CN115358544A - Urban intelligent infrastructure planning and designing method - Google Patents
Urban intelligent infrastructure planning and designing method Download PDFInfo
- Publication number
- CN115358544A CN115358544A CN202210918561.4A CN202210918561A CN115358544A CN 115358544 A CN115358544 A CN 115358544A CN 202210918561 A CN202210918561 A CN 202210918561A CN 115358544 A CN115358544 A CN 115358544A
- Authority
- CN
- China
- Prior art keywords
- layout
- sensing
- facility
- scale
- type
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 50
- 230000005540 biological transmission Effects 0.000 claims abstract description 134
- 230000008447 perception Effects 0.000 claims abstract description 52
- 238000004088 simulation Methods 0.000 claims abstract description 28
- 238000012545 processing Methods 0.000 claims description 49
- 230000001149 cognitive effect Effects 0.000 claims 2
- 238000010276 construction Methods 0.000 description 12
- 230000006870 function Effects 0.000 description 4
- 238000007726 management method Methods 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 230000005236 sound signal Effects 0.000 description 4
- 230000002776 aggregation Effects 0.000 description 3
- 238000004220 aggregation Methods 0.000 description 3
- 239000000779 smoke Substances 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000009472 formulation Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000037081 physical activity Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000002352 surface water Substances 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A30/00—Adapting or protecting infrastructure or their operation
- Y02A30/60—Planning or developing urban green infrastructure
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Databases & Information Systems (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Remote Sensing (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a planning and designing method of urban intelligent infrastructure, which comprises the steps of constructing a standardized space simulation model of each land parcel on a planning area according to an obtained urban controllability planning rule based on a preset standardized simulation rule; determining the deployment type of the sensing facilities on each land parcel, the layout scale of each type of sensing facilities and the transmission scale of sensing data according to a standardized spatial simulation model based on a preset deployment rule of the sensing facilities; determining the layout scale and the layout requirement of each type of intelligent infrastructure according to the measured layout scale of the sensing facilities and the measured transmission scale of the sensing data based on a preset layout rule of the intelligent infrastructure; and outputting the deployment type of the perception facilities on each land, the layout scale of each type of perception facilities, the transmission scale of perception data, the layout scale of each type of intelligent infrastructure and the layout requirements. The urban intelligent infrastructure layout scheme is reasonable and low in cost.
Description
Technical Field
The application relates to the technical field of urban planning, in particular to a planning and designing method for an urban intelligent infrastructure.
Background
The city intelligence infrastructure can develop the people and give birth to the service wisdom and use, promotes existing infrastructure's ability and management and control efficiency, effectively promotes city traffic efficiency, ensures traffic safety, promotes city improvement and service level. The construction and the reconstruction of the urban intelligent infrastructure can also accelerate the transformation of the Chinese infrastructure network to intellectualization.
In the related art, intelligent infrastructures in an urban area are set according to requirements, and are difficult to meet the requirements of various periods, especially for cities which have been built for many years. For example, an urban area constructed for many years requires the addition of smart infrastructure. When planning the intelligent infrastructure, the kind of the intelligent infrastructure to be added needs to be determined. As the urban area is built, the layout position of the intelligent infrastructure has certain limitation. Therefore, it is necessary to obtain a layout plan of the intelligent infrastructure by actually investigating the layout position of the intelligent infrastructure.
However, the redeployment according to the obtained scheme still causes certain limitation, so that the scheme needs to be replanned every time the intelligent infrastructure is newly added, and further resource waste is caused.
Disclosure of Invention
The method can provide a reasonable urban intelligent infrastructure layout scheme with low cost for urban areas needing to deploy intelligent infrastructures.
The above object of the present application is achieved by the following technical solutions:
a city intelligent infrastructure planning method comprises the following steps:
based on a preset standardized simulation rule, constructing a standardized space simulation model of each land parcel on a planning region according to the acquired urban controllability planning rule, wherein the urban controllability planning rule is a limit on building parameters, and the standardized space simulation model is used for providing urban space basic parameters for measuring and calculating the layout scale of sensing facilities;
determining a sensing facility deployment type, a sensing facility deployment scale and a sensing data transmission scale on each land according to a standardized spatial simulation model based on a preset sensing facility deployment rule, wherein the sensing facility deployment rule comprises a corresponding relation between the sensing facility deployment type and an urban space and a corresponding relation between the sensing facility deployment type and the data scale of the sensing facility, and the sensing facility is used for collecting sensing data on the land;
determining the layout scale and the layout requirement of each type of intelligent infrastructure according to the measured layout scale of the sensing facilities and the measured transmission scale of the sensing data based on a preset intelligent infrastructure layout rule, wherein the intelligent infrastructure comprises an intelligent gateway, a transmission facility and a processing facility;
and outputting the deployment type of the perception facilities on each land, the layout scale of each type of perception facilities, the transmission scale of perception data, the layout scale of each type of intelligent infrastructure and the layout requirements.
By adopting the technical scheme, the deployment type and the layout scale of each type of sensing facility, the layout number of intelligent gateways, the type of intelligent infrastructure, the layout scale and the layout requirement of each type of intelligent infrastructure on each land parcel of the planning region can be determined. All the steps are implemented based on management and control indexes, construction modes and implementation operation requirements, so that a reasonable urban intelligent infrastructure layout scheme with low cost can be provided for urban areas where intelligent infrastructures need to be deployed.
The present application may be further configured in a preferred example to: the method for determining the deployment type of the sensing facilities on each land parcel according to the standardized spatial simulation model based on the preset deployment rules of the sensing facilities comprises the following steps:
the standardized space simulation model comprises urban space types and space information of each type, wherein the urban space types at least comprise a road space, a building space, an outdoor public space and an underground space;
determining the deployment type of the perception facility to be laid on the land according to the urban space type and the acquired perception requirement on the urban engineering environment based on a perception facility library; the perception facility library comprises a corresponding relation between a perception facility deployment type and each urban space type, each urban space type comprises multiple urban engineering environments, and each urban engineering environment corresponds to multiple perception facilities.
The application may be further configured in a preferred example to: the method for determining the layout scale of each type of sensing facilities on each land parcel of a planning region according to a standardized spatial simulation model based on the preset sensing facility deployment rule comprises the following steps:
and determining the layout scale of each type of sensing facility according to the spatial information of each type and the deployment type of the sensing facility required to be laid in the land block based on a sensing facility layout standard library, wherein the sensing facility layout standard library comprises the corresponding relation between the deployment type of the sensing facility and the spatial information.
