CN114819423B - Carbon emission control system applying GIS technology and data information fusion system - Google Patents

Carbon emission control system applying GIS technology and data information fusion system Download PDF

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CN114819423B
CN114819423B CN202210756333.1A CN202210756333A CN114819423B CN 114819423 B CN114819423 B CN 114819423B CN 202210756333 A CN202210756333 A CN 202210756333A CN 114819423 B CN114819423 B CN 114819423B
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夏凤霞
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Nanjing Zhongxin Yunchuang Software Technology Co ltd
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Abstract

The invention discloses a carbon emission control system applying a GIS technology and a data information fusion system, and belongs to the technical field of carbon emission control. The system comprises a GIS data acquisition module, a regional supervision module, an archive storage module, a regional analysis module, an alarm module and a carbon emission control module; the output end of the GIS data acquisition module is connected with the input end of the region supervision module; the output end of the region supervision module is connected with the input end of the archive storage module; the output end of the archive storage module is connected with the input end of the area analysis module; the output end of the area analysis module is connected with the input end of the alarm module; and the output end of the alarm module is connected with the input end of the carbon emission control module. The method and the device can optimize the indexes of the domestic carbon emission in the area, accurately determine the carbon emission condition in the area, and generate corresponding carbon emission suggestions according to different carbon emission values.

Description

Carbon emission control system applying GIS technology and data information fusion system
Technical Field
The invention relates to the technical field of carbon emission control, in particular to a carbon emission control system applying a GIS technology and a data information fusion system.
Background
Human production and life use a large amount of fossil fuels, and a large amount of sulfur dioxide, nitrogen oxides, fine particulate matters and other atmospheric pollutants are discharged in the combustion and utilization process of the fossil fuels, so that the quality of environmental air is influenced; and simultaneously, carbon dioxide is discharged to accelerate the warming of the climate. In recent years, the energy consumption of China is continuously increased, the use amount of fossil fuels is increased year by year, so that a large amount of greenhouse gas and atmospheric pollutants are emitted, and in order to promote the cooperative emission reduction work of the greenhouse gas and the atmospheric pollutants, China proposes a double target of carbon peak reaching and carbon neutralization.
The GIS technology is based on geographic space, adopts a geographic model analysis method to provide various spatial and dynamic geographic information in real time, can display a range from an intercontinental map to a very detailed block map, and is an important technical means for researching an area, wherein real objects comprise population, sales condition, transportation line and other contents.
Disclosure of Invention
The invention aims to provide a carbon emission control system applying a GIS technology and a data information fusion system so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme:
the carbon emission control system applies the GIS technology and the data information fusion system, and comprises a GIS data acquisition module, a region supervision module, a file storage module, a region analysis module, an alarm module and a carbon emission control module;
the GIS data acquisition module is used for constructing a data acquisition area and acquiring personnel data and travel data in the area; the region supervision module is used for supervising and processing the personnel flow information in the data acquisition region; the archive storage module is used for constructing archive data and archiving personnel data and travel data in the data acquisition area for query; the region analysis module is used for constructing a data information fusion model and optimizing carbon emission indexes; the alarm module is used for monitoring the carbon emission in the data acquisition area in real time and sending alarm information data if the carbon emission exceeds a carbon emission index; the carbon emission treatment module is used for intelligently generating a carbon emission treatment suggestion after receiving the alarm information data;
the output end of the GIS data acquisition module is connected with the input end of the region supervision module; the output end of the area supervision module is connected with the input end of the archive storage module; the output end of the archive storage module is connected with the input end of the area analysis module; the output end of the area analysis module is connected with the input end of the alarm module; the output end of the alarm module is connected with the input end of the carbon emission control module.
According to the technical scheme, the GIS data acquisition module comprises an area construction unit, a personnel data acquisition unit and a trip data acquisition unit;
the area construction unit is used for constructing a data acquisition area, and the data acquisition area is a monitoring area set by the system; the personnel data acquisition unit is used for acquiring personnel flow data in the data acquisition area and marking the external person mouth; the travel data acquisition unit is used for acquiring travel data in the data acquisition area;
the output end of the region construction unit is connected with the input ends of the personnel data acquisition unit and the trip data acquisition unit; the output ends of the personnel data acquisition unit and the trip data acquisition unit are connected with the input end of the region supervision module.
