CN111882801A - Regional fire position identification method and system - Google Patents
Regional fire position identification method and system Download PDFInfo
- Publication number
- CN111882801A CN111882801A CN202010575222.1A CN202010575222A CN111882801A CN 111882801 A CN111882801 A CN 111882801A CN 202010575222 A CN202010575222 A CN 202010575222A CN 111882801 A CN111882801 A CN 111882801A
- Authority
- CN
- China
- Prior art keywords
- fire
- people
- sound
- sound data
- location
- 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.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
- G06Q50/265—Personal security, identity or safety
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/53—Recognition of crowd images, e.g. recognition of crowd congestion
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/14—Central alarm receiver or annunciator arrangements
Abstract
The invention discloses a method and a system for identifying a regional fire position. The method comprises the following steps: when people gather in the area, whether a fire disaster occurs or not is judged according to the position of the people gather, the action route and/or the sound data and/or the use condition of the fire fighting equipment, and the position of the fire disaster is identified. The method and the system solve the technical problem of identifying the fire occurrence position in the area according to the personnel gathering condition.
Description
Technical Field
The invention belongs to the technical field of intelligent fire fighting, and particularly relates to a method and a system for identifying a regional fire position.
Background
At present, regional fire is mainly monitored by adopting a fire detection algorithm according to sensor data or images. The existing fire detection technology, for example, chinese patent "a safety early warning management system based on deep learning image fire identification" with publication number CN110032977A, proposes that image preprocessing is performed by a foreground detection technology, fire detection is completed based on deep learning modeling, an artificial model is established based on enterprise staff and actual experience, and fire is classified according to the severity level of hazard, so as to realize graded early warning. In a Chinese patent 'a real-time fire detection early warning method under a video sequence' with publication number CN108399359A, a frame difference method is adopted to extract a motion area in a video; matching the moving pixel points of the moving area with the flame color characteristic model and the smoke color characteristic model, so as to identify the flame area and the smoke area; if a flame area or a smoke area is detected, the occurrence of flame or smoke is indicated, and at the moment, fire early warning is carried out. Chinese patent CN110852174A, an early smoke detection method based on video monitoring, proposes to read video information stream from a monitoring platform and convert the information stream into a format of video frame image; performing background modeling on the frame image by adopting a ViBe background modeling method to extract a foreground pixel point region; intercepting original images of foreground areas from corresponding video frames; and then the smoke is sent to a trained deep neural network, so that the smoke is judged.
The fire detection technology mainly carries out fire identification and detection through shape characteristics, image characteristics and the like of flames, and the algorithms need fine flame images, but when a fire disaster happens to a certain part in an area but the flames cannot be accurately identified, the algorithms are difficult to accurately and timely find the accurate position of the area fire disaster, and are not beneficial to timely preventing the spread of the area fire disaster.
At present, no technical scheme for identifying the fire occurrence position in the area according to the personnel gathering condition exists. Therefore, a method and a system for identifying the location of a regional fire are provided.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method and a system for identifying a fire location in a region.
The invention relies on an environment monitoring sensor and a fire-fighting facility management system deployed in an area, wherein the environment monitoring sensor comprises a sound sensor, a monitoring camera and the like.
The invention discloses a regional fire position identification method, which comprises the following steps:
when people gather in the area, whether a fire disaster occurs or not is judged according to the position of the people gather, the action route and/or the sound data and/or the use condition of the fire fighting equipment, and the position of the fire disaster is identified.
The specific description is as follows:
the judging whether a fire disaster occurs according to the personnel gathering position and/or the action route and/or the sound data and/or the use condition of the fire-fighting equipment comprises the following steps: judging whether a fire occurs according to the crowd position, judging whether a fire occurs according to the action route, judging whether a fire occurs according to the sound data, judging whether a fire occurs according to the use condition of the fire-fighting equipment, judging whether a fire occurs according to the crowd position and the action route, judging whether a fire occurs according to the crowd position and the sound data, judging whether a fire occurs according to the crowd position and the use condition of the fire-fighting equipment, judging whether a fire occurs according to the action route and the use condition of the fire-fighting equipment, judging whether a fire occurs according to the sound data and the use condition of the fire-fighting equipment, judging whether a fire occurs according to the crowd position, the action route and the use condition of the fire-fighting equipment, and the like, Judging whether a fire disaster occurs according to the personnel gathering position, the sound data and the fire-fighting facility, judging whether a fire disaster occurs according to the action route, the sound data and the service condition of the fire-fighting facility, and judging whether a fire disaster occurs according to the personnel gathering position, the action route, the sound data and the service condition of the fire-fighting facility.
