CN117634788B - Electric resource and traffic monitoring management method, system and medium for digital city - Google Patents

Abstract

The application provides a digital city electric resource and traffic monitoring management method, system and medium. The method comprises the following steps: the method comprises the steps of obtaining intelligent meter data and historical energy consumption statistical data of a preset area, respectively calculating and obtaining electricity consumption population and gas consumption population, further obtaining population of the preset area through population calculation model processing, obtaining free travel traffic tool data of the preset area, obtaining bus stop demand index according to the population, obtaining bus stop demand grade after comparison, counting the number of times of each demand grade of a bus stop which is evaluated at regular time within preset time, comparing the number of times with a bus stop set threshold, and finally obtaining bus stop set state information. According to the application, the population of the preset area is obtained through analyzing the data of the intelligent electric meter and the intelligent gas meter, so that the intelligent evaluation of the bus stop setting is realized.

Description

Electric resource and traffic monitoring management method, system and medium for digital city

Technical Field

The application relates to the field of electric resource and traffic monitoring management, in particular to a method, a system and a medium for managing electric resource and traffic monitoring of a digital city.

Background

The electric resource and traffic monitoring are basic guarantees that the urban electric resource can normally run, the distribution and the energy consumption of the urban electric resource reflect the personnel quantity condition to a certain extent, so that the electric resource is known clearly and dynamic monitoring is realized, a certain auxiliary effect can be achieved on the population quantity dynamic grasp of the whole urban, the traffic monitoring can be achieved through the knowledge of the dynamic population, but the current monitoring of the urban electric resource only stays in the aspects of energy consumption, cost statistics and the like, population quantity statistics and dynamic management are not involved, and the data is not fully utilized.

In view of the above problems, an effective technical solution is currently needed.

Disclosure of Invention

In view of the above problems, the present application is directed to providing a method, a system and a medium for electric resource and traffic monitoring management in a digital city, which can obtain the population of electricity consumption and the population of gas consumption by obtaining intelligent meter data and historical energy consumption statistics data of a preset area, respectively calculating the population of electricity consumption and the population of gas consumption, further obtaining the population of the preset area by population calculation model processing, obtaining free travel traffic tool data of the preset area, obtaining a bus stop demand index according to the population, obtaining a bus stop demand grade after comparison, counting the number of times of each demand grade of a bus stop which is evaluated at regular time within a preset time, comparing with a bus stop setting threshold, and finally obtaining bus stop setting state information. According to the application, the population of the preset area is obtained through analyzing the data of the intelligent electric meter and the intelligent gas meter, so that the intelligent evaluation of the bus stop setting is realized.

The application also provides a digital city electric resource and traffic monitoring management method, which comprises the following steps:

Acquiring intelligent meter data of a preset area, wherein the intelligent meter data comprise intelligent ammeter data and intelligent gas meter data;

Acquiring historical energy consumption statistical data of a preset area, wherein the historical energy consumption statistical data comprise historical average power consumption data and historical average power consumption data;

Respectively obtaining the electricity consumption population and the gas consumption population according to the intelligent meter data and the historical energy consumption statistical data;

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

Acquiring free travel vehicle data of traffic monitoring of a preset area, wherein the free travel vehicle data comprise self-driving data and riding data;

Processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index, and comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

And obtaining the number of times of each demand level of the bus stop, which is evaluated at regular time in a preset time period of a preset area, and comparing the number of times with a bus stop setting threshold value to obtain bus stop setting state information.

Optionally, in the method for electric resource and traffic monitoring management of a digital city according to the present application, the obtaining intelligent meter data of a preset area includes intelligent electric meter data and intelligent gas meter data, specifically includes:

Acquiring intelligent ammeter data and intelligent gas meter data of a preset area;

the intelligent ammeter data comprise intelligent ammeter initial electric quantity data, intelligent ammeter final electric quantity data and electric quantity statistics period time data;

the intelligent gas meter data comprise intelligent gas meter initial electric quantity data, intelligent gas meter termination electric quantity data and gas quantity statistics cycle time data.

Optionally, in the method for electric resource and traffic monitoring management of a digital city according to the present application, the obtaining the electricity consumption population and the gas consumption population according to the smart meter data and the historical energy consumption statistics includes:

calculating to obtain the electricity consumption personnel mouth number according to the historical electricity consumption per person data and the intelligent ammeter data;

and calculating according to the historical per-person gas consumption data and the intelligent gas meter data to obtain the gas consumption population.

Optionally, in the method for electric resource and traffic monitoring management of a digital city according to the present application, the step of inputting the electricity consumption population and the gas consumption population into a preset area population calculation model to obtain a preset area population includes:

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

the calculation formula of the population of the preset area is as follows:

Wherein R _k is regional population, D _r is electricity consumption population, Q _r is gas-electricity consumption population, and alpha and beta are preset characteristic coefficients.

Optionally, in the method for electric resource and traffic monitoring management of a digital city according to the present application, the processing according to the population of the preset area and the data of the free travel vehicles to obtain a bus stop demand index, and comparing with a bus stop demand level threshold to obtain a bus stop demand level includes:

processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index;

comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

the bus stop demand level comprises a strong demand, a medium demand or a weak demand;

the calculation formula of the bus stop demand index is as follows:

wherein X _q is a bus stop demand index, J _c is self-driving data, Q _x is riding data, and delta, eta and lambda are preset characteristic coefficients.

In this scheme, still include:

Acquiring power pipeline subsection information, gas pipeline distribution information and traffic road distribution information in a preset area;

Obtaining shared line distribution information according to the electric power pipeline subsection information, the gas pipeline distribution information and the traffic road distribution information;

Respectively acquiring finishing construction planning information of an electric pipeline, a gas pipeline and a traffic road;

Judging whether the finishing construction planning information is positioned in a shared line or not according to the finishing construction planning information, if so, synchronizing the finishing construction planning information to electric power, fuel gas and road authorities;

and the electric power, the fuel gas and the road authorities comprehensively stage the construction time according to the finishing construction planning information.