According to the technical scheme, the region supervision module comprises a face snapshot unit, a face study and judgment unit and a database;
the face snapshot unit is used for setting a face recognition device in the data acquisition area, constructing time periods, carrying out face snapshot on the person entering and leaving in each time period, and recording images into the database; the face studying and judging unit is used for judging a regular population and an external population according to the stored data in the database; the database is used for storing personnel images in the data acquisition area, and the personnel images are house resident personnel images provided by house property owners in the data acquisition area;
the output end of the face snapshot unit is connected with the input end of the database; the output end of the database is connected with the input end of the face studying and judging unit;
the database comprises a storage unit and a newly-added unit;
the storage unit is used for storing personnel images in the data acquisition area; the newly added unit is used for newly adding personnel images in the data acquisition area;
the judgment process of the face studying and judging unit comprises the following steps:
acquiring face snapshot data under each time period, and inputting the face snapshot data into a face studying and judging unit according to a time sequence to compare the similarity:
Figure DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure 880515DEST_PATH_IMAGE002
representing the similarity of two groups of face images;
Figure 339179DEST_PATH_IMAGE003
any feature representing a face being recognized in the face snapshot data;
Figure 946877DEST_PATH_IMAGE004
any feature of a face representing an image of a person in a database;
Figure 264726DEST_PATH_IMAGE005
represents a serial number;
Figure 107917DEST_PATH_IMAGE006
representing a characteristic quantity;
setting a similarity threshold if any
Figure 562032DEST_PATH_IMAGE002
If the threshold value is exceeded, the comparison is successful; if any exist
Figure 465266DEST_PATH_IMAGE002
If the comparison fails, the image is transmitted to a newly added unit, and the next comparison is waited; if any face image comparison success times exceed in a fixed period
Figure 4832DEST_PATH_IMAGE007
Secondly, judging that the personnel is the permanent population, wherein the fixed period is the system setting,
Figure 651714DEST_PATH_IMAGE007
representing a threshold number of times.
In the technical scheme, the standing population and the foreign population are mainly analyzed, the flowing condition of the personnel can be effectively judged based on the face recognition of the personnel entering and exiting, and meanwhile, new personnel images are continuously added to the newly added units according to the time sequence, so that the comparison range is expanded, and the system accuracy is improved.
According to the technical scheme, the archive storage module comprises a personnel archive storage unit and a trip archive storage unit;
the personnel file storage unit is used for storing and recording the number of the permanent population in the data acquisition area;
the travel archive storage unit is used for storing travel modes in the recorded data acquisition area.
According to the technical scheme, the regional analysis module comprises a travel analysis unit, a data information fusion unit and a carbon emission index optimization unit;
the travel analysis unit is used for analyzing the travel frequency of the population in the region; the data information fusion unit is used for constructing a data information fusion model, analyzing and predicting a staged increasing trend of the standing population and a travel variation trend of the standing population; the carbon emission index optimizing unit is used for optimizing an original carbon emission index according to an analysis result of the data information fusion unit to generate a new carbon emission index;
the output end of the travel analysis unit is connected with the input end of the data information fusion unit; and the output end of the data information fusion unit is connected with the input end of the carbon emission index optimization unit.
According to the above technical solution, the data information fusion unit includes:
obtaining vehicle travel data, specifying travel data at T moment, representing travel times of any vehicle in a time range T, continuously collecting N groups of travel data at T moment, and establishing a data information fusion model under historical data:
Figure 225915DEST_PATH_IMAGE008
Figure DEST_PATH_IMAGE009
and (3) realizing an updating process by using Kalman filtering:
Figure 763032DEST_PATH_IMAGE010
Figure DEST_PATH_IMAGE011
Figure 117790DEST_PATH_IMAGE012
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE013
representing a system state matrix at the moment k, namely an estimated value in a prior state;
Figure 302784DEST_PATH_IMAGE014
represents
A state transition matrix; b represents a control input matrix; h represents a state observation matrix;
Figure DEST_PATH_IMAGE015
representing processing noise, wherein the noise is the difference between a processing model and an actual situation, such as vehicle traveling, and is influenced by external factors such as weather and road section restriction;
Figure 59387DEST_PATH_IMAGE016
representing the optimal state estimation value at the k-1 moment;
Figure DEST_PATH_IMAGE017
representing the optimal state estimation value at the moment k;
Figure 38845DEST_PATH_IMAGE018
representing a Kalman gain matrix;
Figure 553003DEST_PATH_IMAGE019
representing the covariance between the true and predicted values;
Figure 541687DEST_PATH_IMAGE020
representing the covariance between the true value and the optimal state estimate;
Figure 559322DEST_PATH_IMAGE021
a covariance representing process noise; r represents the covariance of the measurement noise;
Figure 240839DEST_PATH_IMAGE022
representing the measured value of the system state.
