CN111686392A - Artificial intelligence fire extinguishing system is surveyed to full scene of vision condition - Google Patents
Artificial intelligence fire extinguishing system is surveyed to full scene of vision condition Download PDFInfo
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Abstract
The invention discloses a full-view fire detection artificial intelligence fire extinguishing system, which relates to the technical field of artificial intelligence and comprises an artificial intelligence platform for receiving information, a fire detection module, a man-machine interaction module and a fire extinguishing module, wherein the fire detection module, the man-machine interaction module and the fire extinguishing module are connected with the artificial intelligence platform, the artificial intelligence platform is used for receiving data information monitored by the modules and analyzing and processing the data information, and the artificial intelligence platform analyzes the relevance between a fire occurrence point and a nearest certain fire extinguishing module according to an output result after analysis and a layout position of the fire extinguishing module according to an artificial intelligence linkage strategy and the layout position of the fire extinguishing module and can control the fire extinguishing module to go to the fire occurrence point of a specified area to perform fire extinguishing processing. This artificial intelligence fire extinguishing systems is surveyed to full scene of vision condition, the condition of fire detection module based on the distributed overall arrangement of full scene of vision is judged the conflagration emergence point to carry out the linkage through artificial intelligence and fire-fighting robot's overall arrangement position, can be quick put out a fire the preliminary treatment to the conflagration emergence point.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a full-field fire detection artificial intelligence fire extinguishing system.
Background
At present, with the continuous development of social science and technology, an artificial intelligence system is an intelligent system which can simulate the real link of biological cerebral neurons in the brain and has the capability of autonomously analyzing external signals. However, the traditional fire system generally comprises a fire detector and a regional alarm, because the detector has poor intelligence, false alarm and delayed alarm often occur, so that the functionality of the system is greatly reduced, meanwhile, before a fire brigade comes, the fire occurrence point is difficult to be preprocessed, and the fire extinguishing time is prolonged.
Therefore, the artificial intelligent fire extinguishing system for the fire detection in the full view field is provided to solve the problems.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an artificial intelligent fire extinguishing system for fire detection in a full view field, which aims to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: an artificial intelligence fire extinguishing system for fire detection in a full view field comprises an artificial intelligence platform for receiving information, and a fire detection module, a human-computer interaction module and a fire extinguishing module which are connected with the artificial intelligence platform;
the artificial intelligence platform is used for receiving the data information monitored by each module and analyzing and processing the data information, and the artificial intelligence platform analyzes the relevance between a fire occurrence point and a nearest certain fire extinguishing module according to an output result after analysis and a layout position of the fire extinguishing module according to an artificial intelligence linkage strategy and the layout position of the fire extinguishing module, and can control the fire extinguishing module to go to the fire occurrence point of a specified area for fire extinguishing processing;
the fire detection module comprises flame image acquisition equipment and smoke image acquisition equipment, wherein the flame image acquisition equipment is used for preprocessing an acquired flame image and transmitting the flame image to the artificial intelligence platform for geometric characteristic analysis, and the smoke image acquisition equipment is used for preprocessing the acquired smoke image and transmitting the smoke image to the artificial intelligence platform for geometric characteristic analysis;
the man-machine interaction module comprises loudspeakers and an electronic display screen which are distributed in a region, the loudspeakers are used for early warning and broadcasting related personnel possibly existing in the region and explaining the specific position of a fire occurrence point, and the electronic display screen marks the fire occurrence point in the region and displays a specific escape route;
the fire extinguishing module comprises a plurality of fire fighting robots for extinguishing fire, the fire fighting robots adopt laser navigation and generate an area map by a laser ranging method, fire extinguishing routes of the fire fighting robots are reasonably planned on the basis, a rotatable laser emitting head and a matched receiver are arranged at the top ends of the fire fighting robots, the distances from the fire fighting robots to each point on the boundary are scanned by emitting laser, so that specific routes for extinguishing fire are generated, and reasonable fire extinguishing routes are provided for a plurality of follow-up fire fighting robots.