The present application may be further configured in a preferred example to: the method for determining the transmission scale of the sensed data on each land comprises the following steps:
calling a standardized transmission model, wherein the standardized transmission model comprises a corresponding relation between deployment types of sensing facilities and data scales of the sensing facilities, each sensing facility corresponds to a signal type, and each signal type corresponds to a data standard quantity;
and determining the scale of the perception data transmission of each land parcel according to the standardized transmission module, the deployment type of the perception facility of each land parcel and the scale of the deployment of each perception facility.
The application may be further configured in a preferred example to: the method for determining the layout scale of the intelligent gateway according to the measured layout scale of the sensing facilities and the measured data transmission scale based on the preset intelligent infrastructure layout rule comprises the following steps:
and determining the arrangement number of the intelligent gateways according to the transmission scale of the sensed data on each land and the acquired transmission rate of the intelligent gateways.
The present application may be further configured in a preferred example to: the method for determining the layout scale of the intelligent gateway according to the measured layout scale of the sensing facilities and the measured data transmission scale based on the preset intelligent infrastructure layout rule further comprises the following steps:
acquiring the layout requirement of an intelligent gateway;
judging whether the layout number of the intelligent gateways meets the layout requirements of the intelligent gateways or not; and if so, taking the number of the intelligent gateways as the final number of the intelligent gateways.
The present application may be further configured in a preferred example to: the method for determining the layout scale and the layout requirement of the intelligent gateway according to the measured layout scale and the measured data transmission scale of the sensing facilities based on the preset intelligent infrastructure layout rule further comprises the following steps:
and when the layout number of the intelligent gateways does not meet the layout requirement of the intelligent gateways, determining the final layout number of the intelligent gateways according to the layout requirement of the intelligent gateways.
The application may be further configured in a preferred example to: the method for determining the layout scales of the processing facilities and the transmission facilities according to the measured layout scale of the sensing facilities and the measured data transmission scale based on the preset intelligent infrastructure layout rule comprises the following steps:
dividing the planning area according to a preset area division rule to obtain a plurality of designated areas, wherein the designated areas comprise a street room unit, a neighborhood unit and a community unit, and a plurality of plots are contained in the street room unit, the neighborhood unit and the community unit;
determining the transmission scale of the sensing data of each street unit, the transmission scale of the sensing data of each neighborhood unit and the transmission scale of the sensing data of each community unit according to the transmission scale of the sensing data of each plot;
calling a region comparison table, and obtaining actual region information corresponding to the neighborhood unit, the neighborhood unit and the community unit in a planning zone according to the region comparison table, wherein the region comparison table comprises region type information, the actual region information and corresponding relation information of each region and the actual region;
and determining the type of the intelligent infrastructure and the arrangement number of each type of intelligent infrastructure according to the sensing data transmission scale of the neighborhood unit, the sensing data transmission scale of the neighborhood unit and the sensing data transmission scale of the community unit.
The present application may be further configured in a preferred example to: the method for determining the layout requirements of the processing facilities and the transmission facilities according to the measured layout scale of the sensing facilities and the measured data transmission scale based on the preset layout rule of the intelligent infrastructure comprises the following steps:
and determining the layout position of each intelligent infrastructure according to the actual region information and the data processing facilities and the preset layout rule.
The present application may be further configured in a preferred example to: the method for determining the types of the intelligent infrastructures and the distribution number of each type of intelligent infrastructures according to the sensing data transmission scale of the neighborhood unit, the sensing data transmission scale of the neighborhood unit and the sensing data transmission scale of the community unit comprises the following steps:
calling a facility comparison table, wherein the facility comparison table comprises region type information, facility type information of intelligent infrastructure and corresponding relation information of each region and facility;
respectively obtaining facility type information of intelligent infrastructures corresponding to the street units, the neighborhood units and the community units according to the facility comparison table;
acquiring a sensing data quantity threshold of an intelligent infrastructure, wherein the intelligent infrastructure comprises a data transmission facility and a data processing facility, and the sensing data quantity threshold comprises a data transmission quantity threshold of the data transmission facility and a data processing quantity threshold of the data processing facility;
comparing the sensing data transmission scale of the neighborhood unit, the sensing data transmission scale of the neighborhood unit and the sensing data transmission scale of the community unit with a sensing data amount threshold of the intelligent infrastructure respectively;
and determining the layout quantity of the intelligent infrastructures corresponding to the street units, the neighborhood units and the community units.
In summary, the present application includes at least one of the following beneficial technical effects:
according to the method and the system, a sensing facility layout planning scheme meeting all indexes can be determined according to planning requirements, and the subsequent reference is facilitated for construction personnel when the sensing facilities in the new city area are installed. The planning scheme provided by the application is reasonable and practicable, and the cost can be saved to a certain extent.
Drawings
Fig. 1 is a schematic flow chart of a city intelligent infrastructure planning method according to an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to the attached drawings.
The present embodiment is only for explaining the present application, and it is not limited to the present application, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present application.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
The embodiment of the application provides a method for planning urban intelligent infrastructure, which is mainly used for planning urban intelligent infrastructure. For urban areas without urban intelligent infrastructure planning or renovated urban areas, the urban intelligent infrastructure planning method provided by the embodiment of the application can provide a reasonable urban intelligent infrastructure arrangement scheme with low cost for the urban areas needing to be provided with intelligent infrastructures.
The embodiments of the present application will be described in further detail with reference to the drawings.
The main flow of the city intelligent infrastructure planning method is described as follows.
As shown in fig. 1:
step S100: and based on a preset standardized simulation rule, constructing a standardized space simulation model of each land parcel on the planning region according to the acquired urban controllability planning rule.
The standardized simulation rule is a model called from a memory or a database, and can simulate the most reasonable deployment meeting the urban controllability detailed planning requirement on each plot so as to present the standardized space simulation model of each plot. The standardized space simulation model is used for providing urban space basic parameters for measuring and calculating the layout scale of the sensing facilities. For example, if a designated land is used for building a building, the standardized space simulation model can reflect information such as the size of the building land on the land, the size of the greening land, the size of the public land, the sizes of other land, the height of the building floor, the number of the building floors, the number of elevators, and the like.