In this scheme, still include:

acquiring power demand reference electric quantity information of a preset area;

Acquiring power demand influence factor information of a preset area, wherein the power demand influence factor information comprises weather temperature change data, old population proportion data and average income and expense ratio of living population;

Calculating according to the power demand influence factor information to obtain a power demand variation index;

correspondingly obtaining the power resource demand fluctuation according to the power demand reference electric quantity information and the power demand fluctuation index;

The power demand variation index calculation formula is as follows:

Wherein D _z is the power demand variation index, W _b is the weather temperature variation data, L _n is the aged population proportion data, S _z is the average income and expense ratio of the living population, Sigma and omega are preset characteristic coefficients.

In this scheme, still include:

acquiring congestion information of a traffic congestion road section, wherein the congestion information comprises congestion duration data, congestion vehicle distance data and congestion vehicle data;

Inputting a congestion index calculation model according to the congestion information to obtain a congestion index;

comparing the congestion index with a preset congestion level threshold value to obtain a congestion level;

Acquiring traffic police position information around a congested road section;

Correspondingly obtaining support traffic police information according to the congestion index and the traffic police position information;

Transmitting the supporting traffic police information to a supporting traffic police mobile equipment end;

The congestion index calculation formula is as follows:

Wherein Y _z is a congestion index, Y _s is congestion duration data, Y _j is congestion vehicle distance data, Y _c is congestion vehicle data, Θ, ψ are preset feature coefficients.

In a second aspect, the present application provides a digital urban electrical resource and traffic monitoring management system comprising: the system comprises a memory and a processor, wherein the memory comprises programs of electric resources and traffic monitoring management methods of a digital city, and the programs of the electric resources and the traffic monitoring management methods of the digital city realize the following steps when executed by the processor:

Acquiring intelligent meter data of a preset area, wherein the intelligent meter data comprise intelligent ammeter data and intelligent gas meter data;

Acquiring historical energy consumption statistical data of a preset area, wherein the historical energy consumption statistical data comprise historical average power consumption data and historical average power consumption data;

Respectively obtaining the electricity consumption population and the gas consumption population according to the intelligent meter data and the historical energy consumption statistical data;

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

Acquiring free travel vehicle data of traffic monitoring of a preset area, wherein the free travel vehicle data comprise self-driving data and riding data;

Processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index, and comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

And obtaining the number of times of each demand level of the bus stop, which is evaluated at regular time in a preset time period of a preset area, and comparing the number of times with a bus stop setting threshold value to obtain bus stop setting state information.

In a third aspect, the present application also provides a computer readable storage medium, including therein a digital city electrical resource and traffic monitoring management method program, which when executed by a processor, implements the steps of the digital city electrical resource and traffic monitoring management method as described in any one of the above.

As can be seen from the above, the method, system and medium for electric resource and traffic monitoring management of digital city provided by the application are characterized in that the electricity consumption population and gas consumption population are respectively calculated and obtained by obtaining intelligent meter data and historical energy consumption statistical data of a preset area, the population of the preset area is further obtained by population calculation model processing, then the free travel traffic tool data of the preset area is obtained, the bus stop demand index is obtained according to the population, the bus stop demand grade is obtained after comparison, the number of times of each demand grade of the bus stop which is evaluated at regular time within the preset time is counted, and the bus stop setting state information is finally obtained after comparison with the bus stop setting threshold. According to the application, the population of the preset area is obtained through analyzing the data of the intelligent electric meter and the intelligent gas meter, so that the intelligent evaluation of the bus stop setting is realized.

Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for managing electric resources and traffic monitoring in a digital city according to an embodiment of the present application;

FIG. 2 is a flow chart of obtaining a bus stop demand level of a digital city electric resource and traffic monitoring management method according to an embodiment of the present application;

Fig. 3 is a schematic structural diagram of an electrical resource and traffic monitoring management system for a digital city according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.

It should be noted that like reference numerals and letters refer to like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.

Referring to fig. 1, fig. 1 is a flowchart of a method for managing electric resources and traffic monitoring in a digital city according to some embodiments of the present application. The electric resource and traffic monitoring management method of the digital city comprises the following steps:

s101, acquiring intelligent meter data of a preset area, wherein the intelligent meter data comprise intelligent electric meter data and intelligent gas meter data;

S102, acquiring historical energy consumption statistical data of a preset area, wherein the historical energy consumption statistical data comprise historical average electricity consumption data and historical average electricity consumption data;

s103, respectively obtaining the electricity consumption population and the gas consumption population according to the intelligent meter data and the historical energy consumption statistical data;

S104, inputting the electricity consumption population and the gas consumption population into a preset regional population calculation model to obtain a preset regional population;

S105, acquiring free travel vehicle data of traffic monitoring of a preset area, wherein the free travel vehicle data comprise self-driving data and riding data;

S106, processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index, and comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

s107, obtaining the number of times of each demand level of the bus stop which is evaluated at regular time in a preset time period of a preset area, and comparing the number of times with a bus stop setting threshold value to obtain bus stop setting state information.

The intelligent electricity meter data and the intelligent gas meter data of the preset area, the historical average electricity consumption data and the historical average electricity consumption data are obtained, and the preset area is an area which is set in advance according to the needs, can be a cell or a community, and can be selected and adjusted according to the needs; the population of electricity consumption and the population of gas consumption are respectively obtained through the obtained data and are used for predicting the population of a certain area, and because the electricity consumption and the gas consumption of each family/person are inconsistent, the population obtained by calculation only by the intelligent meter data has certain error, in order to realize more accurate population prediction, the population of the preset area is obtained through the processing of a preset area population calculation model, and after the population of the preset area is obtained, the free travel traffic tool data monitored through preset traffic comprises the self-driving data, namely the number of vehicles traveling from the self-driving; riding data, namely the number of bicycles which are ridden and out; according to the population number of the preset area and the data of the free travel vehicles, a bus stop demand index can be obtained, namely the intensity index of the people in the area on the bus stop demand is obtained, the bus stop demand index reflects the proportion of people taking the bus in the preset area to travel to a certain extent, and the bus stop demand index is compared with a bus stop demand grade threshold value after the bus stop demand index is obtained to obtain a bus stop demand grade comprising strong demands, general demands and weak demands; in this embodiment, the bus stop demand level threshold is set as: [0, 0.5), the bus stop demand level is a weak demand; 0.5,0.7) the bus stop demand level is the general demand; 0.7,1, the bus stop demand level is a strong demand; when the demand index of the bus stops is calculated to be 0.85, the demand grade of the bus stops in the preset area is a strong demand; because the fluidity of the user and other factors are that the bus stop demand level of one or two months is not necessarily the most realistic demand occasionally, in this embodiment, the distribution condition of the bus stop demand level of each month in the preset area of 6 months is continuously counted, the counted condition is compared with the bus stop setting threshold value, and the bus stop setting state information is obtained, in this embodiment, when the bus stop demand level of more than 4 months in 6 months is a strong demand, the bus stop setting state is the allowable setting.