Wherein judging whether a fire occurs according to the sound data includes: judging whether a fire disaster occurs according to the sound decibel number, judging whether the fire disaster occurs according to the sound chaos degree, judging whether the fire disaster occurs according to whether the SOS sound exists, judging whether the fire disaster occurs according to the sound decibel number and the sound chaos degree, judging whether the fire disaster occurs according to the sound decibel number and the SOS sound, judging whether the fire disaster occurs according to the sound chaos degree and whether the SOS sound exists, and judging whether the fire disaster occurs according to the sound decibel number and the sound chaos degree and whether the SOS sound exists.
Preferably, the people gathering is a phenomenon that a plurality of people gather from different locations to the same area; the people gathering location is an area location where the crowd density data is greater than a certain threshold.
Preferably, the course of action is between a person leaving a building and moving to a gathering location.
Preferably, the sound data includes any one or more of a sound decibel number, a degree of sound confusion, and whether or not there is a distress sound.
Preferably, the usage of the fire protection equipment includes any one or more of current usage of the fire protection equipment in the area near the aggregation location, and historical usage of the fire protection equipment in the area near the aggregation location.
Preferably, the judging whether a fire occurs according to the people gathering position and/or the action route and/or the sound data and/or the use condition of the fire-fighting equipment is judging whether a fire occurs according to the number of people in a certain range of the people gathering position, judging whether a fire occurs according to the repetition degree of the action route between people leaving from the building to the gathering position, judging whether a fire occurs according to whether the sound data accords with the fire characteristics, judging whether a fire occurs according to whether the difference value between the current fire-fighting equipment use rate and the historical use rate in the area near the gathering position is larger than a certain threshold value, judging whether a fire occurs according to the number of people in the certain range of the people gathering position and the repetition degree of the action route between people leaving from the building to the gathering position, judging whether a fire occurs according to the number of people in the certain range of the people gathering position and according to whether the sound data accords with the, Judging whether a fire occurs according to the number of people in a certain range of the people gathering position and whether the difference value between the current fire-fighting equipment utilization rate and the historical utilization rate in the area near the gathering position is larger than a certain threshold value, judging whether a fire occurs according to the repetition degree of the action route between the people leaving from the building to the gathering position and whether the sound data accords with the fire characteristics, judging whether a fire occurs according to the repetition degree of the action route between the people leaving from the building to the gathering position and whether the difference value between the current fire-fighting equipment utilization rate and the historical utilization rate in the area near the gathering position is larger than a certain threshold value, judging whether a fire occurs according to the fact that the sound data accords with the fire characteristics and whether the difference value between the current fire-fighting equipment utilization rate and the historical utilization rate in the area near the gathering position is larger than a certain threshold value, and judging whether a fire occurs according to the number of people in a certain range of the Judging whether a fire occurs according to whether the degree and the sound data conform to fire characteristics, judging whether a fire occurs according to whether the number of people in a certain range of the people gathering position, the repetition degree of an action route between people leaving from a building to the gathering position and the difference between the current utilization rate of the fire fighting equipment and the historical utilization rate in an area near the gathering position are larger than a certain threshold, judging whether a fire occurs according to whether the number of people in the certain range of the people gathering position and the sound data conform to fire characteristics and whether the difference between the current utilization rate of the fire fighting equipment and the historical utilization rate in the area near the gathering position is larger than a certain threshold, judging whether a fire occurs according to whether the repetition degree and the sound data of the action route between people leaving from the building to the gathering position conform to the fire characteristics and the difference between the current utilization rate of the fire fighting equipment and the historical utilization rate in the area near the gathering position, And judging whether a fire disaster occurs according to the number of people in a certain range of the people gathering position, the repetition degree of the action route between the people leaving from the building to the gathering position and whether the sound data accord with the fire disaster characteristics, and whether the difference value between the current fire-fighting equipment utilization rate and the historical utilization rate in the area near the gathering position is larger than a certain threshold value.