The city controllability planning rule is a restriction on building parameters, is a controllability planning index, at least comprises volume ratio, building height, building density, greenbelt rate, infrastructure, public service facilities, land scale of public safety facilities, underground pipeline control requirements, and also relates to four-line and control requirements such as control boundary lines of infrastructure land, control lines of various greenbelt ranges, protection range boundary lines of historical cultural blocks and historical buildings, region boundary lines of surface water protection and control, and the like. Since the upper limits of various indexes on the land can be determined based on the parameters, a standardized spatial simulation model for each land can be obtained based on a standardized simulation rule. The standardized spatial simulation model is the architectural shape on the land parcel, which comprises city space types and spatial information of each type. The urban space types include at least a road space, a building space, an outdoor public space, and an underground space. Each urban space type comprises various urban engineering environments, and various perception facilities can be arranged in each urban engineering environment. Different city space types correspond to different space information. For example, the spatial information of the road space is the road length and width; the space information of the building space is information such as the number of the highest floors of the building, the length, the width, the height, the land area of each floor, the number of stairs, the number of elevators, the number of windows and the like. Specifically, the intermediate value of each parameter can be determined, and then a standardized spatial simulation model is obtained according to the detailed planning requirement of city controllability. This technique is conventional and will not be described in great detail.
The above examples only provide spatial information about the building space and are not illustrated here for other urban space types.
Step S200: and determining the deployment type of the sensing facilities on each land parcel, the layout scale of each type of sensing facilities and the transmission scale of sensing data according to a standardized spatial simulation model based on a preset sensing facility deployment rule.
The sensing facility deployment rule comprises a sensing facility library, a sensing facility layout standard library and a standardized transmission model, wherein the sensing facility library comprises a corresponding relation between a sensing facility deployment type and each city space type. The perception facility layout standard library comprises the corresponding relation between the perception facility deployment type and the spatial information. The standardized transmission module comprises a corresponding relation between the deployment type of the perception facility and the data scale of the perception facility.
The specific steps are as follows (step S210-step S240):
step S210: and determining the deployment type of the perception facilities required to be laid on the land parcel based on the perception facility library according to the urban space type and the acquired perception requirement on the urban engineering environment.
The perception facility library mainly relates to seven urban engineering systems including municipal engineering, natural environment and resources, emergency management, underground space, transportation, civil life and construction, each urban engineering system comprises a plurality of urban engineering subsystems, each urban engineering subsystem comprises various urban engineering environments, and each urban engineering environment relates to various perception facilities. For example: the sensing facilities for monitoring the indoor environment comprise an indoor value environment anemometer, an indoor CO2 concentration detector, an indoor PM2.5 detector, an indoor humidity sensor and an indoor temperature measuring instrument. Specifically, the indoor environment is an urban engineering environment, the corresponding urban engineering subsystem is an informatization application system, and the corresponding urban engineering system is a municipal engineering system. In this application, perceptual facilities repository fuses the ISO 37105 city infrastructure, and the facilities wisdom city data fusion part 5: 795 sensing facilities coexist and are stored in municipal infrastructure data elements, intelligent city sensing facility basic operation, urban space land property classification and division modes of related city planning practice.
The perception requirement on the urban engineering environment is the environment required to be perceived by each plot, and the functions to be realized by the plots can be determined according to the land use property of the plots and the requirements of each project of the building. Furthermore, the sensing facility deployment type required by the plot can be determined by comparing the functions of the plot and the urban engineering environment with the sensing facility library. Wherein the demand for the construction project is obtained by obtaining a construction project schedule.
In a specific example, the sensing requirement of the urban engineering environment is that the indoor environment needs to be monitored, and the corresponding sensing facilities are an indoor value environment anemometer, an indoor CO2 concentration detector, an indoor PM2.5 detector, an indoor humidity sensor and an indoor temperature measuring instrument. In fact, since individual sensing facilities cannot be laid out according to each spatial information, sensing facilities that can be applied can be selected from among the sensing facilities for environmental monitoring.
Step S220: and determining the layout scale of each type of sensing facilities according to the spatial information of each type and the deployment type of the sensing facilities to be laid in the land block based on the sensing facility layout standard library.
The sensing facility layout requirement standard library is a database consisting of various sensing facility layout requirements and standards. The sensing facility layout standard library comprises all the sensing facility layout types and matched layout requirements, and the layout requirements, namely the layout mode, the requirements and the standards of each type of sensing facilities are obtained through national standards, row standards, group standards and experiences. For example: the method is characterized in that the method comprises the following steps of according to the layout requirements of the length of a pipe gallery, the length of a road or the perimeter of a building, the layout requirements of the area of the building or the area of a room, the layout requirements of the number of stairs or the number of elevators, and corresponding layout requirements are correspondingly arranged in each case. After the sensing facilities required to be laid in each land parcel are determined, the number of the layout of the deployment types of each sensing facility on each land parcel is determined in sequence.
The method comprises the following specific steps: firstly, spatial information corresponding to the layout requirement is screened from the spatial information of the land parcel. For example, the arrangement requirement of the smoke detector is set to be one for every 3 meters on a corridor, the spatial information comprises the number of the highest floors of the building, the length, the width, the height and the land area of each floor and the corridor length of each floor, and the spatial information corresponding to the arrangement requirement of the smoke detector is the corridor length of each floor. Specifically, the screening can be performed according to the keywords. And then, determining the layout scale of the sensing facilities according to the layout requirements and the spatial information obtained by screening. For example: if the corridor length is 100 meters, the number of smoke detectors arranged = [ corridor length/arrangement requirement ] = [100/3] = 33.
It is worth to be noted that, for the same kind of sensing facilities, the same sensing facilities are applied to different urban engineering environments, and the layout requirements are different. The layout requirements of each type of perception facility mainly stem from the particularity of the type of perception facility. In a specific example, the sensing device is a camera, and can be applied to road traffic state monitoring and motor vehicle peccancy whistle snapshot and evidence obtaining. If the camera is used for monitoring the road traffic state, the layout requirement is determined to be one for every 1000 meters according to the road length and one for every 150 meters according to the tunnel length. Further, if the actual road length is 30000 meters, 30 cameras need to be arranged on the road. If the vehicle-mounted camera is used for snapshotting and evidence obtaining of motor vehicle illegal whistle, the layout requirement is determined to be that one camera is arranged every 800 meters according to the length of the road on the section where whistle is forbidden.
Step S300: and determining the layout scale and the layout requirement of each type of intelligent infrastructure according to the measured layout scale of the sensing infrastructure and the measured transmission scale of the sensing data based on a preset intelligent infrastructure layout rule, wherein the intelligent infrastructure comprises an intelligent gateway, a transmission facility and a processing facility.