According to an embodiment of the present invention, the obtaining smart meter data of a preset area includes smart meter data and smart gas meter data, and specifically includes:

Acquiring intelligent ammeter data and intelligent gas meter data of a preset area;

the intelligent ammeter data comprise intelligent ammeter initial electric quantity data, intelligent ammeter final electric quantity data and electric quantity statistics period time data;

the intelligent gas meter data comprise intelligent gas meter initial electric quantity data, intelligent gas meter termination electric quantity data and gas quantity statistics cycle time data.

It should be noted that, the preset area may be a cell, may also be a community, or may be other units, and may be set according to actual needs, where the smart meter data and the smart gas meter data in the preset area are obtained, where the smart meter data includes smart meter start power data, smart meter end power data, and power statistics cycle time data, where the smart meter start power data is power display data of the electric meter at the beginning of statistics, the smart meter end power data is power display data of the electric meter at the end of statistics, and the power statistics cycle time data is cycle time required from the beginning of statistics to the end of statistics, where the cycle time is in a minimum unit of days; the intelligent gas meter data comprise intelligent gas meter initial power data, intelligent gas meter final power data and gas quantity statistics cycle time data.

According to the embodiment of the invention, the electricity consumption population and the gas consumption population are respectively obtained according to the intelligent meter data and the historical energy consumption statistical data, and the method specifically comprises the following steps:

calculating to obtain the electricity consumption personnel mouth number according to the historical electricity consumption per person data and the intelligent ammeter data;

and calculating according to the historical per-person gas consumption data and the intelligent gas meter data to obtain the gas consumption population.

In order to calculate population according to electricity consumption and gas consumption, firstly, historical average electricity consumption data and historical average gas consumption data are required to be obtained, the historical average electricity consumption data can be taken as daily electricity consumption of people in the last year or daily gas consumption of people in the last year, the electricity consumption population can be calculated according to intelligent meter data and historical average electricity consumption data, and the gas consumption population is calculated according to the historical average gas consumption data and intelligent gas meter data;

The calculation formula of the electricity consumption personnel mouth number is as follows:

Wherein D _r is the number of people who use electricity, D _zz is the data of the termination electric quantity of the intelligent electric meter, D _qs is the data of the initial electric quantity of the intelligent electric meter, D _rj is the data of the average air consumption of historical people, and t is the number of days of the statistical period;

the calculation formula of the air consumption population is as follows:

Wherein, Q _r is the population of gas consumption, Q _zz is the data of the termination electric quantity of the intelligent gas meter, Q _qs is the data of the initial electric quantity of the intelligent gas meter, Q _rj is the data of the average gas consumption of historical people, and t is the statistical period days.

According to an embodiment of the present invention, the processing of inputting the electricity consumption population and the gas consumption population into a preset area population calculation model to obtain a preset area population specifically includes:

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

the calculation formula of the population of the preset area is as follows:

Wherein R _k is regional population, D _r is electricity population, Q _r is gas-electricity population, and alpha and beta are preset characteristic coefficients (the preset characteristic coefficients are obtained by inquiring a preset third-party electrical resource and a traffic monitoring management platform).

It should be noted that, the electricity consumption population and the gas consumption population are obtained according to the intelligent meter data and the historical energy consumption statistics, and because people have different habits of using energy sources, the population calculated according to a single energy source has a larger degree of error, so that the use conditions of the two energy sources need to be comprehensively considered, and on the basis of the electricity consumption population and the gas consumption population, a relatively accurate preset area population is obtained by using a preset area population calculation model.

Referring to fig. 2, fig. 2 is a flowchart of a method for obtaining a bus stop demand level according to an electric resource and traffic monitoring management method of a digital city according to some embodiments of the present application. According to the embodiment of the application, the processing is performed according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index, and the bus stop demand grade is obtained by comparing with a bus stop demand grade threshold, which specifically comprises:

s201, processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index;

s202, comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

s203, the bus stop demand level comprises a strong demand, a medium demand or a weak demand;

the calculation formula of the bus stop demand index is as follows:

Wherein X _q is a bus stop demand index, J _c is self-driving data, Q _x is riding data, delta, eta and lambda are preset characteristic coefficients (the preset characteristic coefficients are obtained by inquiring a preset third-party electrical resource and a traffic monitoring management platform).

It should be noted that after the population of the preset area is obtained, the population of the preset area is intuitively known, but the travel mode is various, a part of the travel mode is occupied by the bus, in order to better and truly count the travel situation of the bus, after the self-driving data and the riding data of the traffic monitoring of the preset area are obtained, the bus stop demand index is needed to be processed by combining the population of the preset area through a bus stop demand index formula, the bus stop demand index reflects the demand degree of the population of the preset area on the bus stop, the demand degree can be intuitively and conveniently known, the obtained bus stop demand index is compared with a bus stop demand grade threshold to further divide the demand degree, the bus stop demand grade threshold is classified according to the size of the bus stop demand index, and the classification of the bus stop demand grade comprises strong demand, medium demand or weak demand and is also a reflection of the emergency degree and the urgent degree of the bus stop demand. In this embodiment, the bus stop demand level threshold is set as: [0, 0.5), the bus stop demand level is a weak demand; 0.5,0.7) the bus stop demand level is the general demand; 0.7,1, the bus stop demand level is a strong demand; when the demand index of the bus stops is calculated to be 0.85, the demand grade of the bus stops in the preset area is a strong demand.