According to the above technical solution, the carbon emission index optimizing unit includes:
obtaining the optimal state estimation value at the k moment
Figure 242293DEST_PATH_IMAGE017
The predicted running number value at the moment k of the vehicle is used as the predicted running number value;
constructing a vehicle travel time threshold, and if the predicted travel time value at the vehicle k moment is lower than the vehicle travel time threshold, judging that the vehicle is in an unusual vehicle condition, namely, uniformly classifying the vehicle into a 'corpse vehicle' condition;
counting the number of vehicles belonging to the condition of the unusual vehicles, wherein the number is L, and then:
Figure 910035DEST_PATH_IMAGE023
wherein the content of the first and second substances,
Figure 906810DEST_PATH_IMAGE024
represents an optimized index of carbon emission;
Figure 634594DEST_PATH_IMAGE025
representing the index of the carbon emission of the original plan;
Figure 982399DEST_PATH_IMAGE026
represents a first adjustment factor;
Figure 188252DEST_PATH_IMAGE027
representing the number of the population judged as a standing population;
Figure 305113DEST_PATH_IMAGE028
representsThe number of the human mouths in the newly added unit;
Figure DEST_PATH_IMAGE029
representing the number of registered population in the data collection area;
Figure 62853DEST_PATH_IMAGE030
representing the second adjustment factor.
According to the technical scheme, the alarm module comprises an alarm judgment unit and a notification unit;
the alarm judging unit is used for setting an alarm threshold according to the optimized carbon emission index, generating an alarm instruction after the carbon emission exceeds the alarm threshold, and transmitting the alarm instruction to the notification unit; the notification unit is used for feeding the alarm instruction back to the system in an information form, and system workers click to check and accept;
the output end of the alarm judging unit is connected with the input end of the informing unit, and the output end of the informing unit is connected with the input end of the carbon emission control module.
According to the technical scheme, the carbon emission control module comprises an alarm analysis unit and a suggestion unit;
the alarm analysis unit is used for acquiring the carbon emission exceeding value, analyzing the carbon emission exceeding value and generating a carbon emission control suggestion; the suggestion unit is used for outputting carbon emission treatment suggestions.
According to the technical scheme, the carbon emission control suggestion comprises the following steps:
acquiring a carbon emission exceeding value, setting a carbon emission exceeding value threshold, and generating a first carbon emission control suggestion when the carbon emission exceeding value exceeds the carbon emission exceeding value threshold; when the carbon emission exceeding value does not exceed the carbon emission exceeding value threshold, generating a second carbon emission control suggestion;
the first carbon emission control suggestion is a suggestion for implementing route management and control and a single-double restriction policy;
the second carbon emission control suggestion is a suggestion for adjusting the number of new energy charging devices and improving the utilization rate of new energy vehicles;
adjusting the number of new energy charging devices comprises:
acquiring the number of new energy vehicles and the number of new energy charging devices in any region, and constructing a linear function relation;
the trend prediction equation is established as follows:
Figure 507741DEST_PATH_IMAGE031
wherein the content of the first and second substances,
Figure 641919DEST_PATH_IMAGE032
representing the number of new energy charging devices at the current earlier stage, corresponding
Figure 754232DEST_PATH_IMAGE033
Representing the number of new energy vehicles at the current earlier stage;
Figure 682873DEST_PATH_IMAGE034
is the cycle length;
Figure 146216DEST_PATH_IMAGE035
is as follows
Figure 693872DEST_PATH_IMAGE036
Predicted value of period, representing linear increase in number of new energy charging devices
Figure 785325DEST_PATH_IMAGE036
Predicting the number of new energy vehicles after the period;
Figure 760234DEST_PATH_IMAGE037
is a first
Figure 569927DEST_PATH_IMAGE032
Smoothing the estimated level of the phase;
Figure 186853DEST_PATH_IMAGE038
is as follows
Figure 132812DEST_PATH_IMAGE032
Smoothing the predicted trend of the period;
Figure 544202DEST_PATH_IMAGE039
is a first
Figure 581471DEST_PATH_IMAGE032
The predicted season of the season is smooth;
constructing an adjusting range:
Figure 470930DEST_PATH_IMAGE040
wherein E represents a carbon emission excess value;
Figure 536975DEST_PATH_IMAGE041
representing the maximum difference of carbon emission values after the new energy vehicle replaces the fuel vehicle;
Figure 853687DEST_PATH_IMAGE042
the minimum difference distance of the carbon emission values of the new energy vehicle after replacing the fuel vehicle;
in that
Figure 372393DEST_PATH_IMAGE035
When satisfying the control range, calculate and draw h, according to h generation second carbon row and administer the suggestion, adjust new forms of energy charging device quantity.
Compared with the prior art, the invention has the following beneficial effects:
the method comprises the steps of constructing a data acquisition area by using a GIS data acquisition module, and acquiring personnel data and travel data in the area; monitoring and processing the personnel flow information in the data acquisition area by using an area monitoring module; establishing archive data by using an archive storage module, and archiving personnel data and travel data in a data acquisition area for query; a data information fusion model is constructed by using a region analysis module, and carbon emission indexes are optimized; monitoring the carbon emission in the data acquisition area in real time by using an alarm module, and sending alarm information data if the carbon emission exceeds a carbon emission index; after the carbon emission control module receives the alarm information data, a carbon emission treatment suggestion is generated intelligently; the method can optimize the domestic carbon emission indexes in the region, reduce the weight of 'zombie cars', 'empty rooms' and the like in the carbon emission indexes, accurately determine the carbon emission condition in the region, and generate corresponding carbon emission suggestions according to different carbon emission values.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow diagram of a carbon emission control system using a GIS technology and a data information fusion system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious 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.
Referring to fig. 1, in the present embodiment: the system comprises a GIS data acquisition module, a region supervision module, a file storage module, a region analysis module, an alarm module and a carbon emission control module;
the GIS data acquisition module is used for constructing a data acquisition area, and acquiring personnel data and travel data in the area; the region supervision module is used for supervising and processing the personnel flow information in the data acquisition region; the archive storage module is used for constructing archive data and archiving personnel data and travel data in the data acquisition area for query; the region analysis module is used for constructing a data information fusion model and optimizing carbon emission indexes; the alarm module is used for monitoring the carbon emission in the data acquisition area in real time and sending alarm information data if the carbon emission exceeds a carbon emission index; the carbon emission treatment module is used for intelligently generating a carbon emission treatment suggestion after receiving the alarm information data;
the output end of the GIS data acquisition module is connected with the input end of the region supervision module; the output end of the region supervision module is connected with the input end of the archive storage module; the output end of the archive storage module is connected with the input end of the area analysis module; the output end of the area analysis module is connected with the input end of the alarm module; the output end of the alarm module is connected with the input end of the carbon emission control module.
In this embodiment, taking a certain cell as an example: the data acquisition area is the cell; a region supervision module is arranged at the doorway of the community;
the region supervision module comprises a face snapshot unit, a face study and judgment unit and a database;
the face snapshot unit is used for setting a face recognition device in the data acquisition area, constructing time periods, carrying out face snapshot on the person entering and leaving in each time period, and recording images into the database; the face studying and judging unit is used for judging a regular living population and an external population according to the stored data in the database; the database is used for storing personnel images in the data acquisition area, and the personnel images are house resident images provided by house property persons in the data acquisition area;
the output end of the face snapshot unit is connected with the input end of the database; the output end of the database is connected with the input end of the face studying and judging unit;
the database comprises a storage unit and a newly-added unit;
the storage unit is used for storing personnel images in the data acquisition area; the newly added unit is used for newly adding personnel images in the data acquisition area;
the judgment process of the face studying and judging unit comprises the following steps:
acquiring face snapshot data under each time period, and inputting the face snapshot data into a face studying and judging unit according to a time sequence to compare the similarity:
Figure 331121DEST_PATH_IMAGE001
wherein, the first and the second end of the pipe are connected with each other,
Figure 127039DEST_PATH_IMAGE002
representing the similarity of two groups of face images;
Figure 4865DEST_PATH_IMAGE003
any feature representing a face being recognized in the face snapshot data;
Figure 886234DEST_PATH_IMAGE004
any feature of a face representing an image of a person in a database;
Figure 242129DEST_PATH_IMAGE005
represents a serial number;
Figure 158132DEST_PATH_IMAGE006
representing a characteristic quantity;
setting a similarity threshold if any
Figure 206859DEST_PATH_IMAGE002
If the threshold value is exceeded, the comparison is successful; if any exist
Figure 575524DEST_PATH_IMAGE002
If the comparison fails, the image is transmitted to a newly added unit, and the next comparison is waited; if any face image comparison success times exceed in a fixed period
Figure 735110DEST_PATH_IMAGE007
Secondly, judging that the personnel is the permanent population, wherein the fixed period is the system setting,
Figure 240040DEST_PATH_IMAGE007
representing a threshold number of times.
The file storage module comprises a personnel file storage unit and a trip file storage unit;
the personnel file storage unit is used for storing and recording the number of the permanent population in the data acquisition area;
the travel archive storage unit is used for storing travel modes in the recorded data acquisition area.
The regional analysis module comprises a trip analysis unit, a data information fusion unit and a carbon emission index optimization unit;
the travel analysis unit is used for analyzing the travel frequency of the population in the region; the data information fusion unit is used for constructing a data information fusion model, analyzing and predicting a staged population living increasing trend and a travel variation trend of the population living; the carbon emission index optimizing unit is used for optimizing the original carbon emission index according to the analysis result of the data information fusion unit to generate a new carbon emission index;
the output end of the travel analysis unit is connected with the input end of the data information fusion unit; and the output end of the data information fusion unit is connected with the input end of the carbon emission index optimization unit.
The data information fusion unit includes:
obtaining vehicle travel data, specifying travel data at T moment, representing travel times of any vehicle in a time range T, continuously collecting N groups of travel data at T moment, and establishing a data information fusion model under historical data:
Figure 459669DEST_PATH_IMAGE008
Figure 315630DEST_PATH_IMAGE009
and (3) realizing an updating process by using Kalman filtering:
Figure 154273DEST_PATH_IMAGE010
Figure 903923DEST_PATH_IMAGE011
Figure 169819DEST_PATH_IMAGE012
wherein, the first and the second end of the pipe are connected with each other,
Figure 372130DEST_PATH_IMAGE013
representing a system state matrix at the moment k, namely an estimated value in a prior state;
Figure 14464DEST_PATH_IMAGE014
represents
A state transition matrix; b represents a control input matrix; h represents a state observation matrix;
Figure 884200DEST_PATH_IMAGE015
representing processing noise;
Figure 320998DEST_PATH_IMAGE016
representing the optimal state estimation value at the k-1 moment;
Figure 10605DEST_PATH_IMAGE017
representing the optimal state estimation value at the moment k;
Figure 925472DEST_PATH_IMAGE018
representing a Kalman gain matrix;
Figure 649714DEST_PATH_IMAGE019
representing the covariance between the true and predicted values;
Figure 522992DEST_PATH_IMAGE020
representing the covariance between the true value and the optimal state estimate;
Figure 575262DEST_PATH_IMAGE021
a covariance representing process noise; r represents the covariance of the measurement noise;
Figure 418453DEST_PATH_IMAGE022
representing the measured value of the system state.
The carbon emission index optimizing unit includes:
obtaining the optimal state estimation value at the k moment
Figure 872568DEST_PATH_IMAGE017
The predicted running number value at the moment k of the vehicle is used as the predicted running number value;
constructing a vehicle travel time threshold, and if the predicted travel time value at the vehicle k moment is lower than the vehicle travel time threshold, judging that the vehicle is in a condition of not using the vehicle frequently;
counting the number of vehicles belonging to the condition of the unusual vehicles, wherein the number is L, and then:
Figure 41381DEST_PATH_IMAGE023
wherein the content of the first and second substances,
Figure 580947DEST_PATH_IMAGE024
represents an optimized index of domestic carbon emission;
Figure 227829DEST_PATH_IMAGE025
representing the carbon emission index of the original plan life;
Figure 536450DEST_PATH_IMAGE026
represents a first adjustment factor;
Figure 751531DEST_PATH_IMAGE027
representing the number of the population judged as a standing population;
Figure 655026DEST_PATH_IMAGE028
representing the number of the human mouths in the newly added unit;
Figure 980965DEST_PATH_IMAGE029
representing the number of registered population in the data collection area;
Figure 268727DEST_PATH_IMAGE030
representing the second adjustment factor.
The living carbon emission index generally comprises two major aspects of population and trip, and the current statistics adopts the registered population number, the actual vehicle data is subjected to average statistics, and the carbon emission index is set; in practical situations, the situations of vacant rooms, renting, zombie cars and the like are not taken into consideration, which leads to the situation that the carbon emission exceeds the standard in the area, but still stays in the index, so in the embodiment, the two situations are fully considered.
The alarm module comprises an alarm judging unit and a notification unit;
the alarm judging unit is used for setting an alarm threshold value according to the optimized carbon emission index, generating an alarm instruction after the carbon emission exceeds the alarm threshold value, and transmitting the alarm instruction to the notification unit; the notification unit is used for feeding the alarm instruction back to the system in an information form, and system workers click to check and accept;
the output end of the alarm judging unit is connected with the input end of the informing unit, and the output end of the informing unit is connected with the input end of the carbon emission control module.
The carbon emission control module comprises an alarm analysis unit and a suggestion unit;
the alarm analysis unit is used for acquiring the carbon emission exceeding value, analyzing the carbon emission exceeding value and generating a carbon emission control suggestion; the suggestion unit is used for outputting carbon emission treatment suggestions.