Further preferably, whether the sound data conforms to the fire characteristic or not is calculated according to a positive correlation relationship between the sound decibel number and the fire weight, whether the sound data conforms to the fire characteristic or not is judged according to whether the fire weight value is larger than a certain threshold or not, the sound chaos degree is calculated according to the number of different types of sounds, whether the sound data conforms to the fire characteristic or not is judged according to whether a keyword related to distress or rescue exists in the sound data or not, whether the keyword related to distress or rescue exists or not is judged according to whether the keyword related to distress or rescue exists in the sound data or not and whether the keyword related to distress or rescue exists in the sound data or not is judged according to whether the keyword related to distress or rescue exists in the sound data or not, whether the distress sound data conforms to the fire characteristic or not is judged according to the distress or not according to the keyword related to distress or rescue exists in the sound data or not is calculated according to the positive Whether the fire disaster characteristic is met or not is judged according to the fire disaster weight value and the number of the key words of the distress sound, the sound confusion degree is calculated according to the number of different types of sounds, whether the distress sound is met or not is judged according to whether the key words related to the distress or the rescue exist in the sound data or not, whether the fire disaster characteristic is met or not is judged according to the sound confusion degree and the number of the key words of the distress sound, the fire disaster weight value is calculated according to the positive correlation relation between the sound decibel and the fire disaster weight, the sound confusion degree is calculated according to the number of the different types of sounds, whether the key words related to the distress or the rescue exist in the sound data or not is judged according to any item of the fire disaster characteristic or not according to the fire disaster weight.
Preferably, the location of the identified fire is a location of a person source where the repetition of the action route calculated from the location of the person group and the action route is the greatest.
A computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to perform the above method.
A zone fire location identification system, comprising:
an environmental monitoring sensor;
fire-fighting equipment;
a processor;
a memory;
and
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the programs causing the computer to perform the above-described method.
The method and the system have the advantages that:
(1) the sound data of the personnel gathering and personnel gathering source positions are used as the fire identification elements, the reaction and the behavior of personnel to the fire are fully utilized, and the regional fire and the specific position of the fire can be timely and effectively identified.
(2) According to the use rate of the fire-fighting facilities near the personnel gathering position and the personnel gathering source position, the area range influenced by the regional fire can be effectively identified, and residents in the influenced area can be timely reminded by the utilization area.
Drawings
FIG. 1 is a block diagram of a method for identifying a location of a regional fire according to an embodiment of the present invention;
fig. 2 is a flowchart of a zone fire location identification method according to an embodiment of the present invention.
Detailed Description
The following describes in detail preferred embodiments of the present invention.
The embodiment of the invention depends on an environment monitoring sensor and a fire fighting facility management system which are deployed in an area, wherein the environment monitoring sensor comprises a sound sensor, a monitoring camera and the like.
The method for identifying the location of a regional fire according to the invention is implemented as a block diagram shown in fig. 1. The method comprises the steps that environmental monitoring sensors deployed in an area detect movement conditions of personnel, when the situation that personnel congregation occurs in a certain area is detected, a fire control center detects personnel congregation positions and/or action routes and/or sound data and/or use conditions of fire fighting facilities according to data of a plurality of environmental monitoring sensors, judges whether a fire disaster occurs or not according to the personnel congregation positions and/or action routes and/or sound data and/or use conditions of the fire fighting facilities, identifies the fire disaster occurrence positions according to the personnel congregation positions and the action routes, and sends out fire control alarms.
An embodiment of the method for identifying the location of a regional fire according to the present invention is shown in fig. 2. The method comprises the following steps:
when people gather in the area, whether a fire disaster occurs or not is judged according to the position of the people gather, the action route and/or the sound data and/or the use condition of the fire-fighting equipment, and the position of the fire disaster is identified.
The people gathering is a phenomenon that a plurality of people gather in the same area from different positions.
The judging whether a fire disaster occurs according to the personnel gathering position and/or the action route and/or the sound data and/or the use condition of the fire-fighting equipment comprises the following steps: judging whether a fire occurs according to the crowd position, judging whether a fire occurs according to the action route, judging whether a fire occurs according to the sound data, judging whether a fire occurs according to the use condition of the fire-fighting equipment, judging whether a fire occurs according to the crowd position and the action route, judging whether a fire occurs according to the crowd position and the sound data, judging whether a fire occurs according to the crowd position and the use condition of the fire-fighting equipment, judging whether a fire occurs according to the action route and the use condition of the fire-fighting equipment, judging whether a fire occurs according to the sound data and the use condition of the fire-fighting equipment, judging whether a fire occurs according to the crowd position, the action route and the use condition of the fire-fighting equipment, and the like, Judging whether a fire disaster occurs according to the personnel gathering position, the sound data and the fire-fighting facility, judging whether a fire disaster occurs according to the action route, the sound data and the service condition of the fire-fighting facility, and judging whether a fire disaster occurs according to the personnel gathering position, the action route, the sound data and the service condition of the fire-fighting facility.
