CN115687936A - Intelligent module area address selection method and device - Google Patents
Intelligent module area address selection method and device Download PDFInfo
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- CN115687936A CN115687936A CN202110825041.4A CN202110825041A CN115687936A CN 115687936 A CN115687936 A CN 115687936A CN 202110825041 A CN202110825041 A CN 202110825041A CN 115687936 A CN115687936 A CN 115687936A
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Abstract
The invention provides an intelligent module area address selection method and device, which comprise the following steps: acquiring an intelligent module set to be selected and a grid set of an area to be addressed; determining an environment characteristic index and a people stream characteristic index of a first grid in the grid set based on the grid set; determining a module characteristic index of a first intelligent module in the intelligent module set corresponding to the first grid according to the environment characteristic index, the people stream characteristic index and the intelligent module set of the first grid; and determining a target intelligent module of the area to be addressed according to the module characteristic index, the environment characteristic index and the people stream characteristic index. The intelligent module area site selection method and the intelligent module area site selection device respectively consider the intelligent module and the matching degree between the intelligent module and the intelligent module from the two angles of the environment and the people stream of an area scene, and ensure the rationality of intelligent building site selection; and the reliability and the accuracy of the data are ensured by applying a principal component analysis method; and the site selection efficiency is improved.
Description
Technical Field
The invention relates to the field of big data, in particular to an intelligent module area address selecting method and device.
Background
In the current internet of things era of everything interconnection, the acquisition of regional data does not rely on the measurement of a software and hardware system at the cloud end, and a sensing terminal of an intelligent building can also undertake data preprocessing, operation and simple decision, so that the location position of the intelligent building is determined to be the primary decision requirement in the construction of a smart city in order to collect and analyze regional effective data more accurately.
In the prior art, the site selection position of an intelligent building mainly considers two aspects, including construction requirements and limiting conditions, wherein the construction requirements only consider the objective environment of site selection, and the human factors such as human flow and the like are not sufficiently emphasized; the limiting conditions are mainly the consideration analysis of the relation between intelligent buildings, the consideration analysis can only solve the problem of site selection of the intelligent building cluster mode, and an effective analysis means is difficult to provide for the non-cluster mode.
Therefore, how to more comprehensively consider and determine the site selection position of the intelligent building is a problem to be solved urgently.
Disclosure of Invention
In view of the above drawbacks of the prior art, an object of the present invention is to provide an intelligent module area location method and apparatus, which are used to solve the problem that the location of an intelligent building cannot be fully considered and determined in the prior art.
In order to achieve the above objects and other related objects, the present invention provides a method and an apparatus for intelligent module area address selection, comprising the steps of: acquiring an intelligent module set to be selected and a grid set of an area to be addressed; determining an environment characteristic index and a people stream characteristic index of a first grid in the grid set based on the grid set; the first grid is any grid in the grid set; determining module characteristic indexes of a first intelligent module in the intelligent module set corresponding to the first grid according to the environment characteristic indexes and the people stream characteristic indexes of the first grid and the intelligent module set; the first intelligent module is any intelligent module in the intelligent module set; and determining a target intelligent module of the area to be addressed according to the module characteristic index, the environment characteristic index and the people stream characteristic index.
In an embodiment of the present invention, the intelligent module set includes modules that use building energy consumption values of different energy sources; the grid set is determined according to a preset division rule based on the area to be selected.
In an embodiment of the present invention, the environmental characteristic indicators include area, ground depth, geographic location, energy information, and interest point information; the people flow characteristic indexes comprise people flow rate level, interest degree of people in the area, people consumption level and people consumption tendency.
In an embodiment of the present invention, the module characteristic indicators include an energy characteristic indicator, a cost characteristic indicator and a revenue characteristic indicator; the determining, according to the environment characteristic index, the people flow characteristic index, and the intelligent module set of the first grid, a module characteristic index of a first intelligent module in the intelligent module set corresponding to the first grid includes: according to the environmental characteristic index of the first grid and the building energy consumption value of the first intelligent module, applying a preset statistical rule to determine an energy characteristic index of the first intelligent module corresponding to the first grid; according to the people stream characteristic index of the first grid and the first intelligent module, applying a preset cost measurement rule to determine a cost characteristic index of the first intelligent module corresponding to the first grid; and according to the environment characteristic index of the first grid, the people flow characteristic index of the first grid and the first intelligent module, applying a preset releasing and collecting rule to determine the collecting and collecting characteristic index of the first intelligent module corresponding to the first grid.
