Multi-source data collaborative weather phenomenon decision-making method and related equipment

Abstract

The invention provides a method for cooperatively deciding a weather phenomenon through multi-source data and related equipment, which can provide high-precision latest weather phenomenon information, ensure the real-time performance and accuracy of weather data, and weaken the subsequent influence caused by the missing of a single data type at the same time. The method comprises the following steps: if real-time positioning of a target user is in a target area, acquiring first rainfall data of an area weather station in a target period; if the real-time positioning is not in the target area or the first rainfall data does not meet the preset condition, acquiring second rainfall data of the national meteorological station in the target period; if the second rainfall data does not meet the preset condition, obtaining target meteorological data of the target area in the target period through a corresponding weather phenomenon observer; if the target meteorological data does not contain the meteorological data corresponding to the preset weather type, obtaining the total cloud amount of the target area in the target period through a weather phenomenon observer; and determining the weather phenomenon of the target area according to the total cloud amount.

Description

Technical Field

[0001] The present invention relates to the field of meteorology, and in particular to a method for collaborative decision-making on weather phenomena using multi-source data and related equipment. Background Art

[0002] Weather refers to the specific state of the atmosphere close to the surface of a certain area in a short period of time. Weather phenomena refer to various natural phenomena occurring in the atmosphere, that is, the comprehensive expression of the spatial distribution of various meteorological elements (such as temperature, air pressure, humidity, wind, cloud, fog, rain, lightning, snow, frost, thunder, hail and haze) in the atmosphere at a certain moment.

[0003] At present, national-level weather phenomena are mainly based on the recognition results output by the weather phenomenon video intelligent observation instrument, which is obtained through decoding and analysis. The update frequency is every hour, and only the national meteorological station has the relevant equipment. The data accuracy is insufficient, which leads to the low accuracy of the obtained weather phenomena. Summary of the invention

[0004] The embodiments of the present invention provide a method and related equipment for collaborative decision-making on weather phenomena based on multi-source data, which can provide high-precision and up-to-date weather phenomenon information, ensure the real-time and accuracy of weather data acquisition, and the coordinated decision-making of multi-source data weakens the subsequent impact caused by the lack of a single data type.

[0005] A first aspect of the present invention provides a method for collaborative decision-making on weather phenomena using multi-source data, comprising:

[0006] Determine whether the real-time location of the target user is within the target area at the current moment;

[0007] If the real-time positioning of the target user is within the target area, obtaining the first precipitation data of the regional meteorological station corresponding to the target area within a target period, where the target period is the period corresponding to the current moment;

[0008] Determining whether the first precipitation data meets a target preset condition;

[0009] If the real-time positioning is not within the target area or the first precipitation data does not meet the target preset condition, obtaining second precipitation data within the target period from the national meteorological station corresponding to the target area;

[0010] If the second precipitation data does not meet the target preset condition, obtaining the target meteorological data of the target area in the target period through the weather phenomenon observation instrument corresponding to the national meteorological station;

[0011] Determining whether the target meteorological data includes meteorological data corresponding to a preset weather type;

[0012] If the target meteorological data does not include the meteorological data corresponding to the preset weather type, obtaining the total cloud cover of the target area within the target period through the weather phenomenon observation instrument;

[0013] The weather phenomenon of the target area is determined according to the total cloud cover.

[0014] In a possible design, determining the weather phenomenon of the target area according to the total cloud cover includes:

[0015] Determining whether the total cloud cover meets the target preset condition;

[0016] If the total cloud amount meets the target preset condition, determining the weather phenomenon corresponding to the real-time positioning according to the total cloud amount;

[0017] If the total cloud cover does not meet the target preset condition, determining whether the weather value in the target meteorological data is a preset value;

[0018] If the weather value in the target meteorological data is the preset value, the weather phenomenon corresponding to the target area is determined according to the preset value.

[0019] In one possible design, the method further includes:

[0020] If the weather value in the target meteorological data is not the preset value, the weather phenomenon corresponding to the target area will not be displayed.

[0021] In one possible design, the method further includes:

[0022] If the first precipitation data meets the target preset condition, determining a first precipitation level corresponding to the target area according to the first precipitation data;

[0023] The first precipitation level is determined as the weather phenomenon in the target area and displayed.