And determining the distribution quantity of the intelligent gateways according to the sensed data transmission scale on each land and the acquired transmission rate of the intelligent gateways.
It will be appreciated that the data collected by the sensing facility is uploaded for processing and analysis. In order to facilitate data transmission, a plurality of intelligent gateways are required to be arranged around the arranged perception facilities. Before determining the number of intelligent gateways to be deployed, the scale of the sensing data transmission on each land, i.e., the total amount of data collected by all sensing facilities, needs to be determined through steps S230 and S240.
Step S230: a standardized transmission model is invoked.
Wherein, each kind of perception facility corresponds to a kind of signal type, and each kind of signal type corresponds to has the data standard quantity.
The signal types are forms of output data of the sensing facility and are specifically divided into five types, namely video signals, image signals, audio signals, text signals and switching signals. Each type of signal corresponds to a different standard amount of data, i.e., the size of data transmitted per unit time. Specifically, in the standardized transmission model, the data standard quantity of each signal type needs to be determined by the data quality requirements and the data protocol requirements. The data quality requirement is a requirement for data quality, for example, a video signal requires high definition quality, and an audio signal requires clear sound quality. The data protocol requirement is a transmission protocol to which data needs to adhere in the transmission process. The respective data quality requirements and data protocol requirements are different for different types of signals.
Therefore, in determining the data standard quantity of each type of signal, a data quality requirement affecting the quality of each type of signal and a data protocol requirement matching each type of signal are acquired first. For video signals, the data quality requirements affecting the signal quality are mainly pixel length, pixel width, frame per second and delay requirements, and the data protocol requirements are pixel encoding, video encoding mode and protocol header. For an image signal, the data quality requirements affecting the signal quality are mainly pixel length, pixel width, frame per second and delay requirements, and the data protocol requirements are pixel encoding and protocol header. For audio signals, the data quality requirements affecting the signal quality mainly include frequency, sampling bit number, channel number and delay requirements, and the data protocol requirement is a protocol header. For text signals, the data quality requirements affecting the signal quality are mainly text content and delay requirements, and the data protocol requirements are protocol headers. For a switching signal, the data quality requirements affecting the signal quality of the switching signal are mainly the switching value and the delay requirement of the switching signal, and the data protocol requirement is a protocol header. All of the data quality requirements and data protocol requirements mentioned above can be derived by obtaining performance parameters of the aware facility.
It will be appreciated that some of the data quality requirements that affect signal quality can be used directly to calculate the data metrics, while both the data protocol requirements and other data quality requirements that affect signal quality need to be quantified and used to calculate the data metrics.
Further, the data standard quantity of each type of signal is determined according to a preset data quantity calculation formula. The standard quantity of data for each type of signal is calculated as follows:
video signal: the normalized data size of the data = (pixel length × pixel width × pixel code × frames per second)/G1 (delay requirement, video coding mode) + G2 (protocol header), which is about 12M/s.
Image signal: normalized data size of data = (pixel length pixel width pixel code frame per second)/G1 (delay requirement) + G2 (protocol header), about 1.5M/s.
Audio signal: the normalized data size of the data = G1 (hertz frequency, number of samples) × number of channels/G2 (delay requirement) + G3 (protocol header), about 300KB/s.
Text signal: the normalized data size of the data = G1 (text content)/G2 (latency requirement) + G3 (protocol header), about 30KB/s.
Switching signals: the normalized data size of the data = G1 (switching signal)/G2 (delay requirement) + G3 (protocol header), about 5KB/s.
Wherein G (a, b) is expressed as a functional relation with independent variables a and b.
Step S240: and determining the transmission scale of the perception data of each land according to the standardized transmission module, the deployment type of the perception facility of each land and the layout scale of each perception facility.
The sensing data transmission scale is the sum of the transmission data amount of all sensing facilities in the land parcel in unit time.
Preferably, the method for calculating the transmission scale of the sensing data comprises the following steps:
1. determining a signal type of output data of each type of sensing facility;
the type of signal from which each type of sensing facility outputs data is determined by the sensing facility itself. For example: the signal type of the data output by the camera is a video signal, and the signal type of the data output by the temperature sensor is a text signal. A perception facility library can be preset. The perception appliance library includes various perception appliances and signal types corresponding to each perception appliance. The signal type corresponding to each sensing facility in the sensing facility library can be preset according to experience. Then, each sensing facility in the determined land parcel is corresponding to the sensing facility library so as to determine the signal type of each sensing facility.
2. Determining the data standard quantity of each type of sensing facility according to the layout scale of each type of sensing facility and the corresponding data standard quantity;
after the signal type of the sensing facility is determined, the data standard quantity of the sensing facility can be obtained. For the convenience of calculation, the data standard quantity of each signal type is the maximum data quantity of the transmission data in the unit time of the signal type, that is, the data quality requirement and the data protocol requirement are the highest level data quality requirement and the highest level data protocol requirement.
Preferably, the standard amount of data per type aware facility = standard amount of data per type aware facility layout scale.
3. And accumulating the data standard quantity of each type of sensing facility to obtain the sensing data transmission scale.
Of course, in addition to calculating the data standard quantity according to the type and then accumulating the data standard quantity to obtain the sensing data transmission scale, the data standard quantity of each sensing facility can also be accumulated to obtain the sensing data transmission scale after the signal type of each sensing facility is determined.
The intelligent gateway is used for transmitting data collected by each sensing facility, the transmission rate of the intelligent gateway is usually within a preset range, and the transmission rate of the intelligent gateway can be obtained through the performance parameters of the intelligent gateway. In the application, the intelligent gateway is preferably a Hub, and can provide a transmission rate of 10240 KB/sec to 12800 KB/sec. It is understood that, since the transmission rate of an intelligent gateway is limited, in order to upload data collected by all sensing facilities in a designated area, the intelligent gateway needs to be configured in multiple numbers. The number of the intelligent gateways is mainly determined by the transmission rate and the sensing data transmission scale of the intelligent gateways, and specifically comprises the following steps: the number of the intelligent gateways laid = [ the sensing data transmission scale/the transmission rate of the intelligent gateway ] +1.
In order to ensure that the intelligent gateway can transmit the data collected by all sensing facilities, the transmission rate of the intelligent gateway is preferably 10240 KB/second when the layout number of the intelligent gateway is calculated. Meanwhile, the data quantity which is less than the transmission rate provided by one intelligent gateway is configured to one intelligent gateway for the transmission of data.