In an embodiment of the present invention, the determining a target intelligent module of a to-be-addressed area according to the module characteristic index, the environment characteristic index, and the people stream characteristic index includes: according to the module characteristic indexes and the environment characteristic indexes, a preset module and environment matching evaluation rule is applied to determine a first matching degree of each index in the module characteristic indexes and each index in the environment characteristic indexes; according to the module characteristic indexes and the people stream characteristic indexes, a preset module and people stream matching evaluation rule is applied to determine a second matching degree of each index in the module characteristic indexes and each index in the people stream characteristic indexes; according to the first matching degree and the second matching degree, determining the environment matching degree of the first intelligent module and the first grid and the people stream matching degree of the first intelligent module and the first grid by applying a principal component analysis method; and traversing the intelligent module set and the grid set according to the environment matching degree and the people flow matching degree, and determining a target intelligent module of the area to be addressed.
In an embodiment of the present invention, the dividing rule is to determine interval information of the to-be-addressed area according to a preset relationship between density and interval of the to-be-addressed area; and dividing the area to be addressed into grids at equal intervals according to the interval information.
Correspondingly, the invention provides an intelligent module area addressing device, which comprises: the acquisition module is used for acquiring an intelligent module set to be selected and a grid set of an area to be addressed; the first processing module is used for determining an environment characteristic index and a people flow characteristic index of a first grid in the grid set based on the grid set; the first grid is any grid in the grid set; the second processing module is used for determining the module characteristic indexes of the first intelligent module in the intelligent module set corresponding to the first grid according to the environment characteristic indexes, the people flow characteristic indexes and the intelligent module set of the first grid; the first intelligent module is any intelligent module in the intelligent module set; and the determining module is used for determining the target intelligent module of the area to be addressed according to the module characteristic index, the environment characteristic index and the people stream characteristic index.
In an embodiment of the invention, the intelligent module set includes modules of building energy consumption values using different energy sources; the grid set is determined according to a preset division rule based on the area to be addressed.
The present invention provides a storage medium having stored thereon a computer program which, when executed by a processor, implements the intelligent module area addressing method described above.
The invention provides a regional addressing platform, which comprises a memory, a first data storage and a second data storage, wherein the memory is used for storing a computer program; and the processor is used for operating the computer program to realize the intelligent module area addressing method.
As described above, the intelligent module area address selecting method and device of the present invention have the following beneficial effects:
(1) In the site selection process, from the two aspects of environment and people flow of an area scene, the intelligent modules and the matching degree between the intelligent modules and people flow are respectively considered, so that the intelligent building can effectively obtain a reasonable site selection position no matter in a cluster mode or a non-cluster mode.
(2) And in the aspect of processing the matching degree between the intelligent module and the environment and the human flow, the reliability and the accuracy of the data are ensured by applying a principal component analysis method.
(3) The site selection time can be shortened, and the site selection efficiency of the intelligent building is improved.
(4) The method of dividing the region by the grid is utilized to effectively cover all positions of the region, and the region division is more flexible and perfect.
Drawings
Fig. 1 is a flowchart illustrating an intelligent module area addressing method according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of an intelligent module area addressing device according to an embodiment of the present invention.
Fig. 3 shows an area addressing platform of an intelligent module area addressing device in an embodiment of the invention.
Description of the element reference
21. Acquisition module
22. First processing module
23. Second processing module
24. Determining module
31. Processor with a memory having a plurality of memory cells
32. Memory device
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
According to the intelligent module area site selection method and device, in the site selection process, from the two aspects of the environment and the people flow of an area scene, the intelligent module and the matching degree between the intelligent module and the intelligent module are respectively considered, so that the intelligent building can effectively obtain a reasonable site selection position no matter in a cluster mode or a non-cluster mode; and in the aspect of processing the matching degree between the intelligent module and the environment and the human flow, the reliability and the accuracy of the data are ensured by applying a principal component analysis method; in addition, the method effectively covers all positions of the area by means of dividing the area by the grid, the area division is more flexible and complete, the time consumed by site selection can be shortened by the processing method, and the site selection efficiency of the intelligent building is improved.
As shown in fig. 1, in an embodiment, the method for selecting an address of an intelligent module area of the present invention includes the following steps:
s1, acquiring an intelligent module set to be selected and a grid set of an area to be addressed.
Specifically, the intelligent module set comprises modules adopting building energy consumption values of different energy sources; the grid set is determined according to a preset division rule based on the area to be addressed.
Further specifically, a to-be-addressed area of an intelligent module to be launched is divided into a plurality of grids, and the division rule is to determine interval information of the to-be-addressed area according to a preset relation between density and interval of the to-be-addressed area; and dividing the area to be addressed into grids at equal intervals according to the interval information. The area density to be selected refers to the number of buildings suitable for releasing in a certain area, for example, the wilderness is not suitable for releasing in the buildings, and the area density is small, the interval setting is large; the city is suitable for putting in the building, and regional density is big, then the interval sets up for little. Further, after being divided into equally spaced grids, the grids may be sequentially numbered, such as S1 to Sn, thereby more flexibly classifying the divided regions.
S2, determining an environment characteristic index and a people stream characteristic index of a first grid in the grid set based on the grid set; the first grid is any grid in the grid set.
Specifically, based on a grid set, crawling interest point data of the area from a map by using a crawler technology, and then collecting and obtaining an environmental characteristic index and a people stream characteristic index corresponding to the interest point of the area according to a Geographic Information System (GIS), wherein the environmental characteristic index comprises an area, a foundation depth, a Geographic position, energy Information and interest point Information; the people flow characteristic indexes comprise people flow rate level, interest degree of people in the area, people consumption level and people consumption tendency. For example, after the pedestrian volume of the interest point of the area is obtained through the GIS, the pedestrian volume level of the area is obtained through statistics; meanwhile, the more the flow of people in one area, the higher the consumption tendency of people, and the consumption tendency of people is obtained through statistics; and the interest points of the region are many, the interest degree of the region of the crowd is reflected to be high, and the interest degree of the region of the crowd is obtained through statistics.
S3, determining a module characteristic index of a first intelligent module in the intelligent module set corresponding to the first grid according to the environment characteristic index, the people stream characteristic index and the intelligent module set of the first grid; the first intelligent module is any intelligent module in the intelligent module set.
Specifically, the module characteristic indexes include an energy characteristic index, a cost characteristic index and a revenue characteristic index; according to the environmental characteristic index of the first grid and the building energy consumption value of the first intelligent module, applying a preset statistical rule to determine an energy characteristic index of the first intelligent module corresponding to the first grid; according to the people stream characteristic index of the first grid and the first intelligent module, applying a preset cost measurement rule to determine a cost characteristic index of the first intelligent module corresponding to the first grid; and according to the environment characteristic index of the first grid, the people flow characteristic index of the first grid and the first intelligent module, applying a preset releasing and collecting rule to determine the collecting and collecting characteristic index of the first intelligent module corresponding to the first grid. For example, the energy characteristic index is determined by comprehensively counting the building energy consumption value of the first intelligent module and the environmental characteristic index of the area where the first grid is located, such as the geographic position, the energy information, the ground depth, and the like, for example, the hydroenergy energy consumption value of the first intelligent module is a, and when the hydroenergy of the area where the first grid is located is sufficient, the energy characteristic index of the first intelligent module corresponding to the first grid is the hydroenergy energy consumption value a; when the water energy of the area where the first grid is located is insufficient, the first intelligent module needs to consider the statistics of the additionally increased other energy consumption and energy consumption cost corresponding to the energy characteristic index of the first grid. The cost characteristic index is determined by calculating the manpower maintenance cost corresponding to the first grid according to the people flow characteristic index of the first grid, such as the people flow level, the crowd consumption level and the crowd consumption tendency. The revenue characteristic index is determined by putting the first intelligent module into the first grid virtually, and counting revenue levels of the first intelligent module corresponding to the first grid according to the environment characteristic index and the people stream characteristic index of the first grid, such as the store entrance rate and the energy profit to the environment.
And S4, determining a target intelligent module of the area to be addressed according to the module characteristic index, the environment characteristic index and the people stream characteristic index.
Specifically, according to the module characteristic indexes and the environment characteristic indexes, a preset module and environment matching evaluation rule is applied to determine a first matching degree of each index in the module characteristic indexes and each index in the environment characteristic indexes; according to the module characteristic indexes and the people stream characteristic indexes, a preset module and people stream matching evaluation rule is applied to determine a second matching degree of each index in the module characteristic indexes and each index in the people stream characteristic indexes; according to the first matching degree and the second matching degree, determining the environment matching degree of the first intelligent module and the first grid and the people stream matching degree of the first intelligent module and the first grid by applying a principal component analysis method; and traversing the intelligent module set and the grid set according to the environment matching degree and the people flow matching degree, and determining a target intelligent module of the area to be addressed.
According to the module characteristic indexes and the environment characteristic indexes, applying a preset index matching corresponding relationship between the module and the environment to obtain a first matching degree of each index in the module characteristic indexes and each index in the environment characteristic indexes, for example, dividing by taking a value of 0-1, wherein 0 represents mismatch, and 1 represents match; similarly, according to the module characteristic indexes and the people stream characteristic indexes, a preset module and people stream index matching corresponding relation is applied to obtain a second matching degree of each index in the module characteristic indexes and each index in the people stream characteristic indexes. After the first matching degree is obtained, performing weighted analysis on each index in the module characteristic indexes and each index in the environment characteristic indexes by using a principal component analysis method to obtain the overall environment matching degree of the first intelligent module on the first grid; similarly, obtaining the overall people stream matching degree of the first intelligent module on the first grid by applying a principal component analysis method; then, comprehensively weighting and re-analyzing the overall environment matching degree and the overall people flow matching degree of the first intelligent module in the first grid to obtain the overall matching degree of the first intelligent module in the first grid; according to the overall matching degree, traversing the intelligent module set to be selected and the grid set of the area to be addressed to obtain the intelligent module with the highest matching degree with each grid of the area to be addressed, and accordingly determining the target intelligent module of the area to be addressed. In addition, because the importance of different intelligent modules in the construction process is different, when the overall matching degree of the first intelligent module in the first grid is determined, the weight coefficient can be adjusted according to the actual situation, wherein the consideration of the weight coefficient comprises the importance of the grid and other factors besides the importance of the intelligent module; in addition, in the extended scenario, the angle of the people flow characteristic index may also be replaced by any variable related to the activities of people other than the objective environment, such as the traffic flow, and other situations are not described again.
As shown in fig. 2, in an embodiment, the intelligent module area address selecting device of the present invention includes:
an obtaining module 21, configured to obtain an intelligent module set to be selected and a grid set of an area to be addressed;
the first processing module 22 is configured to determine an environmental characteristic index and a people stream characteristic index of a first grid in the grid set based on the grid set; the first grid is any grid in the grid set;
a second processing module 23, configured to determine, according to the environment characteristic index of the first grid, the people flow characteristic index, and the intelligent module set, a module characteristic index of the first intelligent module in the intelligent module set, where the first intelligent module corresponds to the first grid; the first intelligent module is any intelligent module in the intelligent module set;
and the determining module 24 is configured to determine a target intelligent module of the area to be addressed according to the module characteristic index, the environment characteristic index and the people flow characteristic index.
The intelligent module set comprises modules adopting building energy consumption values of different energy sources; the grid set is determined according to a preset division rule based on the area to be addressed.
The technical features of the specific implementation of the intelligent module area addressing device in this embodiment are basically the same as the principles of the steps in the intelligent module area addressing method in embodiment 1, and the general technical contents between the method and the device are not repeated.
The storage medium of the present invention stores thereon a computer program that, when executed by a processor, implements the above-described intelligent module area addressing method.
As shown in fig. 3, in an embodiment, the area addressing platform of the present invention includes: a processor 31 and a memory 32.
The memory 32 is used for storing computer programs.
The memory 32 includes: various media that can store program codes, such as ROM, RAM, magnetic disk, U-disk, memory card, or optical disk.
The processor 31 is connected to the memory 32, and is configured to execute the computer program stored in the memory 32, so that the area addressing platform executes the intelligent module area addressing method described above.
Preferably, the Processor 31 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components.
In summary, in the site selection process, from the two aspects of environment and people flow of the regional scene, the intelligent module and the matching degree between the intelligent module and the intelligent module are respectively considered, so that the intelligent building can effectively obtain a reasonable site selection position no matter in a cluster mode or a non-cluster mode; and in the aspect of processing the matching degree between the intelligent module and the environment and the human flow, the reliability and the accuracy of the data are ensured by applying a principal component analysis method; in addition, the method effectively covers all positions of the area by means of dividing the area by the grid, the area division is more flexible and complete, the time consumed by site selection can be shortened by the processing method, and the site selection efficiency of the intelligent building is improved. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which may be made by those skilled in the art without departing from the spirit and scope of the present invention as defined in the appended claims.
Claims (10)
1. An intelligent module area address selecting method is characterized by comprising the following steps:
acquiring an intelligent module set to be selected and a grid set of an area to be addressed;
determining an environment characteristic index and a people stream characteristic index of a first grid in the grid set based on the grid set; the first grid is any grid in the grid set;
determining a module characteristic index of a first intelligent module in the intelligent module set corresponding to the first grid according to the environment characteristic index, the people stream characteristic index and the intelligent module set of the first grid; the first intelligent module is any intelligent module in the intelligent module set;
and determining a target intelligent module of the area to be addressed according to the module characteristic index, the environment characteristic index and the people flow characteristic index.
2. The method of claim 1, wherein the set of intelligent modules includes modules that employ building energy consumption values of different energy sources; the grid set is determined according to a preset division rule based on the area to be addressed.
3. The method of claim 2, wherein the environmental characteristic indicators include area, ground depth, geographic location, energy information, and point of interest information; the people flow characteristic indexes comprise people flow rate level, interest degree of people in the area, people consumption level and people consumption tendency.
4. The method of claim 3, wherein the module characteristic indicators comprise an energy characteristic indicator, a cost characteristic indicator, and a revenue characteristic indicator; the determining, according to the environment characteristic index, the people flow characteristic index, and the intelligent module set of the first grid, a module characteristic index of a first intelligent module in the intelligent module set corresponding to the first grid includes:
according to the environmental characteristic index of the first grid and the building energy consumption value of the first intelligent module, applying a preset statistical rule to determine an energy characteristic index of the first intelligent module corresponding to the first grid;
according to the people stream characteristic index of the first grid and the first intelligent module, applying a preset cost measurement rule to determine a cost characteristic index of the first intelligent module corresponding to the first grid;
and according to the environment characteristic index of the first grid, the people flow characteristic index of the first grid and the first intelligent module, applying a preset releasing and collecting rule to determine the collecting and collecting characteristic index of the first intelligent module corresponding to the first grid.
5. The method according to claim 4, wherein the determining a target intelligent module of the area to be addressed according to the module characteristic index, the environment characteristic index and the people flow characteristic index comprises:
according to the module characteristic indexes and the environment characteristic indexes, a preset module and environment matching evaluation rule is applied to determine a first matching degree of each index in the module characteristic indexes and each index in the environment characteristic indexes;
according to the module characteristic indexes and the people stream characteristic indexes, a preset module and people stream matching evaluation rule is applied to determine a second matching degree of each index in the module characteristic indexes and each index in the people stream characteristic indexes;
according to the first matching degree and the second matching degree, determining the environment matching degree of the first intelligent module and the first grid and the people stream matching degree of the first intelligent module and the first grid by applying a principal component analysis method;
and traversing the intelligent module set and the grid set according to the environment matching degree and the people flow matching degree, and determining a target intelligent module of the area to be addressed.
6. The method according to claim 2, wherein the division rule is to determine interval information of the to-be-addressed area according to a preset relation between density and interval of the to-be-addressed area; and dividing the area to be addressed into grids at equal intervals according to the interval information.
7. An intelligent module area addressing device, comprising:
the acquisition module is used for acquiring an intelligent module set to be selected and a grid set of an area to be addressed;
the first processing module is used for determining an environment characteristic index and a people stream characteristic index of a first grid in the grid set based on the grid set; the first grid is any grid in the grid set;
the second processing module is used for determining the module characteristic indexes of the first intelligent module in the intelligent module set corresponding to the first grid according to the environment characteristic indexes, the people flow characteristic indexes and the intelligent module set of the first grid; the first intelligent module is any intelligent module in the intelligent module set;
and the determining module is used for determining the target intelligent module of the area to be addressed according to the module characteristic index, the environment characteristic index and the people stream characteristic index.
8. The apparatus of claim 7, wherein the set of intelligent modules comprises modules that employ building energy consumption values of different energy sources; the grid set is determined according to a preset division rule based on the area to be addressed.
9. A storage medium storing program instructions, wherein the program instructions, when executed, implement the steps of the intelligent module area addressing method of any of claims 1-6.
10. An area addressing platform, characterized by: comprising a memory for storing a computer program; a processor for running the computer program to implement the steps of the intelligent module area addressing method of any one of claims 1 to 6.
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