CN116523312A - Smart city data management method and system - Google Patents
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Abstract
The application relates to the technical field of smart cities and provides a smart city data management method and system. Acquiring operation characteristic information sets of a plurality of operation areas of a city, and inputting a model to acquire a plurality of operation risk analysis results, an early warning management scheme and a plurality of operation risk range information; obtaining a plurality of safety monitoring management areas by using the operation danger range information to correspondingly mark the peripheral area of the operation area; and acquiring image information in the safety monitoring management area to obtain a plurality of dangerous behavior analysis results, and starting a corresponding early warning management scheme when the dangerous behavior analysis results are dangerous behaviors. The method solves the technical problem that the dangerous construction behavior of the construction operation area cannot be timely identified and effectively interfered due to the fact that the potential safety hazard investigation in the urban construction process depends on manual experience in the prior art, achieves the technical effects of timely identifying and effectively interfering the dangerous construction behavior, and improves the timeliness and effectiveness of the potential safety hazard identification elimination in the urban construction process.
Description
Technical Field
The application relates to the technical field of smart cities, in particular to a smart city data management method and system.
Background
With rapid development of social economy and continuous acceleration of urban process, urban accommodation population increases gradually, so that urban construction is planned and constructed, a good living environment is created for citizens, normal life of the citizens is ensured, and economic and social development of serving cities becomes an important guide for urban development and construction.
Based on urban livability and economic development demands, various types of building construction are carried out in various areas of the city, how to ensure the construction safety of urban construction process, ensure the life safety of construction constructors, and avoid the interference of urban construction progress by construction safety risk events to become an important problem to be solved by current urban construction tap.
At present, urban construction safety depends on plaintext regulations and manual experience of safety management staff, the current construction safety management method often has a preventive value larger than actual effect, and cannot effectively intervene in dynamic risks in the construction process in time, so that the effectiveness of eliminating potential safety hazards of construction is insufficient.
In summary, in the prior art, the problem that the dangerous construction behavior of the construction operation area cannot be timely identified and effectively interfered due to the fact that the potential safety hazard investigation in the urban construction process depends on manual experience exists.
Disclosure of Invention
Based on the above, it is necessary to provide a smart city data management method and system capable of realizing timely identification and effectively intervening in dangerous construction behaviors and improving timeliness and effectiveness of identification and elimination of potential safety hazards in city construction process.
A smart city data management method, the method comprising: acquiring a plurality of operation areas of a target project in a target city; collecting multi-type operation characteristic information of the plurality of operation areas to obtain a plurality of operation characteristic information sets, wherein the multi-type operation characteristic information comprises operation type information and operation scale information; respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes; inputting the plurality of operation characteristic information sets into a dangerous range analysis model to obtain a plurality of operation dangerous range information; marking peripheral areas of the plurality of operation areas by adopting the plurality of operation danger range information to obtain a plurality of safety monitoring management areas; based on the Internet of things, collecting a plurality of image information in the plurality of safety monitoring management areas according to a preset time period, respectively inputting the image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results, and carrying out early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
A smart city data management system, the system comprising: the operation area acquisition module is used for acquiring a plurality of operation areas of the target engineering in the target city; the operation feature acquisition module is used for acquiring multi-type operation feature information of the plurality of operation areas to obtain a plurality of operation feature information sets, wherein the multi-type operation feature information comprises operation type information and operation scale information; the early warning scheme generation module is used for respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes; the dangerous scope obtaining module is used for inputting the plurality of operation characteristic information sets into a dangerous scope analysis model to obtain a plurality of operation dangerous scope information; the management area obtaining module is used for marking peripheral areas of the plurality of operation areas by adopting the plurality of operation dangerous range information to obtain a plurality of safety monitoring management areas; the early warning management execution module is used for acquiring a plurality of image information in the plurality of safety monitoring management areas according to a preset time period based on the Internet of things, respectively inputting the image information into a plurality of dangerous behavior analysis units in the dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results, and carrying out early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
acquiring a plurality of operation areas of a target project in a target city;
collecting multi-type operation characteristic information of the plurality of operation areas to obtain a plurality of operation characteristic information sets, wherein the multi-type operation characteristic information comprises operation type information and operation scale information;
respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes;
inputting the plurality of operation characteristic information sets into a dangerous range analysis model to obtain a plurality of operation dangerous range information;
marking peripheral areas of the plurality of operation areas by adopting the plurality of operation danger range information to obtain a plurality of safety monitoring management areas;
based on the Internet of things, collecting a plurality of image information in the plurality of safety monitoring management areas according to a preset time period, respectively inputting the image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results, and carrying out early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring a plurality of operation areas of a target project in a target city;
collecting multi-type operation characteristic information of the plurality of operation areas to obtain a plurality of operation characteristic information sets, wherein the multi-type operation characteristic information comprises operation type information and operation scale information;
respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes;
inputting the plurality of operation characteristic information sets into a dangerous range analysis model to obtain a plurality of operation dangerous range information;
marking peripheral areas of the plurality of operation areas by adopting the plurality of operation danger range information to obtain a plurality of safety monitoring management areas;
based on the Internet of things, collecting a plurality of image information in the plurality of safety monitoring management areas according to a preset time period, respectively inputting the image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results, and carrying out early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
The smart city data management method and system solve the technical problem that in the prior art, safety hidden danger investigation in the city construction process depends on manual experience, so that dangerous construction behaviors in a construction operation area cannot be timely identified and effectively interfered, and the technical effects of timely identifying and effectively interfering dangerous construction behaviors and improving timeliness and effectiveness of safety hidden danger identification and elimination in the city construction process are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
FIG. 1 is a flow chart of a smart city data management method according to an embodiment;
FIG. 2 is a flow chart of a method for obtaining an early warning management scheme in a smart city data management method according to an embodiment;
FIG. 3 is a block diagram of a smart city data management system, in one embodiment;
fig. 4 is an internal structural diagram of a computer device in one embodiment.
Reference numerals illustrate: the system comprises an operation area acquisition module 1, an operation characteristic acquisition module 2, an early warning scheme generation module 3, a dangerous range acquisition module 4, a management area acquisition module 5 and an early warning management execution module 6.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
As shown in fig. 1, the present application provides a smart city data management method, which includes:
s100, acquiring a plurality of operation areas of a target project in a target city;
specifically, in this embodiment, the target city is any development scale city to be subjected to city construction engineering safety management based on smart city data, including, but not limited to, a direct jurisdiction city, a provincial city, a local level city, and a county level city.
The target engineering is municipal construction engineering in a construction state at present, such as road traffic engineering, public construction engineering, underground pipeline engineering and the like. The target engineering is characterized in that the construction occupied area is large, the construction operation type is complex, the construction operation areas are large, the construction operation can be synchronously performed in the plurality of construction operation areas, the construction operation staff are numerous, and the construction operation safety management difficulty is high.
For easy explanation and understanding of the technical scheme of the present invention, the embodiment takes the target engineering as an example of public building engineering in municipal building engineering, and performs detailed explanation of the technical scheme, and it should be understood that the target engineering in the embodiment is not limited to public building engineering.
The method includes the steps that a plurality of operation areas of a target project in a target city are obtained, when the target project is a public building project (such as a public rental house), the operation areas of the public building project are divided into foundation and foundation construction operation areas, main structure construction operation areas, building decoration operation areas, building roof construction operation areas, building water supply and drainage and heating construction operation areas and building electric construction operation areas according to building construction types based on the public building project which can be divided into various building construction types such as public buildings, public roads and residential buildings.
It should be understood that in this embodiment, the working areas are divided according to the type of the construction operation, and one or more working areas of the same type may exist in the target engineering, and meanwhile, two or more working areas of different types are allocated for the construction operation at the same time, so that the working efficiency of the building construction can be improved.
S200, collecting multi-type operation characteristic information of the plurality of operation areas to obtain a plurality of operation characteristic information sets, wherein the multi-type operation characteristic information comprises operation type information and operation scale information;
in one embodiment, collecting multiple types of operation feature information of the multiple operation areas to obtain multiple operation feature information sets, and the method step S200 provided in the present application further includes:
s210, collecting a plurality of job type information and a plurality of job scale information in a plurality of job areas;
s220, acquiring the plurality of job characteristic information sets based on the plurality of job type information and the plurality of job scale information.
Specifically, in this embodiment, each type of operation area includes a plurality of operation types and operation scales, for example, the operation types in the construction operation area for building water supply and drainage and heating include the operation types of pipe-laying and drilling, pipe-laying and pipe-line installation, and the operation scales corresponding to the operation types include the hole diameter and hole depth of the pipe-laying and drilling, the pre-laying depth and pre-laying size of the pipe-laying and pipe-line installation, and the installation method.
And acquiring a plurality of job type information and a plurality of job scale information in the plurality of job areas based on construction planning information and manual construction experience, and integrating the plurality of job type information and the plurality of job scale information to obtain the plurality of job feature information sets.
The plurality of job feature information sets correspond to the plurality of job areas, and each job feature information set includes a plurality of sets of job type-job scale information having a mapping relationship.
According to the method and the device, the operation characteristic information set is constructed by analyzing the specific operation types and the operation scale of each operation type in the operation area, so that the technical effect of providing basic data for subsequent target work operation construction risk analysis and construction operation WeChat early warning management scheme determination is achieved.
S300, respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes;
in one embodiment, as shown in fig. 2, the job type information in the plurality of job feature information sets is respectively input into a risk analysis unit in a job management model to obtain a plurality of job risk analysis results, and is input into a management analysis unit in the job management model to obtain a plurality of early warning management schemes, and step S300 of the method provided in the present application further includes:
S310, acquiring a plurality of sample operation types of a plurality of sample operation areas, and grading the operation dangers to acquire a plurality of sample operation dangers analysis results;
s320, constructing a mapping relation between the plurality of sample operation types and the plurality of sample operation risk analysis results to obtain the risk analysis unit;
s330, respectively inputting the operation type information in the operation characteristic information sets into the risk analysis unit to obtain operation risk analysis results;
s340, inputting the operation risk analysis results into the management analysis unit to obtain the early warning management schemes.
In one embodiment, the plurality of operation risk analysis results are input into the management analysis unit to obtain the plurality of early warning management schemes, and the method provided in step S340 further includes:
s341, constructing a plurality of corresponding early warning management schemes according to the operation risk analysis results of the plurality of samples;
s342, constructing mapping relations between the operation risk analysis results of the samples and the early warning management schemes to obtain the management analysis unit, and combining the risk analysis unit to obtain the operation management model;
S343, inputting the operation risk analysis results into the management analysis unit to obtain the early warning management schemes.
Specifically, in the present embodiment, the purpose of obtaining the plurality of job feature information sets is to perform job risk analysis based on the plurality of job feature information sets and further analyze and determine an early warning management scheme for performing effective intervention elimination of job risk based on the result of the job risk analysis.
In order to improve the analysis scientificity and the analysis efficiency of determining the operation risk based on the operation characteristic information set, the embodiment constructs the risk analysis unit to replace manual experience for operation risk analysis.
The input data of the risk analysis unit is the operation type information in the operation characteristic information set, the output result is an operation risk analysis result corresponding to the operation type, the operation risk analysis result is a construction operation risk grade, and the probability and the severity degree of a dangerous accident of a construction operation of a certain operation type are represented.
The method for generating the operation risk analysis result comprises the steps of adopting a public channel or letter mode to contact a plurality of experts in the field of building engineering, carrying out operation risk grading on the same operation type by the plurality of experts from the frequency dimension of construction operation risk accidents and the severity dimension of construction operation risk accidents, obtaining the accident frequency risk grade and the accident severity grade, and carrying out average calculation on the two grades to obtain the operation risk analysis result of the operation type. And carrying out average value calculation on operation risk analysis results of the same operation type by a plurality of experts to serve as operation risk analysis results capable of objectively and accurately reflecting the operation risk of the operation type.
And obtaining a plurality of sample operation types of the plurality of sample operation areas, and grading the operation dangers by adopting the method to obtain a plurality of sample operation dangers analysis results.
The early warning management scheme is a prompting mode for prompting safe operation of construction operators and prompting alien personnel to keep away, for example, audible and visual alarms with different colors and sound decibels are carried out on alien personnel entering into different operation type operation areas, the greater the risk rating is, the greater the alarm sound decibels are, the installation monitoring is carried out on the operation areas, the entrance guard is subjected to personnel identity verification and the like.
And generating a search instruction according to the first sample operation type, and traversing the big data to obtain a plurality of historical early warning management schemes. And taking the first sample operation type and the first sample operation risk analysis result with the mapping relation as references, and determining a historical early warning management scheme with the highest adaptation degree with the sample operation risk analysis result of the first sample operation type based on the expert analysis of the construction engineering field as the first early warning management scheme of the first sample operation type. And determining a plurality of early warning management schemes corresponding to the risk analysis results of the plurality of sample operations by adopting the same method of determining the first early warning management scheme corresponding to the first sample operation type.
The method comprises the steps of constructing a mapping relation between a plurality of sample operation types and a plurality of sample operation risk analysis results to obtain a risk analysis unit, wherein the risk analysis unit is a mapping model, traversing the risk analysis unit to obtain a sample operation type consistent with an operation type on the basis of obtaining a first operation type, and taking the sample operation risk analysis result mapped by the sample operation type as the first operation risk analysis result of the first operation type.
The method comprises the steps of constructing a mapping relation between a plurality of sample operation risk analysis results and a plurality of early warning management schemes, obtaining a management analysis unit, wherein the management analysis unit is a mapping model, traversing the management analysis unit by taking the first operation risk analysis result as a search instruction on the basis of obtaining the first operation risk analysis result of a first operation type, obtaining the sample operation risk analysis result consistent with the first operation risk analysis result, and taking the early warning management scheme of the sample operation risk analysis result as the early warning management scheme of the first operation type.
And connecting the output end of the risk analysis unit with the input end of the management analysis unit, configuring a data input port, and constructing the multi-level operation management model by a data output port.
Respectively inputting the operation type information in the operation characteristic information sets into the risk analysis unit to obtain operation risk analysis results; and inputting the operation risk analysis results into the management analysis unit to obtain the early warning management schemes corresponding to the operation types.
The early warning devices of the construction sites of the operation types in the operation characteristic information set are distributed according to the plurality of early warning management schemes, so that the safety construction of construction operators can be effectively prompted, foreign personnel can be prompted to prohibit the construction operators from approaching the construction operation area, and the safety of construction operations is improved.
According to the embodiment, by constructing the job management model, an early warning management scheme which is matched with the accident severity level of the job type is efficiently obtained on the basis of obtaining the job type, the technical effects of reducing the dependency of the determination of the construction job management scheme on the manual experience and improving the generation efficiency of the accident job management scheme and the scheme scientificity are achieved.
S400, inputting the plurality of operation characteristic information sets into a dangerous range analysis model to obtain a plurality of operation dangerous range information;
In one embodiment, the plurality of operation feature information sets are input into a hazard range analysis model to obtain a plurality of operation hazard range information, and the method step S400 provided in the present application further includes:
s410, acquiring a plurality of sample operation characteristic information sets of a plurality of sample operation areas, and dividing dangerous areas to acquire a plurality of sample operation dangerous range information;
s420, constructing the dangerous range analysis model based on a BP neural network;
s430, marking the data of the plurality of sample operation characteristic information sets and the plurality of sample operation dangerous range information to obtain a construction data set;
s440, performing supervision training on the dangerous range analysis model by adopting the constructed data set, and training network parameters of the dangerous range analysis model through gradient descent updating until the accuracy of the dangerous range analysis model meets the preset requirement;
s450, inputting the plurality of operation characteristic information sets into the dangerous range analysis model to obtain the plurality of operation dangerous range information.
Specifically, in this embodiment, the operation risk range is a spatial range defined by taking the operation scale of the operation type as a reference, and the hazard of the operation risk event does not exceed the spatial range in the municipal construction operation process. The operation danger range of the pedestrian drop risk event occurring in the type of the buried pipe hole in the construction operation area for water supply and drainage and heating for a building is a circular space drawn by adding 2m to the radius of the hole of the buried pipe hole.
It should be appreciated that the operational hazard ranges for different types and scales of operations are different, such as for aloft operations and for natural gas leakage repair.
Thus, in the present embodiment, the operation hazard ranges of the plurality of operation types included in the plurality of operation areas are determined according to the plurality of kinds of operation characteristic information of the plurality of operation areas of the target project in the target city, and the operation hazard ranges are defined by constructing and training the hazard range analysis model instead of the manual experience in order to enhance the scientificity of the analysis determination of the operation hazard ranges.
The input data of the dangerous range analysis model is operation characteristic information, the output result is an operation dangerous range, the dangerous range analysis model is a data analysis model constructed based on a BP neural network, and the training data acquisition method of the dangerous range analysis model is as follows:
the sample operation area is consistent with the operation area in the steps S100-S200, each type of sample operation area comprises a plurality of sample operation types and sample operation scales, and the sample operation types and the sample operation scales have a mapping relation. The sample job feature information set and the job feature information set in step S200 have the same meaning.
A plurality of sample operation characteristic information sets of a plurality of sample operation areas are acquired, the sample operation characteristic information sets comprise a plurality of sample operation characteristic information, and each sample operation characteristic information is composed of sample operation type information and sample operation scale information.
And acquiring a historical municipal construction record, wherein the historical municipal construction record is reserved with the information of the delineated operation dangerous range when municipal construction operations of different construction operation types and different construction operation scales are carried out.
And traversing the history municipal construction records by taking the sample job type as a first retrieval instruction, and extracting and obtaining various historical job hazard range information of various different historical job scales of a plurality of historical job types which are the same as the sample job type. And traversing a plurality of different historical operation scales of a plurality of historical operation types by taking the sample operation scale as a second retrieval instruction, obtaining a historical operation scale which is consistent with the sample operation scale or has the highest similarity of the size data, and taking the historical operation dangerous range information corresponding to the historical operation scale as sample operation dangerous range information of the sample operation type. In order to improve the data reliability of the sample operation dangerous range information, before setting the historical operation dangerous range information corresponding to the historical operation scale as the sample operation dangerous range information of the sample operation type, a construction experience enriching person or a construction engineering field expert can be selected to verify the correctness of the historical operation dangerous range information.
By adopting the method, dangerous area division is carried out on a plurality of sample operation characteristic information sets of a plurality of sample operation areas, and a plurality of sample operation dangerous range information is obtained.
Constructing the dangerous range analysis model based on a BP neural network; and carrying out data annotation on the plurality of sample operation characteristic information sets and the plurality of sample operation dangerous range information to obtain a construction data set, wherein the construction data set comprises a training set, a testing set and a verification set.
And performing supervised training on the dangerous range analysis model by adopting the training set and the testing set in the constructed data set, and updating and training network parameters of the dangerous range analysis model through the existing gradient so as to minimize the error mean square error between the output of the dangerous range analysis model and the expected output value, and performing output accuracy verification on the dangerous range analysis model based on the testing set until the accuracy of the dangerous range analysis model meets the preset output accuracy requirement higher than 90%.
And disassembling the plurality of operation characteristic information sets to obtain a plurality of operation characteristic information, inputting the plurality of operation characteristic information sets into the trained dangerous range analysis model one by one, and carrying out data analysis based on the dangerous range analysis model to obtain the plurality of operation dangerous range information. The plurality of job hazard range information corresponds to a plurality of job feature information.
The method achieves the technical effects of improving the scientificity of analyzing and determining the operation danger range by constructing the danger range analysis model, and meanwhile, replacing manual experience with the danger range analysis model to define the operation danger range, and improving the efficiency of obtaining the operation danger range.
S500, marking peripheral areas of the plurality of operation areas by adopting the plurality of operation danger range information to obtain a plurality of safety monitoring management areas;
specifically, in the present embodiment, each of the plurality of job areas includes a plurality of job types, and the job scale of each job type is not uniform, so there is a difference in the job hazard range of each job type.
The present embodiment obtains the plurality of job hazard range information corresponding to the plurality of job feature information according to step S400. And integrating the plurality of operation danger range information according to a plurality of characteristic information sets from which the plurality of operation characteristic information is subordinate to, so as to obtain a plurality of operation danger range information sets.
And according to the mapping relation between the plurality of operation characteristic information sets and the plurality of operation areas, the operation characteristic information sets are called to carry out operation dangerous range information sets of the corresponding operation areas, operation dangerous range division of various operation types in the operation areas is carried out based on the operation dangerous range information sets, marking of peripheral areas of the plurality of operation areas is completed, a plurality of safety monitoring management areas are defined and obtained, and the safety monitoring management areas are the influence ranges of construction operation safety accidents.
And S600, acquiring a plurality of image information in the plurality of safety monitoring management areas according to a preset time period based on the Internet of things, respectively inputting the image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results, and carrying out early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
In one embodiment, based on the internet of things, a plurality of image information in the plurality of security monitoring management areas is collected according to a preset time period and is respectively input into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model, so as to obtain a plurality of dangerous behavior analysis results, and a method step S600 provided by the present application further includes:
s610, arranging image acquisition devices in the plurality of safety monitoring management areas based on the Internet of things;
s620, collecting a plurality of image information in the plurality of safety monitoring management areas according to the preset time period by the image collecting device;
s630, acquiring a plurality of sample image sets in the plurality of safety monitoring management areas, and identifying dangerous behaviors to acquire a plurality of sample dangerous behavior analysis result sets;
S640, constructing a plurality of dangerous behavior analysis units in the dangerous behavior analysis model by adopting the sample image set and a plurality of sample dangerous behavior analysis result sets;
s650, respectively inputting the image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results.
In one embodiment, the method step S640 further includes constructing the plurality of dangerous behavior analysis units in the dangerous behavior analysis model by using the sample image set and a plurality of sample dangerous behavior analysis result sets:
s641, constructing a first dangerous behavior analysis unit corresponding to a first operation area based on a convolutional neural network;
s642, performing supervision training, verification and test on the first dangerous behavior analysis unit by adopting a sample image set and a sample dangerous behavior analysis result set corresponding to a first operation area in a plurality of operation areas until the accuracy of the first dangerous behavior analysis unit meets the preset requirement;
s643, continuing to construct a plurality of dangerous behavior analysis units corresponding to other plurality of working areas to obtain the dangerous behavior analysis model.
Specifically, in this embodiment, image acquisition devices are disposed in the plurality of security monitoring management areas, and are connected based on the internet of things, and the plurality of image information in the plurality of security monitoring management areas is acquired by the image acquisition devices according to the preset time period.
And acquiring a plurality of sample image sets in the plurality of safety monitoring management areas, for example, acquiring the acquired images in the plurality of safety monitoring management areas in the past time, and carrying out dangerous behavior identification marking according to safety construction standard standards based on manual work, wherein dangerous behaviors comprise that pedestrians enter the safety monitoring management areas, pedestrians touch construction equipment and the like, and acquiring a plurality of sample dangerous behavior analysis result sets through identification and marking.
The method for identifying the municipal construction dangerous behavior in the safety monitoring management areas of the plurality of operation areas is described by taking the method for identifying the municipal construction dangerous behavior in the safety monitoring management areas of the first operation area as an example.
Based on a convolutional neural network, a first dangerous behavior analysis unit corresponding to a first operation area is constructed, a sample image set and a sample dangerous behavior analysis result set corresponding to the first operation area are divided and identified into a training set, a testing set and a verification set according to the sample image-sample dangerous behavior analysis result in the sample image set and the sample dangerous behavior analysis result set, and a plurality of groups of sample image-sample dangerous behavior analysis results are arranged in each data set. And performing supervision training and testing on the first dangerous behavior analysis unit based on a training set and a testing set, and performing accuracy verification on the output result of the first dangerous behavior analysis unit based on a verification set until the accuracy of the first dangerous behavior analysis unit meets the preset requirement (the accuracy of the output result is higher than 90%).
And continuously constructing a plurality of dangerous behavior analysis units corresponding to other plurality of operation areas by adopting the same method for constructing the first dangerous behavior analysis unit of the first operation area, and obtaining the dangerous behavior analysis model, wherein the plurality of dangerous behavior analysis units are arranged in parallel and are isolated from each other in the dangerous behavior analysis units.
And respectively inputting the image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model according to the corresponding operation area of the image information acquisition, and obtaining a plurality of dangerous behavior analysis results.
Municipal construction manager carries out municipal construction operation dangerous behavior reminding based on a plurality of operation areas corresponding to a plurality of dangerous analysis results, so that dangerous construction behaviors are intervened in time, and potential safety hazards in the urban construction process are eliminated.
The embodiment achieves the technical effects of timely identifying and effectively intervening dangerous construction behaviors and improving timeliness and effectiveness of identifying and eliminating potential safety hazards in the urban construction process.
In one embodiment, as shown in fig. 3, there is provided a smart city data management system, comprising: the system comprises an operation area acquisition module 1, an operation characteristic acquisition module 2, an early warning scheme generation module 3, a dangerous range acquisition module 4, a management area acquisition module 5 and an early warning management execution module 6, wherein:
the operation area acquisition module 1 is used for acquiring a plurality of operation areas of a target project in a target city;
the operation feature collection module 2 is used for collecting multi-type operation feature information of the plurality of operation areas to obtain a plurality of operation feature information sets, wherein the multi-type operation feature information comprises operation type information and operation scale information;
the early warning scheme generating module 3 is used for respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes;
The dangerous scope obtaining module 4 is used for inputting the plurality of operation characteristic information sets into a dangerous scope analysis model to obtain a plurality of operation dangerous scope information;
a management area obtaining module 5, configured to use the plurality of operation danger range information to mark surrounding areas of the plurality of operation areas, and obtain a plurality of safety monitoring management areas;
the early warning management execution module 6 is configured to collect multiple image information in the multiple safety monitoring management areas according to a preset time period based on the internet of things, and input the multiple image information into multiple dangerous behavior analysis units in the dangerous behavior analysis model respectively, obtain multiple dangerous behavior analysis results, and perform early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
In one embodiment, the system further comprises:
the area information acquisition unit is used for acquiring a plurality of job type information and a plurality of job scale information in the plurality of job areas;
and a region information analysis unit configured to obtain the plurality of job feature information sets based on the plurality of job type information and the plurality of job scale information.
In one embodiment, the system further comprises:
the sample information analysis unit is used for acquiring a plurality of sample operation types of a plurality of sample operation areas, grading the operation dangers and acquiring a plurality of sample operation dangers analysis results;
the mapping relation construction unit is used for constructing mapping relations between the plurality of sample operation types and the plurality of sample operation risk analysis results to obtain the risk analysis unit;
the operation risk analysis unit is used for respectively inputting the operation type information in the operation characteristic information sets into the risk analysis unit to obtain operation risk analysis results;
and the management scheme generating unit is used for inputting the operation risk analysis results into the management analysis unit to obtain the early warning management schemes.
In one embodiment, the system further comprises:
the management scheme construction unit is used for constructing a plurality of corresponding early warning management schemes according to the plurality of sample operation risk analysis results;
the mapping relation establishing unit is used for establishing mapping relation between the operation risk analysis results of the plurality of samples and the early warning management schemes to obtain the management analysis unit, and combining the risk analysis unit to obtain the operation management model;
And the management scheme analysis unit is used for inputting the operation risk analysis results into the management analysis unit to obtain the early warning management schemes.
In one embodiment, the system further comprises:
the sample information acquisition unit is used for acquiring a plurality of sample operation characteristic information sets of a plurality of sample operation areas, dividing dangerous areas and acquiring a plurality of sample operation dangerous range information;
the analysis model construction unit is used for constructing the dangerous range analysis model based on the BP neural network;
the data annotation execution unit is used for carrying out data annotation on the plurality of sample operation characteristic information sets and the plurality of sample operation dangerous range information to obtain a construction data set;
the model supervision training unit is used for performing supervision training on the dangerous range analysis model by adopting the constructed data set, and updating and training network parameters of the dangerous range analysis model through gradient until the accuracy of the dangerous range analysis model meets the preset requirement;
and the dangerous range analysis unit is used for inputting the plurality of operation characteristic information sets into the dangerous range analysis model to obtain the plurality of operation dangerous range information.
In one embodiment, the system further comprises:
the image acquisition laying unit is used for arranging image acquisition devices in the plurality of safety monitoring management areas based on the Internet of things;
the image information acquisition unit is used for acquiring a plurality of image information in the plurality of safety monitoring management areas according to the preset time period through the image acquisition device;
the dangerous behavior identification unit is used for acquiring a plurality of sample image sets in the plurality of safety monitoring management areas and carrying out dangerous behavior identification to acquire a plurality of sample dangerous behavior analysis result sets;
the dangerous behavior analysis unit is used for constructing a plurality of dangerous behavior analysis units in the dangerous behavior analysis model by adopting the sample image set and a plurality of sample dangerous behavior analysis result sets;
and the analysis result obtaining unit is used for respectively inputting the plurality of image information into a plurality of dangerous behavior analysis units in the dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results.
In one embodiment, the system further comprises:
the analysis unit construction unit is used for constructing a first dangerous behavior analysis unit corresponding to the first operation area based on the convolutional neural network;
The analysis unit training unit is used for performing supervision training, verification and test on the first dangerous behavior analysis unit by adopting a sample image set and a sample dangerous behavior analysis result set corresponding to a first operation area in a plurality of operation areas until the accuracy of the first dangerous behavior analysis unit meets the preset requirement;
and the analysis model generation unit is used for continuously constructing a plurality of dangerous behavior analysis units corresponding to a plurality of other working areas to obtain the dangerous behavior analysis model.
For an embodiment of a smart city data management system, reference is made to the above embodiment of a smart city data management method, which is not described herein. Each of the above modules in a smart city data management system may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing news data, time attenuation factors and other data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a method for managing smart city data.
Those skilled in the art will appreciate that the structures shown in FIG. 4 are block diagrams only and do not constitute a limitation of the computer device on which the present aspects apply, and that a particular computer device may include more or less components than those shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer readable storage medium is provided, comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program: acquiring a plurality of operation areas of a target project in a target city; collecting multi-type operation characteristic information of the plurality of operation areas to obtain a plurality of operation characteristic information sets, wherein the multi-type operation characteristic information comprises operation type information and operation scale information; respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes; inputting the plurality of operation characteristic information sets into a dangerous range analysis model to obtain a plurality of operation dangerous range information; marking peripheral areas of the plurality of operation areas by adopting the plurality of operation danger range information to obtain a plurality of safety monitoring management areas; based on the Internet of things, collecting a plurality of image information in the plurality of safety monitoring management areas according to a preset time period, respectively inputting the image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results, and carrying out early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A method of smart city data management, the method comprising:
acquiring a plurality of operation areas of a target project in a target city;
collecting multi-type operation characteristic information of the plurality of operation areas to obtain a plurality of operation characteristic information sets, wherein the multi-type operation characteristic information comprises operation type information and operation scale information;
Respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes;
inputting the plurality of operation characteristic information sets into a dangerous range analysis model to obtain a plurality of operation dangerous range information;
marking peripheral areas of the plurality of operation areas by adopting the plurality of operation danger range information to obtain a plurality of safety monitoring management areas;
based on the Internet of things, collecting a plurality of image information in the plurality of safety monitoring management areas according to a preset time period, respectively inputting the image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results, and carrying out early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
2. The method of claim 1, wherein collecting a plurality of types of job feature information for the plurality of job areas to obtain a plurality of sets of job feature information, comprises:
Collecting a plurality of job type information and a plurality of job scale information in the plurality of job areas;
the plurality of job feature information sets are obtained based on the plurality of job type information and the plurality of job scale information.
3. The method according to claim 1, wherein inputting the job type information in the plurality of job feature information sets into a risk analysis unit in a job management model to obtain a plurality of job risk analysis results, and into a management analysis unit in the job management model to obtain a plurality of early warning management schemes, respectively, comprises:
acquiring a plurality of sample operation types of a plurality of sample operation areas, and grading the operation dangers to acquire a plurality of sample operation dangers analysis results;
constructing a mapping relation between the plurality of sample operation types and the plurality of sample operation risk analysis results to obtain the risk analysis unit;
respectively inputting the operation type information in the operation characteristic information sets into the risk analysis unit to obtain operation risk analysis results;
and inputting the operation risk analysis results into the management analysis unit to obtain the early warning management schemes.
4. The method of claim 3, wherein inputting the plurality of job hazard analysis results into the management analysis unit to obtain the plurality of pre-warning management schemes comprises:
constructing a plurality of corresponding early warning management schemes according to the operation risk analysis results of the plurality of samples;
constructing mapping relations between the operation risk analysis results of the samples and the early warning management schemes, obtaining the management analysis unit, and combining the risk analysis unit to obtain the operation management model;
and inputting the operation risk analysis results into the management analysis unit to obtain the early warning management schemes.
5. The method of claim 1, wherein inputting the plurality of sets of operational characteristic information into a hazard range analysis model to obtain a plurality of operational hazard range information comprises:
acquiring a plurality of sample operation characteristic information sets of a plurality of sample operation areas, and dividing dangerous areas to acquire a plurality of sample operation dangerous range information;
constructing the dangerous range analysis model based on a BP neural network;
marking data of the plurality of sample operation characteristic information sets and the plurality of sample operation dangerous range information to obtain a construction data set;
Performing supervision training on the dangerous range analysis model by adopting the constructed data set, and updating and training network parameters of the dangerous range analysis model through gradient descent until the accuracy of the dangerous range analysis model meets the preset requirement;
and inputting the plurality of operation characteristic information sets into the dangerous range analysis model to obtain the plurality of operation dangerous range information.
6. The method of claim 1, wherein based on the internet of things, collecting a plurality of image information in the plurality of safety monitoring management areas according to a preset time period, and respectively inputting the plurality of image information into a plurality of dangerous behavior analysis units in a dangerous behavior analysis model, to obtain a plurality of dangerous behavior analysis results, comprises:
based on the Internet of things, arranging image acquisition devices in the plurality of safety monitoring management areas;
collecting a plurality of image information in the plurality of safety monitoring management areas according to the preset time period by the image collecting device;
acquiring a plurality of sample image sets in the plurality of safety monitoring management areas, and identifying dangerous behaviors to acquire a plurality of sample dangerous behavior analysis result sets;
Constructing a plurality of dangerous behavior analysis units in the dangerous behavior analysis model by adopting the sample image set and a plurality of sample dangerous behavior analysis result sets;
and respectively inputting the plurality of image information into a plurality of dangerous behavior analysis units in the dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results.
7. The method of claim 6, wherein constructing the plurality of risk behavior analysis units within the risk behavior analysis model using the sample image set and a plurality of sample risk behavior analysis result sets, comprises:
constructing a first dangerous behavior analysis unit corresponding to a first operation area based on a convolutional neural network;
performing supervision training, verification and testing on the first dangerous behavior analysis unit by adopting a sample image set and a sample dangerous behavior analysis result set corresponding to a first operation area in a plurality of operation areas until the accuracy of the first dangerous behavior analysis unit meets the preset requirement;
and continuously constructing a plurality of dangerous behavior analysis units corresponding to other plurality of working areas to obtain the dangerous behavior analysis model.
8. A smart city data management system, the system comprising:
The operation area acquisition module is used for acquiring a plurality of operation areas of the target engineering in the target city;
the operation feature acquisition module is used for acquiring multi-type operation feature information of the plurality of operation areas to obtain a plurality of operation feature information sets, wherein the multi-type operation feature information comprises operation type information and operation scale information;
the early warning scheme generation module is used for respectively inputting the operation type information in the operation characteristic information sets into a risk analysis unit in an operation management model to obtain a plurality of operation risk analysis results, and inputting the operation risk analysis results into a management analysis unit in the operation management model to obtain a plurality of early warning management schemes;
the dangerous scope obtaining module is used for inputting the plurality of operation characteristic information sets into a dangerous scope analysis model to obtain a plurality of operation dangerous scope information;
the management area obtaining module is used for marking peripheral areas of the plurality of operation areas by adopting the plurality of operation dangerous range information to obtain a plurality of safety monitoring management areas;
the early warning management execution module is used for acquiring a plurality of image information in the plurality of safety monitoring management areas according to a preset time period based on the Internet of things, respectively inputting the image information into a plurality of dangerous behavior analysis units in the dangerous behavior analysis model to obtain a plurality of dangerous behavior analysis results, and carrying out early warning management through a corresponding early warning management scheme when any dangerous behavior analysis result is dangerous behavior.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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