CN112907876A - Self-recognition and safety code fire-fighting early warning system - Google Patents
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Abstract
The invention provides a self-recognition and safety code fire-fighting early warning system. The information acquisition module: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring temperature data and video data of a fire-fighting early warning area, judging whether a fire disaster happens or not according to the temperature data, and determining scene elements in an early warning scene according to the video data; a self-recognition module: the system is used for adaptively identifying the scene elements when a fire disaster is likely to happen, and determining combustibles; a security code module: the method is used for converting the inflammable into a safety code in a preset character database through a type matching rule; the early warning module: and the safety code is matched with a corresponding alarm mechanism to implement fire early warning.
Description
Technical Field
The invention relates to the technical field of fire fighting, in particular to a fire fighting early warning system with self-recognition and safety codes.
Background
At present, in order to ensure the fire safety of public fire areas such as buildings, parking lots, markets and the like, the fire areas are always in a good operation working state, regular inspection tests can be carried out on the fire areas, and fire early warning is carried out. People research and design a remote inspection monitoring system by using a public wireless network. By adding the small programmable logic controller, the wireless network communication module and the upper computer system, the system is accessed to a fire control center, so that the emergency fire-fighting early warning of a fire-fighting system is realized. In the prior art, fire control early warning is through the line transmission picture, need artifical control, but the condition to not taking place but probably taking place the conflagration like this is unable to be monitored, and can carry out among the fire early warning technical scheme, all there is data transmission through the network, but the unable complete transmission of current artificial intelligence technique is comprehensive, and specific early warning information, cause the information to miss very easily, and then lead to the fire incident, though there is the early warning but unclear place and specific early warning situation, can't prevent the conflagration to take place.
Disclosure of Invention
The invention provides a self-recognition and safety code fire-fighting early warning system, which is used for solving the problems that in the prior art, fire-fighting early warning is realized by transmitting pictures through a line and needs manual monitoring, but the situation that a fire possibly occurs but does not occur is not monitored, and in the technical scheme of fire early warning, data transmission is realized through a network, but the conventional artificial intelligence technology cannot completely transmit comprehensive and specific early warning information, so that information loss is easily caused, a fire event is caused, and the situation that the fire is caused cannot be prevented although the place and the specific early warning situation are not known although early warning exists.
A self-identifying and security code fire warning system, comprising:
the information acquisition module: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring temperature data and video data of a fire-fighting early warning area, judging whether a fire disaster happens or not according to the temperature data, and determining scene elements in an early warning scene according to the video data;
a self-recognition module: the system is used for adaptively identifying the scene elements when a fire disaster is likely to happen, and determining combustibles;
a security code module: the method is used for converting the inflammable into a safety code in a preset character database through a type matching rule;
the early warning module: and the safety code is matched with a corresponding alarm mechanism to implement fire early warning.
Preferably, the information acquisition module includes:
an early warning area determination unit: the early warning system is used for determining the acquisition position and the data acquisition range of a pre-arranged data acquisition device, constructing a three-dimensional acquisition space according to the acquisition position and the data acquisition range, and determining a specific early warning area according to the acquisition space;
a temperature acquisition module: the temperature acquisition device is used for acquiring temperature data; wherein the content of the first and second substances,
the temperature data comprises time data and position data;
a video data acquisition unit: the data acquisition device is used for acquiring video data through video acquisition equipment in the data acquisition device;
a fire determination unit: the temperature data is compared with a preset temperature threshold value to judge whether a fire disaster occurs;
scene element acquisition unit: and the system is used for dyeing and framing the video data and screening out scene elements in the video data through a filtering algorithm.
Preferably, the screening of the scene elements by the scene element collection unit includes the following steps:
step 1: performing color rendering on the video data and generating a rendered image;
step 2: framing the rendered image and generating a frame image set;
and step 3: constructing a color distribution model according to the frame image set;
wherein H represents a color distribution model; xijExpressing the pixel characteristics of a jth pixel point on the ith frame image; μ represents a mathematical expectation; δ represents the variance of the pixel characteristic; 1, 2, 3 … … n; j is 1, 2, 3 … … m; n represents the total number of frame images; m represents the number of pixel points on each frame image;
and 4, step 4: constructing a scene element characteristic screening model through a preset scene element database:
wherein C represents a scene element feature screening model; f. oflFeatures representing the ith scene element in a scene model database; glRepresenting a weight of the ith scene element in the scene model database;
representing a feature mean of scene elements in a scene model database;
representing the weight mean value of scene elements in a scene model database; beta represents the variance of scene elements in the scene model database; gamma represents the variance of the weights of scene elements in the scene model database; 1, 2, 3 … … q; q represents the total number of scene elements in the scene model database;
and 5: according to the scene element feature screening model and the color distribution model, screening the scene elements in the frame image, and determining the scene elements in the color distribution model through the following formula (1):
when K is larger than or equal to 1, determining corresponding frame images and pixel points of the images, and corresponding the value of K to the corresponding frame images and pixel points of the images to generate an element sequence;
step 6: counting K values of the element sequences, and taking the element sequences with the same K values as scene element groups;
and 7: and determining corresponding scene elements according to the scene element groups.
Preferably, the information collecting module further includes:
basic data setting unit: the system comprises a data acquisition device, a data processing device and a data processing device, wherein the data processing device is used for acquiring specification parameters and quality parameters of the data acquisition device and setting basic parameters of the data acquisition device according to the specification parameters and the quality parameters;
a monitoring strategy setting unit: the monitoring system is used for determining historical abnormal frequency and historical abnormal level according to historical abnormal conditions and generating a monitoring strategy according to the historical abnormal frequency and the historical abnormal level;
regularly maintain the data acquisition unit: the system comprises a data acquisition device and a video data acquisition device, and is used for acquiring the timing maintenance data of the data acquisition device and the fire fighting equipment in the fire fighting early warning area, and determining the basic temperature of temperature data acquisition and the initial video of video data acquisition according to the timing maintenance data and the basic parameters.
Preferably, the self-recognition module includes:
an information acquisition unit: the system is used for receiving the scene elements of the corresponding time period when the information acquisition module judges that the fire disaster is likely to happen;
an adaptive identification unit: the system comprises a scene element detection module, a fire early warning database and a fire early warning database, wherein the scene element detection module is used for detecting scene elements in the scene element detection module, identifying combustibles which possibly generate a fire through the preset fire early warning database and extracting combustibles characteristics of the combustibles;
a symmetric unit: and the system is used for symmetrically distributing the scene elements and the combustibles in the fire early warning database and combining the scene elements and the combustibles to generate an outputable data block.
Preferably, the self-identification module further comprises the following identification steps:
step S1: calibrating video data of fire occurrence;
step S2: preprocessing the video data to obtain preprocessed data; wherein the content of the first and second substances,
the pretreatment comprises the following steps: data graying and data filtering;
step S3, determining scene elements related to fire in the video data according to the preprocessing data and the scene elements;
and step S4, substituting the scene elements related to the fire into a pre-trained adaptive recognition model to determine corresponding inflammable matters.
Preferably, the pre-trained adaptive recognition model includes the following training processes:
a1, acquiring fire early warning data and inflammable data in a fire early warning database;
step A2: dividing the fire early warning data into a first training set and a first verification set, and dividing the inflammable data into a second training set and a second verification set;
a3, corresponding the fire early warning elements and the inflammable data in the first training set and the second training set, and combining to generate a comprehensive training set;
step A4: inputting the comprehensive training set into a neural network model for training, and converting the training into a self-recognition fire early warning model based on a neural network;
step A5: and respectively inputting the first verification set and the second verification set into the self-recognition fire early warning model, optimizing parameters of the self-recognition fire early warning model, and taking the optimized self-recognition fire early warning model as a trained self-adaptive recognition model.
Preferably, the security code module includes:
the character database module: the character database is formed by the identification characters;
a type matching unit: the device is used for executing a type matching rule according to the character database and the inflammable matter, and calibrating the inflammable matter through a character combination in the character database;
the type matching rule comprises:
a conversion unit: the method is used for obtaining a character combination for calibrating the inflammable, and generating a safety code through the character combination and the recognition time of the inflammable.
Preferably, the early warning module includes:
preferably, the early warning module includes:
a matching unit: the alarm mechanism is used for acquiring the security code, matching the security code with a preset alarm mechanism and determining early warning;
a judging unit: the safety code is converted into early warning information according to the alarm mechanism;
wherein the content of the first and second substances,
the early warning information includes: the location of the early warning, the object of the early warning, and the early warning condition.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a system diagram of a fire-fighting early warning system with self-recognition and security codes according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As shown in the attached figure 1, the invention relates to a self-recognition and safety code fire-fighting early warning system, which comprises:
the information acquisition module: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring temperature data and video data of a fire-fighting early warning area, judging whether a fire disaster happens or not according to the temperature data, and determining scene elements in an early warning scene according to the video data;
the fire-fighting early warning area is a public area, such as a school, a market, an office building, a square and the like where the camera equipment can be installed. The temperature data is the temperature data of any place in the fire-fighting early warning area, the temperature acquisition equipment can adopt scanning type infrared temperature measurement together to obtain the temperature data of a larger area as far as possible, and the video data is the video data shot by the video monitoring equipment in the fire-fighting early warning area. The temperature data can judge whether a fire is possible or not under the condition of setting a threshold value, and the video data can monitor the place where the fire accident is possible. The judgment is made as to what combustibles are to cause a fire accident.
A self-recognition module: the system is used for adaptively identifying the scene elements when a fire disaster is likely to happen, and determining combustibles; the self-recognition of the invention is realized based on a database and a pre-trained artificial intelligence algorithm. Scene elements and combustible objects are mainly matched, so that intelligent early warning is carried out.
A security code module: the method is used for converting the inflammable into a safety code in a preset character database through a type matching rule; the invention integrates the information of the possible fire accidents into characters, thereby realizing the rapid transmission of data.
The early warning module: and the safety code is matched with a corresponding alarm mechanism to implement fire early warning. The early warning module corresponds the early warning mechanism and the safety code, and after the information of the safety code is transmitted to early warning equipment and is directly sent, the early warning program is directly executed through a preset early warning rule.
According to the invention, through data acquisition of the public site fire-fighting early warning area, whether a fire is possible or not can be judged, and a place where a fire accident is possible is monitored. The judgment is made as to what combustibles are to cause a fire accident. According to the invention, the character string and elements of fire early warning, namely, inflammables are matched with real data transmission, so that operation and maintenance personnel can know what abnormal conditions occur only by transmitting the security code during early warning, and then make corresponding decisions.
Preferably, the information acquisition module includes:
an early warning area determination unit: the early warning system is used for determining the acquisition position and the data acquisition range of a pre-arranged data acquisition device, constructing a three-dimensional acquisition space according to the acquisition position and the data acquisition range, and determining a specific early warning area according to the acquisition space;
because the specification of the data acquisition device is not changed, when data acquisition is carried out, the data acquisition range of each data acquisition device in the data acquisition area is determined, a huge data acquisition network space is required to be constructed according to the acquisition position and the acquisition range for data acquisition, and the size of the early warning area in the data acquisition network space is determined.
A temperature acquisition module: the temperature acquisition device is used for acquiring temperature data; wherein the content of the first and second substances,
the temperature data further comprises time data and location data;
the temperature data not only comprises time information of temperature change, but also comprises position information of temperature change, so that the time of temperature change and the position of temperature change are conveniently monitored, and the possibility of fire disaster can be judged according to time factors and position factors. For example: the circuit temperature is very likely to cause fire, the temperature of glass or wall surfaces in a fire-fighting early warning area changes due to solar irradiation, and in some high-temperature zones, the temperature of the wall surfaces can reach seventy-eight degrees, particularly in hot regions, but the fire is not likely to occur.
The temperature data can judge whether the fire occurs, the time data and the position data can judge the initial value of the monitoring time, and the position data can determine the specific position of the fire sensitive area.
A video data acquisition unit: the data acquisition device is used for acquiring video data through video acquisition equipment in the data acquisition device; the data acquisition device can be a camera in a public area, and also can be a special fire early warning camera with an infrared scanning function.
A fire determination unit: the temperature data is compared with a preset temperature threshold value to judge whether a fire disaster occurs;
scene element acquisition unit: and the system is used for dyeing and framing the video data and screening out scene elements in the video data through a filtering algorithm. The frame division is to dye different pixels for convenient distinction, the frame division can be more accurate in picture processing during data processing, and the filtering algorithm is a general filtering algorithm and is distinguished from elements in the data.
Preferably, the screening of the scene elements by the scene element collection unit includes the following steps:
step 1: performing color rendering on the video data and generating a rendered image;
step 2: framing the rendered image and generating a frame image set;
and step 3: constructing a color distribution model according to the frame image set;
wherein H represents a color distribution model; xijExpressing the pixel characteristics of a jth pixel point on the ith frame image; μ represents a mathematical expectation; δ represents the variance of the pixel characteristic; 1, 2, 3 … … n; j is 1, 2, 3 … … m; n represents the total number of frame images; m represents the number of pixel points on each frame image;
and 4, step 4: constructing a scene element characteristic screening model through a preset scene element database:
wherein C represents a scene element feature screening model; f. oflFeatures representing the ith scene element in a scene model database; glRepresenting a weight of the ith scene element in the scene model database;
representing a feature mean of scene elements in a scene model database;
representing the weight mean value of scene elements in a scene model database; beta represents the variance of scene elements in the scene model database; gamma represents the variance of the weights of scene elements in the scene model database; 1, 2, 3 … … q; q represents the total number of scene elements in the scene model database;
and 5: according to the scene element feature screening model and the color distribution model, screening the scene elements in the frame image, and determining the screening value of the scene elements in the color distribution model through the following formula (1):
wherein K represents a screening value; when K is larger than or equal to 1, determining corresponding frame images and pixel points of the images, and corresponding the value of K to the corresponding frame images and pixel points of the images to generate an element sequence;
step 6: counting K values of the element sequences, and taking the element sequences with the same K values as scene element groups;
and 7: and determining corresponding scene elements according to the scene element groups.
The principle of the technical scheme is as follows: the rendering of the invention is in a color rendering mode, the color of each scene element in the image after the color rendering is more profound, and different pixels can be distinguished more clearly. After the rendered image is framed, the rendered image can be processed according to each frame image, at this time, a large amount of frame image data exists, more accurate processing is facilitated, the essence of the rendered image is still embodied in a video form, and therefore framing can be performed. The function of constructing the color distribution model from the frame image set is to determine the distribution condition of each pixel point in the frame image set based on the mathematical expectation. The element feature screening model constructed according to the scene element database includes all original scene information of the monitored area, newly-added scene elements and original scene elements can be distinguished based on the screening model constructed based on the element feature screening model, and the scene element feature screening model introduces a feature function based on an index, so that the change condition of the scene elements can be embodied in a visual image mode. And finally, when scene elements are determined, setting a screening value to indicate that the scene elements are changed pixel points in the original scene when K is larger than 1. And then dividing the element sequence based on the K values, determining corresponding scene elements according to the divided scene element groups, and when the K values are the same, indicating that the scene elements are the same.
Preferably, the information collecting module further includes:
basic data setting unit: the system comprises a data acquisition device, a data processing device and a data processing device, wherein the data processing device is used for acquiring specification parameters and quality parameters of the data acquisition device and setting basic parameters of the data acquisition device according to the specification parameters and the quality parameters; the specification parameters represent necessary specification characteristics such as a monitoring range, detection sensitivity, monitored power requirement, and the like of the data acquisition device. And the quality parameter represents the quality of the data acquisition device, including the material, the service life and the like of the data acquisition device.
A monitoring strategy setting unit: the monitoring system is used for determining historical abnormal frequency and historical abnormal level according to historical abnormal conditions and generating a monitoring strategy according to the historical abnormal frequency and the historical abnormal level; according to the invention, through historical abnormal data, when the historical abnormal frequency and the historical abnormal level are determined, the rule of the fault occurrence can be determined according to the time, level and position of the fault occurrence, and then a monitoring and monitoring strategy is generated based on the rule of the fault occurrence, so that the strategy accords with the monitoring rule of the fault condition, and the fault occurrence can be determined more accurately. For example, if the scanning type temperature measuring equipment is adopted, the temperature monitoring abnormality is more often seen at ten o 'clock noon in history, and in the monitoring strategy, the temperature scanning is more often stayed at the place where the abnormality is likely to appear at ten o' clock every day, so that the monitoring is more effectively carried out.
Regularly maintain the data acquisition unit: the system comprises a data acquisition device and a video data acquisition device, and is used for acquiring the timing maintenance data of the data acquisition device and the fire fighting equipment in the fire fighting early warning area, and determining the basic temperature of temperature data acquisition and the initial video of video data acquisition according to the timing maintenance data and the basic parameters. The timing maintenance generally monitors the actual situation when the maintenance is carried out, so that the basic temperature of the device and the initial video acquired by the video data during the actual maintenance can be maintained at the timing as a monitoring cycle in a time period, and the previous monitoring data can be deleted in the device, so that the memory occupation is prevented.
Preferably, the self-recognition module includes:
an information acquisition unit: the system is used for receiving the scene elements of the corresponding time period when the information acquisition module judges that the fire disaster is likely to happen; the scene elements of the corresponding time period represent time and combined data corresponding to the scene elements, so that the relevance of the data and the time is emphasized, and the time of the occurrence of the inflammable matters can be more accurately determined.
An adaptive identification unit: the system comprises a scene element detection module, a fire early warning database and a fire early warning database, wherein the scene element detection module is used for detecting scene elements in the scene element detection module, identifying combustibles which possibly generate a fire through the preset fire early warning database and extracting combustibles characteristics of the combustibles;
all data characteristics of the inflammable matters with fire disasters exist in the fire early warning database, and the inflammable matters in the scene elements can be found according to comparison with the scene elements.
A symmetric unit: and the system is used for symmetrically distributing the scene elements and the combustibles in the fire early warning database and combining the scene elements and the combustibles to generate an outputable data block. Scene elements also exist in the fire early warning database, but the scene elements are the same as the scene elements acquired from the video data, so that the inflammable matters which possibly cause fire can be judged more quickly through comparison. The inflammable matters in the invention not only represent gunpowder, but also represent inflammable matters with physical properties such as petroleum, natural gas and inflammable chemical substances, and represent all factors which can cause fire, so that data acquisition needs to be updated in real time through big data and continuously crawled.
Preferably, the self-identification module further comprises the following identification steps:
step S1: calibrating video data of fire occurrence;
step S2: preprocessing the video data to obtain preprocessed data; wherein the content of the first and second substances,
the pretreatment comprises the following steps: data graying and data filtering;
the preprocessing is used for filtering out data which may affect the judgment result in the video data, such as temperature rise caused by electricity, but the temperature rise is in a reasonable range.
Step S3, determining scene elements related to fire in the video data according to the preprocessing data and the scene elements;
and step S4, substituting the scene elements related to the fire into a pre-trained adaptive recognition model to determine corresponding inflammable matters. The self-adaptive identification model is constructed based on the neural network model of the existing artificial intelligence algorithm.
Preferably, the pre-trained adaptive recognition model includes the following training processes:
a1, acquiring fire early warning data and inflammable data in a fire early warning database;
step A2: dividing the fire early warning data into a first training set and a first verification set, and dividing the inflammable data into a second training set and a second verification set;
a3, corresponding the fire early warning elements and the inflammable data in the first training set and the second training set, and combining to generate a comprehensive training set;
step A4: inputting the comprehensive training set into a neural network model for training, and converting the training into a self-recognition fire early warning model based on a neural network;
step A5: and respectively inputting the first verification set and the second verification set into the self-recognition fire early warning model, optimizing parameters of the self-recognition fire early warning model, and taking the optimized self-recognition fire early warning model as a trained self-adaptive recognition model.
The method utilizes the neural network algorithm in the prior art in the training process, but the method also innovates the neural network algorithm, firstly, two training sets and two test sets are generated, the two training sets are correspondingly trained, the trained neural network model can be regarded as a self-recognition fire early warning model, then the first verification set and the second verification set are respectively input to carry out optimization parameters, the condition that the optimization cannot reach the optimal optimization state due to the fact that the characteristics of fire early warning data and the characteristics of combustible substances interfere with each other in the optimization process is prevented, the two training sets correspond to the comprehensive training, and when scene elements are screened, the early warning data can be determined as long as the combustible substances are determined, the combustible substances can be determined as long as the early warning data are determined, and the method is more convenient.
Preferably, the security code module includes:
the character database module: the character database is formed by the identification characters;
the identifying characters represent that each character represents a factor of a fire early warning area. For example: d1 may just represent the power source for the fire early warning area power equipment, D represents the circuit, and 1 represents the power source.
A type matching unit: the device is used for executing a type matching rule according to the character database and the inflammable, and calibrating the inflammable through a character combination in the character database;
the type matching rule comprises: location matching rules (characters determine the location of the combustibles), equipment matching rules (characters determine the equipment to which the combustibles are attached), numerical matching rules (characters determine the real-time temperature), and status matching rules (characters determine whether a fire has occurred).
A conversion unit: the method is used for obtaining a character combination for calibrating the inflammable, and generating a safety code through the character combination and the recognition time of the inflammable. Character combination is already a recognition mode, and the safety code can also reflect the appearance time of the scene element through time marking.
Preferably, the early warning module includes:
a matching unit: the alarm mechanism is used for acquiring the security code, matching the security code with a preset alarm mechanism and determining early warning;
between the safety code and the alarm mechanism, the alarm mechanism can analyze the safety code to determine specific early warning information, the alarm mechanism is preset with corresponding safety code analysis rules and identification rules, and the safety code corresponds to the alarm mechanism through matching.
The judging unit is used for converting the safety code into early warning information according to the warning mechanism;
wherein the content of the first and second substances,
the early warning information includes: the location of the early warning, the object of the early warning, and the early warning condition.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. The utility model provides a fire control early warning system from discernment and security code which characterized in that includes:
the information acquisition module: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring temperature data and video data of a fire-fighting early warning area, judging whether a fire disaster happens or not according to the temperature data, and determining scene elements in an early warning scene according to the video data;
a self-recognition module: the system is used for adaptively identifying the scene elements when a fire disaster is likely to happen, and determining combustibles;
a security code module: the method is used for converting the inflammable into a safety code in a preset character database through a type matching rule;
the early warning module: and the safety code is matched with a corresponding alarm mechanism to implement fire early warning.
2. A self-identifying and security-code fire-fighting early-warning system as recited in claim 1, wherein said information collection module comprises:
an early warning area determination unit: the early warning system is used for determining the acquisition position and the data acquisition range of a pre-arranged data acquisition device, constructing a three-dimensional acquisition space according to the acquisition position and the data acquisition range, and determining a specific early warning area according to the acquisition space;
a temperature acquisition module: the temperature acquisition device is used for acquiring temperature data; wherein the content of the first and second substances,
the temperature data comprises time data and position data;
a video data acquisition unit: the data acquisition device is used for acquiring video data through video acquisition equipment in the data acquisition device;
a fire determination unit: the temperature data is compared with a preset temperature threshold value to judge whether a fire disaster occurs;
scene element acquisition unit: and the system is used for dyeing and framing the video data and screening out scene elements in the video data through a filtering algorithm.
3. A self-identifying and security code fire warning system as recited in claim 2 wherein said scene element capture unit screening out scene elements comprises the steps of:
step 1: performing color rendering on the video data and generating a rendered image;
step 2: framing the rendered image and generating a frame image set;
and step 3: constructing a color distribution model according to the frame image set;
wherein H represents a color distribution model; xijExpressing the pixel characteristics of a jth pixel point on the ith frame image; μ represents a mathematical expectation; δ represents the variance of the pixel characteristic; 1, 2, 3 … … n; j is 1, 2, 3 … … m; n representing frame imagesA total number; m represents the number of pixel points on each frame image;
and 4, step 4: constructing a scene element characteristic screening model through a preset scene element database:
wherein C represents a scene element feature screening model; f. oflFeatures representing the ith scene element in a scene model database; glRepresenting a weight of the ith scene element in the scene model database;
representing a feature mean of scene elements in a scene model database;
representing the weight mean value of scene elements in a scene model database; beta represents the variance of scene elements in the scene model database; gamma represents the variance of the weights of scene elements in the scene model database; 1, 2, 3 … … q; q represents the total number of scene elements in the scene model database;
and 5: according to the scene element feature screening model and the color distribution model, screening the scene elements in the frame image, and determining the scene elements in the color distribution model through the following formula (1):
when K is larger than or equal to 1, determining corresponding frame images and pixel points of the images, and corresponding the value of K to the corresponding frame images and pixel points of the images to generate an element sequence;
step 6: counting K values of the element sequences, and taking the element sequences with the same K values as scene element groups;
and 7: and determining corresponding scene elements according to the scene element groups.
4. A self-identifying and security code fire warning system as recited in claim 1 wherein said information collection module further comprises:
basic data setting unit: the system comprises a data acquisition device, a data processing device and a data processing device, wherein the data processing device is used for acquiring specification parameters and quality parameters of the data acquisition device and setting basic parameters of the data acquisition device according to the specification parameters and the quality parameters;
a monitoring strategy setting unit: the monitoring system is used for determining historical abnormal frequency and historical abnormal level according to historical abnormal conditions and generating a monitoring strategy according to the historical abnormal frequency and the historical abnormal level;
regularly maintain the data acquisition unit: the system comprises a data acquisition device and a video data acquisition device, and is used for acquiring the timing maintenance data of the data acquisition device and the fire fighting equipment in the fire fighting early warning area, and determining the basic temperature of temperature data acquisition and the initial video of video data acquisition according to the timing maintenance data and the basic parameters.
5. A self-identifying and security code fire warning system as recited in claim 1 wherein said self-identifying module comprises:
an information acquisition unit: the system is used for receiving the scene elements of the corresponding time period when the information acquisition module judges that the fire disaster is likely to happen;
an adaptive identification unit: the system comprises a scene element detection module, a fire early warning database and a fire early warning database, wherein the scene element detection module is used for detecting scene elements in the scene element detection module, identifying combustibles which possibly generate a fire through the preset fire early warning database and extracting combustibles characteristics of the combustibles;
a symmetric unit: and the system is used for symmetrically distributing the scene elements and the combustibles in the fire early warning database and combining the scene elements and the combustibles to generate an outputable data block.
6. A self-identifying and security code fire warning system as recited in claim 1 wherein said self-identifying module further comprises the steps of:
step S1: calibrating video data of fire occurrence;
step S2: preprocessing the video data to obtain preprocessed data; wherein the content of the first and second substances,
the pretreatment comprises the following steps: data graying and data filtering;
step S3, determining scene elements related to fire in the video data according to the preprocessing data and the scene elements;
and step S4, substituting the scene elements related to the fire into a pre-trained adaptive recognition model to determine corresponding inflammable matters.
7. A self-identifying and security-code fire-fighting early warning system as recited in claim 6 wherein the pre-trained adaptive identification model comprises the following training process:
a1, acquiring fire early warning data and inflammable data in a fire early warning database;
step A2: dividing the fire early warning data into a first training set and a first verification set, and dividing the inflammable data into a second training set and a second verification set;
a3, corresponding the fire early warning elements and the inflammable data in the first training set and the second training set, and combining to generate a comprehensive training set;
step A4: inputting the comprehensive training set into a neural network model for training, and converting the training into a self-recognition fire early warning model based on a neural network;
step A5: and respectively inputting the first verification set and the second verification set into the self-recognition fire early warning model, optimizing parameters of the self-recognition fire early warning model, and taking the optimized self-recognition fire early warning model as a trained self-adaptive recognition model.
8. A self-identifying and security-code fire-fighting early warning system as recited in claim 1, wherein said security code module comprises:
the character database module: the character database is formed by the identification characters;
a type matching unit: the device is used for executing a type matching rule according to the character database and the inflammable matter, and calibrating the inflammable matter through a character combination in the character database;
the type matching rule comprises:
a conversion unit: the method is used for obtaining a character combination for calibrating the inflammable, and generating a safety code through the character combination and the recognition time of the inflammable.
9. A self-identifying and security-code fire-fighting early-warning system as recited in claim 1, wherein the early-warning module comprises:
a matching unit: the alarm mechanism is used for acquiring the security code, matching the security code with a preset alarm mechanism and determining early warning;
a judging unit: the safety code is converted into early warning information according to the alarm mechanism; wherein the content of the first and second substances,
the early warning information includes: the location of the early warning, the object of the early warning, and the early warning condition.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114913447A (en) * | 2022-02-17 | 2022-08-16 | 国政通科技有限公司 | Police intelligent command room system and method based on scene recognition |
| CN115512307A (en) * | 2022-11-23 | 2022-12-23 | 中国民用航空飞行学院 | Wide-area space infrared multi-point real-time fire detection method and system and positioning method |
| CN117180687A (en) * | 2023-09-08 | 2023-12-08 | 江苏铭星供水设备有限公司 | Intelligent fire-fighting remote monitoring system and method |
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2021
- 2021-01-20 CN CN202110073385.4A patent/CN112907876A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114913447A (en) * | 2022-02-17 | 2022-08-16 | 国政通科技有限公司 | Police intelligent command room system and method based on scene recognition |
| CN114913447B (en) * | 2022-02-17 | 2023-06-30 | 国政通科技有限公司 | Police intelligent command room system and method based on scene recognition |
| CN115512307A (en) * | 2022-11-23 | 2022-12-23 | 中国民用航空飞行学院 | Wide-area space infrared multi-point real-time fire detection method and system and positioning method |
| CN117180687A (en) * | 2023-09-08 | 2023-12-08 | 江苏铭星供水设备有限公司 | Intelligent fire-fighting remote monitoring system and method |
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