In Table A, A1 to A15 show different embodiments for judging the occurrence of a fire
In a preferred embodiment, the location of the fire is identified as a location of a person source where the repetition of the action route calculated based on the location of the group of persons and the action route is the greatest.
A computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to perform the method of the above embodiment.
An embodiment of the zone fire location identification system of the present invention is characterized by comprising:
an environmental monitoring sensor;
fire-fighting equipment;
a processor;
a memory;
and
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the programs causing the computer to perform the method of any of the embodiments described above.
Of course, those skilled in the art should realize that the above embodiments are only used for illustrating the present invention, and not as a limitation to the present invention, and that the changes and modifications of the above embodiments will fall within the protection scope of the present invention as long as they are within the scope of the present invention.
Claims (10)
1. A regional fire location identification method is characterized in that:
when people gather in the area, whether a fire disaster occurs or not is judged according to the position of the people gather, the action route and/or the sound data and/or the use condition of the fire fighting equipment, and the position of the fire disaster is identified.
2. The method of identifying a location of a regional fire of claim 1, wherein the crowd of people is a phenomenon in which a plurality of people gather in the same region from different locations; the people gathering location is a location of an area where the crowd density is greater than a certain threshold.
3. A method of regional fire location identification as claimed in claim 1 wherein the course of action is between a person leaving a building and moving to a gathering location.
4. The method of claim 1, wherein the sound data includes any one or more of a sound decibel number, a degree of confusion, and whether there is a distress sound.
5. The method of claim 1, wherein the usage of the fire fighting equipment includes any one or more of a current usage rate of the fire fighting equipment in the area near the aggregation location, and a historical usage rate of the fire fighting equipment in the area near the aggregation location.
6. The method for identifying a regional fire location according to claim 1, wherein the determining whether a fire occurs according to the people gathering location and/or the action route and/or the sound data and/or the usage of the fire protection equipment is determining whether a fire occurs according to the number of people within a certain range of the people gathering location, determining whether a fire occurs according to the repetition degree of the action route between people leaving from the building to the gathering location, determining whether a fire occurs according to whether the sound data corresponds to the fire characteristic, determining whether a fire occurs according to whether the difference between the current usage rate of the fire protection equipment and the historical usage rate in the area near the gathering location is greater than a certain threshold, determining whether a fire occurs according to the number of people within a certain range of the people gathering location and the repetition degree of the action route between people leaving from the building to the gathering location, determining whether a fire occurs according to the comparison result of, Judging whether a fire occurs according to the number of people in a certain range of the people gathering position and according to whether the sound data accords with the fire characteristics, judging whether a fire occurs according to whether the number of people in the certain range of the people gathering position and the difference value between the current fire fighting equipment utilization rate and the historical utilization rate in the area near the gathering position are larger than a certain threshold value, judging whether a fire occurs according to whether the repetition degree of an action route between people leaving from a building to the gathering position and the sound data accords with the fire characteristics, judging whether a fire occurs according to whether the repetition degree of the action route between people leaving from the building to the gathering position and the difference value between the current fire fighting equipment utilization rate and the historical utilization rate in the area near the gathering position are larger than a certain threshold value, judging whether a fire occurs according to whether the sound data accords with the fire characteristics and whether the difference value between the current fire fighting equipment utilization rate and the historical utilization rate in the area near, Judging whether a fire occurs according to the number of people in a certain range of the people gathering position, the repetition degree of an action route between the people leaving from a building to the gathering position and whether sound data accord with fire characteristics, judging whether a fire occurs according to the number of people in the certain range of the people gathering position, the repetition degree of an action route between the people leaving from the building to the gathering position and whether a difference value between the current utilization rate of fire-fighting equipment and the historical utilization rate in an area near the gathering position is larger than a certain threshold value, judging whether a fire occurs according to the number of people in the certain range of the people gathering position and whether the sound data accord with fire characteristics, whether a difference value between the current utilization rate of fire-fighting equipment and the historical utilization rate in the area near the gathering position is larger than a certain threshold value, judging whether a fire occurs according to the repetition degree of an action route between the people leaving from the building to the gathering position and whether sound data accord with fire characteristics Whether the difference value between the application utilization rate and the historical utilization rate is larger than a certain threshold value or not is judged, and whether a fire disaster occurs or not is judged according to the number of people in a certain range of the people gathering position, the repetition degree of an action route between people leaving from a building to the gathering position and whether the sound data accord with fire characteristics, and whether the difference value between the current fire-fighting equipment utilization rate and the historical utilization rate in an area near the gathering position is larger than a certain threshold value or not.
7. The method of claim 6, wherein the determining whether the sound data matches the fire characteristic includes calculating a fire weight value according to a positive correlation between a decibel of sound and the fire weight, determining whether the sound data matches the fire characteristic according to whether the fire weight value is greater than a threshold, calculating a confusion level according to a quantity of different types of sounds, determining whether the sound data matches the fire characteristic according to whether the confusion level is greater than a threshold, determining whether the sound data has a distress sound according to whether a keyword related to distress or rescue exists in the sound data, determining whether the sound data matches the fire characteristic, calculating a fire weight value according to a positive correlation between a decibel of sound and the fire weight, determining whether the sound data matches the fire characteristic according to a quantity of the sound data and the confusion level, and determining whether the sound data matches the fire characteristic according to the decibel of sound and the confusion level of sound, Calculating a fire weight value according to a positive correlation between the sound decibel number and the fire weight, judging whether a distress sound exists according to whether keywords related to distress or rescue exist in the sound data or not, judging whether the fire characteristics are met or not according to the fire weight value and the number of the keywords related to distress or rescue, calculating the sound disorder degree according to the number of different types of sounds, judging whether the distress sound exists or not according to whether keywords related to distress or rescue exist in the sound data or not, and judging whether the fire characteristics are met or not according to the sound disorder degree and the number of the keywords related to distress, calculating a fire weight value according to the positive correlation of the sound decibel number and the fire weight, calculating the sound confusion degree according to the number of different types of sounds, judging whether any item of fire characteristics is met according to whether keywords related to help seeking or rescue exist in the sound data or not and according to the fire weight value, the sound confusion degree and the number of the keywords of the help seeking sound.
8. The method for identifying a location of a regional fire according to claim 1, wherein the location where the fire is identified is a location of a person source where a repeating degree of a movement route calculated from a location of the group of persons and the movement route is the greatest.
9. A computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to perform the method of claims 1-8.
10. A zone fire location identification system, comprising:
an environmental monitoring sensor;
fire-fighting equipment;
a processor;
a memory;
and
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the programs causing the computer to perform the method of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010575222.1A CN111882801A (en) | 2020-06-22 | 2020-06-22 | Regional fire position identification method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010575222.1A CN111882801A (en) | 2020-06-22 | 2020-06-22 | Regional fire position identification method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111882801A true CN111882801A (en) | 2020-11-03 |
Family
ID=73157863
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010575222.1A Pending CN111882801A (en) | 2020-06-22 | 2020-06-22 | Regional fire position identification method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111882801A (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004213213A (en) * | 2002-12-27 | 2004-07-29 | Hochiki Corp | Evacuation supporting system |
| JP2005020480A (en) * | 2003-06-27 | 2005-01-20 | Nec Commun Syst Ltd | Emergency notification system and emergency notification method |
| CN201832302U (en) * | 2010-08-18 | 2011-05-18 | 清华大学 | System for evaluating building fire situation and indicating personnel evacuation |
| CN103041522A (en) * | 2011-10-17 | 2013-04-17 | 上海日浦信息技术有限公司 | Building fire situation assessment and personnel evacuating indication method and system |
| CN105311783A (en) * | 2014-07-29 | 2016-02-10 | 北京市劳动保护科学研究所 | Fire disaster early warning method and system |
| CN106504750A (en) * | 2016-11-30 | 2017-03-15 | 彭州市运达知识产权服务有限公司 | A kind of device and method thereof of utilization Application on Voiceprint Recognition quick detection scene of fire comburant |
| CN108151802A (en) * | 2017-12-20 | 2018-06-12 | 贵阳宏益房地产开发有限公司 | A kind of fire information display systems and method |
| CN108259625A (en) * | 2018-02-11 | 2018-07-06 | 广西久邻电子商务有限公司 | A kind of escape and rescue method based on Buildings Modeling and personnel's running fix |