[0024] In one possible design, the method further includes:

[0025] If the second precipitation data meets the target preset condition, determining a second precipitation level corresponding to the real-time positioning according to the second precipitation data;

[0026] The second precipitation level is determined as the weather phenomenon in the target area and displayed.

[0027] In one possible design, the method further includes:

[0028] If the target meteorological data includes the target meteorological data corresponding to the preset weather type, determining the target weather phenomenon corresponding to the target meteorological data;

[0029] The target weather phenomenon is displayed.

[0030] In one possible design, the target preset condition is that it has a numerical value, and the numerical value satisfies a preset range.

[0031] A second aspect of the present invention provides a device for collaborative decision-making on weather phenomena using multi-source data, comprising:

[0032] The first judgment module is used to judge whether the real-time positioning of the target user at the current moment is within the target area;

[0033] A first acquisition module is used to acquire first precipitation data of a regional meteorological station corresponding to the target area within a target period if the real-time positioning of the target user is within the target area, wherein the target period is the period corresponding to the current moment;

[0034] A second judgment module is used to judge whether the first precipitation data meets the target preset condition;

[0035] A second acquisition module is used to acquire second precipitation data of the national meteorological station corresponding to the target area within the target period if the real-time positioning is not within the target area or the first precipitation data does not meet the target preset condition;

[0036] A third acquisition module is used to acquire the target meteorological data of the target area in the target period through the weather phenomenon observation instrument corresponding to the national meteorological station if the second precipitation data does not meet the target preset condition;

[0037] A third judgment unit, used to judge whether the target meteorological data includes meteorological data corresponding to a preset weather type;

[0038] A fourth acquisition module, configured to acquire the total cloud cover of the target area within the target period through the weather phenomenon observation instrument if the target meteorological data does not include the meteorological data corresponding to the preset weather type;

[0039] A determination module is used to determine the weather phenomenon of the target area according to the total cloud cover.

[0040] In a possible design, the determining module is specifically used for:

[0041] Determining whether the total cloud cover meets the target preset condition;

[0042] If the total cloud amount meets the target preset condition, determining the weather phenomenon corresponding to the real-time positioning according to the total cloud amount;

[0043] If the total cloud cover does not meet the target preset condition, determining whether the weather value in the target meteorological data is a preset value;

[0044] If the weather value in the target meteorological data is the preset value, the weather phenomenon corresponding to the target area is determined according to the preset value.

[0045] In a possible design, the determining module is further specifically used for:

[0046] If the weather value in the target meteorological data is not the preset value, the weather phenomenon corresponding to the target area will not be displayed.

[0047] In a possible design, the second determination module is further configured to:

[0048] If the first precipitation data meets the target preset condition, determining a first precipitation level corresponding to the target area according to the first precipitation data;

[0049] The first precipitation level is determined as the weather phenomenon in the target area and displayed.

[0050] In a possible design, the third acquisition module is further used to:

[0051] If the second precipitation data meets the target preset condition, determining a second precipitation level corresponding to the real-time positioning according to the second precipitation data;

[0052] The second precipitation level is determined as the weather phenomenon in the target area and displayed.

[0053] In a possible design, the third judgment module is further used to:

[0054] If the target meteorological data includes the target meteorological data corresponding to the preset weather type, determining the target weather phenomenon corresponding to the target meteorological data;

[0055] The target weather phenomenon is displayed.

[0056] In one possible design, the target preset condition is that it has a numerical value, and the numerical value satisfies a preset range.

[0057] A third aspect of the present invention provides an electronic device comprising a memory and a processor, wherein the processor is used to implement the steps of the method for collaborative decision-making on weather phenomena based on multi-source data as described in the first aspect when executing a computer management program stored in the memory.

[0058] A fourth aspect of the present invention provides a computer-readable storage medium having a computer management program stored thereon, which, when executed by a processor, implements the steps of the method for collaborative decision-making on weather phenomena based on multi-source data as described in the first aspect above.

[0059] In summary, it can be seen that in the embodiment provided by the present invention, by checking the availability of each data source, the data source is progressively selected through multi-level decision-making. Once a suitable data source is selected, the weather phenomenon is judged according to the plan, and the calculated weather phenomenon is used to update the display of the weather phenomenon. This can provide high-precision and latest weather phenomenon information, ensure the real-time and accuracy of weather data acquisition, and the coordinated decision-making of multi-source data weakens the subsequent impact caused by the lack of a single data type. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A schematic diagram of a flow chart of a method for collaborative decision-making on weather phenomena using multi-source data provided by an embodiment of the present invention;

[0061] Figure 2 A virtual structural diagram of a device for collaborative decision-making on weather phenomena using multi-source data provided by an embodiment of the present invention;

[0062] Figure 3 A schematic diagram of the hardware structure of the device for collaborative decision-making on weather phenomena using multi-source data provided by an embodiment of the present invention;

[0063] Figure 4 A schematic diagram of an electronic device according to an embodiment of the present invention;

[0064] Figure 5 A schematic diagram of an embodiment of a computer-readable storage medium provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0066] The embodiment of the present invention provides a method and related equipment for collaborative decision-making of weather phenomena using multi-source data, which adopts a priority strategy to determine the optimal data source to calculate the rainfall level and characterize the weather phenomenon, and can dynamically filter information from multiple heterogeneous data sources (including regional weather station rainfall data, national weather station rainfall data, and weather phenomenon instrument data). During the execution process, the candidate data sources are first sorted according to priority, for example, the data of the regional weather station is used first, then the data of the national weather station, and finally the data of the weather phenomenon instrument. Each data source uses time series analysis, spatial analysis, radar and other data fusion detection technologies to ensure the availability and data quality of rainfall data.

[0067] Since the spatial accuracy of regional meteorological stations is much greater than that of national meteorological stations and the quality is very high, the rainfall data of regional meteorological stations is preferred. The rainfall data of regional meteorological stations can better represent the weather phenomena in the current geographical location. The rainfall data of national meteorological stations has high quality, but the spatial accuracy is insufficient, and it is ranked second to the rainfall data of regional meteorological stations. The observation technology of weather phenomenon instruments has made great progress in recent years, but there is still room for improvement. Therefore, the data of weather phenomenon instruments are used only when the rainfall data of automatic stations does not meet the requirements. Weather phenomenon instruments can judge a variety of weather phenomena, such as showers, hail, snow, sandstorms, blowing sand, strong sandstorms, fog, haze, light rain, moderate rain, heavy rain, etc. Compared with the current comprehensive identification, which only has data such as cloud amount and cloud shape, there are many types of weather phenomena. Therefore, in the application here, the data of weather phenomenon instruments is better than the data of comprehensive identification. By checking the availability of each data source, the data source is progressively selected through multi-level decision-making. Data integration and processing: Once the appropriate data source is selected, the weather phenomenon is judged according to the plan. Result presentation and feedback: The calculated weather phenomenon is used to update the display of weather phenomena.

[0068] Acquiring and processing real-time weather data based on interfaces can provide the latest high-precision weather phenomenon information, ensuring the real-time and accuracy of the data. The coordinated decision-making of multi-source data weakens the subsequent impact of the lack of a single data type, and the interface-based judgment method can be easily integrated into various existing systems without requiring a lot of configuration and maintenance work.

[0069] The method for collaborative decision-making on weather phenomena with multi-source data provided by the present invention is described below from the perspective of a device for collaborative decision-making on weather phenomena with multi-source data. The device for collaborative decision-making on weather phenomena with multi-source data can be a server or a service unit in the server, without specific limitation.

[0070] See also Figure 1 , Figure 1 A flowchart of a method for collaborative decision-making on weather phenomena using multi-source data provided by an embodiment of the present invention, the method comprising:

[0071] 101. Determine whether the real-time positioning of the target user at the current moment is within the target area. If so, execute step 102; if not, execute step 104.

[0072] In this embodiment, the device for collaborative decision-making on weather phenomena based on multi-source data first obtains the real-time location of the target user at the current moment, for example, the real-time location of the target user at the current moment can be determined by GPS or Beidou positioning, and it is determined whether the real-time location of the target user is within the target area, which is an area set in advance, for example, it can be within Hubei Province. If the real-time location of the target user at the current moment is within the target area, step 102 is executed; if the real-time location of the target user at the current moment is not within the target area, step 104 is executed.

[0073] 102. Obtain first precipitation data within a target period from a regional meteorological station corresponding to the target area.