The carbon emission control recommendation comprises:
acquiring a carbon emission exceeding value, setting a carbon emission exceeding value threshold, and generating a first carbon emission control suggestion when the carbon emission exceeding value exceeds the carbon emission exceeding value threshold; when the carbon emission exceeding value does not exceed the carbon emission exceeding value threshold, generating a second carbon emission control suggestion;
the first carbon emission control suggestion is a suggestion for implementing route management and control and a single-double restriction policy;
the second carbon emission control suggestion is a suggestion for adjusting the number of new energy charging devices and improving the utilization rate of new energy vehicles;
adjusting the number of new energy charging devices comprises:
acquiring the number of new energy vehicles and the number of new energy charging devices in any region, and constructing a linear function relation;
the trend prediction equation is established as follows:
Figure 389129DEST_PATH_IMAGE043
wherein the content of the first and second substances,
Figure 27921DEST_PATH_IMAGE032
representing the number of new energy charging devices at the current earlier stage, corresponding
Figure 891972DEST_PATH_IMAGE033
Representing the number of new energy vehicles at the current earlier stage;
Figure 34240DEST_PATH_IMAGE034
is the cycle length;
Figure 856703DEST_PATH_IMAGE035
is as follows
Figure 717211DEST_PATH_IMAGE036
Predicted value of period, representing linear increase in number of new energy charging devices
Figure 119374DEST_PATH_IMAGE036
Predicting the number of new energy vehicles after the period;
Figure 381728DEST_PATH_IMAGE037
is as follows
Figure 109512DEST_PATH_IMAGE032
Smoothing the estimated level of the phase;
Figure 191738DEST_PATH_IMAGE038
is as follows
Figure 663171DEST_PATH_IMAGE032
Smoothing the predicted trend of the period;
Figure 780031DEST_PATH_IMAGE039
is as follows
Figure 413138DEST_PATH_IMAGE032
The predicted season of the season is smooth;
wherein the horizontal smoothing equation is:
Figure 389184DEST_PATH_IMAGE044
the trend smoothing equation is:
Figure 523362DEST_PATH_IMAGE045
the seasonal smoothing equation is:
Figure 370095DEST_PATH_IMAGE046
Figure 564316DEST_PATH_IMAGE047
a smoothing parameter that is horizontal;
Figure 496500DEST_PATH_IMAGE048
a smoothing parameter that is a trend;
Figure 434369DEST_PATH_IMAGE049
is a smoothing parameter of the season.
Constructing an adjusting range:
Figure 666768DEST_PATH_IMAGE050
wherein E represents a carbon emission excess value;
Figure 766311DEST_PATH_IMAGE041
representing the maximum difference of carbon emission values after the new energy vehicle replaces the fuel vehicle;
Figure 451370DEST_PATH_IMAGE042
the minimum difference distance of the carbon emission values of the new energy vehicle after replacing the fuel vehicle;
in that
Figure 927351DEST_PATH_IMAGE035
When the adjustment range is met, h is obtained through calculation, a second carbon emission control suggestion is generated according to h, and the number of the new energy charging devices is adjusted.
Using MATLAB software to simulate and generate the product meeting the regulation range
Figure 748676DEST_PATH_IMAGE035
Calculating the existence according to the linear growth rule of the number of the new energy charging devices
Figure 19120DEST_PATH_IMAGE035
The number of the new energy charging devices required by the new energy automobile generates a second carbon emission control suggestion, and new energy development is encouraged.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described above, or equivalents may be substituted for elements thereof. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (7)

1. Use GIS technique and data information fusion system's carbon emission control system, its characterized in that: the system comprises a GIS data acquisition module, a region supervision module, a file storage module, a region analysis module, an alarm module and a carbon emission control module;
the GIS data acquisition module is used for constructing a data acquisition area, and acquiring personnel data and travel data in the area; the region supervision module is used for supervising and processing the personnel flow information in the data acquisition region; the archive storage module is used for constructing archive data and archiving personnel data and travel data in the data acquisition area for query; the region analysis module is used for constructing a data information fusion model and optimizing carbon emission indexes; the alarm module is used for monitoring the carbon emission in the data acquisition area in real time and sending alarm information data if the carbon emission exceeds a carbon emission index; the carbon emission treatment module is used for intelligently generating carbon emission treatment suggestions after receiving the alarm information data;
the output end of the GIS data acquisition module is connected with the input end of the region supervision module; the output end of the region supervision module is connected with the input end of the archive storage module; the output end of the archive storage module is connected with the input end of the area analysis module; the output end of the area analysis module is connected with the input end of the alarm module; the output end of the alarm module is connected with the input end of the carbon emission control module;
the regional analysis module comprises a trip analysis unit, a data information fusion unit and a carbon emission index optimization unit;
the travel analysis unit is used for analyzing the travel frequency of the population in the region; the data information fusion unit is used for constructing a data information fusion model, analyzing and predicting a staged population living increasing trend and a travel variation trend of the population living; the carbon emission index optimizing unit is used for optimizing an original carbon emission index according to an analysis result of the data information fusion unit to generate a new carbon emission index;
the output end of the travel analysis unit is connected with the input end of the data information fusion unit; the output end of the data information fusion unit is connected with the input end of the carbon emission index optimization unit;
the data information fusion unit includes:
obtaining vehicle travel data, specifying travel data at T moment, representing travel times of any vehicle in a time range T, continuously collecting N groups of travel data at T moment, and establishing a data information fusion model under historical data:
Figure 413296DEST_PATH_IMAGE001
Figure 799278DEST_PATH_IMAGE002
and (3) realizing an updating process by using Kalman filtering:
Figure 906911DEST_PATH_IMAGE003
Figure 770962DEST_PATH_IMAGE004
Figure 178810DEST_PATH_IMAGE005
wherein the content of the first and second substances,
Figure 470114DEST_PATH_IMAGE006
representing a system state matrix at the moment k, namely an estimated value in a prior state;
Figure 330622DEST_PATH_IMAGE007
represents a state transition matrix; b represents a control input matrix; h represents a state observation matrix;
Figure 263943DEST_PATH_IMAGE008
representing processing noise;
Figure 526297DEST_PATH_IMAGE009
representing the optimal state estimation value at the k-1 moment;
Figure 988503DEST_PATH_IMAGE010
representing the optimal state estimation value at the moment k;
Figure 336307DEST_PATH_IMAGE011
representing a Kalman gain matrix;
Figure 542161DEST_PATH_IMAGE012
representing the covariance between the true and predicted values;
Figure 659021DEST_PATH_IMAGE013
representing the covariance between the true value and the optimal state estimate;
Figure 823286DEST_PATH_IMAGE014
a covariance representing process noise; r represents the covariance of the measurement noise;
Figure 533753DEST_PATH_IMAGE015
representing the measured value of the system state;
the carbon emission index optimizing unit includes:
obtaining the optimal state estimation value at the k moment
Figure 136773DEST_PATH_IMAGE010
The predicted running number value at the moment k of the vehicle is used as the predicted running number value;
constructing a vehicle travel time threshold, and if the predicted travel time value at the vehicle k moment is lower than the vehicle travel time threshold, judging that the vehicle is in an unusual vehicle condition;
counting the number of vehicles belonging to the condition of the unusual vehicles, wherein the number is L, and then:
Figure 373719DEST_PATH_IMAGE016
wherein the content of the first and second substances,
Figure 177727DEST_PATH_IMAGE017
represents an optimized index of domestic carbon emission;
Figure 500124DEST_PATH_IMAGE018
representing the carbon emission index of the original plan life;
Figure 47780DEST_PATH_IMAGE019
represents a first adjustment factor;
Figure 156811DEST_PATH_IMAGE020
representing the number of the population judged as a standing population;
Figure 397300DEST_PATH_IMAGE021
representing the number of the human mouths in the newly added unit;
Figure 941413DEST_PATH_IMAGE022
representing the number of registered population in the data collection area;
Figure 558340DEST_PATH_IMAGE023
representing the second adjustment factor.
2. The carbon emission control system applying the GIS technology and the data information fusion system according to claim 1, characterized in that: the GIS data acquisition module comprises an area construction unit, a personnel data acquisition unit and a trip data acquisition unit;
the area construction unit is used for constructing a data acquisition area, and the data acquisition area is a monitoring area set by the system; the personnel data acquisition unit is used for acquiring personnel flow data in the data acquisition area and marking the external person mouth; the travel data acquisition unit is used for acquiring travel data in the data acquisition area;
the output end of the region construction unit is connected with the input ends of the personnel data acquisition unit and the trip data acquisition unit; the output ends of the personnel data acquisition unit and the trip data acquisition unit are connected with the input end of the region supervision module.
3. The carbon emission control system applying the GIS technology and the data information fusion system according to claim 2, wherein: the region supervision module comprises a face snapshot unit, a face study and judgment unit and a database;
the face snapshot unit is used for arranging a face recognition device in the data acquisition area,
constructing time periods, carrying out face snapshot on the person entering and leaving in each time period, and recording images into a database; the face studying and judging unit is used for judging a regular population and an external population according to the stored data in the database; the database is used for storing personnel images in the data acquisition area, and the personnel images are house resident images provided by house property persons in the data acquisition area;
the output end of the face snapshot unit is connected with the input end of the database; the output end of the database is connected with the input end of the face studying and judging unit;
the database comprises a storage unit and a newly-added unit;
the storage unit is used for storing personnel images in the data acquisition area; the newly-added unit is used for newly adding personnel images in the data acquisition area;
the judgment process of the face studying and judging unit comprises the following steps:
acquiring face snapshot data under each time period, inputting the face snapshot data into a face study and judgment unit according to a time sequence to compare the similarity:
Figure 379665DEST_PATH_IMAGE024
wherein, the first and the second end of the pipe are connected with each other,
Figure 915689DEST_PATH_IMAGE025
representing the similarity of two groups of face images;
Figure 822465DEST_PATH_IMAGE026
any feature representing a face being recognized in the face snapshot data;
Figure 836557DEST_PATH_IMAGE027
any feature of a face representing an image of a person in a database;
Figure 777968DEST_PATH_IMAGE028
represents a serial number;
Figure 484893DEST_PATH_IMAGE029
representing the number of features;
setting a similarity threshold if any
Figure 878965DEST_PATH_IMAGE025
If the threshold value is exceeded, the comparison is successful; if any exist
Figure 696749DEST_PATH_IMAGE025
If the comparison fails, the image is transmitted to a newly added unit, and the next comparison is waited; if any face image comparison success times exceed in a fixed period
Figure 227087DEST_PATH_IMAGE030
Secondly, judging that the personnel is the permanent population, wherein the fixed period is the system setting,
Figure 104913DEST_PATH_IMAGE030
representing a threshold number of times.
4. The carbon emission control system applying the GIS technology and the data information fusion system according to claim 3, wherein: the file storage module comprises a personnel file storage unit and a trip file storage unit;
the personnel file storage unit is used for storing and recording the number of the permanent population in the data acquisition area;
the travel archive storage unit is used for storing travel modes in the recorded data acquisition area.
5. The carbon emission control system applying the GIS technology and the data information fusion system according to claim 4, wherein: the alarm module comprises an alarm judging unit and a notification unit;
the alarm judging unit is used for setting an alarm threshold according to the optimized carbon emission index, generating an alarm instruction after the carbon emission exceeds the alarm threshold, and transmitting the alarm instruction to the notification unit; the notification unit is used for feeding the alarm instruction back to the system in an information form, and system workers click to check and accept;
the output end of the alarm judging unit is connected with the input end of the informing unit, and the output end of the informing unit is connected with the input end of the carbon emission control module.
6. The carbon emission control system applying the GIS technology and the data information fusion system according to claim 5, wherein: the carbon emission control module comprises an alarm analysis unit and a suggestion unit;
the alarm analysis unit is used for acquiring the carbon emission exceeding value, analyzing the carbon emission exceeding value and generating a carbon emission control suggestion; the suggestion unit is used for outputting carbon emission treatment suggestions.
7. The carbon emission control system applying the GIS technology and the data information fusion system according to claim 6, wherein: the carbon emission control recommendation comprises:
acquiring a carbon emission exceeding value, setting a carbon emission exceeding value threshold, and generating a first carbon emission control suggestion when the carbon emission exceeding value exceeds the carbon emission exceeding value threshold; when the carbon emission exceeding value does not exceed the carbon emission exceeding value threshold, generating a second carbon emission control suggestion;
the first carbon emission control suggestion is a suggestion for implementing route management and control and a single-double restriction policy;
the second carbon emission control suggestion is a suggestion for adjusting the number of new energy charging devices and improving the utilization rate of new energy vehicles;
adjusting the number of new energy charging devices comprises:
acquiring the number of new energy vehicles and the number of new energy charging devices in any region, and constructing a linear function relation;
the trend prediction equation is established as follows:
Figure 986282DEST_PATH_IMAGE031
wherein, the first and the second end of the pipe are connected with each other,
Figure 607756DEST_PATH_IMAGE032
representing the number of new energy charging devices at the current earlier stage, corresponding
Figure 258180DEST_PATH_IMAGE033
Representing the number of new energy vehicles at the current earlier stage;
Figure 41328DEST_PATH_IMAGE034
is the cycle length;
Figure 675572DEST_PATH_IMAGE035
is as follows
Figure 835158DEST_PATH_IMAGE036
Predicted value of period, representing linear increase in number of new energy charging devices
Figure 605668DEST_PATH_IMAGE036
Predicting the number of new energy vehicles after the period;
Figure 559717DEST_PATH_IMAGE037
is as follows
Figure 681257DEST_PATH_IMAGE032
Smoothing the estimated level of the phase;
Figure 519900DEST_PATH_IMAGE038
is as follows
Figure 3971DEST_PATH_IMAGE032
Smoothing the predicted trend of the period;
Figure 269867DEST_PATH_IMAGE039
is as follows
Figure 472179DEST_PATH_IMAGE032
The predicted season of the season is smooth;
constructing an adjusting range:
Figure 114512DEST_PATH_IMAGE040
wherein E represents a carbon emission excess value;
Figure 718669DEST_PATH_IMAGE041
representing the maximum difference of carbon emission values after the new energy vehicle replaces the fuel vehicle;
Figure 155467DEST_PATH_IMAGE042
the minimum difference distance of the carbon emission values of the new energy vehicle after replacing the fuel vehicle;
in that
Figure 845074DEST_PATH_IMAGE035
When satisfying the control range, calculate and draw h, according to h generation second carbon row and administer the suggestion, adjust new forms of energy charging device quantity.
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