| CN110047240A (en) * | 2019-03-07 | 2019-07-23 | 吉林建筑大学 | A kind of intelligent fire warning guidance system and method based on Internet of Things |
| WO2020055585A1 (en) * | 2018-09-13 | 2020-03-19 | Carrier Corporation | Fire detection system - fire smart signalling for fire equipment |
| CN111028493A (en) * | 2019-12-31 | 2020-04-17 | 深圳市泛海三江电子股份有限公司 | Intelligent fire detection system and method |
-
2020
- 2020-06-22 CN CN202010575222.1A patent/CN111882801A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004213213A (en) * | 2002-12-27 | 2004-07-29 | Hochiki Corp | Evacuation supporting system |
| JP2005020480A (en) * | 2003-06-27 | 2005-01-20 | Nec Commun Syst Ltd | Emergency notification system and emergency notification method |
| CN201832302U (en) * | 2010-08-18 | 2011-05-18 | 清华大学 | System for evaluating building fire situation and indicating personnel evacuation |
| CN103041522A (en) * | 2011-10-17 | 2013-04-17 | 上海日浦信息技术有限公司 | Building fire situation assessment and personnel evacuating indication method and system |
| CN105311783A (en) * | 2014-07-29 | 2016-02-10 | 北京市劳动保护科学研究所 | Fire disaster early warning method and system |
| CN106504750A (en) * | 2016-11-30 | 2017-03-15 | 彭州市运达知识产权服务有限公司 | A kind of device and method thereof of utilization Application on Voiceprint Recognition quick detection scene of fire comburant |
| CN108151802A (en) * | 2017-12-20 | 2018-06-12 | 贵阳宏益房地产开发有限公司 | A kind of fire information display systems and method |
| CN108259625A (en) * | 2018-02-11 | 2018-07-06 | 广西久邻电子商务有限公司 | A kind of escape and rescue method based on Buildings Modeling and personnel's running fix |
| WO2020055585A1 (en) * | 2018-09-13 | 2020-03-19 | Carrier Corporation | Fire detection system - fire smart signalling for fire equipment |
| CN110895723A (en) * | 2018-09-13 | 2020-03-20 | 开利公司 | Fire detection system-intelligent fire signalling for fire equipment |
| CN110047240A (en) * | 2019-03-07 | 2019-07-23 | 吉林建筑大学 | A kind of intelligent fire warning guidance system and method based on Internet of Things |
| CN111028493A (en) * | 2019-12-31 | 2020-04-17 | 深圳市泛海三江电子股份有限公司 | Intelligent fire detection system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111079663B (en) | High-altitude parabolic monitoring method and device, electronic equipment and storage medium | |
| CN107437318B (en) | Visible light intelligent recognition algorithm | |
| CN110263686A (en) | A kind of construction site safety of image cap detection method based on deep learning | |
| CN108389359B (en) | Deep learning-based urban fire alarm method | |
| CN107911653A (en) | The module of intelligent video monitoring in institute, system, method and storage medium | |
| KR102149832B1 (en) | Automated Violence Detecting System based on Deep Learning | |
| CN111488799B (en) | Falling object identification method and system based on image identification | |
| CN114973140A (en) | Dangerous area personnel intrusion monitoring method and system based on machine vision | |
| CN116664359A (en) | Intelligent fire early warning decision system and method based on multi-sensor fusion | |
| KR20180118979A (en) | Method and apparatus for risk detection, prediction, and its correspondence for public safety based on multiple complex information | |
| US20230419805A1 (en) | Methods and systems for fire monitoring and early warning in a smart city based on internet of things | |
| CN108256447A (en) | A kind of unmanned plane video analysis method based on deep neural network | |
| CN110674753A (en) | Theft early warning method, terminal device and storage medium | |
| KR20220071880A (en) | Digital twin disaster management system customized for underground public areas | |
| CN112132043A (en) | Fire fighting channel occupation self-adaptive detection method based on monitoring video | |
| CN113044694B (en) | System and method for counting number of persons in building elevator based on deep neural network | |
| CN113554364A (en) | Disaster emergency management method, device, equipment and computer storage medium | |
| KR102157201B1 (en) | System and method for determining disastrous based on image and accident record analysis | |
| CN113269111A (en) | Elevator abnormal behavior detection method and system based on video monitoring | |
| CN111882801A (en) | Regional fire position identification method and system | |
| CN116206253A (en) | Method and system for detecting and judging site fire behavior based on deep learning | |
| KR102648004B1 (en) | Apparatus and Method for Detecting Violence, Smart Violence Monitoring System having the same | |
| CN113299034B (en) | Flame identification early warning method suitable for multiple scenes | |
| CN115880631A (en) | Power distribution station fault identification system, method and medium | |
| CN115798047A (en) | Behavior recognition method and apparatus, electronic device, and computer-readable storage medium |
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 |