In consideration of the fact that the number of the gateways to be laid needs to meet the transmission requirements of all sensing facilities in the designated area and also needs to meet the laying requirements in the designated area, the situation that the data collected by the sensing facilities cannot be uploaded is avoided. For this reason, it is necessary to determine whether the calculated number of the smart gateways distributed satisfies the distribution requirement to reconfirm the number of the smart gateways. Specifically, the following steps (step S310 to step S320):
step S310: acquiring the layout requirement of an intelligent gateway;
step S320: judging whether the layout quantity of the intelligent gateways meets the layout requirements of the intelligent gateways or not; if so, taking the layout number of the intelligent gateways as the final layout number of the intelligent gateways; and if not, determining the final layout quantity of the intelligent gateways according to the layout requirements of the intelligent gateways.
In a specific example, if the intelligent gateway adopts a wireless transmission mode, it is necessary to comply with the condition restriction of the wireless transmission range, that is, the bluetooth transmission range is 100 meters, the Zigbee transmission range is 200 meters, and the infrared transmission range is 100 meters. When the transmission capability of the intelligent gateway is easily influenced by building mixed environments such as building deployment space limit, building electromagnetic environment influence, building partition physical barrier and the like, the scale of the sensing equipment is adjusted by referring to the requirements of GB/T38624.1-2020, GB/T31994-2015 and the like and combining the gateway deployment experience of a complex building.
Step S330: and determining the layout scales of the processing facilities and the transmission facilities according to the measured layout scale of the sensing facilities and the measured data transmission scale based on a preset intelligent infrastructure layout rule.
The method comprises the following specific steps: (step S331-step S335)
Step S331: and dividing the planning area according to a preset area division rule to obtain a plurality of designated areas.
The designated area comprises a street, a neighborhood and a community unit, and a plurality of plots are contained in the street, the neighborhood and the community unit. In order to simplify the algorithm, all the plots in the planning area are preferably regarded as square regions with the same size, and each plot represents a region space with a certain area in the actual scene.
In the embodiment of the application, the designated area is obtained by dividing according to the actual condition in the town and the corresponding dividing rule; specifically, the neighborhood unit, neighborhood unit and community unit herein also refer to a region space with a certain area; the region division rules for different regions are divided based on the number and types of public arrangements, and different numbers and different types of public facilities are arranged in different types of regions.
The community unit is a public facility with perfect education, commercial traffic, cultural and physical activities, old people and the like within a range of fifteen minutes of walking; similarly, a neighborhood unit means that there is a corresponding public facility within five minutes of foot travel, and a neighborhood unit means that there is a corresponding public facility within ten minutes of foot travel.
Step S332: determining the sensing data transmission scale of each street unit, the sensing data transmission scale of each neighborhood unit and the sensing data transmission scale of each community unit according to the sensing data transmission scale of each plot;
the perceived data amount includes a data transmission amount and a data processing amount, that is, an amount of data to be transmitted and an amount of data to be processed and transmitted in the land parcel.
After a plurality of areas and plots are obtained, the number of plots covered in different areas can be known; and then the data volume of each region can be obtained according to the sensing data volume of each land and the number of the land in the region.
It is understood that the data volume mentioned in the embodiment of the present application may also be understood as data density, that is, the proportion of the data volume occupied by each land for the whole planning area, that is, the data density of each land; it can also be understood as the amount of data within each parcel.
Step S333: and calling a region comparison table, and obtaining actual region information corresponding to the neighborhood unit, the neighborhood unit and the community unit in the planning area according to the region comparison table.
The region comparison table comprises region type information, actual region information and corresponding relation information of each region and the actual region;
in the embodiment of the application, before the region comparison table is called from the database, the region comparison table needs to be constructed first, and then the region comparison table is stored in the database, so that the region comparison table is convenient to call later.
The method comprises the steps of establishing a region comparison table, wherein region type information and actual region information are acquired firstly, and the region comparison table is generated; the region type information comprises a street shop unit, a neighborhood unit and a community unit; the actual regional information sequentially comprises buildings, street blocks, streets, neighborhoods, communities, groups and cities from small to large; the building is a specific building, the street blocks comprise a plurality of buildings, the streets comprise a plurality of street blocks, the neighborhoods comprise a plurality of neighborhoods, and the communities comprise a plurality of neighborhoods and are generally provided with organizations such as committees; the group comprises a plurality of communities, and the city is the largest region; then binding the street houses and the street house units according to a preset regional formulation standard, and storing the street houses and the street house units in a regional comparison table; binding the neighborhood and the neighborhood units with each other according to a preset regional formulation standard, and storing the neighborhood and the neighborhood units in a regional comparison table; and binding the communities and the community units according to a preset regional calibration standard, and storing the communities and the community units in a regional comparison table.
It is understood that the regional enactment standard refers to the requirement of the type and the quantity of the public facilities in the region, and different regions are defined according to the positions of the public facilities in the planning region; and binding the area with the corresponding actual region, and storing the corresponding information in a region comparison table.
The region comparison table is obtained through the method, and then the region comparison table is stored in the database, so that after the planning area is divided into a plurality of regions, the actual region information corresponding to the regions can be obtained according to the region comparison table.
Step S334: and determining the type of the intelligent infrastructure and the distribution quantity of each type of intelligent infrastructure according to the sensing data transmission scale of the neighborhood unit, the sensing data transmission scale of the neighborhood unit and the sensing data transmission scale of the community unit.
In the embodiment of the application, a facility comparison table is called from a database; the facility comparison table comprises region type information, facility type information of the intelligent infrastructure and corresponding relation information of the region and the facility; then obtaining facility type information of intelligent infrastructures corresponding to the street units, neighborhood units and community units according to the facility comparison table; in this way, the facility type information of the intelligent infrastructure is determined according to the areas, that is, different types of areas require different types of facilities for processing, for example, a community unit requires a facility with higher data processing capability than a neighborhood unit, and the community unit requires a facility with certain data processing capability for data support.
After determining the types of the smart infrastructures corresponding to the different areas, the number of the smart infrastructures corresponding to the areas is determined.
The method comprises the steps of firstly obtaining a sensing data quantity threshold value of the intelligent infrastructure, then comparing the sensing data quantity value of the street furniture unit, the sensing data quantity value of the neighborhood unit and the sensing data quantity value of the community unit with the sensing data quantity threshold value of the intelligent infrastructure respectively, and determining the layout quantity of the intelligent infrastructure corresponding to the street furniture unit, the neighborhood unit and the community unit.
