CN113887917A - Smart city management platform based on service architecture - Google Patents
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Abstract
The invention discloses a smart city management platform based on a service framework, which relates to the technical field of smart cities and comprises a control center, a greening analysis module and a return visit analysis module; the control center is used for distinguishing types of the received service requests, then analyzing the event type requests, and applying limited human resources to urban problems with high event degree to achieve the maximum resource utilization; after receiving the evaluation coefficient of the citizen, the return visit analysis module is used for calling the consultation/order urging record corresponding to the citizen, and analyzing by combining the evaluation coefficient and the consultation/order urging record so as to return visit to the citizen in time, do the soothing work and avoid the citizen from generating discontent emotion; the greening analysis module is used for analyzing the greening conditions of all the urban subregions and judging whether the urban requirements are met or not so as to timely rectify and improve the green belts, improve the urban greening level and promote the construction process of smart cities.
Description
Technical Field
The invention relates to the technical field of smart cities, in particular to a smart city management platform based on a service architecture.
Background
With the continuous increase of the current urban population, the urbanization construction is developed day by day, the problem of urban diseases in part of areas is severe day by day, and in order to solve the urban development problem and realize the urban sustainable development, the construction of smart cities becomes the historical trend of the current urban development which is irreversible. At present, in the construction process of smart cities, China focuses more on the innovation of the technical level, and the connotation of the smart cities requires optimal configuration to realize the cooperative sharing of people, objects and environments.
However, in the smart city management process, it is difficult to distinguish between real and false city problems fed back by citizens or to determine whether the city problems are only directed to a very small number of people, and it is difficult to investigate and confirm the city problems fed back by citizens in time due to limited human resources; meanwhile, the greening degree of each area of the city cannot be monitored, and the greening belt can be rectified in time, so that the greening level of the city is improved; to this end, we propose a smart city management platform based on a service architecture.
Disclosure of Invention
In order to solve the problems existing in the scheme, the invention provides a smart city management platform based on a service architecture. The invention can apply limited human resources to the urban problem with high spread, thereby achieving the maximization of resource utilization, accelerating the construction process of the smart city, analyzing the greening conditions of all sub-areas of the city, judging whether the urban requirements are met, timely rectifying and reforming the green belt and improving the urban greening level.
The purpose of the invention can be realized by the following technical scheme:
the intelligent city management platform based on the service architecture comprises a consultation module, a control center, a survey module, a greening analysis module, an evaluation module and a return visit analysis module;
a consultation module: the system is used for editing urban problems by citizens, forming service requests, uploading the service requests to a control center and allowing the citizens to perform order-urging operation on the uploaded service requests;
the control center: the system is used for distinguishing the types of the received service requests and judging whether the service requests are transaction requests or not; if the request is a transaction request, performing a popularity analysis on the transaction request; if the waviness degree is larger than or equal to a preset threshold value, the task work order corresponding to the affair request is sent to a business department;
a survey module: the system comprises a data acquisition module, a data analysis module and a data analysis module, wherein the data acquisition module is used for acquiring economic and humanistic data and historical microclimate data of each urban subregion and analyzing the economic and humanistic data and the historical microclimate data to obtain a regional coefficient of each urban subregion;
greening analysis module: the system is used for analyzing the greening condition of each urban subregion and judging whether the urban requirements are met or not; if not, modifying the green belt of the corresponding sub-area;
an evaluation module: and the system is used for evaluating the service of the management platform after the citizen receives the processing result of the service request and returning the evaluation coefficient to the control center.