[0074] In this embodiment, when the device for collaborative decision-making on weather phenomena with multi-source data determines that the real-time positioning of the target user is within the target area, it can obtain the first precipitation data of the regional meteorological station corresponding to the target area within the target period. The first precipitation data is the hourly cumulative value of the minute precipitation of the regional meteorological station within the first period. The target period is the period corresponding to the current time. For example, the target period can be an hourly period. The current time is 9:15 am, then the target period can be a period from 8 to 9 am (of course, the target period can also be other periods, such as a period from 8:15 to 9:15 am, and it can also be adjusted according to actual conditions, without specific limitation), and then the hourly cumulative value of the minute precipitation of the regional meteorological station within the period from 8 to 9 am can be obtained.

[0075] 103. Determine whether the first precipitation data meets the target preset condition. If not, execute step 104; if yes, execute step 109.

[0076] In this embodiment, after obtaining the first precipitation data, the device for collaboratively making decisions on weather phenomena based on multi-source data can determine whether the first precipitation data meets the target preset condition, and the target preset condition is that there is a numerical value and the data satisfies a preset interval, and the preset interval can be, for example, an interval greater than 0 and less than 99999, that is, the device for collaboratively making decisions on weather phenomena based on multi-source data can determine whether the first precipitation data satisfies the condition of having a numerical value and the numerical value is between 0 and 99999. If the first precipitation data satisfies the condition of having a numerical value and the numerical value is between 0 and 99999, step 109 is executed. If the first precipitation data does not satisfy the condition of having a numerical value or is not between 0 and 99999, step 104 is executed.

[0077] 104. Obtain the second precipitation data within the target period from the national meteorological station corresponding to the target area.

[0078] In this embodiment, when the device for collaborative decision-making on weather phenomena based on multi-source data determines that the real-time location of the target user is not within the target area, or the first precipitation data does not meet the target preset conditions, it can obtain the second precipitation data of the national meteorological station corresponding to the target area within the target period.

[0079] 105. If the second precipitation data does not meet the target preset conditions, the target meteorological data of the target area in the target period is obtained through the weather phenomenon observation instrument corresponding to the national meteorological station.

[0080] In this embodiment, after obtaining the second precipitation data, the device for collaborative decision-making on weather phenomena with multi-source data can determine whether the second precipitation data meets the target preset conditions. If the second precipitation data does not meet the target preset conditions, the target meteorological data of the target area in the target period is obtained through the weather phenomenon observation instrument corresponding to the national meteorological station, that is, the device for collaborative decision-making on weather phenomena with multi-source data takes the hourly cumulative value data of the minute precipitation in the most recent period of the national meteorological station. If the data does not meet the condition of having a value and the value is greater than 0 and less than 99999, the target meteorological data of the target area in the target period is obtained according to the WEP_Now column (current weather) code in the hourly value table observed by the national automatic station. The WEP_Now column is generated by the observation of the weather phenomenon instrument of the national meteorological station.

[0081] 106 . Determine whether the target meteorological data includes meteorological data corresponding to the preset weather type. If not, execute step 107 . If yes, execute step 109 .

[0082] In this embodiment, after obtaining the target meteorological data of the target area in the target period, the device for collaborative decision-making on weather phenomena with multi-source data can determine whether the target meteorological data contains meteorological data corresponding to a preset weather type. The preset weather type includes but is not limited to weather phenomena such as showers, hail, snow, sandstorms, blowing sand, strong sandstorms, fog, haze, light rain, moderate rain and heavy rain. If the target meteorological data contains meteorological data corresponding to the preset weather type, step 109 is executed; if the target meteorological data does not include meteorological data corresponding to the preset weather type, step 107 is executed.

[0083] 107. Obtain the total cloud cover in the target area during the target period through the weather phenomenon observation instrument.

[0084] In this embodiment, when the device for collaboratively making decisions on weather phenomena based on multi-source data determines that the target meteorological data does not include meteorological data corresponding to a preset weather type, the total cloud cover in the target area within the target period can be obtained through a weather phenomenon observation instrument.

[0085] 108. Determine the weather phenomena in the target area based on the total cloud cover.

[0086] In this embodiment, after determining the total cloud cover of the target area within the target period, the device for collaboratively deciding weather phenomena with multi-source data can determine whether the total cloud cover meets the target preset conditions, that is, determine whether the total cloud cover has a numerical value, and the numerical value is between 0 and 99999. If the total cloud cover meets the target preset conditions, the weather phenomenon corresponding to the real-time positioning is determined according to the total cloud cover. Specifically, the device for collaboratively deciding weather phenomena with multi-source data can set the weather phenomenon corresponding to the numerical range of the total cloud cover in advance. For example, the weather phenomenon corresponding to less than or equal to 30 is sunny, the weather phenomenon corresponding to 30-90 is cloudy, and the weather phenomenon corresponding to greater than 90 is overcast. The device for collaboratively deciding weather phenomena with multi-source data can determine the weather phenomenon of the target area according to the numerical range of the total cloud cover. If the total cloud cover value is less than or equal to 30, the weather phenomenon in the target area is determined to be sunny, 30-90 is cloudy, and greater than 90 is overcast.

[0087] If the total cloud amount does not meet the target preset conditions, it is determined whether the weather value in the target meteorological data is a preset value, which includes but is not limited to 00, 01, 02, 03 and 19. The preset values ​​correspond to different weather conditions, among which 00, 01, 02 correspond to sunny weather phenomena, and 01, 19 correspond to cloudy weather phenomena. That is, when it is determined that the total cloud amount does not meet the target preset conditions, it can be determined whether there is a value equal to 00, 01, 02, 03 and 19 in the national station hourly value WEP_Now data. If it is 00, 01 or 02, it is determined that the weather phenomenon corresponding to the target area is sunny. If it is 01 or 19, it is determined that the weather phenomenon in the target area is cloudy. If the weather value in the target meteorological data is not the preset value, the weather phenomenon corresponding to the target area is not displayed, that is, it is directly blank and not displayed.

[0088] 109. Perform other operations.

[0089] In this embodiment, the device for collaboratively deciding weather phenomena with multi-source data determines that the first precipitation data meets the target preset conditions, that is, the first precipitation data has a numerical value, and the numerical value is between 0 and 99999, and determines the first precipitation level of the target area according to the first precipitation data. The device for collaboratively deciding weather phenomena with multi-source data can set precipitation levels corresponding to different numerical values ​​in advance. For example, 0.1-1.5 mm is displayed as light rain, 1.6-6.9 mm is displayed as moderate rain, 7-14.9 mm is displayed as heavy rain, 15-39.9 mm is displayed as torrential rain, 40-49.9 mm is displayed as heavy rain, and ≥50 mm is displayed as extremely heavy rain. Therefore, the first precipitation level corresponding to the target area can be determined according to the first precipitation data. For example, if the first precipitation data is 0.13 mm, it can be determined that the first precipitation data is between 0.1-1.5 mm, and the weather phenomenon corresponding to 0.1-1.5 mm is light rain. Then the weather phenomenon in the target area can be displayed as light rain with a precipitation of 0.13 mm.

[0090] The device for collaboratively deciding weather phenomena based on multi-source data determines that the second precipitation data meets the target preset conditions, that is, the second precipitation data has a value and the value is between 0 and 99999, and determines the second precipitation level according to the second precipitation data. Therefore, the second precipitation level corresponding to the target area can be determined according to the second precipitation data. Continuing with the above example, for example, if the first precipitation data is 25 mm, it can be determined that the second precipitation data is between 15-39.9 mm, and the weather phenomenon corresponding to 15-39.9 mm is heavy rain, then the weather phenomenon in the target area can be displayed as heavy rain with a precipitation of 25 mm.

[0091] When the device for collaboratively deciding weather phenomena based on multi-source data determines that the target meteorological data contains the target meteorological data corresponding to the preset weather type, it determines the target weather phenomenon corresponding to the target meteorological data and displays the target weather phenomenon. That is, when it is determined that the target meteorological data contains numerical values ​​corresponding to phenomena such as showers, hail, snow, sandstorms, blowing sand, strong sandstorms, fog, haze, light rain, moderate rain or heavy rain, the weather phenomena in the target area are displayed accordingly.

[0092] In summary, it can be seen that in the embodiment provided by the present invention, by checking the availability of each data source, the data source is progressively selected through multi-level decision-making. Once a suitable data source is selected, the weather phenomenon is judged according to the plan, and the calculated weather phenomenon is used to update the display of the weather phenomenon. This can provide high-precision and latest weather phenomenon information, ensure the real-time and accuracy of weather data acquisition, and the coordinated decision-making of multi-source data weakens the subsequent impact caused by the lack of a single data type.

[0093] The above describes an embodiment of the present invention from the perspective of a method for collaboratively making decisions on weather phenomena based on multi-source data. The following describes an embodiment of the present invention from the perspective of a device for collaboratively making decisions on weather phenomena based on multi-source data.

[0094] See also Figure 2 , Figure 2 Schematic diagram of a virtual structure of a device for collaborative decision-making of weather phenomena using multi-source data in an embodiment of the present invention. The device 200 for collaborative decision-making of weather phenomena using multi-source data includes:

[0095] The first judgment module 201 is used to judge whether the real-time positioning of the target user at the current moment is within the target area;

[0096] A first acquisition module 202 is configured to acquire first precipitation data of a regional meteorological station corresponding to the target area within a target period if the real-time positioning of the target user is within the target area, wherein the target period is the period corresponding to the current moment;

[0097] A second judgment module 203 is used to judge whether the first precipitation data meets the target preset condition;

[0098] A second acquisition module 204 is configured to acquire second precipitation data of a national meteorological station corresponding to the target area within the target period if the real-time positioning is not within the target area or the first precipitation data does not meet the target preset condition;

[0099] The third acquisition module 205 is configured to acquire the target meteorological data of the target area in the target period through the weather phenomenon observation instrument corresponding to the national meteorological station if the second precipitation data does not meet the target preset condition;

[0100] The third judgment unit 206 is used to judge whether the target meteorological data includes meteorological data corresponding to a preset weather type;

[0101] The fourth acquisition module 207 is configured to acquire the total cloud cover of the target area within the target period through the weather phenomenon observation instrument if the target meteorological data does not include the meteorological data corresponding to the preset weather type;

[0102] The determination module 208 is configured to determine the weather phenomenon in the target area according to the total cloud cover.

[0103] In a possible design, the determining module 208 is specifically configured to:

[0104] Determining whether the total cloud cover meets the target preset condition;

[0105] If the total cloud amount meets the target preset condition, determining the weather phenomenon corresponding to the real-time positioning according to the total cloud amount;

[0106] If the total cloud cover does not meet the target preset condition, determining whether the weather value in the target meteorological data is a preset value;

[0107] If the weather value in the target meteorological data is the preset value, the weather phenomenon corresponding to the target area is determined according to the preset value.

[0108] In a possible design, the determining module 208 is further specifically configured to:

[0109] If the weather value in the target meteorological data is not the preset value, the weather phenomenon corresponding to the target area will not be displayed.

[0110] In a possible design, the second determining module 203 is further configured to:

[0111] If the first precipitation data meets the target preset condition, determining a first precipitation level corresponding to the target area according to the first precipitation data;

[0112] The first precipitation level is determined as the weather phenomenon in the target area and displayed.

[0113] In a possible design, the third acquisition module 205 is further used to:

[0114] If the second precipitation data meets the target preset condition, determining a second precipitation level corresponding to the real-time positioning according to the second precipitation data;

[0115] The second precipitation level is determined as the weather phenomenon in the target area and displayed.

[0116] In a possible design, the third determination module 206 is further configured to:

[0117] If the target meteorological data includes the target meteorological data corresponding to the preset weather type, determining the target weather phenomenon corresponding to the target meteorological data;

[0118] The target weather phenomenon is displayed.

[0119] above Figure 3 The apparatus for collaborative decision-making of weather phenomena based on multi-source data in the embodiment of the present invention is described from the perspective of modular functional entities. The apparatus for collaborative decision-making of weather phenomena based on multi-source data in the embodiment of the present invention is described in detail from the perspective of hardware processing. Please refer to Figure 3, a schematic diagram of an embodiment of a device 300 for collaborative decision-making of weather phenomena using multi-source data in an embodiment of the present invention, wherein the device 300 for collaborative decision-making of weather phenomena using multi-source data includes:

[0120] An input device 301, an output device 302, a processor 303 and a memory 304 (the number of the processor 303 can be one or more, Figure 3 In some embodiments of the present invention, the input device 301, the output device 302, the processor 303 and the memory 304 may be connected via a communication bus or other means, wherein: Figure 3 The communication bus connection is taken as an example.

[0121] Wherein, by calling the operation instruction stored in the memory 304, the processor 303 is used to perform the following steps:

[0122] Determine whether the real-time location of the target user is within the target area at the current moment;

[0123] If the real-time positioning of the target user is within the target area, obtaining the first precipitation data of the regional meteorological station corresponding to the target area within a target period, where the target period is the period corresponding to the current moment;

[0124] Determining whether the first precipitation data meets a target preset condition;

[0125] If the real-time positioning is not within the target area or the first precipitation data does not meet the target preset condition, obtaining second precipitation data within the target period from the national meteorological station corresponding to the target area;

[0126] If the second precipitation data does not meet the target preset condition, obtaining the target meteorological data of the target area in the target period through the weather phenomenon observation instrument corresponding to the national meteorological station;

[0127] Determining whether the target meteorological data includes meteorological data corresponding to a preset weather type;

[0128] If the target meteorological data does not include the meteorological data corresponding to the preset weather type, obtaining the total cloud cover of the target area within the target period through the weather phenomenon observation instrument;

[0129] The weather phenomenon of the target area is determined according to the total cloud cover.

[0130] By calling the operation instructions stored in the memory 304, the processor 303 is also used to execute Figure 1 Any method in the corresponding embodiment.

[0131] See also Figure 4 , Figure 4 A schematic diagram of an electronic device according to an embodiment of the present invention.

[0132] like Figure 4 As shown, an embodiment of the present invention provides an electronic device, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0133] Determine whether the real-time location of the target user is within the target area at the current moment;

[0134] If the real-time positioning of the target user is within the target area, obtaining the first precipitation data of the regional meteorological station corresponding to the target area within a target period, where the target period is the period corresponding to the current moment;

[0135] Determining whether the first precipitation data meets a target preset condition;

[0136] If the real-time positioning is not within the target area or the first precipitation data does not meet the target preset condition, obtaining second precipitation data within the target period from the national meteorological station corresponding to the target area;

[0137] If the second precipitation data does not meet the target preset condition, obtaining the target meteorological data of the target area in the target period through the weather phenomenon observation instrument corresponding to the national meteorological station;

[0138] Determining whether the target meteorological data includes meteorological data corresponding to a preset weather type;

[0139] If the target meteorological data does not include the meteorological data corresponding to the preset weather type, obtaining the total cloud cover of the target area within the target period through the weather phenomenon observation instrument;

[0140] The weather phenomenon of the target area is determined according to the total cloud cover.

[0141] In the specific implementation process, when the processor 420 executes the computer program 411, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0142] Since the electronic device introduced in this embodiment is a device adopted by an apparatus for implementing a multi-source data collaborative decision-making weather phenomenon in an embodiment of the present invention, based on the method introduced in the embodiment of the present invention, technical personnel in this field can understand the specific implementation mode of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present invention will not be described in detail here. As long as the equipment adopted by technical personnel in this field to implement the method in the embodiment of the present invention is within the scope of protection of the present invention.

[0143] See also Figure 5 , Figure 5 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention.

[0144] like Figure 5 As shown, the embodiment of the present invention further provides a computer-readable storage medium 500, on which a computer program 511 is stored. When the computer program 511 is executed by a processor, the following steps are implemented:

[0145] Determine whether the real-time location of the target user is within the target area at the current moment;

[0146] If the real-time positioning of the target user is within the target area, obtaining the first precipitation data of the regional meteorological station corresponding to the target area within a target period, where the target period is the period corresponding to the current moment;

[0147] Determining whether the first precipitation data meets a target preset condition;

[0148] If the real-time positioning is not within the target area or the first precipitation data does not meet the target preset condition, obtaining second precipitation data within the target period from the national meteorological station corresponding to the target area;

[0149] If the second precipitation data does not meet the target preset condition, obtaining the target meteorological data of the target area in the target period through the weather phenomenon observation instrument corresponding to the national meteorological station;

[0150] Determining whether the target meteorological data includes meteorological data corresponding to a preset weather type;

[0151] If the target meteorological data does not include the meteorological data corresponding to the preset weather type, obtaining the total cloud cover of the target area within the target period through the weather phenomenon observation instrument;

[0152] The weather phenomenon of the target area is determined according to the total cloud cover.

[0153] In the specific implementation process, the computer program 511 is executed by the processor to achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0154] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0155] The embodiment of the present invention also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes the following Figure 1 The process in the corresponding embodiment.

[0156] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for collaborative decision-making on weather phenomena based on multi-source data, characterized in that: include: Determine whether the real-time location of the target user is within the target area at the current moment; If the real-time positioning of the target user is within the target area, obtaining the first precipitation data of the regional meteorological station corresponding to the target area within a target period, where the target period is the period corresponding to the current moment; Determining whether the first precipitation data meets a target preset condition; If the real-time positioning is not within the target area or the first precipitation data does not meet the target preset condition, obtaining second precipitation data within the target period from the national meteorological station corresponding to the target area; If the second precipitation data does not meet the target preset condition, obtaining the target meteorological data of the target area in the target period through the weather phenomenon observation instrument corresponding to the national meteorological station; Determining whether the target meteorological data includes meteorological data corresponding to a preset weather type; If the target meteorological data does not include the meteorological data corresponding to the preset weather type, obtaining the total cloud cover of the target area within the target period through the weather phenomenon observation instrument; The weather phenomenon of the target area is determined according to the total cloud cover.

2. The method according to claim 1, characterized in that Determining the weather phenomenon of the target area according to the total cloud cover includes: Determining whether the total cloud cover meets the target preset condition; If the total cloud amount meets the target preset condition, determining the weather phenomenon corresponding to the real-time positioning according to the total cloud amount; If the total cloud cover does not meet the target preset condition, determining whether the weather value in the target meteorological data is a preset value; If the weather value in the target meteorological data is the preset value, the weather phenomenon corresponding to the target area is determined according to the preset value.

3. The method according to claim 2, characterized in that The method further comprises: If the weather value in the target meteorological data is not the preset value, the weather phenomenon corresponding to the target area will not be displayed.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: If the first precipitation data meets the target preset condition, determining a first precipitation level corresponding to the target area according to the first precipitation data; The first precipitation level is determined as the weather phenomenon in the target area and displayed.

5. The method according to any one of claims 1 to 3, characterized in that The method further comprises: If the second precipitation data meets the target preset condition, determining a second precipitation level corresponding to the real-time positioning according to the second precipitation data; The second precipitation level is determined as the weather phenomenon in the target area and displayed.

6. The method according to any one of claims 1 to 3, characterized in that The method further comprises: If the target meteorological data includes the target meteorological data corresponding to the preset weather type, determining the target weather phenomenon corresponding to the target meteorological data; The target weather phenomenon is displayed.

7. The method according to any one of claims 1 to 3, characterized in that The target preset condition is that there is a value, and the value satisfies a preset range.

8. A device for collaborative decision-making on weather phenomena using multi-source data, characterized in that: include: The first judgment module is used to judge whether the real-time positioning of the target user at the current moment is within the target area; A first acquisition module is used to acquire first precipitation data of a regional meteorological station corresponding to the target area within a target period if the real-time positioning of the target user is within the target area, wherein the target period is the period corresponding to the current moment; A second judgment module is used to judge whether the first precipitation data meets the target preset condition; A second acquisition module is used to acquire second precipitation data of the national meteorological station corresponding to the target area within the target period if the real-time positioning is not within the target area or the first precipitation data does not meet the target preset condition; A third acquisition module is used to acquire the target meteorological data of the target area in the target period through the weather phenomenon observation instrument corresponding to the national meteorological station if the second precipitation data does not meet the target preset condition; A third judgment unit, used to judge whether the target meteorological data includes meteorological data corresponding to a preset weather type; A fourth acquisition module, configured to acquire the total cloud cover of the target area within the target period through the weather phenomenon observation instrument if the target meteorological data does not include the meteorological data corresponding to the preset weather type; A determination module is used to determine the weather phenomenon of the target area according to the total cloud cover.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the processor is used to implement the method for collaborative decision-making on weather phenomena based on multi-source data as described in any one of claims 1 to 7 when executing a computer management program stored in the memory.

10. A computer-readable storage medium having a computer management program stored thereon, characterized in that: When the computer management program is executed by the processor, the method for collaborative decision-making on weather phenomena using multi-source data as described in any one of claims 1 to 7 is implemented.

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