According to an embodiment of the present invention, further comprising:

Acquiring power pipeline subsection information, gas pipeline distribution information and traffic road distribution information in a preset area;

Obtaining shared line distribution information according to the electric power pipeline subsection information, the gas pipeline distribution information and the traffic road distribution information;

Respectively acquiring finishing construction planning information of an electric pipeline, a gas pipeline and a traffic road;

Judging whether the finishing construction planning information is positioned in a shared line or not according to the finishing construction planning information, if so, synchronizing the finishing construction planning information to electric power, fuel gas and road authorities;

and the electric power, the fuel gas and the road authorities comprehensively stage the construction time according to the finishing construction planning information.

It should be noted that, the layout of the urban electric resource is not separated from the pipeline transportation, and in the city, most of the carriers for transporting the electric resource and the pipeline are located below the road, so that the laying, maintenance and modification of the electric resource transportation line can affect the smoothness of the road, and further affect the traffic condition, the current electric resource and the traffic authorities are different, and the communication between the authorities is often the same road, each authority maintains and modifies at different time to cause the phenomenon that the traffic is not passed for a long time, so that how to coordinate the maintenance and modification of each authorities is a worth exploring problem, in this instance, the electric pipeline subsection information, the gas pipeline subsection information and the traffic road subsection information in the preset area, that is, the electric pipeline subsection information, the gas pipeline subsection information and the traffic road subsection information are obtained, and the information of the two or three shared line distributions are obtained through the analysis of the distribution network diagram, the electric pipeline, the gas pipeline and the traffic authorities often have the trimming construction information, such as a degree, the trimming construction information is obtained according to the trimming information, and the trimming information is judged whether the trimming information is located in the road authorities and the shared road authorities are located in the road planning, if the two or not has the time is reduced, and if the trimming information is planned and the time is reduced. In this embodiment, if the power main department needs to seal the road for 10 days and the gas main department needs to seal the road for 5 days, if the road 15 is needed to be sealed by separate implementation, but if the content is all available in the planning, the two can be combined to achieve the work in 10 days, so that the road sealing time is reduced.

According to an embodiment of the present invention, further comprising:

acquiring power demand reference electric quantity information of a preset area;

Acquiring power demand influence factor information of a preset area, wherein the power demand influence factor information comprises weather temperature change data, old population proportion data and average income and expense ratio of living population;

Calculating according to the power demand influence factor information to obtain a power demand variation index;

correspondingly obtaining the power resource demand fluctuation according to the power demand reference electric quantity information and the power demand fluctuation index;

The power demand variation index calculation formula is as follows:

Wherein D _z is the power demand variation index, W _b is the weather temperature variation data, L _n is the aged population proportion data, S _z is the average income and expense ratio of the living population, Sigma and omega are preset characteristic coefficients (the preset characteristic coefficients are obtained by inquiring a preset third-party electric resource and a traffic monitoring management platform).

It should be noted that, the electricity consumption of each area is continuously changed, but sometimes the total resources are limited, in order to better guarantee and distribute the electricity, a preliminary evaluation needs to be made on the electricity consumption in advance, although the electricity consumption is changed, certain electricity demand reference electricity consumption information exists according to the use condition of the past year, the electricity consumption change is because of more factors influencing the electricity consumption change, although the factors are more, certain relations still exist, in order to better obtain the electricity consumption requirement of the preset area, firstly, the electricity demand reference electricity consumption information of the preset area is obtained, namely, the electricity consumption of a certain period of time floats up and down on a certain reference electricity, then, the electricity demand influence factor information is obtained, including weather temperature change data, old people population proportion data and average income expenditure ratio of living population, in this example, the weather temperature change data is the difference of the front and back temperatures after the temperature rise/fall in summer, the temperature rise, the household air conditioner call is increased, the population proportion data refer to the fact that the old people in the preset area population has a small temperature influence on the old people is not sensitive to the first electricity consumption of the old people, the old people has a strong awareness in summer, or the air conditioner has a strong sense of the air conditioner is saved; the average income and expense ratio of the living population refers to the average ratio of income and expense of the living population in a preset area, the income also affects the electricity consumption condition, the factors are comprehensively considered, the electricity demand variation index is calculated and obtained, the electricity demand variation index represents the up-and-down floating amplitude of the electricity consumption, and the electricity demand variation amount is correspondingly obtained after the electricity demand reference electricity quantity information is multiplied with the electricity demand variation index.

According to an embodiment of the present invention, further comprising:

acquiring congestion information of a traffic congestion road section, wherein the congestion information comprises congestion duration data, congestion vehicle distance data and congestion vehicle data;

Inputting a congestion index calculation model according to the congestion information to obtain a congestion index;

comparing the congestion index with a preset congestion level threshold value to obtain a congestion level;

Acquiring traffic police position information around a congested road section;

Correspondingly obtaining support traffic police information according to the congestion index and the traffic police position information;

Transmitting the supporting traffic police information to a supporting traffic police mobile equipment end;

The congestion index calculation formula is as follows:

Wherein Y _z is a congestion index, Y _s is congestion duration data, Y _j is congestion vehicle distance data, Y _c is congestion vehicle data, Θ, ψ are preset feature coefficients.

It should be noted that, with the development of cities, traffic jam problems are increasingly highlighted, at present, traffic is dredged by means of manual scheduling by a scheduling center, in order to better, more intelligently and more timely dredge traffic, congestion information of a traffic jam road section includes congestion duration data, congestion vehicle distance data and congestion vehicle data is firstly obtained, a congestion index is obtained through formula calculation according to the congestion information, the congestion index is compared with a preset congestion level threshold value to obtain a congestion level, and in this embodiment, the congestion level index is set as follows: [0, 0.5), the congestion level is general congestion; [0.5,0.7 ] the congestion level is congestion; 0.7,1 the congestion level is very congested; when the calculated congestion index is 0.85, the congestion level is very congested; and then acquiring the position information of traffic police around the congested road section, and in order to dredge traffic more quickly, acquiring the number of people needing to support the traffic police and the personnel information needing to support the traffic police according to the position correspondence of the traffic police of the congested grade, and then transmitting the personnel information to a mobile equipment end needing to participate in supporting the traffic police.

As shown in fig. 3, the invention also discloses an electric resource and traffic monitoring management system 3 of a digital city, which comprises a memory 31 and a processor 32, wherein the memory comprises an electric resource and traffic monitoring management method program of the digital city, and the electric resource and traffic monitoring management method program of the digital city realizes the following steps when being executed by the processor:

Acquiring intelligent meter data of a preset area, wherein the intelligent meter data comprise intelligent ammeter data and intelligent gas meter data;

Acquiring historical energy consumption statistical data of a preset area, wherein the historical energy consumption statistical data comprise historical average power consumption data and historical average power consumption data;

Respectively obtaining the electricity consumption population and the gas consumption population according to the intelligent meter data and the historical energy consumption statistical data;

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

Acquiring free travel vehicle data of traffic monitoring of a preset area, wherein the free travel vehicle data comprise self-driving data and riding data;

Processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index, and comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

And obtaining the number of times of each demand level of the bus stop, which is evaluated at regular time in a preset time period of a preset area, and comparing the number of times with a bus stop setting threshold value to obtain bus stop setting state information.

The intelligent electricity meter data and the intelligent gas meter data of the preset area, the historical average electricity consumption data and the historical average electricity consumption data are obtained, and the preset area is an area which is set in advance according to the needs, can be a cell or a community, and can be selected and adjusted according to the needs; the population of electricity consumption and the population of gas consumption are respectively obtained through the obtained data and are used for predicting the population of a certain area, and because the electricity consumption and the gas consumption of each family/person are inconsistent, the population obtained by calculation only by the intelligent meter data has certain error, in order to realize more accurate population prediction, the population of the preset area is obtained through the processing of a preset area population calculation model, and after the population of the preset area is obtained, the free travel traffic tool data monitored through preset traffic comprises the self-driving data, namely the number of vehicles traveling from the self-driving; riding data, namely the number of bicycles which are ridden and out; according to the population number of the preset area and the data of the free travel vehicles, a bus stop demand index can be obtained, namely the intensity index of the people in the area on the bus stop demand is obtained, the bus stop demand index reflects the proportion of people taking the bus in the preset area to travel to a certain extent, and the bus stop demand index is compared with a bus stop demand grade threshold value after the bus stop demand index is obtained to obtain a bus stop demand grade comprising strong demands, general demands and weak demands; in this embodiment, the bus stop demand level threshold is set as: [0, 0.5), the bus stop demand level is a weak demand; 0.5,0.7) the bus stop demand level is the general demand; 0.7,1, the bus stop demand level is a strong demand; when the demand index of the bus stops is calculated to be 0.85, the demand grade of the bus stops in the preset area is a strong demand; because the fluidity of the user and other factors are that the bus stop demand level of one or two months is not necessarily the most realistic demand occasionally, in this embodiment, the distribution condition of the bus stop demand level of each month in the preset area of 6 months is continuously counted, the counted condition is compared with the bus stop setting threshold value, and the bus stop setting state information is obtained, in this embodiment, when the bus stop demand level of more than 4 months in 6 months is a strong demand, the bus stop setting state is the allowable setting.

According to an embodiment of the present invention, the obtaining smart meter data of a preset area includes smart meter data and smart gas meter data, and specifically includes:

Acquiring intelligent ammeter data and intelligent gas meter data of a preset area;

the intelligent ammeter data comprise intelligent ammeter initial electric quantity data, intelligent ammeter final electric quantity data and electric quantity statistics period time data;

the intelligent gas meter data comprise intelligent gas meter initial electric quantity data, intelligent gas meter termination electric quantity data and gas quantity statistics cycle time data.

It should be noted that, the preset area may be a cell, may also be a community, or may be other units, and may be set according to actual needs, where the smart meter data and the smart gas meter data in the preset area are obtained, where the smart meter data includes smart meter start power data, smart meter end power data, and power statistics cycle time data, where the smart meter start power data is power display data of the electric meter at the beginning of statistics, the smart meter end power data is power display data of the electric meter at the end of statistics, and the power statistics cycle time data is cycle time required from the beginning of statistics to the end of statistics, where the cycle time is in a minimum unit of days; the intelligent gas meter data comprise intelligent gas meter initial power data, intelligent gas meter final power data and gas quantity statistics cycle time data.

According to the embodiment of the invention, the electricity consumption population and the gas consumption population are respectively obtained according to the intelligent meter data and the historical energy consumption statistical data, and the method specifically comprises the following steps:

calculating to obtain the electricity consumption personnel mouth number according to the historical electricity consumption per person data and the intelligent ammeter data;

and calculating according to the historical per-person gas consumption data and the intelligent gas meter data to obtain the gas consumption population.

In order to calculate population according to electricity consumption and gas consumption, firstly, historical average electricity consumption data and historical average gas consumption data are required to be obtained, the historical average electricity consumption data can be taken as daily electricity consumption of people in the last year or daily gas consumption of people in the last year, the electricity consumption population can be calculated according to intelligent meter data and historical average electricity consumption data, and the gas consumption population is calculated according to the historical average gas consumption data and intelligent gas meter data;

The calculation formula of the electricity consumption personnel mouth number is as follows:

Wherein D _r is the number of people who use electricity, D _zz is the data of the termination electric quantity of the intelligent electric meter, D _qs is the data of the initial electric quantity of the intelligent electric meter, D _rj is the data of the average air consumption of historical people, and t is the number of days of the statistical period;

the calculation formula of the air consumption population is as follows:

Wherein, Q _r is the population of gas consumption, Q _zz is the data of the termination electric quantity of the intelligent gas meter, Q _qs is the data of the initial electric quantity of the intelligent gas meter, Q _rj is the data of the average gas consumption of historical people, and t is the statistical period days.

According to an embodiment of the present invention, the processing of inputting the electricity consumption population and the gas consumption population into a preset area population calculation model to obtain a preset area population specifically includes:

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

the calculation formula of the population of the preset area is as follows:

Wherein R _k is regional population, D _r is electricity consumption population, Q _r is gas consumption population, and alpha and beta are preset characteristic coefficients (the preset characteristic coefficients are obtained by inquiring a preset third-party electrical resource and a traffic monitoring management platform).

It should be noted that, the electricity consumption population and the gas consumption population are obtained according to the intelligent meter data and the historical energy consumption statistics, and because people have different habits of using energy sources, the population calculated according to a single energy source has a larger degree of error, so that the use conditions of the two energy sources need to be comprehensively considered, and on the basis of the electricity consumption population and the gas consumption population, a relatively accurate preset area population is obtained by using a preset area population calculation model.

According to the embodiment of the invention, the processing is performed according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index, and the bus stop demand grade is obtained by comparing with a bus stop demand grade threshold, which specifically comprises:

processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index;

comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

the bus stop demand level comprises a strong demand, a medium demand or a weak demand;

the calculation formula of the bus stop demand index is as follows:

Wherein X _q is a bus stop demand index, J _c is self-driving data, Q _x is riding data, delta, eta and lambda are preset characteristic coefficients (the preset characteristic coefficients are obtained by inquiring a preset third-party electrical resource and a traffic monitoring management platform).

It should be noted that after the population of the preset area is obtained, the population of the preset area is intuitively known, but the travel mode is various, a part of the travel mode is occupied by the bus, in order to better and truly count the travel situation of the bus, after the self-driving data and the riding data of the traffic monitoring of the preset area are obtained, the bus stop demand index is needed to be processed by combining the population of the preset area through a bus stop demand index formula, the bus stop demand index reflects the demand degree of the population of the preset area on the bus stop, the demand degree can be intuitively and conveniently known, the obtained bus stop demand index is compared with a bus stop demand grade threshold to further divide the demand degree, the bus stop demand grade threshold is classified according to the size of the bus stop demand index, and the classification of the bus stop demand grade comprises strong demand, medium demand or weak demand and is also a reflection of the emergency degree and the urgent degree of the bus stop demand. In this embodiment, the bus stop demand level threshold is set as: [0, 0.5), the bus stop demand level is a weak demand; 0.5,0.7) the bus stop demand level is the general demand; 0.7,1, the bus stop demand level is a strong demand; when the demand index of the bus stops is calculated to be 0.85, the demand grade of the bus stops in the preset area is a strong demand.

According to an embodiment of the present invention, further comprising:

Acquiring power pipeline subsection information, gas pipeline distribution information and traffic road distribution information in a preset area;

Obtaining shared line distribution information according to the electric power pipeline subsection information, the gas pipeline distribution information and the traffic road distribution information;

Respectively acquiring finishing construction planning information of an electric pipeline, a gas pipeline and a traffic road;

Judging whether the finishing construction planning information is positioned in a shared line or not according to the finishing construction planning information, if so, synchronizing the finishing construction planning information to electric power, fuel gas and road authorities;

and the electric power, the fuel gas and the road authorities comprehensively stage the construction time according to the finishing construction planning information.

It should be noted that, the layout of the urban electric resource is not separated from the pipeline transportation, and in the city, most of the carriers for transporting the electric resource and the pipeline are located below the road, so that the laying, maintenance and modification of the electric resource transportation line can affect the smoothness of the road, and further affect the traffic condition, the current electric resource and the traffic authorities are different, and the communication between the authorities is often the same road, each authority maintains and modifies at different time to cause the phenomenon that the traffic is not passed for a long time, so that how to coordinate the maintenance and modification of each authorities is a worth exploring problem, in this instance, the electric pipeline subsection information, the gas pipeline subsection information and the traffic road subsection information in the preset area, that is, the electric pipeline subsection information, the gas pipeline subsection information and the traffic road subsection information are obtained, and the information of the two or three shared line distributions are obtained through the analysis of the distribution network diagram, the electric pipeline, the gas pipeline and the traffic authorities often have the trimming construction information, such as a degree, the trimming construction information is obtained according to the trimming information, and the trimming information is judged whether the trimming information is located in the road authorities and the shared road authorities are located in the road planning, if the two or not has the time is reduced, and if the trimming information is planned and the time is reduced. In this embodiment, if the power main department needs to seal the road for 10 days and the gas main department needs to seal the road for 5 days, if the road 15 is needed to be sealed by separate implementation, but if the content is all available in the planning, the two can be combined to achieve the work in 10 days, so that the road sealing time is reduced.

According to an embodiment of the present invention, further comprising:

acquiring power demand reference electric quantity information of a preset area;

Acquiring power demand influence factor information of a preset area, wherein the power demand influence factor information comprises weather temperature change data, old population proportion data and average income and expense ratio of living population;

Calculating according to the power demand influence factor information to obtain a power demand variation index;

correspondingly obtaining the power resource demand fluctuation according to the power demand reference electric quantity information and the power demand fluctuation index;

The power demand variation index calculation formula is as follows:

Wherein D _z is the power demand variation index, W _b is the weather temperature variation data, L _n is the aged population proportion data, S _z is the average income and expense ratio of the living population, Sigma and omega are preset characteristic coefficients (the preset characteristic coefficients are obtained by inquiring a preset third-party electric resource and a traffic monitoring management platform).

It should be noted that, the electricity consumption of each area is continuously changed, but sometimes the total resources are limited, in order to better guarantee and distribute the electricity, a preliminary evaluation needs to be made on the electricity consumption in advance, although the electricity consumption is changed, certain electricity demand reference electricity consumption information exists according to the use condition of the past year, the electricity consumption change is because of more factors influencing the electricity consumption change, although the factors are more, certain relations still exist, in order to better obtain the electricity consumption requirement of the preset area, firstly, the electricity demand reference electricity consumption information of the preset area is obtained, namely, the electricity consumption of a certain period of time floats up and down on a certain reference electricity, then, the electricity demand influence factor information is obtained, including weather temperature change data, old people population proportion data and average income expenditure ratio of living population, in this example, the weather temperature change data is the difference of the front and back temperatures after the temperature rise/fall in summer, the temperature rise, the household air conditioner call is increased, the population proportion data refer to the fact that the old people in the preset area population has a small temperature influence on the old people is not sensitive to the first electricity consumption of the old people, the old people has a strong awareness in summer, or the air conditioner has a strong sense of the air conditioner is saved; the average income and expense ratio of the living population refers to the average ratio of income and expense of the living population in a preset area, the income also affects the electricity consumption condition, the factors are comprehensively considered, the electricity demand variation index is calculated and obtained, the electricity demand variation index represents the up-and-down floating amplitude of the electricity consumption, and the electricity demand variation amount is correspondingly obtained after the electricity demand reference electricity quantity information is multiplied with the electricity demand variation index.

According to an embodiment of the present invention, further comprising:

acquiring congestion information of a traffic congestion road section, wherein the congestion information comprises congestion duration data, congestion vehicle distance data and congestion vehicle data;

Inputting a congestion index calculation model according to the congestion information to obtain a congestion index;

comparing the congestion index with a preset congestion level threshold value to obtain a congestion level;

Acquiring traffic police position information around a congested road section;

Correspondingly obtaining support traffic police information according to the congestion index and the traffic police position information;

Transmitting the supporting traffic police information to a supporting traffic police mobile equipment end;

The congestion index calculation formula is as follows:

Wherein Y _z is a congestion index, Y _s is congestion duration data, Y _j is congestion vehicle distance data, Y _c is congestion vehicle data, Θ, ψ are preset feature coefficients.

It should be noted that, with the development of cities, traffic jam problems are increasingly highlighted, at present, traffic is dredged by means of manual scheduling by a scheduling center, in order to better, more intelligently and more timely dredge traffic, congestion information of a traffic jam road section includes congestion duration data, congestion vehicle distance data and congestion vehicle data is firstly obtained, a congestion index is obtained through formula calculation according to the congestion information, the congestion index is compared with a preset congestion level threshold value to obtain a congestion level, and in this embodiment, the congestion level index is set as follows: [0, 0.5), the congestion level is general congestion; [0.5,0.7 ] the congestion level is congestion; 0.7,1 the congestion level is very congested; when the calculated congestion index is 0.85, the congestion level is very congested; and then acquiring the position information of traffic police around the congested road section, and in order to dredge traffic more quickly, acquiring the number of people needing to support the traffic police and the personnel information needing to support the traffic police according to the position correspondence of the traffic police of the congested grade, and then transmitting the personnel information to a mobile equipment end needing to participate in supporting the traffic police.

A third aspect of the present invention provides a readable storage medium including therein an electric resource and traffic monitoring management method program of a digital city, which when executed by a processor, implements the steps of the electric resource and traffic monitoring management method of a digital city as described in any one of the above.

According to the electric resource and traffic monitoring management method, system and medium of the digital city, the electricity consumption population and the gas consumption population are respectively calculated and obtained through obtaining intelligent meter data and historical energy consumption statistical data of a preset area, the population of the preset area is further obtained through population calculation model processing, then free travel traffic tool data of the preset area is obtained, a bus stop demand index is obtained according to the free travel traffic tool data, the bus stop demand grade is obtained after comparison, the number of times of each demand grade of a bus stop which is evaluated at regular time in preset time is counted, and finally bus stop setting state information is obtained after comparison with a bus stop setting threshold value.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or optical disk, or the like, which can store program codes.

Or the above-described integrated units of the invention may be stored in a readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.

Claims (6)

1. A method for monitoring and managing electrical resources and traffic in a digital city, comprising:

Acquiring intelligent meter data of a preset area, wherein the intelligent meter data comprise intelligent ammeter data and intelligent gas meter data;

Acquiring historical energy consumption statistical data of a preset area, wherein the historical energy consumption statistical data comprise historical average power consumption data and historical average power consumption data;

Respectively obtaining the electricity consumption population and the gas consumption population according to the intelligent meter data and the historical energy consumption statistical data;

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

Acquiring free travel vehicle data of traffic monitoring of a preset area, wherein the free travel vehicle data comprise self-driving data and riding data;

Processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index, and comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

Acquiring the number of times of each demand level of the bus stop which is evaluated at regular time in a preset time period of a preset area, and comparing the number of times with a bus stop setting threshold value to acquire bus stop setting state information;

the intelligent meter data of the preset area is obtained, the intelligent meter data and the intelligent gas meter data are included, and the intelligent meter data specifically include:

Acquiring intelligent ammeter data and intelligent gas meter data of a preset area;

the intelligent ammeter data comprise intelligent ammeter initial electric quantity data, intelligent ammeter final electric quantity data and electric quantity statistics period time data;

The intelligent gas meter data comprise intelligent gas meter initial power data, intelligent gas meter termination power data and gas quantity statistics cycle time data;

The electricity consumption population and the gas consumption population are respectively obtained according to the intelligent meter data and the historical energy consumption statistical data, and the method specifically comprises the following steps:

calculating to obtain the electricity consumption personnel mouth number according to the historical electricity consumption per person data and the intelligent ammeter data;

Calculating according to the historical average gas consumption data and the intelligent gas meter data to obtain the gas consumption population;

The step of inputting the electricity consumption population and the gas consumption population into a preset regional population calculation model to obtain the preset regional population, specifically comprising the following steps:

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

the calculation formula of the population of the preset area is as follows:

Wherein R _k is regional population, D _r is electricity consumption population, Q _r is gas electricity consumption population, and alpha and beta are preset characteristic coefficients;

The processing is performed according to the population of the preset area and the data of the free travel vehicles to obtain a bus stop demand index, and the bus stop demand index is compared with a bus stop demand grade threshold to obtain a bus stop demand grade, which specifically comprises the following steps:

processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index;

comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

The bus stop demand level comprises strong demand, medium demand or weak demand, and the ranges corresponding to the bus stop demand degree indexes are as follows: [0.7,1], [0.5,0.7), [0, 0.5);

the calculation formula of the bus stop demand index is as follows:

wherein X _q is a bus stop demand index, J _c is self-driving data, Q _x is riding data, and delta, eta and lambda are preset characteristic coefficients.

2. The digital city electrical resource and traffic monitoring management method of claim 1, further comprising:

Acquiring power pipeline subsection information, gas pipeline distribution information and traffic road distribution information in a preset area;

Obtaining shared line distribution information according to the electric power pipeline subsection information, the gas pipeline distribution information and the traffic road distribution information;

Respectively acquiring finishing construction planning information of an electric pipeline, a gas pipeline and a traffic road;

Judging whether the finishing construction planning information is positioned in a shared line or not according to the finishing construction planning information, if so, synchronizing the finishing construction planning information to electric power, fuel gas and road authorities;

and the electric power, the fuel gas and the road authorities comprehensively stage the construction time according to the finishing construction planning information.

3. The digital city electrical resource and traffic monitoring management method of claim 2, further comprising:

acquiring power demand reference electric quantity information of a preset area;

Acquiring power demand influence factor information of a preset area, wherein the power demand influence factor information comprises weather temperature change data, old population proportion data and average income and expense ratio of living population;

Calculating according to the power demand influence factor information to obtain a power demand variation index;

correspondingly obtaining the power resource demand fluctuation according to the power demand reference electric quantity information and the power demand fluctuation index;

The power demand variation index calculation formula is as follows:

Wherein D _z is the power demand variation index, W _b is the weather temperature variation data, L _n is the aged population proportion data, S _z is the average income and expense ratio of the living population, Sigma and omega are preset characteristic coefficients.

4. The digital city electrical resource and traffic monitoring management method of claim 3, further comprising:

acquiring congestion information of a traffic congestion road section, wherein the congestion information comprises congestion duration data, congestion vehicle distance data and congestion vehicle data;

Inputting a congestion index calculation model according to the congestion information to obtain a congestion index;

comparing the congestion index with a preset congestion level threshold value to obtain a congestion level;

Acquiring traffic police position information around a congested road section;

Correspondingly obtaining support traffic police information according to the congestion index and the traffic police position information;

Transmitting the supporting traffic police information to a supporting traffic police mobile equipment end;

The congestion index calculation formula is as follows:

Wherein Y _z is a congestion index, Y _s is congestion duration data, Y _j is congestion vehicle distance data, Y _c is congestion vehicle data, Θ, ψ are preset feature coefficients.

5. The system for managing the electric resources and traffic monitoring of the digital city is characterized by comprising a memory and a processor, wherein the memory comprises a digital city electric resource and traffic monitoring management method program, and the digital city electric resource and traffic monitoring management method program realizes the following steps when being executed by the processor:

Acquiring intelligent meter data of a preset area, wherein the intelligent meter data comprise intelligent ammeter data and intelligent gas meter data;

Acquiring historical energy consumption statistical data of a preset area, wherein the historical energy consumption statistical data comprise historical average power consumption data and historical average power consumption data;

Respectively obtaining the electricity consumption population and the gas consumption population according to the intelligent meter data and the historical energy consumption statistical data;

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

Acquiring free travel vehicle data of traffic monitoring of a preset area, wherein the free travel vehicle data comprise self-driving data and riding data;

Processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index, and comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

Acquiring the number of times of each demand level of the bus stop which is evaluated at regular time in a preset time period of a preset area, and comparing the number of times with a bus stop setting threshold value to acquire bus stop setting state information;

the intelligent meter data of the preset area is obtained, the intelligent meter data and the intelligent gas meter data are included, and the intelligent meter data specifically include:

Acquiring intelligent ammeter data and intelligent gas meter data of a preset area;

the intelligent ammeter data comprise intelligent ammeter initial electric quantity data, intelligent ammeter final electric quantity data and electric quantity statistics period time data;

The intelligent gas meter data comprise intelligent gas meter initial power data, intelligent gas meter termination power data and gas quantity statistics cycle time data;

The electricity consumption population and the gas consumption population are respectively obtained according to the intelligent meter data and the historical energy consumption statistical data, and the method specifically comprises the following steps:

calculating to obtain the electricity consumption personnel mouth number according to the historical electricity consumption per person data and the intelligent ammeter data;

Calculating according to the historical average gas consumption data and the intelligent gas meter data to obtain the gas consumption population;

The step of inputting the electricity consumption population and the gas consumption population into a preset regional population calculation model to obtain the preset regional population, specifically comprising the following steps:

inputting the electricity consumption population and the air consumption population into a preset regional population calculation model to process to obtain a preset regional population;

the calculation formula of the population of the preset area is as follows:

Wherein R _k is regional population, D _r is electricity consumption population, Q _r is gas electricity consumption population, and alpha and beta are preset characteristic coefficients;

The processing is performed according to the population of the preset area and the data of the free travel vehicles to obtain a bus stop demand index, and the bus stop demand index is compared with a bus stop demand grade threshold to obtain a bus stop demand grade, which specifically comprises the following steps:

processing according to the population of the preset area and the free travel vehicle data to obtain a bus stop demand index;

comparing the bus stop demand index with a bus stop demand level threshold to obtain a bus stop demand level;

The bus stop demand level comprises strong demand, medium demand or weak demand, and the ranges corresponding to the bus stop demand degree indexes are as follows: [0.7,1], [0.5,0.7), [0, 0.5);

the calculation formula of the bus stop demand index is as follows:

wherein X _q is a bus stop demand index, J _c is self-driving data, Q _x is riding data, and delta, eta and lambda are preset characteristic coefficients.

6. A computer readable storage medium, characterized in that it comprises therein a digital city electrical resource and traffic monitoring management method program, which when executed by a processor, implements the steps of a digital city electrical resource and traffic monitoring management method according to any of claims 1 to 4.