Further, the calculation method of the waviness degree comprises the following steps:
when the control center receives the transaction request, automatically counting down, and automatically returning the counting down to the original value and counting down again if the same request is received in the counting down stage; otherwise, the countdown returns to zero;
extracting keywords of the uploaded transaction requests, and when the keyword overlap ratio of the two uploaded transaction requests reaches a preset overlap ratio lambda%, considering the two uploaded transaction requests as the same request; wherein lambda is a preset value;
acquiring the occurrence times of the same request in the countdown phase and marking as P1; acquiring the occurrence places of the same request, and taking the occurrence place with the largest occurrence frequency as a corresponding work order place; the mark is centered on the work order location, and the area within radius R1 is the area of influence;
acquiring economic humanistic data of an influence area, wherein the economic humanistic data comprises daily average pedestrian flow, daily average vehicle flow, regional resident population and corresponding daily average GDP of the influence area;
evaluating the economic human character coefficient of the affected area according to the economic human character data and marking the economic human character coefficient as GR;
carrying out normalization processing on the occurrence times P1 and the economic humanity coefficient GR and taking the numerical values;
using formulas
Is calculated toThe degree of spread RQ to the transaction class request, where f1 and f1 are predetermined coefficient factors, and η is a fixed value.
Further, the specific analysis steps of the investigation module are as follows:
acquiring economic human data of a corresponding subregion, evaluating the economic human coefficient of the subregion according to the economic human data, and marking the economic human coefficient as GW;
acquiring historical microclimate data of corresponding sub-areas through a meteorological platform, wherein the microclimate data comprise rainfall, wind speed, wind direction, temperature, humidity and air quality data;
evaluating the weather sensitivity of the sub-area according to historical microclimate data and marking the weather sensitivity as QX;
carrying out normalization processing on economic human factor GW and meteorological sensitivity QX and taking the numerical values;
using formulas
Calculating a region coefficient LK of the sub-region, wherein a1 and a2 are coefficient factors;
the investigation module is used for transmitting the area coefficient LK to the greening analysis module, and stamping a time stamp on the area coefficient LK and storing the area coefficient LK in the storage module.
Further, the specific analysis steps of the greening analysis module are as follows:
aiming at a certain city subregion, acquiring a green belt outline of the subregion, directly generating a path which walks around the green belt outline through a contour line extraction algorithm, and marking the path as a green belt path;
calculating the area radiance F1 of the corresponding green belt relative to the sub-area in the map according to the green belt path;
acquiring a regional coefficient LK of the sub-region, and determining a greening grade corresponding to the regional coefficient LK according to the regional coefficient LK and by combining a database; determining a corresponding standard radiance range according to the greening grade;
if the area radiance F1 is less than the lower limit value of the standard radiance range, a greening correction signal is generated and sent to the control center; and the control center sends the greening and reforming work order to the service department after receiving the greening and reforming signal.
Further, the specific calculation method of the area radiance F1 is as follows:
taking a certain point on a green belt path as a circle center, marking an area in the radius R2 as a point radiation area corresponding to the green belt, and integrating all the point radiation areas to obtain a limit radiation area corresponding to the green belt; the area radiance F1 of the corresponding green belt is the area coincidence rate of the limited radiance area of the corresponding green belt and the sub-area.
Further, after receiving the evaluation coefficient, the control center controls the return visit analysis module to call the consultation/order-urging record corresponding to the citizen, and the return visit analysis module is used for analyzing by combining the evaluation coefficient and the consultation/order-urging record to obtain the return visit coefficient of the citizen;
if the return visit coefficient is larger than or equal to the preset coefficient threshold, generating a return visit signal and feeding the return visit signal back to the control center; and after receiving the return visit signal, the control center arranges the staff to return visit to the citizen.
Further, a comparison table of the area coefficient range and the greening grade is stored in the database; each greening grade has a corresponding standard radiance range.
Further, the specific analysis steps of the revisit analysis module are as follows:
obtaining an evaluation coefficient of a citizen and marking the evaluation coefficient as Qs; calling a consultation/order urging record corresponding to the citizen, and calculating the time difference between the moment when the citizen uploads the corresponding service request for the first time and the corresponding work order feedback moment to obtain a request processing time QT 1; counting the number of invoicing times of the citizen and marking as C1;
carrying out normalization processing on the evaluation coefficient, the request processing time and the order hastening times and taking the numerical values of the evaluation coefficient, the request processing time and the order hastening times;
the return visit coefficient HF of the citizen is calculated by the formula HF ═ C1 × b1+ QT1 × b2)/(Qs × b3), where b1, b2, b3 are all coefficient factors.
Compared with the prior art, the invention has the beneficial effects that:
1. the control center distinguishes the type of the received service request, if the service request is a transaction request, the transaction request is subjected to the spread degree analysis; if the spread degree is larger than or equal to the preset threshold value, the corresponding task work order of the affair request is sent to a business department, limited human resources are applied to the urban problem with high spread degree, the resource utilization maximization is achieved, and the construction process of the smart city is accelerated;
2. after receiving the evaluation coefficient of the citizen, the return visit analysis module is used for calling the consultation/order urging record corresponding to the citizen, analyzing by combining the evaluation coefficient and the consultation/order urging record to obtain the return visit coefficient of the citizen, and if the return visit coefficient HF is larger than or equal to a preset coefficient threshold value, returning the citizen to do soothing work to avoid the citizen from generating discontent emotion;
3. the greening analysis module is used for analyzing the greening conditions of all the urban subregions; aiming at a certain urban sub-area, calculating the area radiance of a corresponding green belt relative to the sub-area in the map according to the green belt path; determining a corresponding standard radiance range by combining the area coefficients of the corresponding sub-areas; and if the area radiance is smaller than the corresponding standard radiance range, the green belts of the sub-area are modified, the urban greening level is improved, and the construction process of the smart city is promoted.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the smart city management platform based on the service architecture includes a consultation module, a control center, a survey module, a greening analysis module, a storage module, a database, an evaluation module, and a return visit analysis module;
the consulting module is used for citizens to edit urban problems, form service requests and upload the service requests to the control center, the control center receives the service requests sent by the citizens through the consulting module, distinguishes types of the received service requests, and then processes the service requests in a classified mode, and the specific steps are as follows:
the method comprises the following steps: distinguishing types of the received service requests, and judging whether the service requests are consultation requests or transaction requests;
step two: if the inquiry request is the inquiry request, the database stores a uniform question reply standard, and the staff replies the inquiry request of citizens by referring to the standard;
step three: if the request is a transaction request, judging whether the request is the acceptance range of the control center; the affair request carries the occurrence location of the corresponding urban problem;
if not, the reply citizen does not accept and informs the reason of leaving the way; if the request is within the acceptance range, performing the waviness analysis on the transaction request; if the spread degree is larger than or equal to a preset threshold value, sending a task work order corresponding to the affair request to a business department, and receiving the task work order by the business department, dispatching investigators to the places where the corresponding urban problems appear, and investigating and processing the places;
step four: after the business department finishes processing, the task work order flow returns to the control center, then the hot line, the APP and the WeChat channel are called to feed back the processing result to citizens, and the time when the processing result is fed back to the citizens is marked as the work order feedback time;
the control center is connected with the request processing department through an informatization system, the appeal of citizens does not need to be transmitted among all departments in a manual mode, and the system is completely based on the network application of the Internet, so that the processing speed of all departments is greatly improved, the intermediate time-consuming link is reduced, the creation of an efficient and transparent smart city is facilitated, meanwhile, the control center analyzes the coverage degree of affair requests, limited human resources are applied to the problem of the city with high coverage degree, the resource utilization maximization is achieved, and the construction process of the smart city is accelerated;
the analysis method of the popularity degree comprises the following steps:
s1: when the control center receives the transaction request, the task work order information is recorded; the task work order information comprises a work order place;
s2: when a transaction request is received, automatically counting down, wherein the counting down duration is T1 time; if the same request is received in the countdown phase, the countdown is automatically returned to the original value, and the countdown is performed again according to T1; otherwise, the countdown is zeroed, e.g., 24 hours for T1;
extracting keywords of the uploaded transaction requests, and when the keyword overlap ratio of the two uploaded transaction requests reaches a preset overlap ratio lambda%, considering the two uploaded transaction requests as the same request; wherein lambda is a preset value;
s3: acquiring the occurrence times of the same request in the countdown phase and marking the occurrence times as request frequency P1;
marking the occurrence places of the uploaded transaction requests of the same request, and taking the occurrence place with the largest occurrence frequency as a corresponding work order place;
s4: the mark is centered on the work order location, and the area within radius R1 is the area of influence;
acquiring economic humanistic data of an affected area, wherein the economic humanistic data comprises daily average pedestrian flow, daily average vehicle flow, regional resident population and corresponding daily average GDP of the affected area;
evaluating the economic human character coefficient of the affected area according to the economic human character data and marking the economic human character coefficient as GR;
s5: using formulas
Calculated to obtain the transaction class requestThe waviness degree RQ, wherein f1 and f1 are preset coefficient factors, and eta is a fixed value;
the investigation module is used for collecting economic and humanistic data and historical microclimate data of each urban subregion and analyzing the economic and humanistic data and the historical microclimate data to obtain the regional coefficient of each urban subregion, and the method specifically comprises the following steps:
acquiring economic human data of a corresponding subregion, evaluating the economic human coefficient of the subregion according to the economic human data, and marking the economic human coefficient as GW;
acquiring historical microclimate data of corresponding sub-areas through a meteorological platform, wherein the microclimate data comprise rainfall, wind speed, wind direction, temperature, humidity and air quality data;
evaluating the weather sensitivity of the sub-area according to historical microclimate data and marking the weather sensitivity as QX;
using formulas
Calculating a region coefficient LK of the sub-region, wherein a1 and a2 are coefficient factors;
the investigation module is used for transmitting the area coefficient LK to the greening analysis module, and stamping a time stamp on the area coefficient LK and storing the area coefficient LK in the storage module;
the greening analysis module is used for analyzing the greening conditions of all the urban subregions, judging whether the urban requirements are met, and if the urban requirements are not met, rectifying and modifying the green belts of the corresponding subregions; the specific analysis steps are as follows:
v1: aiming at a certain city subregion, acquiring a green belt outline of the subregion, directly generating a path which walks around the green belt outline through a contour line extraction algorithm, and marking the path as a green belt path;
v2: calculating the area radiance F1 of the corresponding green belt relative to the sub-area in the map according to the green belt path; the specific calculation method comprises the following steps:
taking a certain point on a green belt path as a circle center, marking an area in the radius R2 as a point radiation area corresponding to the green belt, and integrating all the point radiation areas to obtain a limit radiation area corresponding to the green belt; wherein R2 is a preset value;
the area radiance F1 of the corresponding green belt is the area coincidence rate of the limited radiance area of the corresponding green belt and the sub-area;
v3: acquiring a regional coefficient LK of the sub-region, and determining a greening grade corresponding to the regional coefficient LK according to the regional coefficient LK and by combining a database; the method specifically comprises the following steps:
the database stores a comparison table of the area coefficient range and the greening grade, wherein the larger the area coefficient is, the higher the greening grade is; each greening grade has a corresponding green belt area radiance range;
determining the greening grade corresponding to the area coefficient LK according to the comparison table;
matching the greening grade with all greening grades to obtain a corresponding greening belt area radiance range, and marking the corresponding greening belt area radiance range as a standard radiance range;
v4: comparing the area radiance F1 of the corresponding green belt with the standard radiance range; wherein K1 and K2 are the upper and lower limits of the standard radiance range, and K1 is less than K2;
if the area radiance F1 is less than K1, judging that the greening condition of the sub-area does not meet the urban requirement, and generating a greening correction signal;
the greening analysis module is used for sending a greening rectification signal to the control center, the control center sends a greening rectification work order to the service department after receiving the greening rectification signal, the service department distributes workers to rectify the green belts in the sub-area, and the area radiance of the rectified green belts is in the corresponding standard radiance range by smoothing, stretching and screening the green belt path, so that the urban greening level is improved, and the construction process of a smart city is promoted;
the consultation module is also used for citizens to perform order urging operation on the uploaded service requests;
the evaluation module is used for evaluating the service of the management platform after citizens receive the processing result of the service request and returning an evaluation coefficient to the control center, and the evaluation coefficient rule is as follows: scoring the management platform, wherein the full score is 100;