Further optimize this technical scheme, flame image acquisition equipment, flue gas image acquisition equipment in the fire detection module all carry out regional distributing type installation based on the panorama overall arrangement, flame image acquisition equipment, flue gas image acquisition equipment adopt the combination of 360 high definition probes and high-speed ball camera equipment to obtain the flame image and the flue gas image of real-time full field of view.
Further optimizing the technical scheme, the geometric characteristics of the flame image and the smoke image comprise the area of flame, the area of smoke outline, the edge perimeter of flame and the edge perimeter of smoke outline, the areas of flame and smoke are obtained by the artificial intelligence platform based on the data of a plurality of static images through weighted average, the edges of flame and smoke are obtained by the artificial intelligence platform based on the data of a plurality of static images through weighted average, and the geometric data of the flame image and the smoke image after analysis are output.
Further optimizing the technical scheme, the geometric data of the flame image and the smoke image are calculated through a circularity calculation formula to obtain the circularity of the flame and the circularity of the smoke, and whether the fire accident happens is judged according to different preset threshold values of the circularity of the flame and the circularity of the smoke.
Further optimizing the technical scheme, the preset threshold value of the smoke circularity is 3, if the image of the smoke circularity larger than 3 is calculated, the smoke image of the fire accident is judged, otherwise, the smoke image of the non-fire accident is judged, the preset threshold value of the flame circularity is 2, if the image of the flame circularity larger than 2 is calculated, the flame image of the fire accident is judged, otherwise, the flame image of the non-fire accident is judged.
Further optimizing the technical scheme, the fire-fighting robot in the fire-fighting module comprises a plurality of jet ports, the jet mode of the jet ports adopts a jet flow type, and different jet ports are selected for targeted fire extinguishing according to different dangerous goods on fire.
According to the technical scheme, different types of fire extinguishing articles, such as water, carbon dioxide, dry powder and other fire extinguishing articles based on physical or chemical principles, are connected with the plurality of spraying ports.
The technical scheme is further optimized, the artificial intelligence platform simulates the activity mode of nerve cells in human or animal brains based on an artificial neural network operation technology, relevant data are added into convolutional neural network model parameters after fire extinguishment each time, the models are trained, the trained models are stored, and data operation models preset by a system are formed and used for analyzing and processing the data, so that the subsequent convolutional neural network models improve the identification accuracy.
Compared with the prior art, the invention provides an artificial intelligent fire extinguishing system for fire detection in a full view field, which has the following beneficial effects:
this artificial intelligence fire extinguishing systems is surveyed to full scene of vision condition, the condition of fire detection module based on the distributed overall arrangement of full scene of vision is judged the conflagration emergence point to carry out the linkage through artificial intelligence and fire-fighting robot's overall arrangement position, can be quick put out a fire the preliminary treatment to the conflagration emergence point, and according to the type of the hazardous articles that catch fire, select the article of putting out a fire that correspond and put out a fire, thereby prevent the scale enlargement of conflagration.