The intelligent infrastructure herein includes a data transmission facility and a data processing facility, and the perceived data volume threshold includes a data transmission volume threshold of the data transmission facility and a data processing volume threshold of the data processing facility.
When the number of the intelligent infrastructures is determined, judgment is needed according to the specific sensing data volume in the area; specifically, the intelligent infrastructure comprises a data processing facility, wherein the data processing facility comprises a processing main center, a processing branch center and an edge computing node; wherein, the processing main center is only one in one city generally; the processing sub-centers comprise a group level convergence center, a community level processing center and a neighborhood convergence center, and the sequence of the processing sub-centers is reduced in sequence according to the data processing capacity; the edge computing nodes comprise a street level edge computing node, a street block level edge computing node and a micro edge computing node; for example, the data volume of the region needs to be transmitted by at least two group level aggregation centers, the group level aggregation centers are firstly distributed, then the neighbor aggregation centers are used for filling the residual sensing data volume, and the type and the number of the intelligent infrastructures needed in the region are determined in such a way; that is, when an intelligent infrastructure is selected, the corresponding intelligent infrastructure is selected according to a preset facility priority; the facility priority here refers to the data processing capacity and the data transmission capacity of the facility, and the higher the data processing capacity is, the higher the facility priority is, the higher the data transmission capacity is, the higher the facility priority is; the data processing capability and the data transmission capability do not interfere with each other.
In the embodiment of the application, the types of the intelligent infrastructures corresponding to the street units and the community units are data processing facilities; the facility type of the intelligent infrastructure corresponding to the neighborhood unit is a data transmission facility; it needs to be known that, for the neighboring units, the neighboring units correspond to neighboring neighbors, and the neighboring neighbors are internally provided with data transmission facilities; in the actual facility layout situation, the data processing facility is generally laid out in the community, and the facility in the neighborhood is only used for transmission, and then a separate data processing facility is laid out in the street, wherein the street comprises buildings, and can be micro data processing facilities such as black boxes placed in the buildings; then arranging data transmission facilities in the neighborhood, and sending the data processed by the miniature data processing facilities in the building to the community through the neighborhood; the communities then send the data to the city via the community groups, i.e. the data transmission facilities are also arranged at the community groups, while the data processing facilities are arranged at both the community and the community groups.
Step S335: and determining the layout position of no intelligent infrastructure according to the actual region information, the data processing facility and a preset layout rule.
Firstly, acquiring public facility information in a planning area; then, according to the public facility information in the planning area, public facility information in the range of the street units, neighborhood units and community units is obtained, and the combined construction priority of each public facility is obtained according to the layout rule; and finally, according to the co-building priority of each public facility, co-building the intelligent infrastructures corresponding to the street units, the neighborhood units and the community units and the public facilities in the street units, the neighborhood units and the community units.
It can be understood that the intelligent infrastructure needs to be co-constructed with the public facilities, and when the intelligent infrastructure is laid, the public facilities in the area need to be considered, and then the corresponding public facilities are selected according to the preset public facility co-construction priority; the co-construction priority is established according to the characteristics of the public facilities, for example, the public facilities include community/neighborhood center, cultural facility land, primary and secondary schools, hospital, greenbelt, living support facility, transformer substation, energy station, switch station and transportation land, so the co-construction priority of the public facilities is the community/neighborhood center > cultural facility land > primary and secondary school > hospital > greenbelt > living support facility > transformer substation > energy station > switch station > transportation land.
In the embodiment of the application, the layout rule sets different layout modes and setting requirements for different intelligent infrastructures; for example, for the main processing center, the main processing center is arranged in a manner of independent land construction, the setting requirement is that the main processing center is close to sufficient and reliable power supply, and a region near the lake side or the winter monsoon is selected; for the processing sub-center, the processing sub-center comprises a group level convergence center, a community level processing center and a neighborhood convergence center; the group level convergence centers are arranged in a way that planning and site selection should be combined with a community level processing center, the setting requirement is that the same group of administrative service centers are preferentially selected to be jointly built or are jointly built with public service facilities of adjacent service centers, and if necessary, the individual site selection can be carried out to build and the processing center function of the community where the administrative center is located can be considered; the layout mode of the community-level processing center is that planning and site selection should be combined with community-level cultural facility land, primary and secondary school land, medical and health land, transformer substation, comprehensive energy station or switching station, and setting requirements should be combined with adjacent public service facilities or combined with the community service center; the neighborhood convergence center is arranged in a mode that planning and site selection should be combined with the street level edge computing nodes, and the setting requirement is that the neighborhood convergence center is preferentially selected to be jointly built with adjacent public service facilities or a community service center; for the edge computing nodes, the edge computing nodes comprise a street level edge computing node, a street block level edge computing node and a micro edge computing node; the layout mode of the street level edge computing nodes is combined with residential matching management land and matching education land in the street, and the setting requirement is that the local land is not independently occupied and the public building is combined; the layout mode of the street block level edge computing nodes is that the nodes are combined with land used by public service facilities in a street block, urban green land, transformer substations, energy stations and the like, the setting requirement is that the nodes do not occupy the land independently, and are preferentially combined with public service buildings in the street block; the layout mode of the micro edge computing nodes comprises the combination of barrel transportation land and urban buildings in park green land, and the setting requirement is that the micro edge computing nodes occupy no independent land.
According to the method, the data processing facilities and the data transmission facilities are arranged, the facility arrangement is optimized, the facility arrangement is considered in combination with the specific city condition, and the facility arrangement accuracy and reasonability are improved.
It is to be understood that, under special circumstances, such as consideration of the functional properties of the co-constructed buildings, the construction timing sequence, the building density of the intelligent facilities, and other factors, the layout of the data processing facilities can be adjusted within a certain range, so that the layout of the data processing facilities can better conform to the urban planning and actual conditions; for another example, in the process of building a new city or renovating a city, it often takes a long time, and in order to ensure that the whole data processing facility system is operated before the completion of building or renovating the city, important network nodes, that is, data processing facilities at important positions need to be co-built with buildings which are preferentially developed and built.
Step S400: and outputting the deployment type of the perception facilities on each land parcel, the layout scale of each type of perception facilities, the transmission scale of perception data, the layout scale of each type of intelligent infrastructure and the layout requirements.
The foregoing description is only exemplary of the preferred embodiments of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the application referred to in the present application is not limited to the embodiments with a particular combination of the above-mentioned features, but also encompasses other embodiments with any combination of the above-mentioned features or their equivalents without departing from the spirit of the application. For example, the above features may be replaced with (but not limited to) features having similar functions as those described in this application.
Claims (10)
1. A city intelligent infrastructure planning method is characterized by comprising the following steps:
based on a preset standardized simulation rule, constructing a standardized space simulation model of each land parcel on a planning region according to the acquired urban controllability planning rule, wherein the urban controllability planning rule is a limit on building parameters, and the standardized space simulation model is used for providing urban space basic parameters for measuring and calculating the layout scale of sensing facilities;
determining a sensing facility deployment type, a sensing facility deployment scale and a sensing data transmission scale on each land according to a standardized spatial simulation model based on a preset sensing facility deployment rule, wherein the sensing facility deployment rule comprises a corresponding relation between the sensing facility deployment type and an urban space and a corresponding relation between the sensing facility deployment type and the data scale of the sensing facility, and the sensing facility is used for collecting sensing data on the land;
determining the layout scale and the layout requirement of each type of intelligent infrastructure according to the measured layout scale of the sensing facilities and the measured transmission scale of the sensing data based on a preset intelligent infrastructure layout rule, wherein the intelligent infrastructure comprises an intelligent gateway, a transmission facility and a processing facility;
and outputting the deployment type of the perception facilities on each land, the layout scale of each type of perception facilities, the transmission scale of perception data, the layout scale of each type of intelligent infrastructure and the layout requirements.
2. The method according to claim 1, wherein the method for determining the deployment type of the sensing facilities on each land according to the standardized spatial simulation model based on the preset sensing facility deployment rules comprises:
the standardized space simulation model comprises urban space types and space information of each type, wherein the urban space types at least comprise a road space, a building space, an outdoor public space and an underground space;
determining the deployment type of the perception facilities required to be laid on the land parcel according to the urban space type and the acquired perception requirement on the urban engineering environment based on a perception facility library; the perception facility library comprises a corresponding relation between a perception facility deployment type and each urban space type, each urban space type comprises multiple urban engineering environments, and each urban engineering environment corresponds to multiple perception facilities.
3. The method as claimed in claim 1, wherein the method for determining the scale of each type of the cognitive facility layout on each land parcel of the planned section according to the standardized spatial simulation model based on the preset cognitive facility deployment rules comprises:
and determining the layout scale of each type of sensing facility according to the spatial information of each type and the deployment type of the sensing facility required to be laid in the land block based on a sensing facility layout standard library, wherein the sensing facility layout standard library comprises the corresponding relation between the deployment type of the sensing facility and the spatial information.
4. The method of claim 1, wherein the method for determining the perceived data transmission size per parcel comprises:
calling a standardized transmission model, wherein the standardized transmission model comprises a corresponding relation between deployment types of sensing facilities and data scales of the sensing facilities, each sensing facility corresponds to a signal type, and each signal type corresponds to a data standard quantity;
and determining the transmission scale of the perception data of each land according to the standardized transmission module, the deployment type of the perception facility of each land and the layout scale of each perception facility.
5. The method as claimed in claim 1, wherein the method for determining the layout scale of the intelligent gateway according to the measured layout scale of the sensing facilities and the measured data transmission scale based on the preset intelligent infrastructure layout rules comprises:
and determining the arrangement number of the intelligent gateways according to the transmission scale of the sensed data on each land and the acquired transmission rate of the intelligent gateways.
6. The method as claimed in claim 5, wherein the method for determining the layout scale of the intelligent gateway according to the measured layout scale of the sensing facilities and the measured data transmission scale based on the preset intelligent infrastructure layout rules further comprises:
acquiring the layout requirement of an intelligent gateway;
judging whether the layout number of the intelligent gateways meets the layout requirements of the intelligent gateways or not; and if so, taking the number of the intelligent gateways as the final number of the intelligent gateways.
7. The method of claim 6, wherein the method for determining the layout scale of the intelligent gateway according to the measured layout scale of the sensing facilities and the measured data transmission scale based on the preset layout rule of the intelligent infrastructure further comprises:
and when the layout number of the intelligent gateways does not meet the layout requirement of the intelligent gateways, determining the final layout number of the intelligent gateways according to the layout requirement of the intelligent gateways.
8. The method as claimed in claim 1, wherein the method of determining the layout scale of the processing facility and the transmission facility according to the measured layout scale of the sensing facility and the data transmission scale based on the preset intelligent infrastructure layout rule comprises:
dividing the planning area according to a preset area division rule to obtain a plurality of designated areas, wherein the designated areas comprise a street room unit, a neighborhood unit and a community unit, and a plurality of plots are contained in the street room unit, the neighborhood unit and the community unit;
determining the transmission scale of the sensing data of each street unit, the transmission scale of the sensing data of each neighborhood unit and the transmission scale of the sensing data of each community unit according to the transmission scale of the sensing data of each plot;
calling a region comparison table, and obtaining actual region information corresponding to the street units, neighborhood units and community units in a planning region according to the region comparison table, wherein the region comparison table comprises region type information, the actual region information and corresponding relation information of each region and an actual region;
and determining the type of the intelligent infrastructure and the distribution quantity of each type of intelligent infrastructure according to the sensing data transmission scale of the neighborhood unit, the sensing data transmission scale of the neighborhood unit and the sensing data transmission scale of the community unit.
9. The method of claim 8, wherein the method of determining the layout requirements of the processing facilities and the transmission facilities based on the measured scale of the sensing facilities and the scale of the data transmission based on the preset intelligent infrastructure layout rules comprises:
and determining the layout position of each intelligent infrastructure according to the actual regional information and the data processing facilities and according to a preset layout rule.
10. The method as claimed in claim 9, wherein the method for determining the type of the intelligent infrastructure and the number of deployments of each type of the intelligent infrastructure according to the sensing data transmission size of the neighborhood unit, the sensing data transmission size of the neighborhood unit and the sensing data transmission size of the community unit comprises:
calling a facility comparison table, wherein the facility comparison table comprises region type information, facility type information of intelligent infrastructure and corresponding relation information of each region and facility;
respectively obtaining facility type information of intelligent infrastructures corresponding to the street units, the neighborhood units and the community units according to the facility comparison table;
acquiring a sensing data quantity threshold of an intelligent infrastructure, wherein the intelligent infrastructure comprises a data transmission facility and a data processing facility, and the sensing data quantity threshold comprises a data transmission quantity threshold of the data transmission facility and a data processing quantity threshold of the data processing facility;
comparing the sensing data transmission scale of the neighborhood unit, the sensing data transmission scale of the neighborhood unit and the sensing data transmission scale of the community unit with a sensing data amount threshold of the intelligent infrastructure respectively;
and determining the layout quantity of the intelligent infrastructures corresponding to the street units, the neighborhood units and the community units.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210918561.4A CN115358544B (en) | 2022-08-01 | 2022-08-01 | Urban intelligent infrastructure planning and designing method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210918561.4A CN115358544B (en) | 2022-08-01 | 2022-08-01 | Urban intelligent infrastructure planning and designing method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115358544A true CN115358544A (en) | 2022-11-18 |
| CN115358544B CN115358544B (en) | 2023-04-07 |
Family
ID=84032765
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210918561.4A Active CN115358544B (en) | 2022-08-01 | 2022-08-01 | Urban intelligent infrastructure planning and designing method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115358544B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115375109A (en) * | 2022-08-01 | 2022-11-22 | 北京清华同衡规划设计研究院有限公司 | Data node facility layout method and system based on data scale |
| CN116186854A (en) * | 2023-02-15 | 2023-05-30 | 深圳市城市规划设计研究院股份有限公司 | Method and device for calculating volume rate of land, electronic equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014016729A1 (en) * | 2012-07-24 | 2014-01-30 | Koninklijke Philips N.V. | Sensing information service and its use in urban service planning system |
| WO2016008601A1 (en) * | 2014-07-16 | 2016-01-21 | Siemens Aktiengesellschaft | System and method for optimizing use of infrastructure facilities of an urban district |
| CN112132729A (en) * | 2020-10-19 | 2020-12-25 | 林文旭 | Intelligent city planning system |
| CN112348317A (en) * | 2020-10-15 | 2021-02-09 | 中国城市规划设计研究院 | Project planning condition generation method and system for smart city |
| CN113642946A (en) * | 2021-10-18 | 2021-11-12 | 南京派光智慧感知信息技术有限公司 | Perception information integration access system based on city important infrastructure |
-
2022
- 2022-08-01 CN CN202210918561.4A patent/CN115358544B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014016729A1 (en) * | 2012-07-24 | 2014-01-30 | Koninklijke Philips N.V. | Sensing information service and its use in urban service planning system |
| WO2016008601A1 (en) * | 2014-07-16 | 2016-01-21 | Siemens Aktiengesellschaft | System and method for optimizing use of infrastructure facilities of an urban district |
| CN112348317A (en) * | 2020-10-15 | 2021-02-09 | 中国城市规划设计研究院 | Project planning condition generation method and system for smart city |
| CN112132729A (en) * | 2020-10-19 | 2020-12-25 | 林文旭 | Intelligent city planning system |
| CN113642946A (en) * | 2021-10-18 | 2021-11-12 | 南京派光智慧感知信息技术有限公司 | Perception information integration access system based on city important infrastructure |
Non-Patent Citations (3)
| Title |
|---|
| 曹阳等: "智慧城市仿真模型组织架构", 《科技导报》 * |
| 曹阳等: "智慧城市规划仿真模型组织架构与标准体系研究", 《建设科技》 * |
| 陈晓晋等: "基于传感网的基础设施智能云平台", 《物联网技术》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115375109A (en) * | 2022-08-01 | 2022-11-22 | 北京清华同衡规划设计研究院有限公司 | Data node facility layout method and system based on data scale |
| CN115375109B (en) * | 2022-08-01 | 2023-04-07 | 北京清华同衡规划设计研究院有限公司 | Data node facility layout method and system based on data scale |
| CN116186854A (en) * | 2023-02-15 | 2023-05-30 | 深圳市城市规划设计研究院股份有限公司 | Method and device for calculating volume rate of land, electronic equipment and storage medium |
| CN116186854B (en) * | 2023-02-15 | 2023-09-26 | 深圳市城市规划设计研究院股份有限公司 | Method and device for calculating volume rate of land, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115358544B (en) | 2023-04-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115358544B (en) | Urban intelligent infrastructure planning and designing method | |
| Ramyar et al. | Ecosystem services mapping for green infrastructure planning–The case of Tehran | |
| Ismagiloiva et al. | Role of smart cities in creating sustainable cities and communities: A systematic literature review | |
| Song et al. | Resilience-vulnerability balance to urban flooding: A case study in a densely populated coastal city in China | |
| Bishop et al. | Prediction of scenic beauty using mapped data and geographic information systems | |
| CN109284619A (en) | The region Locating Type edge calculations system and method for heterologous city Internet of Things | |
| CN107872808B (en) | WLAN station address prediction analysis method and device | |
| CN109617947A (en) | The heterologous Internet of Things edge calculations system and method in city being arranged according to management category | |
| CN110545558B (en) | High-speed service area crowd density estimation system based on Wi-Fi data | |
| CN101807222A (en) | Station-based urban public traffic network optimized configuration method | |
| KR20200119114A (en) | Disaster management system using 3D BIM object model and disaster management Method | |
| CN112184282A (en) | Cinema site selection model establishing method, cinema site selection method and cinema site selection platform | |
| CN115357127B (en) | Digital twin intelligent building brain machine device and system | |
| CN112070304B (en) | City group element interaction measuring method, equipment and storage medium | |
| KR101369764B1 (en) | System for forecasting change of u-city | |
| Huang et al. | Livability assessment of 101,630 communities in China’s major cities: A remote sensing perspective | |
| Nematchoua et al. | A study of life cycle assessment in two old neighbourhoods in Belgium | |
| CN114511281A (en) | Design scheme auxiliary examination method and system based on CIM | |
| CN113011768B (en) | Public facility data processing method, system, electronic device and medium | |
| Shapurjee et al. | Backyard housing in Gauteng: An analysis of spatial dynamics | |
| Kickert et al. | Surveying density, urban characteristics, and development capacity of station areas in the Delta Metropolis | |
| La et al. | Explore urban population distribution using nighttime lights, land-use/land-cover and population census data | |
| CN114925994A (en) | Urban village risk assessment and risk factor positioning method based on deep learning | |
| CN113554221A (en) | Simulation and prediction method for town development boundary under 'flow space' view angle | |
| CN113127950A (en) | Method for generating, analyzing and evaluating well-equipped urban residential areas |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |