Weather data processing method, device, electronic device and storage medium

Abstract

The present disclosure provides a method, device, electronic device and storage medium for processing weather data, and relates to the technical fields of intelligent weather and the like. The specific implementation scheme is: based on the weather data of at least two reference data resources, the candidate weather data set of the designated location to be pushed is verified and processed to obtain the target weather data set of the designated location to be pushed; based on the target weather data set of the designated location to be pushed, the data of the weather application is pushed. The present disclosure can effectively improve the accuracy and quality of weather data.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, specifically to the field of intelligent weather and other technical fields, and in particular to a method, device, electronic device and storage medium for processing weather data. Background Art

[0002] With the popularization of smart terminals, more and more application products are used on smart terminals, which greatly facilitates users.

[0003] For example, weather applications are very practical products that have emerged with the popularization of smart terminals. Users can refer to the real-time weather data provided by weather applications to make travel plans and add clothes in a timely manner. Application providers that provide weather applications can obtain weather data in real time from third-party data resources and store it in a local weather database. Then, based on the local weather database, real-time weather data is pushed to the weather application. Summary of the invention

[0004] The present disclosure provides a method, device, electronic device and storage medium for processing weather data.

[0005] According to one aspect of the present disclosure, a method for processing weather data is provided, comprising:

[0006] Based on the weather data of at least two reference data resources, the candidate weather data set of the designated location to be pushed is verified to obtain the target weather data set of the designated location to be pushed;

[0007] Based on the target weather data set to be pushed to the designated location, data push for the weather application is performed.

[0008] According to another aspect of the present disclosure, there is provided a weather data processing device, comprising:

[0009] A verification processing module, used to verify the candidate weather data set of the designated location to be pushed this time based on the weather data of at least two reference data resource parties, and obtain the target weather data set of the designated location to be pushed this time;

[0010] The push processing module is used to push data for the weather application based on the target weather data set of the designated location to be pushed this time.

[0011] According to another aspect of the present disclosure, there is provided an electronic device, comprising:

[0012] at least one processor; and

[0013] a memory communicatively connected to the at least one processor; wherein,

[0014] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any possible implementation manner and the aspects described above.

[0015] According to yet another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the method of the above-mentioned aspect and any possible implementation manner.

[0016] According to yet another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the computer program implements the above-mentioned aspects and any possible implementation method.

[0017] According to the technology disclosed in the present invention, the accuracy of weather data can be effectively improved.

[0018] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0020] Figure 1 is a schematic diagram according to a first embodiment of the present disclosure;

[0021] Figure 2 is a schematic diagram according to a second embodiment of the present disclosure;

[0022] Figure 3 is a schematic diagram according to a third embodiment of the present disclosure;

[0023] Figure 4 is a schematic diagram according to a fourth embodiment of the present disclosure;

[0024] Figure 5 is a schematic diagram according to a fifth embodiment of the present disclosure;

[0025] Figure 6 The block diagram is a block diagram of an electronic device for implementing the method of the embodiment of the present disclosure. DETAILED DESCRIPTION

[0026] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0027] Obviously, the described embodiments are only part of the embodiments of the present disclosure, but not all of them. Based on the embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present disclosure.

[0028] It should be noted that the terminal devices involved in the embodiments of the present disclosure may include but are not limited to mobile phones, personal digital assistants (PDAs), wireless handheld devices, tablet computers and other smart devices; display devices may include but are not limited to personal computers, televisions and other devices with display functions.

[0029] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0030] In addition to meeting the requirements of real-time performance, the accuracy of weather data provided by weather applications is also a very important quality indicator of weather applications. For example, if the accuracy of weather data provided by weather applications is poor, it will inevitably lead to users' trust in weather applications, and then cause the loss of user traffic. After obtaining weather data from third-party data resources in real time, weather applications in the prior art store it in a local weather database, and then directly push the weather data obtained in real time from the weather database. However, no verification is performed on the accuracy of the obtained weather data, resulting in poor accuracy of the weather data.

[0031] Figure 1 is a schematic diagram according to the first embodiment of the present disclosure; Figure 1 As shown, this embodiment provides a method for processing weather data, which can be applied to a server side that pushes weather data to a weather application, and specifically may include the following steps:

[0032] S101, based on the weather data of at least two reference data resource parties, verify the candidate weather data set of the designated location to be pushed this time, and obtain the target weather data set of the designated location to be pushed this time;

[0033] S102: Push data for a weather application based on the target weather data set for the designated location to be pushed this time.

[0034] In the weather application, different types of weather data can be included, and different types of weather data are updated at different frequencies. For example, for real-time weather data, it can be updated every five minutes, that is, real-time weather data is obtained every 5 minutes and pushed to the weather application. For the weather data for the next 24 hours, it can be updated every hour, that is, the weather data for the next 24 hours is obtained every hour and pushed to the weather application. For the remaining weather data for the next few days, it can be updated 4 times a day at a fixed time, that is, each time at a preset fixed time, the remaining weather data for the next few days is obtained and pushed to the weather application.