Drawings
Fig. 1 is a schematic structural diagram of a full-field fire detection artificial intelligence fire extinguishing system provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Example (b):
referring to fig. 1, a fire detection artificial intelligence fire extinguishing system for a full view field comprises an artificial intelligence platform for receiving information, a fire detection module, a man-machine interaction module and a fire extinguishing module, wherein the fire detection module, the man-machine interaction module and the fire extinguishing module are connected with the artificial intelligence platform;
the artificial intelligence platform is used for receiving the data information monitored by each module and analyzing and processing the data information, and the artificial intelligence platform analyzes the relevance between a fire occurrence point and a nearest certain fire extinguishing module according to an output result after analysis and a layout position of the fire extinguishing module according to an artificial intelligence linkage strategy and the layout position of the fire extinguishing module, and can control the fire extinguishing module to go to the fire occurrence point of a specified area for fire extinguishing processing;
the fire detection module comprises flame image acquisition equipment and smoke image acquisition equipment, wherein the flame image acquisition equipment is used for preprocessing an acquired flame image and transmitting the flame image to the artificial intelligence platform for geometric characteristic analysis, and the smoke image acquisition equipment is used for preprocessing the acquired smoke image and transmitting the smoke image to the artificial intelligence platform for geometric characteristic analysis;
the man-machine interaction module comprises loudspeakers and an electronic display screen which are distributed in a region, the loudspeakers are used for early warning and broadcasting related personnel possibly existing in the region and explaining the specific position of a fire occurrence point, and the electronic display screen marks the fire occurrence point in the region and displays a specific escape route;
the fire extinguishing module comprises a plurality of fire fighting robots for extinguishing fire, the fire fighting robots adopt laser navigation and generate an area map by a laser ranging method, fire extinguishing routes of the fire fighting robots are reasonably planned on the basis, a rotatable laser emitting head and a matched receiver are arranged at the top ends of the fire fighting robots, the distances from the fire fighting robots to each point on the boundary are scanned by emitting laser, so that specific routes for extinguishing fire are generated, and reasonable fire extinguishing routes are provided for a plurality of follow-up fire fighting robots.
Specifically, flame image acquisition equipment and flue gas image acquisition equipment in the fire detection module are all based on the panorama layout and carry out regional distributed installation, flame image acquisition equipment, flue gas image acquisition equipment adopt the combination of 360 high definition probes and high-speed ball camera equipment to obtain the flame image and the flue gas image of real-time full visual field.
Specifically, the geometric features of the flame image and the smoke image include the area of flame, the area of smoke outline, the edge perimeter of flame and the edge perimeter of smoke outline, the areas of flame and smoke are obtained by weighted average of an artificial intelligence platform based on data of a plurality of static images, the edges of flame and smoke are obtained by weighted average of the artificial intelligence platform based on data of a plurality of static images, and the geometric data are output as the analyzed flame image and smoke image.
Specifically, the circularity of the flame and the circularity of the smoke are calculated according to the geometrical data of the flame image and the smoke image through a circularity calculation formula, and whether the fire accident happens is judged according to a preset threshold value different from the circularity of the flame and the circularity of the smoke.
The circularity is calculated by multiplying the area by 4 pi divided by the square of the circumference, i.e., e = (4 pi area)/(circumference).
Specifically, the preset threshold value of the smoke circularity is 3, if the image of the smoke circularity greater than 3 is calculated, the smoke image of the fire accident is determined, otherwise, the smoke image of the non-fire accident is determined, the preset threshold value of the flame circularity is 2, if the image of the flame circularity greater than 2 is calculated, the flame image of the fire accident is determined, otherwise, the flame image of the non-fire accident is determined.
Specifically, the fire-fighting robot in the fire-fighting module comprises a plurality of jet ports, the jet mode of the jet ports adopts a jet pattern, and different jet ports are selected according to different dangerous goods on fire for targeted fire extinguishing.
Specifically, the plurality of spraying openings are connected with different types of fire extinguishing substances, such as water, carbon dioxide, dry powder and other fire extinguishing substances based on physical or chemical principles.
Specifically, the artificial intelligence platform simulates the activity mode of nerve cells in the human or animal brain based on an artificial neural network operation technology, after fire extinguishment is carried out each time, relevant data are added into convolutional neural network model parameters, the model is trained, the trained model is stored, a data operation model preset by a system is formed and used for analyzing and processing the data, and the identification accuracy of a subsequent convolutional neural network model is improved.
The invention has the beneficial effects that: this artificial intelligence fire extinguishing systems is surveyed to full scene of vision condition, the condition of fire detection module based on the distributed overall arrangement of full scene of vision is judged the conflagration emergence point to carry out the linkage through artificial intelligence and fire-fighting robot's overall arrangement position, can be quick put out a fire the preliminary treatment to the conflagration emergence point, and according to the type of the hazardous articles that catch fire, select the article of putting out a fire that correspond and put out a fire, thereby prevent the scale enlargement of conflagration.
Those of ordinary skill in the art will appreciate that the various illustrative modules described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. An artificial intelligence fire extinguishing system for fire detection in a full view field is characterized by comprising an artificial intelligence platform for receiving information, and a fire detection module, a man-machine interaction module and a fire extinguishing module which are connected with the artificial intelligence platform;
the artificial intelligence platform is used for receiving the data information monitored by each module and analyzing and processing the data information, and the artificial intelligence platform analyzes the relevance between a fire occurrence point and a nearest certain fire extinguishing module according to an output result after analysis and a layout position of the fire extinguishing module according to an artificial intelligence linkage strategy and the layout position of the fire extinguishing module, and can control the fire extinguishing module to go to the fire occurrence point of a specified area for fire extinguishing processing;
the fire detection module comprises flame image acquisition equipment and smoke image acquisition equipment, wherein the flame image acquisition equipment is used for preprocessing an acquired flame image and transmitting the flame image to the artificial intelligence platform for geometric characteristic analysis, and the smoke image acquisition equipment is used for preprocessing the acquired smoke image and transmitting the smoke image to the artificial intelligence platform for geometric characteristic analysis;
the man-machine interaction module comprises loudspeakers and an electronic display screen which are distributed in a region, the loudspeakers are used for early warning and broadcasting related personnel possibly existing in the region and explaining the specific position of a fire occurrence point, and the electronic display screen marks the fire occurrence point in the region and displays a specific escape route;
the fire extinguishing module comprises a plurality of fire fighting robots for extinguishing fire, the fire fighting robots adopt laser navigation and generate an area map by a laser ranging method, fire extinguishing routes of the fire fighting robots are reasonably planned on the basis, a rotatable laser emitting head and a matched receiver are arranged at the top ends of the fire fighting robots, the distances from the fire fighting robots to each point on the boundary are scanned by emitting laser, so that specific routes for extinguishing fire are generated, and reasonable fire extinguishing routes are provided for a plurality of follow-up fire fighting robots.
2. The full-field fire detection artificial intelligence fire extinguishing system according to claim 1, wherein the flame image collection devices and the flue gas image collection devices in the fire detection module are installed in an area distribution manner based on a panoramic layout, and the flame image collection devices and the flue gas image collection devices adopt a combination of a 360-degree high-definition probe and a high-speed ball-rotating camera device to acquire real-time full-field flame images and flue gas images.
3. The full-field fire detection artificial intelligence fire extinguishing system according to claim 1, wherein the geometric features of the flame image and the smoke image include an area of flames, an area of smoke outline, an edge perimeter of flames and an edge perimeter of smoke outline, the areas of flames and smoke are obtained by weighted average of an artificial intelligence platform based on data of a plurality of static images, the edges of flames and smoke perimeter are obtained by weighted average of the artificial intelligence platform based on data of a plurality of static images, and the geometric data are output as the analyzed flame image and smoke image.
4. The full-field fire detection artificial intelligence fire extinguishing system according to claim 3, wherein the circularity of the flame and the circularity of the smoke are calculated from the geometrical data of the flame image and the smoke image through a circularity calculation formula, and whether a fire accident occurs is determined according to a preset threshold value that the circularity of the flame and the circularity of the smoke are different.
5. The full-field fire detection artificial intelligence fire extinguishing system according to claim 4, wherein the preset threshold of the smoke circularity is 3, if the image of the smoke circularity greater than 3 is calculated, the smoke image of the fire accident is determined, otherwise, the smoke image of the non-fire accident is determined, the preset threshold of the flame circularity is 2, if the image of the flame circularity greater than 2 is calculated, the flame image of the fire accident is determined, otherwise, the flame image of the non-fire accident is determined.
6. The full-field fire detection artificial intelligence fire extinguishing system according to claim 1, wherein the fire fighting robot in the fire extinguishing module comprises a plurality of injection ports, the injection mode of the injection ports adopts a jet flow type, and different injection ports are selected according to different dangerous goods on fire for targeted fire extinguishing.
7. The full field fire detection artificial intelligence fire extinguishing system according to claim 6, wherein the plurality of spraying ports are connected with different types of fire extinguishing materials, such as water, carbon dioxide, dry powder and other fire extinguishing materials based on physical or chemical principles.
8. The all-field fire detection artificial intelligence fire extinguishing system according to claim 1, wherein the artificial intelligence platform simulates the activity of nerve cells in human or animal brains based on an artificial neural network operation technology, after each fire is extinguished, relevant data is added to convolutional neural network model parameters, the models are trained, the trained models are stored, and a data operation model preset by the system is formed and used for analyzing and processing the data, so that the recognition accuracy of subsequent convolutional neural network models is improved.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112657109A (en) * | 2020-12-28 | 2021-04-16 | 长沙中联消防机械有限公司 | Machine learning fire extinguishing system and method based on cloud computing and fire fighting equipment |
| CN112990660A (en) * | 2021-02-04 | 2021-06-18 | 西安美格智联软件科技有限公司 | Petrochemical fire-extinguishing rescue auxiliary control method and system, storage medium and terminal |
| CN113781736A (en) * | 2021-09-23 | 2021-12-10 | 深圳市保国特卫安保技术服务有限公司 | Building fire-fighting early warning method, system, equipment and storage medium |
| CN113995999A (en) * | 2021-10-22 | 2022-02-01 | 浙江辉博电力设备制造有限公司 | Monitoring fire extinguishing system for fire |
| CN114648853A (en) * | 2022-03-09 | 2022-06-21 | 国网安徽省电力有限公司电力科学研究院 | Early fire mode identification and grading early warning system of high-voltage switch cabinet |
| CN114849127A (en) * | 2022-07-08 | 2022-08-05 | 四川坤弘远祥科技有限公司 | Method, apparatus and medium for controlling non-pressure storage type explosion suppression system |
| CN115569338A (en) * | 2022-11-09 | 2023-01-06 | 国网安徽省电力有限公司蚌埠供电公司 | Multi-class fire early warning data distributed training and local fire extinguishing method and system |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11276619A (en) * | 1998-03-31 | 1999-10-12 | Nohmi Bosai Ltd | Preferential fife-fighting method by plural fire-fighting robots and facility therefor |
| CN105459093A (en) * | 2016-01-14 | 2016-04-06 | 任曲波 | Autonomous navigation harmful gas detecting robot |
| CN107050724A (en) * | 2017-04-24 | 2017-08-18 | 广州思瑞智能科技有限公司 | A kind of full filed condition of a fire detection artificial intelligence fire extinguishing system and method |
| CN108284427A (en) * | 2017-11-24 | 2018-07-17 | 浙江国自机器人技术有限公司 | Security robot and its automatic detecting method |
| CN109276839A (en) * | 2017-07-19 | 2019-01-29 | 上海赛特斯信息科技股份有限公司 | Fire extinguishing system based on artificial intelligence |
| CN109598193A (en) * | 2018-10-25 | 2019-04-09 | 安徽新浩信息科技有限公司 | A kind of flame image recognition methods based on artificial intelligence |
| CN109598194A (en) * | 2018-10-25 | 2019-04-09 | 安徽含光软件开发有限公司 | A kind of fire smoke image-recognizing method based on artificial intelligence |
