CN112991129A - Public security event processing method and device based on artificial intelligence - Google Patents
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Abstract
The invention discloses a public safety event processing method and a device based on artificial intelligence, wherein the method comprises the following steps: acquiring target image data of a target area in a target time period, and judging whether a public safety event occurs in the target area or not based on an image recognition algorithm according to the target image data; when the target area is judged to have a public safety event, acquiring all related image data of the area near the target area in the target time period from a related image block chain; and analyzing the target image data and all related image data based on a public safety event analysis model, and determining processing information and a processing scheme corresponding to the public safety event. Therefore, the method and the device realize the automatic handling and processing of the public safety events through the artificial intelligence algorithm, and compared with the existing mode of using communication equipment and making a manual decision, the method and the device have the advantages of higher processing efficiency and better processing effect.
Description
Technical Field
The invention relates to the technical field of smart cities, in particular to a public safety event processing method and device based on artificial intelligence.
Background
Along with the intellectualization of cities, the prevention of public safety events by government departments is also gradually improved, and along with the rise and the density of urban population, the prevention of public safety events is more and more important. How to efficiently and timely acquire public safety events becomes a key technical difficulty for treating smart cities.
The existing public safety event processing technology still stays at the level of performing emergency call and emergency processing when a public safety event occurs by using communication equipment, the advantage of target image data brought by cameras which are more and more spread in a city is not realized, meanwhile, when a processing scheme of the public safety event is determined, a manual decision-making mode is still adopted, the efficiency is low, and when some emergent public safety events are sent, the processing effect is unsatisfactory.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide an artificial intelligence-based public security event processing method and apparatus, which can determine a public security event in a target area according to target image data, and automatically obtain corresponding processing information and processing scheme based on an analysis model in combination with related image data of other nearby areas, thereby implementing automatic handling and processing of public security events through an artificial intelligence algorithm.
In order to solve the technical problem, a first aspect of the present invention discloses a public safety event processing method based on artificial intelligence, including:
acquiring target image data of a target area in a target time period, and judging whether a public safety event occurs in the target area or not based on an image recognition algorithm according to the target image data;
when the target area is judged to have a public safety event, acquiring all related image data of the area near the target area in the target time period from a related image block chain;
analyzing the target image data and all related image data based on a public safety event analysis model, and determining processing information and a processing scheme corresponding to the public safety event; the processing information comprises one or more of information of a accountability object, information of responsibility proportion of each object, information of a victim object and information of a responsible department corresponding to the public security incident.
As an alternative embodiment, in the first aspect of the present invention, the public safety event comprises one or more of a natural disaster event, a terrorist attack event, a traffic accident event and a construction accident event; the related image block chain comprises one or more of a vehicle event data recorder image block chain, a street camera image block chain and a shop camera image block chain; the related image data includes one or more of a tachograph image of a vehicle of the vicinity, a street camera image of the vicinity, a shop camera image of the vicinity.
As an optional implementation manner, in the first aspect of the present invention, the determining, according to the target image data and based on an image recognition algorithm, whether a public safety event occurs in the target area includes:
identifying a pedestrian image and a natural disaster image in the target image data based on an image identification algorithm; the natural disaster image comprises one or more of a green space flame image, a large water flow image, a giant animal image and a ground crack image;
and when the fact that the advancing directions of all the pedestrian images are far away from the natural disaster image and the advancing acceleration of the pedestrian images is positive in the target image data is judged, judging that the natural disaster event occurs in the target area.
As an optional implementation manner, in the first aspect of the present invention, the determining, according to the target image data and based on an image recognition algorithm, whether a public safety event occurs in the target area includes:
judging whether a murder image set, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the image similarity of the murder image set and the fleeing person image set is lower than a preset threshold value; an included angle between the moving direction of the murder image set and the moving direction of the fleeing person image set is smaller than a preset first included angle threshold value; the average advancing speed of the escaper image set is greater than that of the murder image set, and the difference value of the two advancing speeds is greater than a preset speed difference threshold value; the pedestrian posture of the victim image set is falling down;
when the situation that the murder image set, the fleeer image set and the victim image set exist in the target image data is judged, the target area is judged to have a terrorist attack event;
and/or the presence of a gas in the gas,
judging whether an explosion image, an escaper image set and a victim image set exist in the target image data based on an image recognition algorithm; the direction of travel of the set of escaper images is away from the explosion image; the pedestrian posture of the victim image set is falling down;
and when the situation that the murder image set, the escaper image set and the victim image set exist in the target image data is judged, judging that the terrorist attack event occurs in the target area.
As an optional implementation manner, in the first aspect of the present invention, the determining, according to the target image data and based on an image recognition algorithm, whether a public safety event occurs in the target area includes:
judging whether an overspeed vehicle image set, a damaged vehicle image set, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the speed of the vehicle images in the overspeed vehicle image set is higher than a preset safe speed threshold; the advancing direction of the overspeed vehicle image set and the escaper image set is smaller than a preset second included angle threshold value; the pedestrian posture of the victim image set is falling down; the image state of the damaged vehicle image set is damaged, burnt or scorched;
and when judging that one or more of the overspeed vehicle image set, the damaged vehicle image set, the escaper image set and the victim image set exist in the target image data, judging that a traffic accident event occurs in the target area.
As an optional implementation manner, in the first aspect of the present invention, the determining, according to the target image data and based on an image recognition algorithm, whether a public safety event occurs in the target area includes:
judging whether the target image data belongs to a construction site scene or not based on an image recognition algorithm;
when the target image data is judged to belong to a construction site scene, judging whether an engineering accident image, an escaper image set and a victim image set exist in the target image data; the engineering accident image comprises one or more of a building collapse image, a column body fracture image and a construction explosion image; the pedestrian posture of the victim image set is falling down; the moving direction of the escaper image set is far away from the engineering accident image;
and when judging that the engineering accident image, the escaper image set and the victim image set exist in the target image data, judging that the construction accident event occurs in the target area.
As an optional implementation manner, in the first aspect of the present invention, the acquiring, from the related image block chain, all related image data of the vicinity of the target region in the target time period includes:
acquiring marks of all camera shooting main bodies in the area near the target area; the camera shooting main body comprises one or more of a vehicle driving recorder, a street camera and a shop camera;
and downloading all the related image data recorded by the camera main body in the target time period from the related image block chain according to the identification of the camera main body.
As an alternative implementation, in the first aspect of the present invention, the method further includes:
sending processing information and a processing scheme corresponding to the public safety event to corresponding processing equipment; the processing device comprises one or more of a government department terminal device, a regional broadcast device and a mobile terminal device of a target user.
The invention discloses a public safety event processing device based on artificial intelligence in a second aspect, which comprises:
the judging module is used for acquiring target image data of a target area in a target time period and judging whether a public safety event occurs in the target area based on an image recognition algorithm according to the target image data;
the acquisition module is used for acquiring all related image data of the area near the target area in the target time period from a related image block chain when the target area is judged to have a public safety event;
the analysis module is used for analyzing the target image data and all the related image data based on a public safety event analysis model and determining processing information and a processing scheme corresponding to the public safety event; the processing information comprises one or more of information of a accountability object, information of a victim object and information of a responsible department corresponding to the public safety event.
As an alternative embodiment, in the second aspect of the present invention, the public safety event includes one or more of a natural disaster event, a terrorist attack event, a traffic accident event and a construction accident event; the related image block chain comprises one or more of a vehicle event data recorder image block chain, a street camera image block chain and a shop camera image block chain; the related image data includes one or more of a tachograph image of a vehicle of the vicinity, a street camera image of the vicinity, a shop camera image of the vicinity.
As an optional implementation manner, in the second aspect of the present invention, a specific manner of determining, by the determining module, whether a public safety event occurs in the target area based on an image recognition algorithm according to the target image data includes:
identifying a pedestrian image and a natural disaster image in the target image data based on an image identification algorithm; the natural disaster image comprises one or more of a green space flame image, a large water flow image, a giant animal image and a ground crack image;
and when the fact that the advancing directions of all the pedestrian images are far away from the natural disaster image and the advancing acceleration of the pedestrian images is positive in the target image data is judged, judging that the natural disaster event occurs in the target area.
As an optional implementation manner, in the second aspect of the present invention, a specific manner of determining, by the determining module, whether a public safety event occurs in the target area based on an image recognition algorithm according to the target image data includes:
judging whether a murder image set, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the image similarity of the murder image set and the fleeing person image set is lower than a preset threshold value; an included angle between the moving direction of the murder image set and the moving direction of the fleeing person image set is smaller than a preset first included angle threshold value; the average advancing speed of the escaper image set is greater than that of the murder image set, and the difference value of the two advancing speeds is greater than a preset speed difference threshold value; the pedestrian posture of the victim image set is falling down;
when the situation that the murder image set, the fleeer image set and the victim image set exist in the target image data is judged, the target area is judged to have a terrorist attack event;
and/or the presence of a gas in the gas,
judging whether an explosion image, an escaper image set and a victim image set exist in the target image data based on an image recognition algorithm; the direction of travel of the set of escaper images is away from the explosion image; the pedestrian posture of the victim image set is falling down;
and when the situation that the murder image set, the escaper image set and the victim image set exist in the target image data is judged, judging that the terrorist attack event occurs in the target area.
As an optional implementation manner, in the second aspect of the present invention, a specific manner of determining, by the determining module, whether a public safety event occurs in the target area based on an image recognition algorithm according to the target image data includes:
judging whether an overspeed vehicle image set, a damaged vehicle image set, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the speed of the vehicle images in the overspeed vehicle image set is higher than a preset safe speed threshold; the advancing direction of the overspeed vehicle image set and the escaper image set is smaller than a preset second included angle threshold value; the pedestrian posture of the victim image set is falling down; the image state of the damaged vehicle image set is damaged, burnt or scorched;
and when judging that one or more of the overspeed vehicle image set, the damaged vehicle image set, the escaper image set and the victim image set exist in the target image data, judging that a traffic accident event occurs in the target area.
As an optional implementation manner, in the second aspect of the present invention, a specific manner of determining, by the determining module, whether a public safety event occurs in the target area based on an image recognition algorithm according to the target image data includes:
judging whether the target image data belongs to a construction site scene or not based on an image recognition algorithm;
when the target image data is judged to belong to a construction site scene, judging whether an engineering accident image, an escaper image set and a victim image set exist in the target image data; the engineering accident image comprises one or more of a building collapse image, a column body fracture image and a construction explosion image; the pedestrian posture of the victim image set is falling down; the moving direction of the escaper image set is far away from the engineering accident image;
and when judging that the engineering accident image, the escaper image set and the victim image set exist in the target image data, judging that the construction accident event occurs in the target area.
As an optional implementation manner, in the second aspect of the present invention, a specific manner of acquiring, by the acquisition module, all relevant image data of the vicinity of the target region in the target time period from the relevant image block chain includes:
acquiring marks of all camera shooting main bodies in the area near the target area; the camera shooting main body comprises one or more of a vehicle driving recorder, a street camera and a shop camera;
and downloading all the related image data recorded by the camera main body in the target time period from the related image block chain according to the identification of the camera main body.
As an alternative embodiment, in the second aspect of the present invention, the apparatus further comprises:
the sending module is used for sending the processing information and the processing scheme corresponding to the public safety event to corresponding processing equipment; the processing device comprises one or more of a government department terminal device, a regional broadcast device and a mobile terminal device of a target user.
The third aspect of the invention discloses another public safety event processing device based on artificial intelligence, which comprises:
a memory storing executable program code;
a processor coupled with the memory;
the processor calls the executable program code stored in the memory to execute part or all of the steps of the artificial intelligence based public safety event processing method disclosed in the first aspect of the embodiment of the invention.
A fourth aspect of the embodiments of the present invention discloses a computer storage medium, where the computer storage medium stores computer instructions, and when the computer instructions are called, the computer instructions are used to execute part or all of the steps in the artificial intelligence based public safety event processing method disclosed in the first aspect of the embodiments of the present invention.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
in the embodiment of the invention, target image data of a target area in a target time period is obtained, and whether a public safety event occurs in the target area is judged based on an image recognition algorithm according to the target image data; when the target area is judged to have a public safety event, acquiring all related image data of the area near the target area in the target time period from a related image block chain; analyzing the target image data and all related image data based on a public safety event analysis model, and determining processing information and a processing scheme corresponding to the public safety event; the processing information comprises one or more of information of a accountability object, information of responsibility proportion of each object, information of a victim object and information of a responsible department corresponding to the public security incident. Therefore, the method and the device can judge the public safety event in the target area according to the target image data, and automatically obtain the corresponding processing information and processing scheme based on the analysis model by combining the related image data of other nearby areas, so that the public safety event can be automatically responded and processed through an artificial intelligence algorithm.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a public safety event processing method based on artificial intelligence disclosed in an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an artificial intelligence-based public safety event processing apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another artificial intelligence-based public safety event processing apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or article.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The invention discloses a public safety event processing method and device based on artificial intelligence, which can judge a public safety event in a target area according to target image data, and automatically obtain corresponding processing information and a processing scheme based on an analysis model by combining related image data of other nearby areas, thereby realizing automatic handling and processing of the public safety event through the artificial intelligence algorithm. The following are detailed below.
Example one
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a public safety event processing method based on artificial intelligence according to an embodiment of the present invention. As shown in fig. 1, the artificial intelligence based public safety event processing method may include the following operations:
101. and acquiring target image data of the target area in a target time period, and judging whether a public safety event occurs in the target area based on an image recognition algorithm according to the target image data.
In embodiments of the present invention, public safety events include one or more of natural disaster events, terrorist attack events, traffic accident events and construction accident events.
102. And when the public safety event occurs in the target area, acquiring all related image data of the vicinity area of the target area in the target time period from the related image block chain.
In an embodiment of the invention, the related image block chain includes one or more of a car recorder image block chain, a street camera image block chain, and a shop camera image block chain.
In an embodiment of the invention, the relevant image data comprises one or more of a tachograph image of a vehicle of said vicinity, a street camera image of said vicinity, a shop camera image of said vicinity.
103. And analyzing the target image data and all related image data based on the public safety event analysis model, and determining processing information and a processing scheme corresponding to the public safety event.
In the embodiment of the present invention, the processing information includes one or more of information of a liability object, information of a liability proportion of each object, information of a victim object, and information of a responsible department corresponding to the public security event.
Therefore, by implementing the embodiment of the invention, the public safety event in the target area can be judged according to the target image data, and the corresponding processing information and processing scheme can be automatically obtained based on the analysis model by combining the related image data of other nearby areas, so that the public safety event can be automatically responded and processed by an artificial intelligence algorithm.
As an alternative embodiment, in step 101, determining whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
identifying a pedestrian image and a natural disaster image in the target image data based on an image identification algorithm; the natural disaster image comprises one or more of a green space flame image, a large water flow image, a giant animal image and a ground crack image;
and when the moving direction of all the pedestrian images in the target image data is determined to be far away from the natural disaster image and the moving acceleration of the pedestrian images is positive, determining that the natural disaster event occurs in the target area.
Therefore, by implementing the optional embodiment, the natural disaster event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through the algorithm, and compared with the existing mode of using manual identification response, the method has the advantages of higher identification efficiency and better identification effect.
As an alternative embodiment, in step 101, determining whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
judging whether a murder image set, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the image similarity of the murder image set and the fleeing person image set is lower than a preset threshold value; the included angle between the moving direction of the murder image set and the moving direction of the escaper image set is smaller than a preset first included angle threshold value; the average advancing speed of the escaper image set is greater than that of the murder image set, and the difference value of the two advancing speeds is greater than a preset speed difference threshold value; the pedestrian posture of the victim image set is falling down;
and when judging that the target image data contains a murder image set, an escaper image set and a victim image set, judging that the target area has a terrorist attack event.
Therefore, through the implementation of the optional embodiment, the terrorist attack event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through the algorithm, and compared with the existing mode of using manual identification response, the method has the advantages of higher identification efficiency and better identification effect.
As an alternative embodiment, in step 101, determining whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
judging whether an explosion image, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the moving direction of the escaper image set is far away from the explosion image; the pedestrian posture of the victim image set is falling down;
and when judging that the target image data contains a murder image set, an escaper image set and a victim image set, judging that the target area has a terrorist attack event.
Therefore, through the implementation of the optional embodiment, the terrorist attack event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through the algorithm, and compared with the existing mode of using manual identification response, the method has the advantages of higher identification efficiency and better identification effect.
As an alternative embodiment, in step 101, determining whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
judging whether an overspeed vehicle image set, a damaged vehicle image set, an escaper image set and a victim image set exist in target image data or not based on an image recognition algorithm; the speed of the vehicle images in the overspeed vehicle image set is higher than a preset safe speed threshold; the advancing direction of the overspeed vehicle image set and the escaper image set is smaller than a preset second included angle threshold value; the pedestrian posture of the victim image set is falling down; the image state of the damaged vehicle image set is damaged, burnt or scorched;
and when judging that one or more of an overspeed vehicle image set, a damaged vehicle image set, an escaper image set and a victim image set exist in the target image data, judging that a traffic accident event occurs in the target area.
Therefore, by implementing the optional embodiment, the traffic accident event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through the algorithm, and compared with the existing manual identification response mode, the method has the advantages of higher identification efficiency and better identification effect.
As an alternative embodiment, in step 101, determining whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
judging whether the target image data belongs to a construction site scene or not based on an image recognition algorithm;
when the target image data are judged to belong to the construction site scene, judging whether an engineering accident image, an escaper image set and a victim image set exist in the target image data; the engineering accident image comprises one or more of a building collapse image, a column body fracture image and a construction explosion image; the pedestrian posture of the victim image set is falling down; the moving direction of the escaper image set is far away from the engineering accident image;
and when judging that the target image data contains the engineering accident image, the escaper image set and the victim image set, judging that the construction accident event occurs in the target area.
Therefore, by implementing the optional embodiment, the construction accident event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through an algorithm, and compared with the existing mode of using manual identification response, the method has the advantages of higher identification efficiency and better identification effect.
As an alternative embodiment, in step 102, acquiring all relevant image data of the vicinity of the target region in the target time period from the relevant image block chain includes:
acquiring marks of all camera shooting main bodies in a region near a target region;
and downloading all the recorded related image data of the shooting subject in the target time period from the related image block chain according to the identification of the shooting subject.
In the embodiment of the invention, the camera body comprises one or more of a vehicle driving recorder, a street camera and a shop camera.
Therefore, by implementing the optional embodiment, all the related image data recorded by the camera main body in the target time period can be downloaded from the related image block chain, so that the authenticity and reliability of the target image data which is accidentally removed are ensured by utilizing the block chain technology, and compared with the existing mode of calling image data, the authenticity of the target image data is higher.
As an alternative embodiment, the method further comprises:
and sending the processing information and the processing scheme corresponding to the public safety event to corresponding processing equipment.
In the embodiment of the invention, the processing equipment comprises one or more of government department terminal equipment, regional broadcast equipment and mobile terminal equipment of target users.
Therefore, by implementing the optional embodiment, the processing information and the processing scheme corresponding to the public safety event can be sent to the corresponding processing equipment, so that the processing equipment can inform relevant departments of the acquisition, recording and emergency treatment of the public safety event, or inform relevant personnel of the field evacuation.
As an optional embodiment, the public safety event analysis model in step 103 may include a relational database of correspondence between various public safety events and the processing information and the processing scheme, or may be a predictive neural network model obtained by training in advance using training data including public safety event information and corresponding processing information and processing scheme, where the public safety event information may include information such as the type, scale, time, and location of the public safety event.
In a further embodiment, the analyzing the target image data and all the related image data in step 103 to determine the processing information and the processing scheme corresponding to the public safety event may include:
processing the target image data and all related image data based on an image recognition algorithm, and recognizing a murder image set or an overspeed vehicle image set in the target image data and all related image data;
determining a murder image set or an overspeed vehicle image set as information of an accountability object in processing information corresponding to public safety time;
and/or the presence of a gas in the gas,
processing the target image data and all related image data based on an image recognition algorithm, and recognizing a damaged vehicle image set, an escaper image set or a victim image set in the target image data and all related image data;
and determining the damaged vehicle image set, the escaper image set or the victim image set as victim information in the processing information corresponding to the public safety time.
Therefore, by implementing the further embodiment, the target image data and all related image data can be analyzed based on the image recognition algorithm, and the victim object information and the accountability object information in the processing information corresponding to the public safety event are determined, so that the processing information of the public safety event is automatically determined through the artificial intelligence algorithm.
Example two
Referring to fig. 2, fig. 2 is a schematic structural diagram of an artificial intelligence-based public safety event processing apparatus according to an embodiment of the present invention. As shown in fig. 2, the apparatus may include:
the determining module 201 is configured to acquire target image data of a target area in a target time period, and determine whether a public safety event occurs in the target area based on an image recognition algorithm according to the target image data.
In embodiments of the present invention, public safety events include one or more of natural disaster events, terrorist attack events, traffic accident events and construction accident events.
An obtaining module 202, configured to obtain all relevant image data of a vicinity area of the target area in the target time period from the relevant image block chain when it is determined that the public safety event occurs in the target area.
In an embodiment of the invention, the related image block chain includes one or more of a car recorder image block chain, a street camera image block chain, and a shop camera image block chain.
In an embodiment of the invention, the relevant image data comprises one or more of a tachograph image of a vehicle of said vicinity, a street camera image of said vicinity, a shop camera image of said vicinity.
And the analysis module 203 is configured to analyze the target image data and all related image data based on the public safety event analysis model, and determine processing information and a processing scheme corresponding to the public safety event.
In the embodiment of the present invention, the processing information includes one or more of information of a liability object, information of a liability proportion of each object, information of a victim object, and information of a responsible department corresponding to the public security event.
Therefore, by implementing the embodiment of the invention, the public safety event in the target area can be judged according to the target image data, and the corresponding processing information and processing scheme can be automatically obtained based on the analysis model by combining the related image data of other nearby areas, so that the public safety event can be automatically responded and processed by an artificial intelligence algorithm.
As an optional embodiment, the specific way for determining, by the determining module 201, whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
identifying a pedestrian image and a natural disaster image in the target image data based on an image identification algorithm; the natural disaster image comprises one or more of a green space flame image, a large water flow image, a giant animal image and a ground crack image;
and when the moving direction of all the pedestrian images in the target image data is determined to be far away from the natural disaster image and the moving acceleration of the pedestrian images is positive, determining that the natural disaster event occurs in the target area.
Therefore, by implementing the optional embodiment, the natural disaster event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through the algorithm, and compared with the existing mode of using manual identification response, the method has the advantages of higher identification efficiency and better identification effect.
As an optional embodiment, the specific way for determining, by the determining module 201, whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
judging whether a murder image set, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the image similarity of the murder image set and the fleeing person image set is lower than a preset threshold value; the included angle between the moving direction of the murder image set and the moving direction of the escaper image set is smaller than a preset first included angle threshold value; the average advancing speed of the escaper image set is greater than that of the murder image set, and the difference value of the two advancing speeds is greater than a preset speed difference threshold value; the pedestrian posture of the victim image set is falling down;
and when judging that the target image data contains a murder image set, an escaper image set and a victim image set, judging that the target area has a terrorist attack event.
Therefore, through the implementation of the optional embodiment, the terrorist attack event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through the algorithm, and compared with the existing mode of using manual identification response, the method has the advantages of higher identification efficiency and better identification effect.
As an optional embodiment, the specific way for determining, by the determining module 201, whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
judging whether an explosion image, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the moving direction of the escaper image set is far away from the explosion image; the pedestrian posture of the victim image set is falling down;
and when judging that the target image data contains a murder image set, an escaper image set and a victim image set, judging that the target area has a terrorist attack event.
Therefore, through the implementation of the optional embodiment, the terrorist attack event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through the algorithm, and compared with the existing mode of using manual identification response, the method has the advantages of higher identification efficiency and better identification effect.
As an optional embodiment, the specific way for determining, by the determining module 201, whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
judging whether an overspeed vehicle image set, a damaged vehicle image set, an escaper image set and a victim image set exist in target image data or not based on an image recognition algorithm; the speed of the vehicle images in the overspeed vehicle image set is higher than a preset safe speed threshold; the advancing direction of the overspeed vehicle image set and the escaper image set is smaller than a preset second included angle threshold value; the pedestrian posture of the victim image set is falling down; the image state of the damaged vehicle image set is damaged, burnt or scorched;
and when judging that one or more of an overspeed vehicle image set, a damaged vehicle image set, an escaper image set and a victim image set exist in the target image data, judging that a traffic accident event occurs in the target area.
Therefore, by implementing the optional embodiment, the traffic accident event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through the algorithm, and compared with the existing manual identification response mode, the method has the advantages of higher identification efficiency and better identification effect.
As an optional embodiment, the specific way for determining, by the determining module 201, whether a public safety event occurs in the target area based on the image recognition algorithm according to the target image data includes:
judging whether the target image data belongs to a construction site scene or not based on an image recognition algorithm;
when the target image data are judged to belong to the construction site scene, judging whether an engineering accident image, an escaper image set and a victim image set exist in the target image data; the engineering accident image comprises one or more of a building collapse image, a column body fracture image and a construction explosion image; the pedestrian posture of the victim image set is falling down; the moving direction of the escaper image set is far away from the engineering accident image;
and when judging that the target image data contains the engineering accident image, the escaper image set and the victim image set, judging that the construction accident event occurs in the target area.
Therefore, by implementing the optional embodiment, the construction accident event in the target area can be judged according to the target image data, so that the public safety event can be automatically identified through an algorithm, and compared with the existing mode of using manual identification response, the method has the advantages of higher identification efficiency and better identification effect.
As an alternative embodiment, the specific manner of acquiring all the relevant image data of the vicinity of the target region in the target time period from the relevant image block chain by the acquiring module 202 includes:
acquiring marks of all camera shooting main bodies in a region near a target region;
and downloading all the recorded related image data of the shooting subject in the target time period from the related image block chain according to the identification of the shooting subject.
In the embodiment of the invention, the camera body comprises one or more of a vehicle driving recorder, a street camera and a shop camera.
Therefore, by implementing the optional embodiment, all the related image data recorded by the camera main body in the target time period can be downloaded from the related image block chain, so that the authenticity and reliability of the target image data which is accidentally removed are ensured by utilizing the block chain technology, and compared with the existing mode of calling image data, the authenticity of the target image data is higher.
As an alternative embodiment, the apparatus further comprises:
and the sending module is used for sending the processing information and the processing scheme corresponding to the public safety event to the corresponding processing equipment.
In the embodiment of the invention, the processing equipment comprises one or more of government department terminal equipment, regional broadcast equipment and mobile terminal equipment of target users.
Therefore, by implementing the optional embodiment, the processing information and the processing scheme corresponding to the public safety event can be sent to the corresponding processing equipment, so that the processing equipment can inform relevant departments of the acquisition, recording and emergency treatment of the public safety event, or inform relevant personnel of the field evacuation.
As an optional embodiment, the public safety event analysis model in the analysis module 103 may include a relational database of correspondence between various public safety events and the processing information and processing schemes, or may be a predictive neural network model obtained by training in advance using training data including public safety event information and corresponding processing information and processing schemes, where the public safety event information may include information such as types, scales, times, and locations of the public safety events.
In a further embodiment, the analyzing module 103 analyzes the target image data and all related image data to determine a specific manner of processing information and a processing scheme corresponding to the public safety event, which may include:
processing the target image data and all related image data based on an image recognition algorithm, and recognizing a murder image set or an overspeed vehicle image set in the target image data and all related image data;
determining a murder image set or an overspeed vehicle image set as information of an accountability object in processing information corresponding to public safety time;
and/or the presence of a gas in the gas,
processing the target image data and all related image data based on an image recognition algorithm, and recognizing a damaged vehicle image set, an escaper image set or a victim image set in the target image data and all related image data;
and determining the damaged vehicle image set, the escaper image set or the victim image set as victim information in the processing information corresponding to the public safety time.
Therefore, by implementing the further embodiment, the target image data and all related image data can be analyzed based on the image recognition algorithm, and the victim object information and the accountability object information in the processing information corresponding to the public safety event are determined, so that the processing information of the public safety event is automatically determined through the artificial intelligence algorithm.
EXAMPLE III
Referring to fig. 3, fig. 3 is a schematic structural diagram of another artificial intelligence-based public safety event processing apparatus according to an embodiment of the present invention. As shown in fig. 3, the apparatus may include:
a memory 301 storing executable program code;
a processor 302 coupled to the memory 301;
the processor 302 calls the executable program code stored in the memory 301 to execute part or all of the steps of the artificial intelligence based public safety event processing method disclosed in the embodiment of the present invention.
Example four
The embodiment of the invention discloses a computer storage medium, which stores computer instructions, and when the computer instructions are called, the computer instructions are used for executing part or all of the steps in the public safety event processing method based on artificial intelligence disclosed by the embodiment of the invention.
EXAMPLE five
The embodiment of the invention discloses a public safety event processing system based on artificial intelligence, which comprises a data transmission module. The data transmission module is used for executing part or all of the steps in the artificial intelligence based public safety event processing method disclosed by the embodiment of the invention.
The above-described embodiments of the apparatus are merely illustrative, and the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above detailed description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. Based on such understanding, the above technical solutions may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, where the storage medium includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc-Read-Only Memory (CD-ROM), or other disk memories, CD-ROMs, or other magnetic disks, A tape memory, or any other medium readable by a computer that can be used to carry or store data.
Finally, it should be noted that: the method and the device for processing public safety events based on artificial intelligence disclosed in the embodiment of the invention are only the preferred embodiment of the invention, and are only used for illustrating the technical scheme of the invention, but not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A public safety event processing method based on artificial intelligence is characterized by comprising the following steps:
acquiring target image data of a target area in a target time period, and judging whether a public safety event occurs in the target area or not based on an image recognition algorithm according to the target image data;
when the target area is judged to have a public safety event, acquiring all related image data of the area near the target area in the target time period from a related image block chain;
analyzing the target image data and all related image data based on a public safety event analysis model, and determining processing information and a processing scheme corresponding to the public safety event; the processing information comprises one or more of information of a accountability object, information of responsibility proportion of each object, information of a victim object and information of a responsible department corresponding to the public security incident.
2. The artificial intelligence based public safety event processing method of claim 1, wherein the public safety event comprises one or more of a natural disaster event, a terrorist attack event, a traffic accident event and a construction accident event; the related image block chain comprises one or more of a vehicle event data recorder image block chain, a street camera image block chain and a shop camera image block chain; the related image data includes one or more of a tachograph image of a vehicle of the vicinity, a street camera image of the vicinity, a shop camera image of the vicinity.
3. The artificial intelligence based public safety incident processing method according to claim 2, wherein the determining whether the target area has a public safety incident based on an image recognition algorithm according to the target image data comprises:
identifying a pedestrian image and a natural disaster image in the target image data based on an image identification algorithm; the natural disaster image comprises one or more of a green space flame image, a large water flow image, a giant animal image and a ground crack image;
and when the fact that the advancing directions of all the pedestrian images are far away from the natural disaster image and the advancing acceleration of the pedestrian images is positive in the target image data is judged, judging that the natural disaster event occurs in the target area.
4. The artificial intelligence based public safety incident processing method according to claim 2, wherein the determining whether the target area has a public safety incident based on an image recognition algorithm according to the target image data comprises:
judging whether a murder image set, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the image similarity of the murder image set and the fleeing person image set is lower than a preset threshold value; an included angle between the moving direction of the murder image set and the moving direction of the fleeing person image set is smaller than a preset first included angle threshold value; the average advancing speed of the escaper image set is greater than that of the murder image set, and the difference value of the two advancing speeds is greater than a preset speed difference threshold value; the pedestrian posture of the victim image set is falling down;
when the situation that the murder image set, the fleeer image set and the victim image set exist in the target image data is judged, the target area is judged to have a terrorist attack event;
and/or the presence of a gas in the gas,
judging whether an explosion image, an escaper image set and a victim image set exist in the target image data based on an image recognition algorithm; the direction of travel of the set of escaper images is away from the explosion image; the pedestrian posture of the victim image set is falling down;
and when the situation that the murder image set, the escaper image set and the victim image set exist in the target image data is judged, judging that the terrorist attack event occurs in the target area.
5. The artificial intelligence based public safety incident processing method according to claim 2, wherein the determining whether the target area has a public safety incident based on an image recognition algorithm according to the target image data comprises:
judging whether an overspeed vehicle image set, a damaged vehicle image set, an escaper image set and a victim image set exist in the target image data or not based on an image recognition algorithm; the speed of the vehicle images in the overspeed vehicle image set is higher than a preset safe speed threshold; the advancing direction of the overspeed vehicle image set and the escaper image set is smaller than a preset second included angle threshold value; the pedestrian posture of the victim image set is falling down; the image state of the damaged vehicle image set is damaged, burnt or scorched;
and when judging that one or more of the overspeed vehicle image set, the damaged vehicle image set, the escaper image set and the victim image set exist in the target image data, judging that a traffic accident event occurs in the target area.
6. The artificial intelligence based public safety incident processing method according to claim 2, wherein the determining whether the target area has a public safety incident based on an image recognition algorithm according to the target image data comprises:
judging whether the target image data belongs to a construction site scene or not based on an image recognition algorithm;
when the target image data is judged to belong to a construction site scene, judging whether an engineering accident image, an escaper image set and a victim image set exist in the target image data; the engineering accident image comprises one or more of a building collapse image, a column body fracture image and a construction explosion image; the pedestrian posture of the victim image set is falling down; the moving direction of the escaper image set is far away from the engineering accident image;
and when judging that the engineering accident image, the escaper image set and the victim image set exist in the target image data, judging that the construction accident event occurs in the target area.
7. The artificial intelligence based public safety incident processing method according to claim 2, wherein the obtaining all relevant image data of the vicinity of the target area in the target time period from the relevant image block chain comprises:
acquiring marks of all camera shooting main bodies in the area near the target area; the camera shooting main body comprises one or more of a vehicle driving recorder, a street camera and a shop camera;
and downloading all the related image data recorded by the camera main body in the target time period from the related image block chain according to the identification of the camera main body.
8. The artificial intelligence based public safety event processing method according to claim 1, further comprising:
sending processing information and a processing scheme corresponding to the public safety event to corresponding processing equipment; the processing device comprises one or more of a government department terminal device, a regional broadcast device and a mobile terminal device of a target user.
9. An artificial intelligence based public safety event processing apparatus, comprising:
the judging module is used for acquiring target image data of a target area in a target time period and judging whether a public safety event occurs in the target area based on an image recognition algorithm according to the target image data;
the acquisition module is used for acquiring all related image data of the area near the target area in the target time period from a related image block chain when the target area is judged to have a public safety event;
the analysis module is used for analyzing the target image data and all the related image data based on a public safety event analysis model and determining processing information and a processing scheme corresponding to the public safety event; the processing information comprises one or more of information of a accountability object, information of a victim object and information of a responsible department corresponding to the public safety event.
10. An artificial intelligence based public safety event processing apparatus, the apparatus comprising:
a memory storing executable program code;
a processor coupled with the memory;
the processor calls the executable program code stored in the memory to perform the artificial intelligence based public safety event processing method of any of claims 1-8.
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