after receiving the evaluation coefficient, the control center controls the return visit analysis module to call the consultation/urging record corresponding to the citizen, when the request processing time of the service request is longer, the urging times are more, and the evaluation coefficient is lower, the probability that the citizen generates discontent emotion is higher, at the moment, the return visit of the citizen needs to be carried out in time, and the soothing work is done, so that the management efficiency of the management platform is improved;
comparing the return visit coefficient HF with a preset coefficient threshold; if the return visit coefficient HF is larger than or equal to the preset coefficient threshold, generating a return visit signal and feeding the return visit signal back to the control center;
after receiving the return visit signal, the control center arranges the staff to return visit to the citizen, and does the soothing work to avoid the citizen from generating discontent emotion.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows:
when the intelligent city management platform based on the service architecture works, the consultation module is used for citizens to edit city problems, form service requests and upload the service requests to the control center, the control center distinguishes types of the received service requests and then classifies the service requests for processing, and if the service requests are transaction requests, the transaction requests are subjected to spread degree analysis; if the spread degree is larger than or equal to the preset threshold value, the corresponding task work order of the affair request is sent to a business department, limited human resources are applied to the urban problem with high spread degree, the resource utilization maximization is achieved, and the construction process of the smart city is accelerated;
the evaluation module is used for evaluating the service of the management platform after the citizen receives the processing result of the service request and returning the evaluation coefficient to the control center, the control center receives the evaluation coefficient and then controls the return visit analysis module to call the consultation/order urging record corresponding to the citizen, the evaluation coefficient and the consultation/order urging record are combined for analysis to obtain the return visit coefficient of the citizen, if the return visit coefficient HF is larger than or equal to a preset coefficient threshold value, a return visit signal is generated, and the control center receives the return visit signal and then arranges a worker to return visit to the citizen, so that the pacifying work is done, and the discontent mood of the citizen is avoided;
the greening analysis module is used for analyzing the greening condition of each urban subregion and judging whether the urban requirements are met; aiming at a certain city sub-area, acquiring a green belt outline of the sub-area, calculating the area radiance of the corresponding green belt relative to the sub-area in the map according to a green belt path, acquiring an area coefficient LK of the sub-area, and determining a green grade corresponding to the area coefficient LK according to the area coefficient LK and by combining a database; if the area radiance F1 is less than the standard radiance range corresponding to the greening grade, a greening correction signal is generated; after receiving the greening rectification signal, the control center distributes workers to rectify the green belts of the sub-area, and the green belt paths are smoothed, stretched and screened, so that the area radiance of the rectified green belts is in the corresponding standard radiance range, the urban greening level is improved, and the construction process of the smart city is promoted.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (8)
1. The intelligent city management platform based on the service architecture is characterized by comprising a consultation module, a control center, a survey module, a greening analysis module, an evaluation module and a return visit analysis module;
a consultation module: the system is used for editing urban problems by citizens, forming service requests, uploading the service requests to a control center and allowing the citizens to perform order-urging operation on the uploaded service requests;
the control center: the system is used for distinguishing the types of the received service requests and judging whether the service requests are transaction requests or not; if the request is a transaction request, performing a popularity analysis on the transaction request; if the waviness degree is larger than or equal to a preset threshold value, the task work order corresponding to the affair request is sent to a business department;
a survey module: the system comprises a data acquisition module, a data analysis module and a data analysis module, wherein the data acquisition module is used for acquiring economic and humanistic data and historical microclimate data of each urban subregion and analyzing the economic and humanistic data and the historical microclimate data to obtain a regional coefficient of each urban subregion;
greening analysis module: the system is used for analyzing the greening condition of each urban subregion and judging whether the urban requirements are met or not; if not, modifying the green belt of the corresponding sub-area;
an evaluation module: and the system is used for evaluating the service of the management platform after the citizen receives the processing result of the service request and returning the evaluation coefficient to the control center.
2. The smart city management platform based on service architecture as claimed in claim 1, wherein the calculation method of the degree of waviness is:
when the control center receives the transaction request, automatically counting down, and automatically returning the counting down to the original value and counting down again if the same request is received in the counting down stage; otherwise, the countdown returns to zero;
acquiring the occurrence times of the same request in the countdown phase and marking as P1; acquiring the occurrence places of the same request, and taking the occurrence place with the largest occurrence frequency as a corresponding work order place; the mark is centered on the work order location, and the area within radius R1 is the area of influence;
acquiring economic humanistic data of an influence area, wherein the economic humanistic data comprises daily average pedestrian flow, daily average vehicle flow, regional resident population and corresponding daily average GDP of the influence area;
evaluating the economic human character coefficient of the affected area according to the economic human character data and marking the economic human character coefficient as GR;
using formulas
And calculating to obtain the degree of coverage RQ of the transaction request, wherein f1 and f1 are preset coefficient factors, and eta is a fixed value.
3. The intelligent city management platform based on service architecture as claimed in claim 1, wherein the specific analysis steps of the greening analysis module are:
aiming at a certain city subregion, acquiring a green belt outline of the subregion, directly generating a path which walks around the green belt outline through a contour line extraction algorithm, and marking the path as a green belt path;
calculating the area radiance F1 of the corresponding green belt relative to the sub-area in the map according to the green belt path;
acquiring a regional coefficient LK of the sub-region, and determining a greening grade corresponding to the regional coefficient LK according to the regional coefficient LK and by combining a database; determining a corresponding standard radiance range according to the greening grade;
if the area radiance F1 is less than the lower limit value of the standard radiance range, a greening correction signal is generated and sent to the control center; and the control center sends the greening and reforming work order to the service department after receiving the greening and reforming signal.
4. The intelligent city management platform based on service architecture as claimed in claim 3, wherein the area radiance F1 is calculated by the following specific method:
taking a certain point on a green belt path as a circle center, marking an area in the radius R2 as a point radiation area corresponding to the green belt, and integrating all the point radiation areas to obtain a limit radiation area corresponding to the green belt; the area radiance F1 of the corresponding green belt is the area coincidence rate of the limited radiance area of the corresponding green belt and the sub-area.
5. The smart city management platform based on the service architecture as claimed in claim 1, wherein the control center controls the return visit analysis module to retrieve the consultation/order-urging record of the corresponding citizen after receiving the evaluation coefficient, and the return visit analysis module is configured to perform analysis by combining the evaluation coefficient and the consultation/order-urging record to obtain the return visit coefficient of the citizen;
if the return visit coefficient is larger than or equal to the preset coefficient threshold, generating a return visit signal and feeding the return visit signal back to the control center; and after receiving the return visit signal, the control center arranges the staff to return visit to the citizen.
6. The intelligent city management platform based on service architecture as claimed in claim 3, wherein the database stores a comparison table of area coefficient range and greening level; each greening grade has a corresponding standard radiance range.
7. The service architecture-based smart city management platform of claim 1, wherein the microclimate data includes rainfall, wind speed, wind direction, temperature, humidity, and air quality data.
8. The smart city management platform based on service architecture as claimed in claim 5, wherein the specific analysis steps of the return visit analysis module are:
obtaining an evaluation coefficient of a citizen and marking the evaluation coefficient as Qs; calling a consultation/order urging record corresponding to the citizen, and calculating the time difference between the moment when the citizen uploads the corresponding service request for the first time and the corresponding work order feedback moment to obtain a request processing time QT 1; counting the number of invoicing times of the citizen and marking as C1;
the return visit coefficient HF of the citizen is calculated by the formula HF ═ C1 × b1+ QT1 × b2)/(Qs × b3), where b1, b2, b3 are all coefficient factors.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115168679A (en) * | 2022-07-20 | 2022-10-11 | 广州聚百洲信息科技有限公司 | Smart city data analysis method based on cloud platform and data analysis system thereof |
| CN115759640A (en) * | 2022-11-21 | 2023-03-07 | 山东睿振建筑工程有限公司 | Public service information processing system and method for smart city |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115168679A (en) * | 2022-07-20 | 2022-10-11 | 广州聚百洲信息科技有限公司 | Smart city data analysis method based on cloud platform and data analysis system thereof |
| CN115759640A (en) * | 2022-11-21 | 2023-03-07 | 山东睿振建筑工程有限公司 | Public service information processing system and method for smart city |
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