CN115938065B - Fire engine intelligent identification system based on edge calculation - Google Patents
Fire engine intelligent identification system based on edge calculation Download PDFInfo
- Publication number
- CN115938065B CN115938065B CN202211166146.4A CN202211166146A CN115938065B CN 115938065 B CN115938065 B CN 115938065B CN 202211166146 A CN202211166146 A CN 202211166146A CN 115938065 B CN115938065 B CN 115938065B
- Authority
- CN
- China
- Prior art keywords
- fire
- image
- sub
- target area
- truck
- 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.)
- Active
Links
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
- Y02A40/28—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture specially adapted for farming
Abstract
The embodiment of the invention discloses an intelligent fire truck identification system based on edge calculation, and relates to the technical field of image identification. The system comprises: the camera is arranged on the fire engine and used for collecting images of a target area; the edge calculation module is connected with the camera, and is used for identifying the fire in the target area image acquired by the camera based on a preset fire identification algorithm and determining the allocation scheme of firefighters for each identified fire area. The fire disaster monitoring system can intelligently identify the fire disaster in the fire disaster area and automatically determine the allocation scheme of firefighters according to the fire disaster information, so that the fire extinguishing efficiency is effectively improved, and the personal safety of the firefighters is ensured.
Description
Technical Field
The invention belongs to the technical field of image recognition, and particularly relates to an intelligent fire truck recognition system based on edge calculation.
Background
The fire engine is a vehicle specially designed and manufactured for fire-fighting operation, is suitable for firefighters to take and equip various fire-fighting equipment or fire extinguishing agents, and is used for fire extinguishment, auxiliary fire extinguishment or fire rescue by the fire-fighting forces. When a fire disaster happens, particularly when a large fire disaster happens, the force of people is very thin and weak, and the fire disaster needs to be extinguished by means of a fire truck, so that the aim of quickly extinguishing the fire is fulfilled, and precious rescue time is prevented from being missed.
However, the existing fire truck using method is not intelligent enough, fire extinguishing equipment and a small amount of sensors are mainly loaded on the fire truck to assist in judging fire conditions, fire fighters are helped to extinguish fire, but clear judgment on fire conditions inside a building cannot be carried out, the fire fighters are caused to manually acquire fire information, the cost is high, and larger safety risks exist.
Disclosure of Invention
In view of the above, the embodiment of the invention provides an intelligent fire truck identification system based on edge calculation, which is used for solving the problems that the existing fire truck using method is not intelligent enough, the fire information is difficult to acquire and safety risks exist. According to the invention, the fire condition of the fire disaster area can be intelligently identified through the fire condition identification algorithm of the edge calculation module, and the allocation scheme of firefighters is automatically determined according to the fire condition information, so that the fire extinguishing efficiency is effectively improved, and the personal safety of firefighters is ensured.
The embodiment of the invention provides an intelligent fire truck identification system based on edge calculation, which comprises the following components:
the camera is arranged on the fire engine and used for collecting images of a target area;
the edge calculation module is connected with the camera, and is used for identifying the fire in the target area image acquired by the camera based on a preset fire identification algorithm and determining the allocation scheme of firefighters for each identified fire area.
In an alternative embodiment, the intelligent fire truck identification system based on edge calculation further includes: a flame sensor installed in front of the fire engine and a turntable installed at the top of the fire engine; the camera is arranged on the turntable;
the flame sensor is used for detecting flame in a target area, and triggering the turntable to rotate when the flame in the target area is detected, so that the camera is aligned to the target area and images of the target area are acquired.
In an alternative embodiment, the preset fire recognition algorithm is an image fire deep learning algorithm based on a convolutional neural network.
In an alternative embodiment, the edge calculation module includes:
the identification unit is used for identifying fire corresponding pixel points in the target area image acquired by the camera based on a preset fire identification algorithm;
the image segmentation unit is used for segmenting the target area image into a plurality of sub-images according to the fire conditions in the target area image and the number of fire fighting water bands of the current fire fighting truck;
the distribution unit is used for distributing firefighters of the current firefighting truck to the actual area corresponding to each sub-image for rescue according to the number of pixel points occupied by the fire condition in each sub-image obtained by dividing the target area image.
In an alternative embodiment, the image segmentation unit is specifically configured to segment the target area image into a plurality of sub-images according to a first formula;
the distribution unit is specifically configured to determine, according to a second formula, the number of firefighters distributed to the actual area corresponding to each sub-image;
wherein, the first formula is:
in the first formula, M represents that the target area image is uniformly divided into k sub-images along the direction of the image row under the condition that M% k=0, and the total number of pixel points of each row in each sub-image is M; m represents the total number of pixel points of each row in the target area image; k represents the number of fire hose of the fire truck; % represents remainder;representing a downward rounding; m is M (m％k) And M else(m％k) Representing randomly dividing the target area image into k sub-images along the direction of the image row in the case of m% k not equal to 0, wherein the total number of pixel points of each row in the m% k sub-images is ensured to be M during random division (m％k) And the total number of pixel points of each row in the rest sub-images is M else(m％k) ；
The second formula is:
in the second formula, n (a) represents the number of firefighters allocated to the actual area corresponding to the a-th sub-image; n represents the total number of firefighters of the current firefighting truck; h (a) represents the number of pixels belonging to a fire identified by the identification unit in the a-th sub-image of the target area image; s (a) represents the total number of all pixel points in the a-th sub-image; h (b) represents the number of pixels belonging to a fire identified by the identification unit in the b-th sub-image of the target area image; s (b) represents the total number of all pixel points in the b-th sub-image; s is S 0 Representing the total number of all pixel points in the target area image; a=1, 2,; b=1, 2,..k.
In an alternative embodiment, the intelligent fire truck identification system based on edge calculation further includes:
the sensor is arranged on the fire engine and is used for detecting high-heat points in the target area image;
the edge calculation module further includes:
and the water supply distribution module is connected with the sensor and used for controlling the water supply distribution ratio of the fire hose in the actual area corresponding to each sub-image according to the number of the pixel points occupied by the fire in each sub-image and the number of the high heat points.
In an alternative embodiment, the water supply distribution module is specifically configured to determine a water supply distribution ratio of the fire hose in the actual area corresponding to each sub-image according to a third formula;
wherein the third formula is:
in the third formula, W (a) represents the water supply distribution ratio of the fire hose in the actual area corresponding to the a-th sub-image; r (a) represents the number of high heat points in the a-th sub-image detected by the sensor.
In an alternative embodiment, the intelligent fire truck identification system based on edge calculation further includes:
the GPS positioning module is arranged on the fire truck and used for acquiring the real-time position of the current fire truck in the network map through a GPS and generating a planned route from the real-time position of the current fire truck in the network map to the destination according to the destination;
the route recommending module is used for acquiring the road condition information in front of the current fire truck through the camera and recommending the planned route with the shortest time consumption in the planned route from the real-time position of the current fire truck in the network map to the destination.
According to the intelligent fire truck identification system based on edge calculation, firstly, a target area image is acquired through a camera on a fire truck, then, the fire in the area image is identified through a fire identification algorithm of an edge calculation module, and an allocation scheme of firefighters is determined for each identified fire area. The fire disaster monitoring system can intelligently identify the fire disaster in the fire disaster area and automatically determine the allocation scheme of firefighters according to the fire disaster information, so that the fire extinguishing efficiency is effectively improved, and the personal safety of the firefighters is ensured.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a fire truck intelligent recognition system based on edge calculation according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be understood that the described embodiments are merely some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a schematic structural diagram of a fire truck intelligent recognition system based on edge calculation according to an embodiment of the present invention. Referring to fig. 1, the system includes:
the camera 1 is arranged on the fire engine and is used for acquiring an image of a target area;
the edge calculation module 2 is connected with the camera 1, and is used for identifying the fire in the target area image acquired by the camera 1 based on a preset fire identification algorithm, and determining the allocation scheme of firefighters for each identified fire area.
In this embodiment, the preset fire recognition algorithm is an image fire deep learning algorithm based on a convolutional neural network. The image fire deep learning algorithm of the convolutional neural network is continuously trained and optimized by taking a large amount of image information of the fire as sample data, so that the accuracy of fire identification can be effectively improved.
The beneficial effects of the technical scheme are as follows: according to the intelligent fire truck identification system based on edge calculation, firstly, a target area image is acquired through a camera 1 on a fire truck, then, the fire in the image is identified through a fire identification algorithm of an edge calculation module 2, and an allocation scheme of firefighters is determined for each identified fire area. The fire disaster monitoring system can intelligently identify the fire disaster in the fire disaster area and automatically determine the allocation scheme of firefighters according to the fire disaster information, so that the fire extinguishing efficiency is effectively improved, and the personal safety of the firefighters is ensured.
As an optional embodiment, the intelligent fire truck identification system based on edge calculation further includes: a flame sensor installed in front of the fire engine and a turntable installed at the top of the fire engine; the camera 1 is arranged on the turntable;
the flame sensor is used for detecting flames in a target area, and triggering the turntable to rotate when the flames in the target area are detected, so that the camera 1 is aligned to the target area and images of the target area are acquired.
The beneficial effects of the technical scheme are as follows: the flame sensor is used for detecting the flame in the area, and then after the flame is detected, the camera 1 is controlled to be aligned with the area and collect the area image, so that the automatic acquisition of the image information of the fire area is realized, and the subsequent edge calculation module 2 is convenient for identifying the fire condition and making a distribution scheme of firefighters.
As an alternative embodiment, the edge calculation module 2 includes:
the identification unit is used for identifying fire corresponding pixel points in the target area image acquired by the camera 1 based on a preset fire identification algorithm;
the image segmentation unit is used for segmenting the target area image into a plurality of sub-images according to the fire conditions in the target area image and the number of fire fighting water bands of the current fire fighting truck; specifically, the image dividing unit divides the target area image into a plurality of sub-images (column height is unchanged) in the direction of the image line.
The distribution unit is used for distributing firefighters of the current firefighting truck to the actual area corresponding to each sub-image for rescue according to the number of pixel points occupied by the fire condition in each sub-image obtained by dividing the target area image.
The beneficial effects of the technical scheme are as follows: the edge computing module 2 firstly uses the recognition unit to recognize fire corresponding points in the regional image, then divides the regional image into a plurality of sub-images according to fire hose data, and finally distributes firefighters for each sub-image, thereby realizing automatic blocking of the fire, providing fire fighting planning for assisting firefighters, and effectively improving fire extinguishing efficiency.
As an optional embodiment, the image segmentation unit is specifically configured to segment the target area image into a plurality of sub-images according to a first formula;
the distribution unit is specifically configured to determine, according to a second formula, the number of firefighters distributed to the actual area corresponding to each sub-image;
wherein, the first formula is:
in the first formula, M represents that the target area image is uniformly divided into k sub-images along the direction of the image row under the condition that M% k=0, and the total number of pixel points of each row in each sub-image is M; m represents the total number of pixel points of each row in the target area image; k represents the number of fire hose of the fire truck; % represents remainder;representing a downward rounding; m is M (m％k) And M else(m％k) Representing randomly dividing the target area image into k sub-images along the direction of the image row in the case of m% k not equal to 0, wherein the total number of pixel points of each row in the m% k sub-images is ensured to be M during random division (m％k) And the total number of pixel points of each row in the rest sub-images is M else(m％k) ；
The second formula is:
in the second formula, n (a) represents the number of firefighters allocated to the actual area corresponding to the a-th sub-image; n represents the total number of firefighters of the current firefighting truck; h (a) represents the number of pixels belonging to a fire identified by the identification unit in the a-th sub-image of the target area image; s (a) represents the total number of all pixel points in the a-th sub-image; h (b) represents the number of pixels belonging to a fire identified by the identification unit in the b-th sub-image of the target area image; s (b) represents the total number of all pixel points in the b-th sub-image; s is S 0 Representing the total number of all pixel points in the target area image; a=1, 2,; b=1, 2,..k.
The beneficial effects of the technical scheme are as follows: the fire image is divided into a plurality of parts along the direction of the image row by utilizing a first formula (1) according to the fire image (namely the target area image) shot by the camera (1) and the number of fire belts of the current fire truck, so that the fire is automatically segmented, a firefighter is assisted in providing planning for fire fighting, and better disaster relief is facilitated; and then, a second formula (2) obtains the number of firefighters allocated to the area corresponding to each segmented image according to the number of pixel points occupied by the fire in each segmented image, so that the firefighters are intelligently and reasonably allocated, and the fire is conveniently controlled.
As an optional embodiment, the intelligent fire truck identification system based on edge calculation further includes:
the sensor is arranged on the fire engine and is used for detecting high-heat points in the target area image;
the edge calculation module 2 further includes:
and the water supply distribution module is connected with the sensor and used for controlling the water supply distribution ratio of the fire hose in the actual area corresponding to each sub-image according to the number of the pixel points occupied by the fire in each sub-image and the number of the high heat points.
The beneficial effects of the technical scheme are as follows: according to the number of fire and high heat points of each sub-image of the regional image, the water supply quantity of the fire fighting belt corresponding to each sub-image is controlled, so that reasonable distribution of water resources is achieved, and the fire extinguishing efficiency is effectively improved.
As an alternative embodiment, the water supply distribution module is specifically configured to determine a water supply distribution ratio of the fire hose in the actual area corresponding to each sub-image according to a third formula;
wherein the third formula is:
in the third formula, W (a) represents the water supply distribution ratio of the fire hose in the actual area corresponding to the a-th sub-image; r (a) represents the number of high heat points in the a-th sub-image detected by the sensor.
The beneficial effects of the technical scheme are as follows: and controlling the water supply distribution ratio of the fire hose in the area corresponding to each segmented image by utilizing a third formula (3) according to the number of pixel points occupied by the fire in each segmented image and the number of high-heat points in each segmented image detected by the sensor, so as to increase the water supply of the area with concentrated fire and heat as much as possible, and facilitating the control of the fire spreading as soon as possible.
As an optional embodiment, the intelligent fire truck identification system based on edge calculation further includes:
the GPS positioning module is arranged on the fire truck and used for acquiring the real-time position of the current fire truck in the network map through a GPS and generating a planned route from the real-time position of the current fire truck in the network map to the destination according to the destination;
the route recommending module is used for acquiring road condition information in front of the current fire truck through the camera 1 and recommending the planned route with the shortest time consumption in the planned route from the real-time position of the current fire truck in the network map to the destination.
The beneficial effects of the technical scheme are as follows: and finally, according to the traffic information and the front road condition information, the planned route with the shortest time consumption and the front road condition information are pushed to firefighters, so that the firefighters can arrive at a fire scene more quickly, and the rescue efficiency is improved.
As can be seen from the above embodiments, the edge calculation module 2 is added to the fire engine, the traffic information is obtained from the GPS, the camera 1 assists in determining the front road condition information, and the sensor and the camera 1 determine the fire condition through edge calculation at the same time, which is helpful for helping the fire fighter to complete the task at a lower cost. The method comprises the following steps: firstly, dividing a fire image into a plurality of parts along the direction of an image row according to the fire image shot by the camera 1 and the number of fire belts of the current fire truck, distributing the current firefighter to the fire area of each divided image according to the number of pixels occupied by the fire in each divided image for rescue, and controlling the water supply distribution ratio of the fire belts in the area corresponding to each divided image according to the number of pixels occupied by the fire in each divided image and the number of high-heat points in each divided image detected by the sensor, thereby improving the safety of executing tasks by the firefighter and improving the fire extinguishing efficiency; the road condition can be analyzed and predicted in traffic, the route is reasonably planned, and the time cost is reduced.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the methods specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the method specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the methods specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof. The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (6)
1. Fire engine intelligent identification system based on edge calculation, characterized by comprising:
the camera is arranged on the fire engine and used for collecting images of a target area;
the edge calculation module is connected with the camera, and is used for identifying the fire in the target area image acquired by the camera based on a preset fire identification algorithm and determining the allocation scheme of firefighters for each identified fire area;
wherein, the edge calculation module includes:
the identification unit is used for identifying fire corresponding pixel points in the target area image acquired by the camera based on a preset fire identification algorithm;
the image segmentation unit is used for segmenting the target area image into a plurality of sub-images according to the fire conditions in the target area image and the number of fire fighting water bands of the current fire fighting truck;
the distribution unit is used for distributing firefighters of the current firefighting truck to the actual area corresponding to each sub-image for rescue according to the number of pixel points occupied by the fire condition in each sub-image obtained by dividing the target area image;
the image segmentation unit is specifically used for segmenting the target area image into a plurality of sub-images according to a first formula;
the distribution unit is specifically configured to determine, according to a second formula, the number of firefighters distributed to the actual area corresponding to each sub-image;
wherein, the first formula is:
in the first formula, M represents that the target area image is uniformly divided into k sub-images along the direction of the image row under the condition that M% k=0, and the total number of pixel points of each row in each sub-image is M; m represents the total number of pixel points of each row in the target area image; k represents the number of fire hose of the fire truck; % represents remainder;representing a downward rounding; m is M (m％k) And M else(m％k) Representing randomly dividing the target area image into k sub-images along the direction of the image row in the case of m% k not equal to 0, wherein the total number of pixel points of each row in the m% k sub-images is ensured to be M during random division (m％k) And the total number of pixel points of each row in the rest sub-images is M else(m％k) ；
The second formula is:
in the second formula, n (a) represents the number of firefighters allocated to the actual area corresponding to the a-th sub-image; n represents the total number of firefighters of the current firefighting truck; h (a) represents the number of pixels belonging to a fire identified by the identification unit in the a-th sub-image of the target area image; s (a) represents the total number of all pixel points in the a-th sub-image; h (b) represents the number of pixels belonging to a fire identified by the identification unit in the b-th sub-image of the target area image; s (b) represents the total number of all pixel points in the b-th sub-image; s is S 0 Representing the target area in the imageThe total number of all pixel points; a=1, 2, …, k; b=1, 2, …, k.
