module comprises a VR device, and the VR device obtains a simulation result of the CFD simulation platform through a machine-computer data interaction module.
4. An intelligent aid decision-making method for emergency evacuation of a large passenger ship is characterized by comprising the following steps:
step 1) realizing collection and transmission of attribute data through Internet of things technology and/or 5G communication;
step 2) simulating the dynamic change trend of fire, smoke and toxic gas through CFD simulation software;
step 3) manually confirming the simulation result through VR simulation;
and 4) combining the GIS technology and the system engineering theory to output an intelligent emergency evacuation scheme of multi-objective optimization.
5. An intelligent aid decision-making method for emergency evacuation of large passenger ships according to claim 4, wherein the step 1 comprises:
identifying and positioning information of a space position, positions of a gas sensor and a smoke sensor, a vent position, a window area and a position, a spray head position and water spray quantity, a door area and a position by an infrared scanner, and transmitting the information identified and positioned by the infrared scanner to a data attribute collection module by 5G communication and optical fibers;
the data attribute collection module converts the information into binary signals through the Internet of things technology and then remotely transmits the binary signals to the emergency plan virtual simulation platform.
6. An intelligent aid decision-making method for emergency evacuation of a large passenger ship according to claim 4, wherein the steps 2 and 3 comprise simulating the spreading and spreading change trend of fire, smoke and toxic gas in a virtual space through a CFD simulation platform;
optimizing the diffusion of fire/smoke according to different environmental conditions by combining the GIS technology and the artificial intelligence technology with data attributes;
and displaying the simulation result of the CFD simulation platform in a three-dimensional virtual space through the VR device.
7. An intelligent aid decision-making method for emergency evacuation of a large passenger ship according to claim 6, wherein the environmental conditions include whether to open windows, whether to ventilate, whether to have personnel and personnel positions, whether to have obstacles, whether to have a fire-fighting system working normally, etc., and the environmental conditions are transmitted in real time in hours by internet of things.
8. The intelligent aid decision-making method for emergency evacuation of large passenger ships according to claim 4, wherein the step 3 comprises determining whether the simulation result displayed by the VR device is feasible or not through the man-machine interaction correction module, interactively transmitting the modification suggestion back to the CFD simulation platform through the man-machine interaction data module for correction until the man-machine interaction correction module confirms that the scheme is feasible, and then transmitting the simulation result of the CFD simulation platform to the intelligent decision-making output module.
9. The intelligent aid decision-making method for emergency evacuation of a large-scale passenger ship according to claim 4, wherein the step 4 comprises the steps of obtaining a simulation result of the CFD simulation platform through computer-computer data interaction by the intelligent aid decision-making platform, performing multi-objective optimization based on a simulated annealing method and a system engineering theory of parallel computing and distributed computing, making a short-term, medium-term and long-term intelligent aid emergency evacuation scheme, and outputting the result.
10. An intelligent aid decision-making method for emergency evacuation of a large passenger ship according to claim 9, characterized in that the short-term intelligent aid emergency evacuation scheme comprises that if a fire can be eliminated in case of determining a fire-fighting spray alone; if the local personnel evacuation is feasible, only a local personnel evacuation scheme needs to be formulated; if not, making an evacuation scheme for all people on the premise of fire alarm;
the middle-term intelligent auxiliary emergency evacuation scheme comprises the steps of evaluating casualties and economic losses on the basis of a personnel evacuation scheme, identifying whether nearby ships exist through a Beidou satellite positioning system so as to transmit emergency rescue signals, or identifying whether the ships can return to nearby ports through the Beidou satellite positioning system;
the scheme for the long-term intelligent auxiliary emergency evacuation comprises the steps of carrying out space layout and optimal configuration of fire fighting positions, fire fighting amount and the like through short-term and medium-term output results.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011203656.5A CN112380678B (en) | 2020-11-02 | 2020-11-02 | Intelligent auxiliary decision making system and decision making method for emergency evacuation of large passenger ship |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011203656.5A CN112380678B (en) | 2020-11-02 | 2020-11-02 | Intelligent auxiliary decision making system and decision making method for emergency evacuation of large passenger ship |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112380678A true CN112380678A (en) | 2021-02-19 |
| CN112380678B CN112380678B (en) | 2024-07-23 |
Family
ID=74576097
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011203656.5A Active CN112380678B (en) | 2020-11-02 | 2020-11-02 | Intelligent auxiliary decision making system and decision making method for emergency evacuation of large passenger ship |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112380678B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112989655A (en) * | 2021-03-01 | 2021-06-18 | 中国石油大学(北京) | Ram blowout preventer shearing performance prediction method, device, equipment and storage medium |
| CN113327394A (en) * | 2021-05-28 | 2021-08-31 | 江苏科技大学 | Digital twin system for fire control monitoring of ship |
| CN113727279A (en) * | 2021-11-03 | 2021-11-30 | 武汉理工大学 | Ship emergency evacuation method based on indoor and outdoor position information |
| CN113920809A (en) * | 2021-10-29 | 2022-01-11 | 航天科工武汉磁电有限责任公司 | Mixed reality teaching system for ship fire-fighting training |
| CN114527757A (en) * | 2022-02-24 | 2022-05-24 | 哈尔滨工程大学 | Ocean passenger ship personnel emergency evacuation path planning algorithm based on virtual nodes |
| CN116805401A (en) * | 2023-05-30 | 2023-09-26 | 北京交通大学 | Site management method, system, equipment and medium based on AR equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102117528A (en) * | 2011-01-14 | 2011-07-06 | 同济大学 | Dynamic feedback type tunnel fire intelligent evacuating and rescuing system based on digitizing technique |
| CN109598076A (en) * | 2018-12-10 | 2019-04-09 | 北京交通大学 | A kind of urban track traffic emergency evacuation analogue system and method |
| CN110110389A (en) * | 2019-04-03 | 2019-08-09 | 河南城建学院 | A kind of indoor and outdoor evacuation emulation method that actual situation combines |
| WO2020187668A1 (en) * | 2019-03-15 | 2020-09-24 | Luxembourg Institute Of Science And Technology (List) | Ship evacuation system |
-
2020
- 2020-11-02 CN CN202011203656.5A patent/CN112380678B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102117528A (en) * | 2011-01-14 | 2011-07-06 | 同济大学 | Dynamic feedback type tunnel fire intelligent evacuating and rescuing system based on digitizing technique |
| CN109598076A (en) * | 2018-12-10 | 2019-04-09 | 北京交通大学 | A kind of urban track traffic emergency evacuation analogue system and method |
| WO2020187668A1 (en) * | 2019-03-15 | 2020-09-24 | Luxembourg Institute Of Science And Technology (List) | Ship evacuation system |
| CN110110389A (en) * | 2019-04-03 | 2019-08-09 | 河南城建学院 | A kind of indoor and outdoor evacuation emulation method that actual situation combines |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112989655A (en) * | 2021-03-01 | 2021-06-18 | 中国石油大学(北京) | Ram blowout preventer shearing performance prediction method, device, equipment and storage medium |
| CN112989655B (en) * | 2021-03-01 | 2023-11-03 | 中国石油大学(北京) | Method, device, equipment and storage medium for predicting shearing performance of ram blowout preventer |
| CN113327394A (en) * | 2021-05-28 | 2021-08-31 | 江苏科技大学 | Digital twin system for fire control monitoring of ship |
| CN113920809A (en) * | 2021-10-29 | 2022-01-11 | 航天科工武汉磁电有限责任公司 | Mixed reality teaching system for ship fire-fighting training |
| CN113727279A (en) * | 2021-11-03 | 2021-11-30 | 武汉理工大学 | Ship emergency evacuation method based on indoor and outdoor position information |
| CN113727279B (en) * | 2021-11-03 | 2022-01-25 | 武汉理工大学 | Ship emergency evacuation method based on indoor and outdoor position information |
| CN114527757A (en) * | 2022-02-24 | 2022-05-24 | 哈尔滨工程大学 | Ocean passenger ship personnel emergency evacuation path planning algorithm based on virtual nodes |
| CN114527757B (en) * | 2022-02-24 | 2024-05-31 | 哈尔滨工程大学 | Ocean passenger ship personnel emergency evacuation path planning algorithm based on virtual nodes |
| CN116805401A (en) * | 2023-05-30 | 2023-09-26 | 北京交通大学 | Site management method, system, equipment and medium based on AR equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112380678B (en) | 2024-07-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112380678A (en) | Intelligent auxiliary decision-making platform and decision-making method for emergency evacuation of large passenger ship | |
| CN112766909A (en) | Intelligent management and control system and method suitable for ship fire safety and computer medium | |
| CN113706355A (en) | Method for building intelligent emergency system of chemical industry park | |
| CN107240216A (en) | Based on 3DGIS+BIM technologies and artificial intelligence O＆M emergent alarm and fast response method | |
| CN112488898B (en) | Emergency handling system and method based on intelligent building management and control | |
| CN111523277B (en) | Fire prediction method, storage device and processor | |
| CN118091054B (en) | Dangerous gas on-line monitoring system and method | |
| CN110853137A (en) | Guiding fire prevention and fire fighting rescue system and method based on three-dimensional scene reduction | |
| CN112102583A (en) | Intelligent building system based on big data | |
| CN112333355A (en) | Tunnel inspection system | |
| CN115809750A (en) | Intelligent evacuation method and system based on-line fire hazard risk evaluation | |
| CN115115117A (en) | Intelligent processing and analyzing system based on block chain | |
| CN111882809A (en) | Method and system for guaranteeing fire safety of residential area based on Internet of things | |
| CN113194140A (en) | Integrated remote monitoring system based on fire-fighting robot | |
| CN113188599A (en) | Wisdom district environmental monitoring system | |
| CN111832173A (en) | Multi-agent emergency evacuation simulation model based on GAMA platform | |
| CN116805401B (en) | Site management method, system, equipment and medium based on AR equipment | |
| CN117122859B (en) | Intelligent voice interaction fire-fighting guard system and method | |
| Qian | Evaluation on sustainable development of fire safety management policies in smart cities based on big data | |
| KR102374541B1 (en) | Decision Support System | |
| CN115862258B (en) | Fire monitoring and disposing system, method, equipment and storage medium | |
| CN117111540A (en) | Environment monitoring and early warning method and system for IO remote control bus module | |
| CN118015805A (en) | Intelligent dispatching system and method for miniature fire station based on Internet of things | |
| Cui et al. | Integrating Bluetooth-Enabled Sensors with Cloud Computing for Fire Hazard Communication Systems | |
| CN116778685A (en) | Automatic warning method and system for building sudden accidents |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Country or region after: China Address after: 200032 Room 201, building 2, 851 Zhongshan South 2nd Road, Xuhui District, Shanghai Applicant after: SHANGHAI SHENBO INFORMATION SYSTEM ENGINEERING Co.,Ltd. Applicant after: Shanghai Shipbuilding Technology Research Institute (the 11th Research Institute of China Shipbuilding Corp.) Address before: 200032 Room 201, building 2, 851 Zhongshan South 2nd Road, Xuhui District, Shanghai Applicant before: SHANGHAI SHENBO INFORMATION SYSTEM ENGINEERING Co.,Ltd. Country or region before: China Applicant before: SHIPBUILDING TECHNOLOGY Research Institute (NO 11 RESEARCH INSTITUTE OF CHINA STATE SHIPBUILDING Corp.,Ltd.) |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |