CN110222675A - A kind of police strength dispatching method, system, terminal and storage medium - Google Patents
A kind of police strength dispatching method, system, terminal and storage medium Download PDFInfo
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Abstract
The invention discloses a kind of police strength dispatching method, include the following steps: the real-time image information for acquiring ambient enviroment；Real-time image information is input in model, the model is formed by the training of multiple groups training data, each group of training data includes first kind training data in training data described in multiple groups, and the first kind training data includes abnormal behaviour image and the identification information for identifying abnormal behaviour image；The image that real-time image information meets abnormal behaviour is exported from model；Obtain the place for meeting the real-time image information acquisition of abnormal behaviour；Issue police strength scheduling request.The present invention provides a kind of Dynamic Recognition abnormal behaviour, and the police strength dispatching method warned to the police.
Description
Technical field
The present invention relates to security administration technical field more particularly to a kind of police strength dispatching method, system, terminal and storages
Medium.
Background technique
With the surge of social population, public place day flow of the people also rise violently therewith.Certain criminals utilize huge people
Some behaviors to endanger public security are done in the shielding of flow.Therefore, the security administration work of the police will face severe examine
It tests.
Again because the human resources of the current police are not sufficient enough to be covered in major public place, once safe thing occurs
Therefore the police will be unable to the processing that is on the scene at the first time again, it is easy to dangerous situation be caused to develop to more dangerous direction.Therefore, originally
A kind of method that technical field is badly in need of Dynamic Recognition abnormal behaviour, so that timely police strength is dispatched.
Summary of the invention
The purpose of the present invention is to provide a kind of Dynamic Recognition abnormal behaviours, and the police strength dispatching method warned to the police.
Technical solution used by a kind of police strength dispatching method disclosed by the invention is:
A kind of police strength dispatching method, includes the following steps:
Acquire the real-time image information of ambient enviroment；
Real-time image information is input in model, the model is formed by the training of multiple groups training data, is instructed described in multiple groups
Practicing each group of training data in data includes first kind training data, and the first kind training data includes abnormal behaviour figure
Picture and identification information for identifying abnormal behaviour image；
The image that real-time image information meets abnormal behaviour is exported from model；
Obtain the place for meeting the real-time image information acquisition of abnormal behaviour；
Issue police strength scheduling request.
Preferably, the police strength scheduling request is sent to centered on collecting location, the police in specified radius
Power.
Preferably, the training data further includes the second class training data, and the second class training data includes
Normal behaviour image and identification information for identifying normal behaviour image.
Preferably, the first kind training data is divided into multistage training data, training data packet described in every level-one
Include the grade of abnormal behaviour image, the identification information for identifying abnormal behaviour image and corresponding abnormal behaviour image；
Output real-time image information meets the image of abnormal behaviour and corresponds to exception level in corresponding model.
Preferably, the first kind training data and the second class training data are true in police's database
Real data.
Preferably, the police strength of the scheduling is allocated according to exception level.
The technical program also provides a kind of police strength scheduling system, including algoritic module, training module, database, image are adopted
Collect module, locating module, police strength scheduler module and multiple execution units；
Wherein the abnormal behaviour image of the training data in training module called data library and corresponding exception level input
It is run to algoritic module, the ability for identifying abnormal behaviour for training algorithm module and grading for abnormal behaviour.
Described image acquisition module includes multiple images acquisition unit, each described image acquisition unit is set to public
The a certain position in place, and the real-time image information obtained in corresponding range is sent to algoritic module；
The algoritic module executes identification abnormal behaviour and the function for abnormal behaviour grading, Dynamic Recognition realtime graphic
Meet the image and exception level of abnormal behaviour in information, at the same algoritic module transmitted according to image acquisition units it is real-time
The IP address of image information determines the precise position information in its reality, and by the image of abnormal behaviour, exception level information with
And the precise position information in image acquisition units reality is sent to police strength scheduler module；
Police strength scheduler module dispatches specified range around the exact position in image acquisition units reality according to exception level
The police strength of interior specified quantity executes task.
Preferably, the database is the database of the true abnormal behaviour of the daily storage of the police.
The technical program also provides a kind of terminal, and the terminal includes:
One or more processors；
Storage device, for storing one or more programs,
When one or more of programs are executed by one or more of processors, so that one or more of places
It manages device and realizes police strength dispatching method as the aforementioned.
The technical program also provides a kind of computer readable storage medium, is stored thereon with computer program, the program quilt
Processor realizes police strength dispatching method as the aforementioned when executing.
A kind of beneficial effect of police strength dispatching method disclosed by the invention is: being identified using training data to model abnormal
The training of behavior image, so that the model is generated one kind can be with the ability of autonomous classification abnormal behaviour image.Public field will be acquired again
Real-time image information input model in, with Dynamic Recognition abnormal behaviour, warn to the police, and in time scheduling police strength execute
Task.Therefore, can by abnormal behaviour bring influence be reduced to it is minimum, guarantee the people, property safe and good order
Sequence.
Detailed description of the invention
Fig. 1 is a kind of structural schematic diagram of police strength dispatching method of the present invention.
Fig. 2 is a kind of structural block diagram of police strength scheduling system of the present invention.
Specific embodiment
The present invention is further elaborated and is illustrated with Figure of description combined with specific embodiments below:
Referring to FIG. 1, a kind of police strength dispatching method, includes the following steps:
Step S101: the real-time image information of ambient enviroment is acquired.
Wherein, the real-time image information of ambient enviroment is real-time by being distributed in the monitor camera of public place actually
The monitoring image information sent out.The monitoring image information mainly includes two parts, and first part is adopted by municipal monitoring center
The public place monitoring image information of collection is mainly used for monitoring the public safety order of public place；Second part is private neck
Domain (such as: inside certain individual enterprise, private industry garden) monitoring image information collected, is mainly used for monitoring internal property, and
Internal order.
Step S102: real-time image information is input in model, and model is formed by the training of multiple groups training data, multiple groups
Each group of training data includes first kind training data in training data, and first kind training data includes abnormal behaviour image
With the identification information for identifying abnormal behaviour image.
Wherein, abnormal behaviour refers to the phenomenon that jeopardizing property safety and public safety order or artificial behavior.
Before real-time image information is input to model, it is also necessary to obtain interface or the private of municipal monitoring center database
The interface in people field monitoring data library.History monitoring image information is grabbed by interface, and it is pre-processed.
The pretreatment specifically includes the image containing abnormal behaviour in the numerous monitoring image information of interception, and identifies for it
The identification information of abnormal behaviour image forms one group of first kind training data.
Aforesaid operations are repeated, the image that all monitoring image information in database include abnormal behaviour is successively made
At first kind training data.Composing training data acquisition system.
User inputs the first kind training data in above-mentioned training data set in progressive die type one by one, and model passes through calculation
Method training obtains the ability of identification abnormal behaviour image.Have the algorithm of autonomous classification abnormal behaviour image.In the present embodiment
The algorithm being previously mentioned is will not to do based on obtained by existing model training frame accordingly, with respect to forming process the present embodiment of algorithm
Excessive narration.
When real-time image information is input in model, the algorithm in model will identify in real-time image information whether include
Abnormal behaviour image information.
Step S103: the image that real-time image information meets abnormal behaviour is exported from model.
Wherein, model identifies abnormal behaviour image according to preparatory trained algorithm, then believes the abnormal behaviour image
Breath is identified.
Step S104: the place for meeting the real-time image information acquisition of abnormal behaviour is obtained.
After obtaining abnormal behaviour image, the IP address of the real-time image information transmitted according to the camera is needed to determine it
Precise position information in reality.
Step S105: police strength scheduling request is issued.
The police strength scheduling request is sent to collect during the actual position information of the camera of abnormal behaviour image is
The heart, the police in specified radius support.
The present embodiment further relates to police's positioning and sends solicited message into specified radius around designated place.
Above two technology belongs to the technology of comparative maturity, and the present embodiment will also not do excessive narration.
Training of the present embodiment using training data to model identification abnormal behaviour image, so that the model is generated one kind can
With the ability of autonomous classification abnormal behaviour image.Again by the real-time image information input model for acquiring public place, with dynamic
It identifies abnormal behaviour, warns to the police, and scheduling police strength executes task in time.Therefore, abnormal behaviour bring can be influenced
Be reduced to it is minimum, guarantee the people, property safe and good order.
Preferably, the training data set in the present embodiment further includes the second class training data, the second class training data packet
Include normal behaviour image and the identification information for identifying normal behaviour image.
Second class training data is the image containing normal behaviour in the numerous monitoring image information of interception, and is identified for it
The identification information of normal behaviour image and the training data formed.
Aforesaid operations are repeated, the image that all monitoring image information in database include normal behaviour is successively made
At the second class training data.It is supplemented in training data set.
In the algorithmic procedure of training pattern, algorithm is trained from positive and negative two dimensions, sets up it quickly
Identify the ability of abnormal behaviour image and normal behaviour image.
Preferably, determination abnormal behaviour in order to be more accurate is to the extent of injury of society, the present embodiment will be to the first kind
Training data classification, is classified as multiple rank input models and is trained.
Every level-one training data includes abnormal behaviour image, the identification information for identifying abnormal behaviour image and right
Answer the grade of abnormal behaviour image.
In other words, trained model algorithm, in the ability for possessing identification abnormal behaviour image and normal behaviour image
Except, also there is the ability to the judgement classification of abnormal behaviour image.
After one section of real-time monitoring images input model, output real-time image information meets abnormal behaviour in corresponding model
Image and corresponding exception level.
Therefore, according to specified in specified range around the exact position in exception level scheduling image acquisition units reality
The police strength of quantity executes task.
First kind training data and the second class training data are the truthful data in police's database in the present embodiment.
It is trained by true training data, the model algorithm of acquisition is in identification process closer in true value.
The technical program is explained below in conjunction with real case.
Application of the dispatching method in industrial park:
Industrial park surrounding arranges monitoring camera, which monitors the environment of industrial park surrounding in real time.
Model algorithm is trained according to industrial park history monitoring image.Firstly the need of according to industrial park history
Monitoring image makes training data.It is assumed that holding violated instrument is abnormal behaviour image.This example only using a kind of behavior as
Abnormal behaviour explains, and not there is only a kind of abnormal behaviours.Extract a certain moment in industrial park history monitoring image
There is the violated instrument of certain human hand held, such image tagged is level-one abnormal behaviour image；More violated instruments of human hand held, such figure
As being labeled as second level abnormal behaviour image.Above two data are denoted as first kind training data.The current label of daily worker is positive
Chang Hangwei image is the second class training data.Correspondence image is input in model algorithm.Model algorithm will will form a set of
The judgment mode of oneself, for judging whether real-time monitoring images include the image information for holding violated instrument；If in the presence of
Hold the image information of violated instrument, it will capture the number for holding violated instrument, commented for the image of the abnormal behaviour
Grade.
At this point, nearby there is the violated instrument of more human hand helds in industrial park main entrance.Model is obtained according to the algorithm after training at this time
It gets and holds this feature of violated instrument, will be immediately abnormal behaviour image to the image tagged；It captures again simultaneously hand-held
Violated instrument it is artificial multiple, therefore abnormal behaviour image is upgraded to second level abnormal behaviour image.And by the violated device of more human hand helds
The specific location of industrial park main entrance is sent to the control centre of the police where the image and camera of tool.Transfer center will
Centered on the main entrance of industrial park, scheduling information is sent to the police strength on duty within two kilometers of surrounding.Again because being second level exception
Behavior image, control centre, which can also take the circumstances into consideration to deploy farther police strength, to be supported.It can caused danger by the dispatching method
It is preceding to control the state of affairs, to maintain public safety order.And it can also reasonably dispatch police strength.
Referring to FIG. 2, the present embodiment also provides a kind of police strength scheduling system, including algoritic module 20, training module 60,
Database 70, image capture module 10, locating module 30, police strength scheduler module 40 and multiple execution units 50.
Database 70 is the database 70 of the true abnormal behaviour of the daily storage of the police.
Wherein the normal behaviour image of the training data in 60 called data library 70 of training module, abnormal behaviour image with
And corresponding exception level is input to the operation of algoritic module 20, for the identification abnormal behaviour of training algorithm module 20 and is abnormal
The ability of behavior grading.
Image capture module 10 includes multiple images acquisition unit 11, is specifically video camera.Each video camera is set to
The a certain position in public place, and obtain the real-time image information in corresponding range and be sent to algoritic module 20.
Algoritic module 20 executes identification abnormal behaviour and the function for abnormal behaviour grading, Dynamic Recognition realtime graphic letter
Meet the image and exception level of abnormal behaviour in breath, while algoritic module 20 is believed according to the realtime graphic that video camera transmits
The IP address of breath determines the precise position information in its reality, and by the image of abnormal behaviour, exception level information and image
Precise position information in 11 reality of acquisition unit is sent to police strength scheduler module 40.
Police strength scheduler module 40 is dispatched according to exception level to be referred in specified range around the exact position in video camera reality
The police strength of fixed number amount executes task.
The present embodiment also provides a kind of terminal, and terminal includes:
One or more processors；
Storage device, for storing one or more programs,
When one or more programs are executed by one or more processors, so that one or more processors are realized as before
The police strength dispatching method stated.
The present embodiment also provides a kind of computer readable storage medium, is stored thereon with computer program, which is located
Reason device realizes police strength dispatching method as the aforementioned when executing.
The present invention provides a kind of police strength dispatching method, the training using training data to model identification abnormal behaviour image,
So that the model is generated one kind can be with the ability of autonomous classification abnormal behaviour image.The realtime graphic for acquiring public place is believed again
It ceases in input model, with Dynamic Recognition abnormal behaviour, warns to the police, and scheduling police strength executes task in time.It therefore, can be with
By abnormal behaviour bring influence be reduced to it is minimum, guarantee the people, property safe and good order.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered
Work as understanding, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (10)
1. a kind of police strength dispatching method, which comprises the steps of:
Acquire the real-time image information of ambient enviroment；
Real-time image information is input in model, the model is formed by the training of multiple groups training data, training number described in multiple groups
Each group of training data includes first kind training data in, and the first kind training data includes abnormal behaviour image and use
In the identification information of mark abnormal behaviour image；
The image that real-time image information meets abnormal behaviour is exported from model；
Obtain the place for meeting the real-time image information acquisition of abnormal behaviour；
Issue police strength scheduling request.
2. a kind of police strength dispatching method as described in claim 1, which is characterized in that the police strength scheduling request is sent to adopt
Centered on collecting place, the police strength in specified radius.
3. a kind of police strength dispatching method as described in claim 1, which is characterized in that the training data further includes the second class instruction
Practice data, the second class training data includes normal behaviour image and the identification information for identifying normal behaviour image.
4. a kind of police strength dispatching method as described in any one of claims 1-3, which is characterized in that the first kind training data
It is divided into multistage training data, training data described in every level-one includes abnormal behaviour image, the mark for identifying abnormal behaviour image
Know the grade of information and corresponding abnormal behaviour image；
Output real-time image information meets the image of abnormal behaviour and corresponds to exception level in corresponding model.
5. a kind of police strength dispatching method as claimed in claim 4, which is characterized in that the first kind training data and the second class
Training data is the truthful data in police's database.
6. a kind of police strength dispatching method as claimed in claim 4, which is characterized in that the police strength of the scheduling is according to exception level
It is allocated.
7. a kind of police strength dispatches system, which is characterized in that including algoritic module, training module, database, image capture module,
Locating module, police strength scheduler module and multiple execution units；
Wherein the abnormal behaviour image of the training data in training module called data library and corresponding exception level are input to calculation
The operation of method module, the ability for identifying abnormal behaviour for training algorithm module and grading for abnormal behaviour.
Described image acquisition module includes multiple images acquisition unit, each described image acquisition unit is set to public place
One position, and the real-time image information obtained in corresponding range is sent to algoritic module；
The algoritic module, which executes, identifies abnormal behaviour and the function for abnormal behaviour grading, in Dynamic Recognition real-time image information
Meet the image and exception level of abnormal behaviour, while the real-time image information that algoritic module is transmitted according to image acquisition units
IP address determine the precise position information in its reality, and the image of abnormal behaviour, exception level information and image are adopted
Precise position information in collection unit reality is sent to police strength scheduler module；
Police strength scheduler module is dispatched according to exception level to be referred in specified range around the exact position in image acquisition units reality
The police strength of fixed number amount executes task.
8. a kind of police strength dispatching method as claimed in claim 7, which is characterized in that the database is that the daily storage of the police is true
The database of real abnormal behaviour.
9. a kind of terminal, which is characterized in that the terminal includes:
One or more processors；
Storage device, for storing one or more programs,
When one or more of programs are executed by one or more of processors, so that one or more of processors are real
Now such as police strength dispatching method as claimed in any one of claims 1 to 6.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor
Such as police strength dispatching method as claimed in any one of claims 1 to 6 is realized when execution.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111107308A (en) * | 2019-09-16 | 2020-05-05 | 安徽农网农业科技有限公司 | Networking alarm system based on camera monitoring |
| CN111832976A (en) * | 2020-07-29 | 2020-10-27 | 深圳市睿策者科技有限公司 | Resource configuration pushing method and device, computer equipment and storage medium |
| CN113129532A (en) * | 2019-12-31 | 2021-07-16 | 深圳云天励飞技术有限公司 | Stranger early warning method and device, electronic equipment and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101883261A (en) * | 2010-05-26 | 2010-11-10 | 中国科学院自动化研究所 | Method and system for abnormal target detection and relay tracking under large-range monitoring scene |
| CN102547241A (en) * | 2011-12-31 | 2012-07-04 | 深圳市永达电子股份有限公司 | Home anomaly detection method and home anomaly detection device as well as home anomaly detection system on basis of wireless network camera |
| CN109410496A (en) * | 2018-10-25 | 2019-03-01 | 北京交通大学 | Attack early warning method, apparatus and electronic equipment |
| CN109447878A (en) * | 2018-11-08 | 2019-03-08 | 四川坤翔科技有限公司 | City big data security administration platform |
| WO2019096181A1 (en) * | 2017-11-14 | 2019-05-23 | 深圳码隆科技有限公司 | Detection method, apparatus and system for security inspection, and electronic device |
| CN109829382A (en) * | 2018-12-30 | 2019-05-31 | 北京宇琪云联科技发展有限公司 | The abnormal object early warning tracing system and method for Behavior-based control feature intelligent analysis |
-
2019
- 2019-07-02 CN CN201910590226.4A patent/CN110222675A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101883261A (en) * | 2010-05-26 | 2010-11-10 | 中国科学院自动化研究所 | Method and system for abnormal target detection and relay tracking under large-range monitoring scene |
| CN102547241A (en) * | 2011-12-31 | 2012-07-04 | 深圳市永达电子股份有限公司 | Home anomaly detection method and home anomaly detection device as well as home anomaly detection system on basis of wireless network camera |
| WO2019096181A1 (en) * | 2017-11-14 | 2019-05-23 | 深圳码隆科技有限公司 | Detection method, apparatus and system for security inspection, and electronic device |
| CN109410496A (en) * | 2018-10-25 | 2019-03-01 | 北京交通大学 | Attack early warning method, apparatus and electronic equipment |
| CN109447878A (en) * | 2018-11-08 | 2019-03-08 | 四川坤翔科技有限公司 | City big data security administration platform |
| CN109829382A (en) * | 2018-12-30 | 2019-05-31 | 北京宇琪云联科技发展有限公司 | The abnormal object early warning tracing system and method for Behavior-based control feature intelligent analysis |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111107308A (en) * | 2019-09-16 | 2020-05-05 | 安徽农网农业科技有限公司 | Networking alarm system based on camera monitoring |
| CN113129532A (en) * | 2019-12-31 | 2021-07-16 | 深圳云天励飞技术有限公司 | Stranger early warning method and device, electronic equipment and storage medium |
| CN111832976A (en) * | 2020-07-29 | 2020-10-27 | 深圳市睿策者科技有限公司 | Resource configuration pushing method and device, computer equipment and storage medium |
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Application publication date: 20190910 |