2. The edge computing-based fire truck intelligent identification system of claim 1, wherein the system further comprises: a flame sensor installed in front of the fire engine and a turntable installed at the top of the fire engine; the camera is arranged on the turntable;
the flame sensor is used for detecting flame in a target area, and triggering the turntable to rotate when the flame in the target area is detected, so that the camera is aligned to the target area and images of the target area are acquired.
3. The edge-calculation-based intelligent fire truck recognition system according to claim 1, wherein the preset fire recognition algorithm is a convolutional neural network-based image fire deep learning algorithm.
4. The edge computing-based fire truck intelligent identification system of claim 1, wherein the system further comprises:
the sensor is arranged on the fire engine and is used for detecting high-heat points in the target area image;
the edge calculation module further includes:
and the water supply distribution module is connected with the sensor and used for controlling the water supply distribution ratio of the fire hose in the actual area corresponding to each sub-image according to the number of the pixel points occupied by the fire in each sub-image and the number of the high heat points.
5. The intelligent fire truck identification system based on edge calculation as set forth in claim 4, wherein the water supply distribution module is specifically configured to determine a water supply distribution ratio of the fire truck in the actual area corresponding to each sub-image according to a third formula;
wherein the third formula is:
in the third formula, W (a) represents the water supply distribution ratio of the fire hose in the actual area corresponding to the a-th sub-image; r (a) represents the number of high heat points in the a-th sub-image detected by the sensor.
6. The edge computing-based fire truck intelligent identification system of any one of claims 1-5, wherein the system further comprises:
the GPS positioning module is arranged on the fire truck and used for acquiring the real-time position of the current fire truck in the network map through a GPS and generating a planned route from the real-time position of the current fire truck in the network map to the destination according to the destination;
the route recommending module is used for acquiring the road condition information in front of the current fire truck through the camera and recommending the planned route with the shortest time consumption in the planned route from the real-time position of the current fire truck in the network map to the destination.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211166146.4A CN115938065B (en) | 2022-09-21 | 2022-09-21 | Fire engine intelligent identification system based on edge calculation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211166146.4A CN115938065B (en) | 2022-09-21 | 2022-09-21 | Fire engine intelligent identification system based on edge calculation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115938065A CN115938065A (en) | 2023-04-07 |
| CN115938065B true CN115938065B (en) | 2023-09-15 |
Family
ID=86654679
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211166146.4A Active CN115938065B (en) | 2022-09-21 | 2022-09-21 | Fire engine intelligent identification system based on edge calculation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115938065B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104299351A (en) * | 2014-10-22 | 2015-01-21 | 常州大学 | Intelligent early warning and fire extinguishing robot |
| CN204833587U (en) * | 2015-08-13 | 2015-12-02 | 威海广泰空港电源设备有限公司 | Family's fire control detector |
| CN110197303A (en) * | 2019-05-30 | 2019-09-03 | 浙江树人学院（浙江树人大学） | A kind of fireman's rescue dispatch method adapting to fire dynamic change |
| CN111047818A (en) * | 2019-11-01 | 2020-04-21 | 浙江省林业技术推广总站(浙江省林业信息宣传中心) | Forest fire early warning system based on video image |
| CN111343598A (en) * | 2020-02-03 | 2020-06-26 | 重庆特斯联智慧科技股份有限公司 | Intelligent fire-fighting vehicle-mounted platform operation method and system with edge computing capability |