| CN110102002A (en) * | 2019-05-15 | 2019-08-09 | 上海荷福人工智能科技（集团）有限公司 | The early warning of fire-fighting robot based on artificial intelligence and fire extinguishing system and method |
| CN110115819A (en) * | 2019-05-14 | 2019-08-13 | 上海荷福人工智能科技（集团）有限公司 | Fire water monitor orientation early warning and extinguishing method, storage medium and fire water monitor based on artificial intelligence |
| CN110314310A (en) * | 2019-06-19 | 2019-10-11 | 中国船舶重工集团应急预警与救援装备股份有限公司 | A kind of control system of intelligent fire robot |
-
2020
- 2020-06-23 CN CN202010581234.5A patent/CN111686392A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11276619A (en) * | 1998-03-31 | 1999-10-12 | Nohmi Bosai Ltd | Preferential fife-fighting method by plural fire-fighting robots and facility therefor |
| CN105459093A (en) * | 2016-01-14 | 2016-04-06 | 任曲波 | Autonomous navigation harmful gas detecting robot |
| CN107050724A (en) * | 2017-04-24 | 2017-08-18 | 广州思瑞智能科技有限公司 | A kind of full filed condition of a fire detection artificial intelligence fire extinguishing system and method |
| CN109276839A (en) * | 2017-07-19 | 2019-01-29 | 上海赛特斯信息科技股份有限公司 | Fire extinguishing system based on artificial intelligence |
| CN108284427A (en) * | 2017-11-24 | 2018-07-17 | 浙江国自机器人技术有限公司 | Security robot and its automatic detecting method |
| CN109598193A (en) * | 2018-10-25 | 2019-04-09 | 安徽新浩信息科技有限公司 | A kind of flame image recognition methods based on artificial intelligence |
| CN109598194A (en) * | 2018-10-25 | 2019-04-09 | 安徽含光软件开发有限公司 | A kind of fire smoke image-recognizing method based on artificial intelligence |
| CN110115819A (en) * | 2019-05-14 | 2019-08-13 | 上海荷福人工智能科技（集团）有限公司 | Fire water monitor orientation early warning and extinguishing method, storage medium and fire water monitor based on artificial intelligence |
| CN110102002A (en) * | 2019-05-15 | 2019-08-09 | 上海荷福人工智能科技（集团）有限公司 | The early warning of fire-fighting robot based on artificial intelligence and fire extinguishing system and method |
| CN110314310A (en) * | 2019-06-19 | 2019-10-11 | 中国船舶重工集团应急预警与救援装备股份有限公司 | A kind of control system of intelligent fire robot |
Non-Patent Citations (5)
| Title |
|---|
| 乔路 等: "《人工智能的法律未来》", 30 June 2018, 知识产权出版社 * |
| 北京市图形图像学学会编: "《图像图形技术研究与应用》", 31 May 2009, 中国传媒大学出版社 * |
| 李孟歆: "《基于机器视觉的图像识别技术及其应用》", 31 January 2019, 中国矿业大学出版社 * |
| 葛世荣 等: "《卓越采矿工程师教程》", 31 March 2017, 煤炭工业出版社 * |
| 邵欣 等: "《机器视觉与传感器技术》", 31 August 2017, 北京航空航天大学出版社 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112990660A (en) * | 2021-02-04 | 2021-06-18 | 西安美格智联软件科技有限公司 | Petrochemical fire-extinguishing rescue auxiliary control method and system, storage medium and terminal |
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| CN114648853A (en) * | 2022-03-09 | 2022-06-21 | 国网安徽省电力有限公司电力科学研究院 | Early fire mode identification and grading early warning system of high-voltage switch cabinet |
| CN114849127A (en) * | 2022-07-08 | 2022-08-05 | 四川坤弘远祥科技有限公司 | Method, apparatus and medium for controlling non-pressure storage type explosion suppression system |
| CN115569338A (en) * | 2022-11-09 | 2023-01-06 | 国网安徽省电力有限公司蚌埠供电公司 | Multi-class fire early warning data distributed training and local fire extinguishing method and system |
| CN115569338B (en) * | 2022-11-09 | 2023-10-13 | 国网安徽省电力有限公司蚌埠供电公司 | Multi-category fire early warning data distributed training and local extinguishing method and system |
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Application publication date: 20200922 |