[0035] In this embodiment, the candidate weather data set for the designated location to be pushed this time can be any of the above-mentioned types of weather data. Since the candidate weather data set can include one, two or more categories of weather data for the designated location, it can be in the form of a collection. When the candidate weather data set is different from the prior art, in this embodiment, the candidate weather data set is not directly used as the target weather data set for data push of the weather application. Instead, the candidate weather data set for the designated location to be pushed this time is first verified based on the weather data of at least two reference data resources to obtain the target weather data set for the designated location to be pushed this time, which can ensure the accuracy of the target weather data set for the designated location to be pushed this time.

[0036] The designated location in this embodiment may be any city, or a certain area in any city, etc.

[0037] In actual applications, the weather application can cooperate with a data resource party to obtain the weather data of the data resource party for data update. For example, in this embodiment, the candidate weather data set of the designated location to be pushed can be obtained from the target data resource party. In order to effectively verify the candidate weather data set obtained locally, in this embodiment, it is necessary to refer to the weather data of at least two reference data resources that are different from the target data resource party to implement verification processing, so as to obtain a more accurate target weather data set.

[0038] The weather data processing method of this embodiment verifies the candidate weather data set of the designated location to be pushed based on the weather data of at least two reference data resources to obtain the target weather data set of the designated location to be pushed. This can improve the accuracy of the target weather data set of the designated location obtained locally, and then when the target weather data set of the designated location to be pushed is used to push data for the weather application, the accuracy of the weather data of the weather application can be improved, and the quality of the weather data of the weather application can be effectively improved. Therefore, it can also improve the user experience of the weather application and enhance the user stickiness of the weather application.

[0039] Figure 2 is a schematic diagram according to the second embodiment of the present disclosure; this embodiment provides a method for processing weather data, in the above Figure 1 Based on the technical solutions of the embodiments shown, the present disclosure is described in more detail. Figure 2 As shown, the weather data processing method of this embodiment may specifically include the following steps:

[0040] S201, based on a preset weather data acquisition rule, obtaining a candidate weather data set of a designated location to be pushed this time from the weather data of a target data resource party;

[0041] The preset weather data acquisition rules can refer to the above Figure 1 Definitions of different types of weather data in the illustrated embodiments. For example, live weather data can be acquired every 5 minutes. Of course, in actual applications, it can also be set to acquire every 3 minutes, 8 minutes, 10 minutes or other minutes based on demand. For the future 24-hour weather data, you can set a fixed time every hour in the preset weather data acquisition rules, such as the 1st minute, the 30th minute or the Xth minute of each hour, to acquire weather data once. For the remaining weather data for the next few days, you can set the preset weather data acquisition rules to acquire weather data at 4 fixed times every day. The 4 fixed times of each day can be evenly distributed throughout the day, or they can be distributed irregularly, and the details can be set based on specific needs.

[0042] In this embodiment, each acquired weather data may carry a timestamp of when the data was acquired.

[0043] In this embodiment, the candidate weather data set for the designated location to be pushed this time can be any weather data acquisition in the above-mentioned preset weather data acquisition rules. In other words, the weather data processing method of this embodiment can be used for each acquired weather data to improve the accuracy of the weather data to be pushed this time.

[0044] In this embodiment, the server side of the weather data actively obtains weather data from the target data resource party as an example. In actual applications, preset weather data push rules can also be set on the target data resource party, which is the same as the principle of the preset weather data acquisition rules mentioned above. The device of the target data resource party actively pushes various types of weather data to the weather data server based on the preset weather data push rules. At this time, correspondingly, on the server side, it is only necessary to receive the candidate weather data set of the designated location to be pushed this time. Regardless of which method is used, the accuracy of the candidate weather data set of the designated location to be pushed this time can be ensured.

[0045] S202, storing the candidate weather data set of the designated location to be pushed this time in a weather database;

[0046] The weather database is a database set up on the server side for storing offline weather data, so as to facilitate subsequent data verification based on the candidate weather data set of the designated location to be pushed this time in the weather database.

[0047] S203, filtering the candidate weather data set of the designated location to be pushed this time based on the historical weather data of the same type of the designated location obtained last time by the nearest neighbor;

[0048] Specifically, the historical weather data of the same type at the designated location last obtained by the nearest neighbor can be obtained from the weather database storing weather data. The same type may refer to the same type as the weather data to be pushed this time. That is, if the live weather data to be pushed this time is real-time weather data, the weather data of the same type at the designated location last obtained by the nearest neighbor may be real-time weather data obtained a few minutes ago, such as 5 minutes ago. If the weather data to be pushed this time is the next 24 hours of weather data, then the weather data of the same type at the designated location last obtained by the nearest neighbor may refer to the next 24 hours of weather data obtained about an hour ago. If the weather data to be pushed this time is the rest of the weather data for the next several days, then the weather data of the same type at the designated location last obtained by the nearest neighbor may refer to the rest of the weather data for the next several days obtained at a fixed time of the last nearest neighbor before the current push in the preset weather data acquisition rules.

[0049] This step is an optional step. Through the above method, it can be ensured that the historical data obtained is the nearest neighbor weather data of the same type and location as the candidate weather data set. Then, the candidate weather data set can be filtered with reference to the historical data to remove unreasonable weather data, thereby effectively improving the accuracy of the weather data.

[0050] S204: Based on the weather data of at least two reference data resource parties, verify the candidate weather data set of the designated location to be pushed this time, and obtain the target weather data set of the designated location to be pushed this time;

[0051] S205: Push data to the weather application based on the target weather data set of the designated location to be pushed in the weather database.

[0052] From the production of weather data to the front-end display in the weather application, the weather data needs to be pushed to the offline weather database through the target data resource party. Then, the online part can read the weather data to be pushed from the offline weather database and display it to the page of the weather application through the front end. Steps S203 and S204 of this embodiment are used to filter and verify the target weather data set of the designated location to be pushed stored in the weather database, so as to improve the accuracy of the target weather data set of the designated location to be pushed.

[0053] The weather data processing method of this embodiment can effectively improve the accuracy of the weather data of the weather application through the above-mentioned filtering processing and verification processing, and further can effectively improve the quality of the weather data of the weather application.

[0054] Figure 3 is a schematic diagram according to the third embodiment of the present disclosure; this embodiment provides a method for processing weather data, in the above Figure 2 Based on the technical solutions of the embodiments shown, the present disclosure is described in more detail. Figure 3 As shown, the weather data processing method of this embodiment may specifically include the following steps:

[0055] S301, receiving a candidate weather data set of a designated location to be pushed this time, sent by a target data resource party based on a preset weather data push rule; and storing the data in a weather database;

[0056] The preset weather data push rules in this embodiment can refer to the above Figure 2 The preset weather data acquisition rules of the illustrated embodiment have the same principle and will not be described in detail here.

[0057] In one embodiment of the present disclosure, each candidate weather data set or target weather data set for a designated location to be pushed includes one, two or more types of weather data, such as temperature, air quality index, weather conditions, air quality conditions, etc.

[0058] S302, filtering the first digital weather data of a preset category in the candidate weather data set by using the second digital weather data of the same preset category in the historical weather data of the same type of the designated location acquired last time as the nearest neighbor;

[0059] That is to say, the filtering process of this embodiment mainly filters the digital weather data in the candidate weather data set. That is, the preset category of this embodiment is the category corresponding to the digital weather data, such as temperature or air quality index.

[0060] For example, when this step is implemented specifically, it may include the following steps:

[0061] (1) Detect whether the absolute value of the difference between the first digital weather data corresponding to a preset category in the candidate weather data set and the second digital weather data is greater than a preset numerical threshold; if so, execute step (2); otherwise, if not, retain the first digital weather data of the preset category in the candidate weather data set and end.

[0062] (2) Filter out the first digital weather data corresponding to the preset category in the candidate weather data set.

[0063] For example, if the preset category is temperature, for real-time weather data, if the absolute value of the temperature difference between two times at the same designated location is greater than 5°C, the temperature value in the candidate weather data set to be pushed is considered unreasonable and is filtered out.

[0064] For another example, the preset category is the control quality index. For real-time weather data, if the absolute value of the difference in air quality index between two times at the same designated location is greater than 200, it is considered that the air quality index in the candidate weather data set to be pushed is unreasonable and is filtered out.

[0065] For another example, for the weather data for the next 24 hours, if the absolute value of the temperature before and after the same time in the future differs by more than 5°C, or the absolute value of the air quality index differs by more than 100, the data of the corresponding preset category of weather in the candidate weather data set to be pushed this time will be filtered.

[0066] After filtering in this step, when data is subsequently pushed to the weather application based on the corresponding target weather data set, the weather data of the preset category in the weather application is not updated, that is, the weather data of the preset category is retained, and the weather data of the previous update is also retained.

[0067] In one embodiment of the present disclosure, after step (2), a data verification request carrying the filtered first digital weather data and corresponding preset categories may be sent to the device of the target data resource party for manual verification by the staff of the target data resource party.

[0068] Step S302 of this embodiment is as follows: Figure 2 An implementation of step S203 of the illustrated embodiment.

[0069] S303, for each category of weather data in the candidate weather data set, determine whether there is weather data of the category at the same location and time provided by at least two reference data resources that is consistent with the weather data of the category in the candidate weather data set within a preset error range; if so, execute step S304; if not, execute step S305;

[0070] S304: taking the weather data of this category in the candidate weather data set as the weather data of this category in the target weather data set of the designated location to be pushed this time; executing step S309;

[0071] The verification process performed in this embodiment is to perform verification processing on each category of weather data to ensure the accuracy of each category of weather data. For example, the temperature, air quality index, air condition or air quality condition of each hour in the weather data of the next 24 hours are each a category. The minimum temperature, maximum temperature, air quality index, air condition or air quality condition of each day in other weather data such as the next few days are each a category.

[0072] In this embodiment, the preset error range may be set differently for different categories and different formats of weather data.

[0073] For example, for temperature, the preset error range may be that the temperature difference is not greater than a preset temperature difference threshold, which may be set based on actual experience, such as 5°C, 6°C, or other temperature difference thresholds. For air quality index, the preset error range may be that the difference in air quality index is not greater than a preset numerical difference threshold, which may be set based on actual experience, such as 100, 200, or other numerical difference thresholds.

[0074] For another example, for a category where weather data is in text form, a preset error range of the text description may be set. For example, the following Table 1 describes various air quality conditions and the corresponding air quality conditions within the preset error range.

[0075] Serial number Air quality conditions Air quality conditions within the preset error range 1 excellent excellent 2 good Excellent, good, slightly polluted 3 Slightly polluted Good, slightly polluted, moderately polluted 4 Moderate pollution Light pollution, moderate pollution, heavy pollution 5 Severe pollution Moderate pollution, heavy pollution, severe pollution 6 Severe pollution Heavy pollution, severe pollution

[0076] As shown in Table 1, the air quality conditions can be divided into 6 levels, namely, excellent, good, lightly polluted, moderately polluted, heavily polluted, and severely polluted. When verifying in this embodiment, the air quality conditions of the same category at the same location differ by no more than two levels, and the air quality conditions within the preset error range can be considered to be consistent.

[0077] For another example, the following Table 2 describes some weather conditions and some weather conditions within the corresponding preset error range.

[0078]

[0079]

[0080] As shown in Table 2 above, only some weather conditions and some weather conditions within the preset error range are described. In practical applications, each weather condition and various weather conditions included in the preset error range can be pre-set according to needs for easy verification and processing, and no further examples will be given here.

[0081] The implementation principle of step S303 and step S304 of this embodiment is: as long as there is a reference data resource party that provides weather data of this category at the same location and time, which is consistent with the weather data of this category in the current candidate weather data set within a preset error range, it means that the weather data of this category in the current candidate weather data set is correct. In specific implementation, the weather data of this category in the current candidate weather data set can be compared with the weather data of this category in the current candidate weather data set in order of priority from high to low of at least two reference data resources. By verifying in this way, the accuracy of the weather of this category in the target weather data set can be effectively improved.

[0082] S305, detecting whether there are at least two candidate data resource parties among at least two reference data resource parties providing weather data of the same category at the same location and time, which are consistent within a preset error range; if so, executing step S306; if not, executing step S307;

[0083] S306, from the weather data of the same category at the same location and at the same time provided by at least two candidate data resource parties, obtain the weather data of the same category at the same location and at the same time provided by the candidate data resource party with the highest priority, as the weather data of the category in the target weather data set of the designated location to be pushed this time; execute step S309;

[0084] The implementation principle of step S305 and step S306 is: the weather data of the category at the same location and at the same time provided by at least two reference data resources are inconsistent with the weather data of the category in the candidate weather data set within the error range. It can be considered that the weather data of the category in the candidate weather data set is incorrect. At this time, if there are at least two candidate data resources in at least two reference data resources, the weather data of the category at the same location and at the same time provided by at least two candidate data resources are consistent within the error range. It is considered that the weather data of the category at the same location and at the same time provided by the at least two candidate data resources are accurate and can be used as a reference. Preferably, the weather data of the category at the same location and at the same time provided by the candidate data resource with the highest priority is obtained as the weather data of the category in the target weather data set of the designated location to be pushed this time. Or if the weather data of the category is in digital format, the mean of the weather data of the category at the same location and at the same time provided by the at least two candidate data resources can also be directly taken. Through the verification in this way, the accuracy of the weather of the category in the target weather data set can be effectively ensured.

[0085] S307, obtaining weather data of the same category detected by three weather stations at the same location and at the same time around the weather station of the target data resource party of the candidate weather data set source and meeting the preset conditions; executing step S308;

[0086] S308: Based on the weather data of the same category detected by the three weather stations at the same location and at the same time, obtain the weather data of the category in the target weather data set of the designated location to be pushed this time; execute step S309;

[0087] The implementation principle of step S307 and step S308 is: there are no two weather data of the same category provided by any two reference data resource parties at the same location and at the same time that are consistent within the error range. In other words, the weather data of the same category at the same location and at the same time of the current target data resource party and at least two reference data resource parties are inconsistent with each other, and it is impossible to prove which weather data is correct. At this time, the weather data of the same location and at the same time detected by three weather stations around the weather station of the target data resource party and meeting the preset conditions can be obtained to further determine the weather data of the category in the target weather data set, thereby effectively improving the accuracy of the weather data.

[0088] The preset conditions can be set based on the category of weather data. For example, if the category is temperature, considering the temperature difference at different altitudes, the preset condition can be set to the nearest neighbor and the altitude difference is not greater than 20 meters. If it is other categories, the preset conditions can also be set according to the characteristics of the category, for example, the nearest neighbor can be set directly.

[0089] For example, when the step S308 is implemented, if the weather data of the category is in digital format, such as temperature, the average of the weather data of the category detected by three weather stations at the same location and at the same time can be obtained as the weather data of the category in the target weather data set of the designated location to be pushed this time. The weather data of the category obtained in this way is reasonable and accurate.

[0090] If the weather data of this category is in text format, the weather data of this category detected at the same location and time by the weather station with the highest priority among the three weather stations can be obtained as the weather data of this category in the target weather data set of the designated location to be pushed this time.

[0091] In addition, in order to further improve the accuracy of weather data of this category, optionally, for weather data of this category in digital format, before step S308 of this embodiment, it may also include: detecting and determining that the absolute value of the difference between the weather data of this category at the same location and at the same time detected by any two of the three meteorological stations is less than or equal to a preset threshold.

[0092] That is to say, when the absolute value of the difference between the weather data of this category at the same location and at the same time detected by any two of the three weather stations is less than or equal to the preset threshold, the weather data of the three weather stations are all valid and the average of the three can be taken. If the absolute value of the difference between the weather data of this category at the same location and at the same time detected by any two of the three weather stations is greater than the preset threshold, it can be considered that there is a problem with the weather data of this category, and there is no reference weather data with higher accuracy available. At this time, the candidate weather data set has the highest priority, and the weather data of this category in the candidate weather data set can still be used as the weather data of this category in the target weather data set for the designated location to be pushed this time; however, an alarm prompt needs to be issued to the device of the target data resource party to prompt the target data resource party to conduct an emergency investigation.

[0093] By using the above steps, the candidate weather data set of the designated location to be pushed in the weather database can be filtered and verified to obtain the corresponding target weather data set, thereby effectively improving the accuracy of the weather data.

[0094] Steps S303-S308 of this embodiment are all verification processes, which can be specifically considered as the above Figure 1 A specific implementation of step S101 of the illustrated embodiment.

[0095] S309, based on the target weather data set to be pushed to the designated location in the weather database, push data to the weather application;

[0096] S310, for the weather data to be pushed this time being the live weather data and the weather data of the temperature category, obtaining the real-time temperature value to be pushed this time;

[0097] S311, check whether the real-time temperature value is within the forecast temperature range of the day; if not, execute step S312; if yes, do not perform any operation for the time being and end.

[0098] S312, based on the real-time temperature value, update the forecast temperature range for the day; execute step S313;

[0099] S313: Push data to the weather application based on the updated forecast temperature range for the day.

[0100] Combined with meteorological knowledge, it can be known that the temperature is lowest before and after sunrise, and the temperature often reaches the peak temperature of the day around noon. Since the forecast temperature range of the day is only updated 4 times a day, the actual temperature often exceeds the forecast temperature range, such as: the weather forecast today is 15℃--23℃, but the actual minimum temperature in the morning reaches 13℃, and the temperature in the afternoon reaches 25℃. If the user inquires about the weather conditions at this time, he will think that the data is contradictory and question the weather data. In order to eliminate such contradictions, when the actual data is greater than or less than the boundary value of the forecast temperature range, steps S310-S313 of this embodiment can be used to update the forecast temperature range of the day and push data, so as to ensure the accuracy of the weather data and eliminate user ambiguity.

[0101] Optionally, steps S310-S312 of this embodiment may be performed before step S309. Step S313 may be combined with step S309 to push data to the weather application.

[0102] The weather data processing method of this embodiment can effectively improve the accuracy of weather data of the weather application by adopting the above filtering and verification processing, and further can effectively improve the quality of weather data of the weather application. This embodiment can improve the user experience of using the weather application and enhance the user stickiness of the weather application.

[0103] Figure 4 is a schematic diagram according to a fourth embodiment of the present disclosure; Figure 4 As shown, this embodiment provides a weather data processing device 400, including:

[0104] The verification processing module 401 is used to verify the candidate weather data set of the designated location to be pushed this time based on the weather data of at least two reference data resources to obtain the target weather data set of the designated location to be pushed this time;

[0105] The push processing module 402 is used to push data for the weather application based on the target weather data set of the designated location to be pushed this time.

[0106] The weather data processing device 400 of this embodiment realizes the implementation principle and technical effect of weather data processing by adopting the above-mentioned modules, which is the same as the implementation of the above-mentioned related method embodiments. For details, please refer to the records of the above-mentioned related method embodiments, which will not be repeated here.

[0107] Figure 5 is a schematic diagram according to the fifth embodiment of the present disclosure; Figure 5 As shown, this embodiment provides a weather data processing device 500, comprising the above Figure 4 The modules with the same name and function are verified by a processing module 501 and a push processing module 502 .

[0108] In this embodiment, the verification processing module 501 is used to:

[0109] For each category of weather data in the candidate weather data set, determine whether there is weather data of the category at the same location and time provided by at least two reference data resources that is consistent with the weather data of the category in the candidate weather data set within a preset error range;

[0110] If so, the weather data of the category in the candidate weather data set is used as the weather data of the category in the target weather data set for the designated location to be pushed this time.

[0111] Further optionally, in the weather data processing device 500 of this embodiment, the verification processing module 501 is further used to:

[0112] If there is no weather data of the same category at the same location and time provided by at least two reference data resources that is consistent with the weather data of the category in the candidate weather data set within a preset error range, it is detected whether there is weather data of the same category at the same location and time provided by at least two candidate data resources in the at least two reference data resources that is consistent within a preset error range;

[0113] If so, the weather data of the same location and time provided by the candidate data resource with the highest priority is obtained from the weather data of the same location and time provided by at least two candidate data resources, as the weather data of the same category in the target weather data set for the designated location to be pushed this time.

[0114] Further optionally, in the weather data processing device 500 of this embodiment, the verification processing module 501 is further used to: if there are no weather data of the same location and the same time category provided by at least two candidate data resource parties in at least two reference data resource parties, and the weather data is consistent within a preset error range, obtain weather data of the same location and the same time category detected by three weather stations that meet preset conditions and are around the weather station of the target data resource party that is the source of the candidate weather data set;

[0115] Based on the weather data of the same location and the same time category detected by three meteorological stations, the weather data of the category in the target weather data set of the designated location to be pushed this time is obtained.

[0116] Further optionally, in the weather data processing device 500 of this embodiment, the verification processing module 501 is further used to:

[0117] If the weather data of the category is in digital format, the average of the weather data of the category detected by the three meteorological stations at the same location and at the same time is obtained as the weather data of the category in the target weather data set of the designated location to be pushed this time.

[0118] Further optionally, in the weather data processing device 500 of this embodiment, the verification processing module 501 is also used to: detect and determine that the absolute value of the difference between the weather data of the same location and the same time category detected by any two of the three meteorological stations is less than or equal to a preset threshold.

[0119] Further optionally, in the weather data processing device 500 of this embodiment, the verification processing module 501 is further used to: if the absolute value of the difference between the weather data of the same location and the same time category detected by any two of the three meteorological stations is greater than a preset threshold, use the weather data of the category in the candidate weather data set as the weather data of the category in the target weather data set for the designated location to be pushed this time;

[0120] And send an alarm to the target data resource party's equipment to prompt the target data resource party to conduct an emergency investigation.

[0121] Further optionally, if Figure 5 As shown, in one embodiment of the present disclosure, the weather data processing device 500 of this embodiment further includes:

[0122] The filtering processing module 503 is used to filter the candidate weather data set of the designated location to be pushed this time based on the historical weather data of the same type of the designated location acquired last time by the nearest neighbor.

[0123] Further optionally, the filtering processing module 503 is used to:

[0124] For the first digital weather data of a preset category in the candidate weather data set, second digital weather data of the same preset category in the historical weather data is used for filtering processing.

[0125] Further optionally, the filtering processing module 503 is used to:

[0126] Detecting whether the absolute value of the difference between the first digital weather data and the second digital weather data corresponding to the preset category in the candidate weather data set is greater than a preset numerical threshold;

[0127] If so, the candidate weather data set of first digital weather data corresponding to the preset category in the candidate weather data set is filtered out.

[0128] Further optionally, if Figure 5 As shown, in one embodiment of the present disclosure, the weather data processing device 500 of this embodiment further includes:

[0129] The acquisition module 504 is used to acquire the candidate weather data set of the designated location to be pushed this time from the weather data of the target data resource party based on the preset weather data acquisition rules.

[0130] Further optionally, in an embodiment of the present disclosure, the acquisition module 504 is further configured to acquire the real-time temperature value to be pushed this time when the weather data to be pushed this time is live weather data and the category is temperature;

[0131] Verification processing module 501, used to detect whether the real-time temperature value is within the forecast temperature range of the day; if not, update the forecast temperature range of the day based on the real-time temperature value;

[0132] The push processing module 502 is used to push data to the weather application based on the updated forecast temperature range for the day.

[0133] The weather data processing device 500 of this embodiment realizes the implementation principle and technical effect of weather data processing by adopting the above-mentioned modules, which is the same as the implementation of the above-mentioned related method embodiments. For details, please refer to the records of the above-mentioned related method embodiments, which will not be repeated here.

[0134] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0135] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0136] Figure 6A schematic block diagram of an example electronic device 600 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0137] like Figure 6 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0138] A number of components in the device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0139] The computing unit 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 601 performs the various methods and processes described above, such as the above-mentioned methods of the present disclosure. For example, in some embodiments, the above-mentioned methods of the present disclosure may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the above-mentioned methods of the present disclosure described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the above-mentioned methods of the present disclosure in any other appropriate manner (e.g., by means of firmware).

[0140] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0141] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0142] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0143] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0144] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0145] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0146] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0147] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for processing weather data, comprising: Based on the weather data of at least two reference data resource parties, verifying and processing the candidate weather data set of the designated location to be pushed this time, and obtaining the target weather data set of the designated location to be pushed this time; the candidate weather data set of the designated location to be pushed this time is obtained from the target data resource party; The target data resource party is different from at least two reference data resource parties; Based on the target weather data set to be pushed to the designated location, data push for the weather application is performed; The candidate weather data set of the designated location to be pushed is verified based on the weather data of at least two reference data resources to obtain the target weather data set at the current moment, including: For each category of weather data in the candidate weather data set, determine whether there is weather data of the category provided by the at least two reference data resources at the same location and at the same time that is consistent with the weather data of the category in the candidate weather data set within a preset error range; If so, the weather data of the category in the candidate weather data set is used as the weather data of the category in the target weather data set for the designated location to be pushed this time.

2. The method according to claim 1, wherein: The method further comprises: If there is no weather data of the category at the same location and time provided by the at least two reference data resources that is consistent with the weather data of the category in the candidate weather data set within a preset error range, detecting whether there is weather data of the category at the same location and time provided by at least two candidate data resources among the at least two reference data resources that is consistent within a preset error range; If so, then from the weather data of the category at the same location and at the same time provided by the at least two candidate data resource parties, obtain the weather data of the category at the same location and at the same time provided by the candidate data resource party with the highest priority, as the weather data of the category in the target weather data set of the designated location to be pushed this time.

3. The method according to claim 2, wherein: The method further comprises: If there are no weather data of the category at the same location and at the same time provided by at least two candidate data resources among the at least two reference data resources, and the weather data is consistent within a preset error range, obtain weather data of the category at the same location and at the same time detected by three weather stations that meet preset conditions and are around the weather station of the target data resource party that is the source of the candidate weather data set; Based on the weather data of the category detected by the three meteorological stations at the same location and at the same time, the weather data of the category in the target weather data set of the designated location to be pushed this time is obtained.

4. The method according to claim 3, wherein: Based on the weather data of the category detected by the three weather stations at the same location and at the same time, obtaining the weather data of the category in the target weather data set to be pushed this time, including: If the weather data of the category is in digital format, the average of the weather data of the category detected by the three meteorological stations at the same location and at the same time is obtained as the weather data of the category in the target weather data set of the designated location to be pushed this time.

5. The method according to claim 4, wherein: Before obtaining the average of the weather data of the category detected by the three meteorological stations at the same location and at the same time as the weather data of the category in the target weather data set to be pushed this time, the method includes: It is detected and determined that the absolute value of the difference between the weather data of the category at the same location and at the same time detected by any two of the three meteorological stations is less than or equal to a preset threshold.

6. The method according to claim 5, wherein: The method further comprises: If the absolute value of the difference between the weather data of the category detected at the same location and at the same time by any two of the three meteorological stations is greater than the preset threshold, the weather data of the category in the candidate weather data set is used as the weather data of the category in the target weather data set of the designated location to be pushed this time; And send an alarm prompt to the equipment of the target data resource party to prompt the target data resource party to conduct an emergency investigation.

7. The method according to any one of claims 1 to 6, wherein: Based on the weather data of at least two reference data resources, before verifying the candidate weather data set of the designated location to be pushed this time and obtaining the target weather data set of the designated location to be pushed this time, the method further includes: Based on the historical weather data of the same type of the designated location acquired last time by the nearest neighbor, the candidate weather data set of the designated location to be pushed this time is filtered.

8. The method according to claim 7, wherein: Based on the historical weather data of the same type of the designated location acquired last time by the nearest neighbor, the candidate weather data set of the designated location to be pushed this time is filtered, including: For the first digital weather data of a preset category in the candidate weather data set, second digital weather data of the same preset category in the historical weather data is used for filtering processing.

9. The method according to claim 8, wherein: The filtering process is performed on the first digital weather data of a preset category in the candidate weather data set by using the second digital weather data of the same preset category in the historical weather data, including: Detecting whether an absolute value of a difference between the first digital weather data and the second digital weather data corresponding to the preset category in the candidate weather data set is greater than a preset numerical threshold; If so, the first digital weather data candidate weather data set corresponding to the preset category in the candidate weather data set is filtered out.

10. The method according to any one of claims 1-6 and 8-9, wherein: Based on the weather data of at least two reference data resources, the candidate weather data set of the designated location to be pushed is verified and processed to obtain the target weather data set of the designated location to be pushed, including: Based on the preset weather data acquisition rules, the candidate weather data set of the designated location to be pushed this time is acquired from the weather data of the target data resource party.

11. The method according to any one of claims 1-6 and 8-9, wherein: Based on the weather data of at least two reference data resources, after verifying the candidate weather data set of the designated location to be pushed this time and obtaining the target weather data set of the designated location to be pushed this time, the method further includes: For the weather data to be pushed this time, which is live weather data and the category is temperature, obtain the real-time temperature value to be pushed this time; Detecting whether the real-time temperature value is within the forecast temperature range for the day; If not, update the forecast temperature range for the day based on the real-time temperature value; And based on the updated forecast temperature range for the day, data push for the weather application is performed.

12. A weather data processing device, comprising: A verification processing module is used to verify the candidate weather data set of the designated location to be pushed this time based on the weather data of at least two reference data resource parties, so as to obtain the target weather data set of the designated location to be pushed this time; the candidate weather data set of the designated location to be pushed this time is obtained from the target data resource party; The target data resource party is different from at least two reference data resource parties; A push processing module, used to push data for the weather application based on the target weather data set of the designated location to be pushed this time; Wherein, the verification processing module is used to: For each category of weather data in the candidate weather data set, determine whether there is weather data of the category provided by the at least two reference data resources at the same location and at the same time that is consistent with the weather data of the category in the candidate weather data set within a preset error range; If so, the weather data of the category in the candidate weather data set is used as the weather data of the category in the target weather data set for the designated location to be pushed this time.

13. The device according to claim 12, wherein: The verification processing module is further used for: If there is no weather data of the category at the same location and time provided by the at least two reference data resources that is consistent with the weather data of the category in the candidate weather data set within a preset error range, detecting whether there is weather data of the category at the same location and time provided by at least two candidate data resources among the at least two reference data resources that is consistent within a preset error range; If so, then from the weather data of the category at the same location and at the same time provided by the at least two candidate data resource parties, obtain the weather data of the category at the same location and at the same time provided by the candidate data resource party with the highest priority, as the weather data of the category in the target weather data set of the designated location to be pushed this time.

14. The device according to claim 13, wherein: The verification processing module is further used for: If there are no weather data of the category at the same location and at the same time provided by at least two candidate data resources among the at least two reference data resources, and the weather data is consistent within a preset error range, obtain weather data of the category at the same location and at the same time detected by three weather stations that meet preset conditions and are around the weather station of the target data resource party that is the source of the candidate weather data set; Based on the weather data of the category detected by the three meteorological stations at the same location and at the same time, the weather data of the category in the target weather data set of the designated location to be pushed this time is obtained.

15. The device according to claim 14, wherein: The verification processing module is further used for: If the weather data of the category is in digital format, the average of the weather data of the category detected by the three meteorological stations at the same location and at the same time is obtained as the weather data of the category in the target weather data set of the designated location to be pushed this time.

16. The device according to claim 15, wherein: The verification processing module is further used for: It is detected and determined that the absolute value of the difference between the weather data of the category at the same location and at the same time detected by any two of the three meteorological stations is less than or equal to a preset threshold.

17. The device according to claim 16, wherein: The verification processing module is further used for: If the absolute value of the difference between the weather data of the category detected at the same location and at the same time by any two of the three meteorological stations is greater than the preset threshold, the weather data of the category in the candidate weather data set is used as the weather data of the category in the target weather data set of the designated location to be pushed this time; And send an alarm prompt to the equipment of the target data resource party to prompt the target data resource party to conduct an emergency investigation.

18. The device according to any one of claims 12 to 17, wherein: The device also includes: The filtering processing module is used to filter the candidate weather data set of the designated location to be pushed this time based on the historical weather data of the same type of the designated location acquired last time by the nearest neighbor.

19. The device according to claim 18, wherein: The filtering processing module is used to: For the first digital weather data of a preset category in the candidate weather data set, second digital weather data of the same preset category in the historical weather data is used for filtering processing.

20. The device according to claim 19, wherein The filtering processing module is used to: Detecting whether an absolute value of a difference between the first digital weather data and the second digital weather data corresponding to the preset category in the candidate weather data set is greater than a preset numerical threshold; If so, the first digital weather data candidate weather data set corresponding to the preset category in the candidate weather data set is filtered out.

21. The device according to any one of claims 12-17 and 19-20, wherein: The device also includes: The acquisition module is used to acquire the candidate weather data set of the designated location to be pushed this time from the weather data of the target data resource party based on the preset weather data acquisition rules.

22. The device according to claim 21, wherein: The acquisition module is further used to acquire the real-time temperature value to be pushed this time when the weather data to be pushed this time is live weather data and the category is temperature; The verification processing module is used to detect whether the real-time temperature value is within the forecast temperature range of the day; If not, update the forecast temperature range for the day based on the real-time temperature value; The push processing module is used to push data for the weather application based on the updated forecast temperature range for the day.

23. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 11.

24. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-11.

25. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 11.

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