| CN113762197A (en) * | 2021-09-16 | 2021-12-07 | 南方电网数字电网研究院有限公司 | Transformer substation fire detection method and device based on terminal power business edge calculation |
| CN114445984A (en) * | 2022-02-07 | 2022-05-06 | 深圳正中云有限公司 | Fire-fighting emergency evacuation system and method for urban large building |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106997461B (en) * | 2017-03-28 | 2019-09-17 | 浙江大华技术股份有限公司 | A kind of firework detecting method and device |
-
2022
- 2022-09-21 CN CN202211166146.4A patent/CN115938065B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104299351A (en) * | 2014-10-22 | 2015-01-21 | 常州大学 | Intelligent early warning and fire extinguishing robot |
| CN204833587U (en) * | 2015-08-13 | 2015-12-02 | 威海广泰空港电源设备有限公司 | Family's fire control detector |
| CN110197303A (en) * | 2019-05-30 | 2019-09-03 | 浙江树人学院（浙江树人大学） | A kind of fireman's rescue dispatch method adapting to fire dynamic change |
| CN111047818A (en) * | 2019-11-01 | 2020-04-21 | 浙江省林业技术推广总站(浙江省林业信息宣传中心) | Forest fire early warning system based on video image |
| CN111343598A (en) * | 2020-02-03 | 2020-06-26 | 重庆特斯联智慧科技股份有限公司 | Intelligent fire-fighting vehicle-mounted platform operation method and system with edge computing capability |
| CN113762197A (en) * | 2021-09-16 | 2021-12-07 | 南方电网数字电网研究院有限公司 | Transformer substation fire detection method and device based on terminal power business edge calculation |
| CN114445984A (en) * | 2022-02-07 | 2022-05-06 | 深圳正中云有限公司 | Fire-fighting emergency evacuation system and method for urban large building |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115938065A (en) | 2023-04-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP7359237B2 (en) | Video processing system, video processing method, and video processing program | |
| CN108883725A (en) | A kind of driving vehicle warning system and method | |
| CN110302488A (en) | Autonomous fire-fighting UAV system and fire-fighting method | |
| US9652981B2 (en) | Method for systematically penalizing drivers who fail to stop at a crosswalk | |
| CN108765872B (en) | Method and system for inferring environmental parameters of trapped object and intelligent wearable equipment | |
| DE112016005034T5 (en) | APPLICATION CONTROL AND METHOD FOR ASSIGNING A ROLE OF A TRACKING VEHICLE | |
| CN107527012A (en) | Make a dash across the red light monitoring method, device and monitoring processing equipment | |
| CN111953937A (en) | Drowning person lifesaving system and drowning person lifesaving method | |
| CN115938065B (en) | Fire engine intelligent identification system based on edge calculation | |
| WO2018151895A1 (en) | Real-time intelligent egress system for high rise building | |
| CN111343598B (en) | Intelligent fire-fighting vehicle-mounted platform operation method and system with edge computing capability | |
| CN116740617A (en) | Data processing method, device, electronic equipment and storage medium | |
| CN105572869A (en) | Intelligent glasses and control method of the intelligent glasses | |
| CN113903163A (en) | Water area safety system and water area lifesaving method | |
| US10176695B2 (en) | Real-time water safety analysis based on color-movement tracking | |
| CN205336543U (en) | Unmanned aerial vehicle | |
| CN111591846B (en) | Method, device and system for managing sitting and falling ladder behaviors | |
| DE102013200815A1 (en) | Apparatus for dynamic output of information for evacuation of people from building during e.g. fire in building, has control unit that outputs information for evacuation of people based on current availability of escape routes | |
| CN112861754A (en) | Abnormity processing method and device for electric energy supply station | |
| DE102019214376A1 (en) | Fire analysis method and system | |
| US10163002B2 (en) | Pedestrian detection system and method | |
| CN116824474A (en) | Method for realizing swimming pool and coast safety monitoring based on AI image recognition technology | |
| CN104599497A (en) | Codebook model based vehicle overload monitoring method | |
| CN109872565A (en) | The system and method for detecting tool menace vehicle | |
| CN117282054B (en) | Tunnel fire-fighting linkage system based on edge calculation |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |