A method, apparatus, and computer-readable storage medium for generating a data heat map

Abstract

The present application discloses a method, apparatus, and computer-readable storage medium for generating a data heat map. The method includes: obtaining a first service data table, where the first service data table includes latitude and longitude information of different locations; encoding the latitude and longitude information to obtain a first hash code value; generating a plurality of hash blocks based on the first hash code value; matching the first hash code value corresponding to the hash block with a preset mapping table to obtain first element-related information that matches the first hash code value, where the preset mapping table includes second element-related information of a plurality of elements and second hash code values that match the second element-related information; evaluating the first element-related information to obtain a first evaluation value; and generating a data heat map based on the first evaluation value. Through the above manner, the present application can facilitate the allocation of personnel and materials according to the data heat map.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and in particular, to a method, apparatus, and computer-readable storage medium for generating a data heat map. Background Art

[0002] With the continuous increase in housing, vehicles, etc., higher requirements are put forward for comprehensive capabilities such as the response speed of rescue, dispatching and command, on-site operations, and scientific rescue. However, the following problems exist in the related rescue systems: it is impossible to intuitively see the local rescue forces, and it is impossible to efficiently and accurately conduct personnel dispatching. Summary of the Invention

[0003] This application provides a method, apparatus, and computer-readable storage medium for generating a data heat map, which can facilitate the invocation of personnel and materials according to the data heat map.

[0004] To solve the above technical problems, the technical solution adopted by this application is: providing a method for generating a data heat map, the method includes: obtaining a first service data table, the first service data table includes latitude and longitude information of different locations; encoding the latitude and longitude information to obtain a first hash code value; generating a plurality of hash blocks based on the first hash code value; matching the first hash code value corresponding to the hash block with a preset mapping table to obtain first element-related information matching the first hash code value, the preset mapping table includes second element-related information of a plurality of elements and a second hash code value matching the second element-related information; evaluating the first element-related information to obtain a first evaluation value; generating a data heat map based on the first evaluation value.

[0005] To solve the above technical problems, another technical solution adopted by this application is: providing a heat map generation apparatus, the heat map generation apparatus includes a memory and a processor connected to each other, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, it is used to implement the method for generating a data heat map in the above technical solution.

[0006] To solve the above technical problems, another technical solution adopted by this application is: providing a computer-readable storage medium, the computer-readable storage medium is used to store a computer program, and when the computer program is executed by the processor, it is used to implement the method for generating a data heat map in the above technical solution.

[0007] Through the above scheme, the beneficial effects of the present application are: first obtain a first business data table including longitude and latitude information of different locations; then encode the longitude and latitude information to generate a first hash code value; then use the first hash code value to realize the division of hash blocks and generate multiple hash blocks; then match the first hash code value corresponding to the hash block with the preset mapping table to obtain the first element related information; then evaluate the first element related information to obtain a first evaluation value; then use the first evaluation value to generate a data heat map, which can intuitively display the element conditions of each location, and can be applied in multiple fields to assist fire brigades to carry out fire dispatch faster, avoid unnecessary losses, and speed up rescue. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0009] Figure 1 It is a flow chart of an embodiment of a method for generating a data heat map provided by the present application;

[0010] Figure 2 It is a flow chart of another embodiment of the method for generating a data heat map provided by the present application;

[0011] Figure 3 is a schematic diagram of multiple hash blocks provided by this application;

[0012] Figure 4 It is a schematic diagram of the distribution of security forces provided by this application;

[0013] Figure 5 It is a structural schematic diagram of an embodiment of a thermal map generating device provided by the present application;

[0014] Figure 6 It is a structural schematic diagram of an embodiment of a computer-readable storage medium provided by the present application. DETAILED DESCRIPTION

[0015] The present application is further described in detail below in conjunction with the accompanying drawings and examples. It is particularly noted that the following examples are only used to illustrate the present application, but are not intended to limit the scope of the present application. Similarly, the following examples are only some embodiments of the present application rather than all embodiments, and all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0016] References to "embodiments" in this application mean that specific features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0017] It should be noted that the terms "first", "second", and "third" in this application are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", and "third" may explicitly or implicitly include at least one such feature. In the description of this application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0018] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of an embodiment of the method for generating a data heat map provided by this application. The method includes:

[0019] S11: Obtain a first business data table.

[0020] The first business data table can be obtained from a database, or data sent by other devices can be received and stored in the first business data table. The first business data table can be a fire department organization table or other types of tables. The first business data table includes longitude and latitude information of different locations, and the longitude and latitude information includes the longitude of the location and the latitude of the location.

[0021] S12: Encode the longitude and latitude information to obtain a first hash code value.

[0022] For the obtained first business data table, the longitude and latitude information of each location can be extracted from the first business data table first; then the longitude and latitude in the longitude and latitude information are encoded using an encoding method to obtain a first hash (Hash) code value. The encoding method can be a hash encoding or a geohash algorithm.

[0023] S13: Generate a plurality of hash blocks based on the first hash code value.

[0024] After completing the encoding of the longitude and latitude information, the first hash code value can be used to generate multiple hash blocks, and the size of each hash block can be the same. Specifically, since each location corresponds to a first hash code value, locations with the same first hash code value can be divided into the same hash block to obtain multiple hash blocks. Alternatively, the area corresponding to all the longitude and latitude information is denoted as the target area, the target area is divided into multiple sub-areas of the same size, and then it is determined whether there are locations with longitude and latitude information in the sub-area. If there are locations with longitude and latitude information in the sub-area, the sub-area is used as a hash block, and the mode of the first hash code values of these locations is used as the first hash code value of the hash block. If there are no locations with longitude and latitude information in the sub-area, no processing is performed.

[0025] S14: Match the first hash code value corresponding to the hash block with the preset mapping table to obtain the first element-related information that matches the first hash code value.

[0026] The element-related information (including the first element-related information and the second element-related information) may include information such as the quantity and category of at least one element. The second element-related information corresponding to the elements of multiple locations is pre-statistically analyzed, and the longitude and latitude information corresponding to the second element-related information is encoded according to the above encoding method to obtain the second hash code value, so as to form a preset mapping table, which includes the second element-related information of multiple elements and the second hash code value that matches the second element-related information.

[0027] Further, after obtaining the first hash code value of the hash block, the first hash code value corresponding to each hash block can be matched with the preset mapping table to determine whether there is a second hash code value in the preset mapping table that matches the first hash code value. If there is a second hash code value in the preset mapping table that matches the first hash code value, the second element-related information corresponding to the second hash code value is used as the first element-related information of the hash block.

[0028] It can be understood that when measuring whether the first hash code value and the second hash code value match, it can be determined whether the two are exactly the same. If the two are exactly the same, it is determined that they match. Alternatively, it can also be determined whether the similarity between the first hash code value and the second hash code value is large. If the similarity is large, it is determined that they match.

[0029] S15: Evaluate the first element-related information to obtain a first evaluation value.

[0030] After obtaining the first relevant element information of each hash block, a preset scoring mechanism can be used to evaluate the first relevant element information to generate a first evaluation value. Specifically, the sub-evaluation values of all elements corresponding to the hash block can be counted first, and the first evaluation value of the hash block can be generated by adding all the sub-evaluation values. For example, assuming that the types of elements are A - C, the number of element A is 3, and the sub-evaluation value of element A is 1; the number of element B is 5, and the sub-evaluation value of element B is 2; the number of element C is 1, and the sub-evaluation value of element C is 4, then the first evaluation value = (3×1)+(5×2)+(1×4) = 17.

[0031] S16: Generate a data heat map based on the first evaluation value.

[0032] After obtaining the first evaluation value, each hash block can be plotted on the corresponding map, and the first evaluation value can be marked on the map; or the hash block can be processed, for example, transformed into an image block of a preset size, and then the image block can be added to the map, and the first evaluation value corresponding to the image block can be added; or, other processing can be performed on the first evaluation value, such as: normalization or weighted processing, etc., and then the processed first evaluation value can be displayed on the map to obtain a data heat map, which includes a military point map, a fire heat map or a security force distribution map.

[0033] When a fire occurs, due to the lack of security forces, it is impossible to achieve efficient fire extinguishing, resulting in losses. Therefore, visually presenting the security forces in a certain area has practical application significance. Based on this, this embodiment provides a solution for generating a fire and security force distribution map based on hash coding, which can visually display the security forces in each area on the map, assist the fire department to dispatch firefighters faster, and can enhance the security forces according to the local situation, thereby avoiding unnecessary losses.

[0034] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of another embodiment of the method for generating a data heat map provided by this application. The method includes:

[0035] S21: Select information on a set number of elements of locations from the third service data table to generate a second service data table.

[0036] In order to obtain the required business table, the data source needs to be connected to the data platform, and the source address of the data, the table name of the data source, and the data update method are determined. The data update method is pre-set, such as: update once a day, update once every day at 6 o'clock, or update in real time. Establish a receiving table (i.e., the third business data table) in the data platform, establish a data connection after determining the access method; then perform the data access operation; finally, check whether the amount of data in the receiving table is consistent with the amount of data in the data source to avoid data loss. Specifically, the third business data table can be a fire agency organization table. The data access method is implemented through Kafka, and the data consumed in Kafka is transferred to the hive data warehouse in a daily increment to update the data.

[0037] Furthermore, during the development process, it is often not necessary to perform development operations on all the fields in the receiving table. Therefore, some data can be taken out according to the key business fields (i.e., the information of the elements) required by the customer and the key business fields required by the business. Although this operation cannot reduce the amount of data, it can greatly reduce the number of data fields, avoid redundant operations when performing subsequent geohash calculation operations, and reduce load pressure. For example: the original data volume in the fire department organization table has more than 50 fields, but many fields are not used in actual business, and customers do not need to display so many fields. Therefore, for each piece of data in the table, 5 key business fields can be selected.

[0038] S22: Deduplication processing is performed on the second business data table and / or dirty data in the second business data table is removed to obtain the first business data table.

[0039] The above operation of extracting key business fields may extract other fields, resulting in some duplicate data in the process of extracting key business fields, so deduplication operation can also be performed; for example, using the ditinct statement for processing, or performing window operation to deduplicate based on the primary key, the windowing effect is better.

[0040] In other embodiments, since there may be some dirty data in the second business data table, the dirty data may also be removed. This embodiment does not remove all dirty data when removing dirty data, because this method may affect the accuracy of the main business. The solution adopted in this embodiment only needs to remove some data in the key business fields that do not meet the requirements / format of normal data, which can minimize the amount of data as much as possible without affecting the accuracy of the final result.

[0041] S23: Encode the hash block using a preset encoding function to obtain a first hash code value.

[0042] The input parameters of the preset encoding function include longitude value, latitude value, and weight value, and the weight value corresponds to the first hash encoding value. Specifically, the geohash algorithm can be used in Java code to generate a geohash encoding function with the required precision according to business needs and import it into the data platform. The geohash encoding values of each table can be calculated using hivesql code through the geohash encoding function.

[0043] Further, the specific geohash encoding scheme is as follows:

[0044] 1) First, divide the latitude range (-90°, 90°) into two intervals (-90°, 0°) and (0°, 90°). If the target latitude (i.e., the latitude in the longitude and latitude information) is in the former interval, the encoding is 0; otherwise, the encoding is 1.

[0045] For example, assume the target latitude is 39.92324°. Since 39.92324° belongs to (0°, 90°), the encoding is 1.

[0046] 2) Divide (0°, 90°) into two intervals (0°, 45°) and (45°, 90°). Since 39.92324° is in (0°, 45°), the encoding is 0. And so on until the precision meets the requirements, and the hash encoding value of 39.92324° is "1011 1000 1100 0111 1001".

[0047] It can be understood that the encoding length of geohash can be specified according to the custom weight value, that is, there is a mapping relationship between the weight value and the encoding length. A mapping table can be established in advance, which includes multiple weight values and the corresponding code lengths. In actual use, by matching the currently set weight value with this mapping table, the encoding length required currently can be determined. Further, the geohash encoding function is as follows:

[0048] geohash('latitude', 'longitude', weight value) formula (1)

[0049] Among them, in formula (1), the weight value is a custom value. The larger the weight value, the larger the obtained encoding length and the larger the range it represents.

[0050] S24: Generate multiple hash blocks based on the first hash encoding value.

[0051] S24 is the same as S13 in the above embodiment and will not be elaborated here.

[0052] S25: Match the first hash encoding value corresponding to the hash block with the preset mapping table to obtain the first element-related information that matches the first hash encoding value.

[0053] The similarity between the first hash code value and the second hash code value can be calculated; then it is determined whether the similarity is greater than a preset similarity, which is a threshold set based on experience or application needs; if the similarity is greater than the preset similarity, the second factor related information matching the second hash code value is determined as the first factor related information.

[0054] In a specific embodiment, taking the fire protection and security business as an example, the two-dimensional coordinate points are represented by a string of characters (i.e., hash code values) through the geohash algorithm, and the nearby security elements are found by comparing the similarity of the geohash values. The security elements include fire agencies, fire stations, fire agency personnel, fire hydrants, and fire trucks, so that the security elements can be used to generate a security force distribution map.

[0055] S26: Calculate the sum of the sub-evaluation values ​​of each element in the first element related information corresponding to the hash block to obtain a first evaluation value.

[0056] Obtain a sub-evaluation value of each element in the first element related information corresponding to the hash block; accumulate the sub-evaluation values ​​to obtain a first evaluation value; specifically, each hash block may correspond to at least two weight values, calculate the sum of the sub-evaluation values ​​of all elements of the hash block corresponding to the weight value, and generate a first evaluation value.

[0057] In a specific embodiment, the first hash code value includes a first code value and a second code value, and a preset coding function can be used to encode the hash block to obtain the first code value, and the input parameters of the preset coding function include longitude value, latitude value and first weight value, and the first weight value corresponds to the first code value; the preset coding function is used to encode the hash block to obtain the second code value, and the input parameters of the preset coding function include longitude value, latitude value and second weight value, and the second weight value corresponds to the second code value; it is determined whether the first preset number of characters in the first code value is the same as the first preset number of characters in the second code value; if the first preset number of characters in the first code value is the same as the first preset number of characters in the second code value, it is determined that the first hash block is the same as the second hash block, and the first hash block is the hash block corresponding to the first weight value, and the second hash block is the hash block corresponding to the second weight value. For example, if the first code value is "1011 10", the second code value is "1011 1000", and the preset number is 5, it is considered that the hash block corresponding to the first code value and the hash block corresponding to the second code value are the same hash block.

[0058] S27: Based on the first evaluation value of the current hash block and the first evaluation values ​​of the surrounding hash blocks, the first evaluation value is updated to obtain a second evaluation value.

[0059] The surrounding hash blocks are the hash blocks located around the current hash block. The weighted sum of the first evaluation value of the current hash block and the first evaluation values of all surrounding hash blocks is calculated to obtain the third evaluation value. For each hash block, the sum of the third evaluation values corresponding to all weight values is calculated to generate the second evaluation value.

[0060] In a specific embodiment, taking the distribution map of fire and police forces as an example, assume that a firefighter accumulates 1 point (civilian staff not counted), a fire hydrant accumulates 3 points, a fire truck accumulates 6 points, and a mini fire station accumulates 6 points; the first weight value is 0.8, and the hash block corresponding to the first weight value is denoted as the geohash6 block; the second weight value is 0.6, and the hash block corresponding to the second weight value is denoted as the geohash5 block.

[0061] 1) Calculate the first evaluation value of each geohash6 block, and then spread the evaluation value of each geohash6 block to the surrounding 8 geohash6 blocks to calculate the third evaluation value of each geohash6 block.

[0062] For example, as Figure 3 shown, assume that the geohash6 blocks are denoted as G1 - G9, and their corresponding first evaluation values are S1 - S9 respectively. Then, the following formula is used to update the first evaluation value corresponding to G5 to obtain the corresponding third evaluation value:

[0063] L1 = 0.8×(S1 + S2 + S3 + S4 + S6 + S7 + S8 + S9) + S5 Formula (2)

[0064] By processing the first evaluation values corresponding to G1 - G4 and G6 - G9 respectively in a calculation method similar to Formula (2), the corresponding third evaluation values can be obtained.

[0065] 2) Calculate the first evaluation value of each geohash5 block, and then spread the evaluation value of each geohash5 block to the surrounding 8 geohash5 blocks to calculate the third evaluation value of each geohash5 block.

[0066] 3) Add the third evaluation value of each geohash5 block to the third evaluation value of the corresponding geohash6 block to obtain the second evaluation value.

[0067] It can be understood that different weight values can also be set according to the types of elements. For example: assume that the element types are denoted as K1 - K2, K1 corresponds to two weight values P1 and P2, and K2 corresponds to two weight values P3 and P4. The implementation solution is similar to the above embodiment and will not be elaborated here.

[0068] S28: Generate a data heat map based on the second evaluation value.

[0069] On the map corresponding to the longitude and latitude information, multiple image blocks corresponding to hash blocks are generated, and a second evaluation value is marked on each image block to generate a data heat map. The colors of the image blocks corresponding to different second evaluation values are different. Specifically, each hash block generates a 20×20 image block on the map. The larger the second evaluation value in each image block, the lighter the color of the image block and the higher the security force; the smaller the second evaluation value in each image block, the darker the color and the weaker the security force. For example, as Figure 4 shown, Figure 4 The area without marked numbers in Figure 4 is the area where longitude and latitude information has not been obtained. Through the

[0070] image shown, the deployment of the security force can be intuitively seen, which is convenient for subsequent scheduling of personnel and materials.

[0071] Please refer to Figure 5 , Figure 5 FIG. is a schematic structural diagram of an embodiment of a heat map generation device provided by the present application. The heat map generation device 50 includes a memory 51 and a processor 52 connected to each other. The memory 51 is used to store a computer program, and when the computer program is executed by the processor 52, it is used to implement the method for generating a data heat map in the above embodiment. The heat map generation device 50 can be a data platform.

[0072] Please refer to Figure 6 , Figure 6 FIG. is a schematic structural diagram of an embodiment of a computer-readable storage medium provided by the present application. The computer-readable storage medium 60 is used to store a computer program 61, and when the computer program 61 is executed by the processor, it is used to implement the method for generating a data heat map in the above embodiment.

[0073] The computer-readable storage medium 60 can be various media that can store program codes, such as a server, a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disc.

[0074] In several embodiments provided by the present application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0075] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0076] In addition, each functional unit in various embodiments of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0077] The above are only the embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present application.

Claims

1. A method for generating a data heat map, characterized in that Including: Obtain a first business data table, where the first business data table includes longitude and latitude information of different locations; Encode the longitude and latitude information based on the geohash algorithm to obtain a first hash code value; Generate a plurality of hash blocks based on the first hash code value; Match the first hash code value corresponding to the hash block with a preset mapping table to obtain first element-related information that matches the first hash code value. The preset mapping table includes second element-related information of multiple elements and second hash code values that match the second element-related information; Obtain the sub-evaluation value of each element in the first element-related information corresponding to the hash block; accumulate the sub-evaluation values to obtain a first evaluation value; Update the first evaluation value based on the first evaluation value of the current hash block and the first evaluation values of surrounding hash blocks to obtain a second evaluation value. The surrounding hash blocks are the hash blocks located around the current hash block; Generate the data heat map based on the second evaluation value.

2. The method for generating a data heat map according to claim 1, wherein The step of generating a plurality of hash blocks based on the first hash code value includes: Divide the locations with the same first hash code value into the same hash block to obtain the plurality of hash blocks.

3. The method for generating a data heat map according to claim 2, wherein The method further includes: Encode the hash block using a preset encoding function to obtain the first hash code value. The input parameters of the preset encoding function include longitude value, latitude value, and weight value, and the weight value corresponds to the first hash code value; Calculate the sum of the sub-evaluation values of all elements of the hash block corresponding to each weight value to generate a first evaluation value; Perform a weighted sum of the first evaluation value of the hash block corresponding to each weight value and the first evaluation values of the corresponding surrounding hash blocks to obtain a third evaluation value; Calculate the sum of the third evaluation values corresponding to all weight values to generate the second evaluation value.

4. The method for generating a data heat map according to claim 3, wherein The first hash code value includes a first code value and a second code value. The method further includes: Encode the hash block using a preset encoding function to obtain the first code value. The input parameters of the preset encoding function include longitude value, latitude value, and a first weight value; Encode the hash block using a preset encoding function to obtain the second code value. The input parameters of the preset encoding function include the longitude value, latitude value, and a second weight value; Determine whether the first preset number of digits in the first code value is the same as the first preset number of digits in the second code value; If so, determine that the hash block corresponding to the first weight value and the hash block corresponding to the second weight value are the same hash block.

5. The method for generating a data heat map according to claim 1, characterized in that The method further includes: Generate a plurality of image blocks corresponding to the hash blocks on the map corresponding to the longitude and latitude information, and label the second evaluation value on the image blocks to generate the data heat map, where the colors of the image blocks corresponding to different second evaluation values are different.

6. The method for generating a data heat map according to claim 1, wherein The step of matching the first hash code value corresponding to the hash block with a preset mapping table to obtain first element-related information that matches the first hash code value includes: Calculate the similarity between the first hash code value and the second hash code value; Determine whether the similarity is greater than a preset similarity; If so, determine the second element-related information that matches the second hash code value as the first element-related information.

7. The method for generating a data heat map according to claim 1, wherein The step of obtaining the first service data table includes: Select information on a set number of elements at the location from the third service data table to generate a second service data table; Perform deduplication processing on the second service data table and / or remove dirty data in the second service data table to obtain the first service data table.

8. A heat map generation device, characterized in that, It includes a mutually connected memory and a processor. Among them, the memory is used to store a computer program, and when the computer program is executed by the processor, it is used to implement the method for generating a data heat map described in any one of claims 1-7.

9. A computer-readable storage medium for storing a computer program, characterized in that, When the computer program is executed by the processor, it is used to implement the method for generating a data heat map described in any one of claims 1-7.

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