CN116975169A - Information acquisition method, device, equipment, medium and product - Google Patents

Abstract

Embodiments of the present disclosure disclose an information acquisition method, device, equipment, medium and product. The method includes: acquiring and storing each real-time feature data and its corresponding real-time location; acquiring the regional location of each grid in the geofence; determining The real-time feature data whose real-time location is within the regional location of the grid in the geo-fence is used as the real-time feature data of the geo-fence. This technical solution can greatly reduce storage costs and is highly scalable, and supports real-time feature data query for new geofences.

Description

Information acquisition methods, devices, equipment, media and products

Technical field

The embodiments of the present disclosure relate to the field of Internet technology, and specifically relate to an information acquisition method, device, equipment, medium and product.

Background technique

A geofence refers to a virtual geographical boundary enclosed by a virtual fence. Its shape can be any polygon, and its regional scope can be represented by a set of clockwise longitude and latitude arrays. The real-time characteristic data of the geofence refers to It is the real-time characteristic data of the entities within the geo-fence, such as the real-time characteristic data of the vehicle in the geo-fence, the real-time characteristic data of the order, etc. The calculation of real-time characteristic data of any geofence has very important guiding significance for the refined operation of the business. The real-time characteristics of the specific business within the geofence can be analyzed through the real-time characteristic data of the geofence. According to the preset management strategy, based on the The real-time characteristics of specific services can be adjusted and managed in a timely manner for specific services within the geofence; for example, in a two-wheeled electric vehicle operation and maintenance power replacement scenario, the real-time power replacement of the geofence can be determined through real-time feature data analysis of the geofence. Value, according to the preset power exchange strategy, the two-wheeled electric vehicles in the geo-fence are exchanged based on the power exchange value. The power exchange strategy can be a strategy that the higher the power exchange value, the priority is given to the power exchange. In this way, it can Priority is given to battery swapping for two-wheeled electric vehicles within geo-fences with high battery swapping value, providing guidance on battery swapping operations for operation and maintenance, improving the quality of battery swapping operations, and reducing the proportion of order losses caused by low power. Therefore, combined with the preset policy algorithm, real-time feature data based on geofences can intelligently drive the business to conduct refined operations in the geographical dimension in real time, giving full play to the value of data drive.

At present, the main solution for obtaining real-time feature data of geofences is: when receiving real-time feature data, determine the geofence to which it belongs based on the longitude and latitude in the real-time feature data, and bind the real-time feature data to the geofence to which it belongs. After storage is determined, query services for real-time feature data of geofences are provided to the outside world. However, this method needs to store each geofence and its corresponding real-time feature data in advance, so the storage cost increases linearly with the increase in the number of fences; if a new geofence is added, the real-time feature data of the geofence must be in that geofence. Real-time feature data can only be obtained after the geofence is added. Real-time feature data acquisition for new geofences is not supported.

Contents of the invention

Embodiments of the present disclosure provide an information acquisition method, device, equipment, media and products.

In a first aspect, an embodiment of the present disclosure provides an information acquisition method.

Specifically, the information acquisition method includes:

Obtain and store each real-time feature data and its corresponding real-time location;

Get the regional location of each grid in the geofence;

Real-time feature data whose real-time location is within the regional location of the grid in the geo-fence is determined as the real-time feature data of the geo-fence.

In a possible implementation, obtaining the regional location corresponding to each grid in the geofence includes:

Obtain the regional location of the geofence;

Based on the regional position of the geofence, the regional positions of the first grid and the second grid in the geofence are obtained, the first grid includes a grid completely covered by the geofence, and the second grid is The grid includes a grid partially covered by the geofence, and the first grid and the second grid are preset fixed-position grids.

In a possible implementation, determining the real-time feature data that the real-time location is within the regional location of the grid in the geo-fence, as the real-time feature data of the geo-fence, includes:

Determine the first real-time characteristic data in which the real-time position is located within the regional position of the first grid as the real-time characteristic data of the geofence;

The method also includes:

Determining that the real-time position is located in the second real-time feature data within the regional position of the second grid;

Third real-time feature data whose real-time location is within the regional location of the geofence is selected from the second real-time feature data as the real-time feature data of the geofence.

In a possible implementation, filtering the third real-time feature data whose real-time location is within the regional location of the geofence from the second real-time feature data includes:

Determine a ray using the real-time position corresponding to the second real-time feature data as a starting point;

If the number of intersections between the ray and the boundary of the geofence is an odd number, it is determined that the second real-time feature data is the third real-time feature data whose real-time position is within the regional position of the geofence;

If the number of intersections between the ray and the boundary of the geofence is an even number, it is determined that the real-time position corresponding to the second real-time feature data is located outside the regional position of the geofence.

In a possible implementation, each grid in the geofence includes a GeoHash grid, and based on the regional location of the geofence, the first grid completely covered by the geofence and the first grid that is completely covered by the geofence are obtained. A second grid covered by the geofence section, including:

Based on the regional location of the geofence, the preset minimum level grid completely covered by the geofence is determined to be the first grid, and the preset minimum level grid partially covered by the geofence is determined to be the first layer part. Cover grid;

Traverse the next level grid in the first layer partially covered grid, determine the next level grid in the first layer partially covered grid that is fully covered by the geofence as the first grid, determine the The next level grid in the first layer of partially covered grids that is partially covered by the geofence is the next layer of partially covered grids, until the next level grid of the next layer of partially covered grids is the default the maximum level grid, then determine the maximum level grid that is fully covered by the geofence in the next layer of partially covered grids as the first grid, determine the maximum level grid that is partially covered by the area where the geofence is located Grid is the second grid;

Among them, the area of the grid at this level is larger than the area of the grid at the next level.

In a possible implementation, based on the regional position of the geofence, it is determined that the preset minimum level grid that is fully covered by the geofence is the first grid, and the preset minimum level grid that is partially covered by the geofence is determined. The default minimum level grid is the first layer partial coverage grid, including:

Determine the minimum circumscribed rectangle of the geofence based on the regional location of the geofence;

Based on the longitude and latitude coordinates of the diagonal points of the minimum circumscribed rectangle, determine the preset minimum level grid that is fully or partially covered by the minimum circumscribed rectangle as the third grid;

The third grid is traversed, the third grid completely covered by the geofence is determined to be the first grid, and the third grid partially covered by the geofence is determined to be the first layer partially covered grid.

In a possible implementation, a preset intermediate level grid is included between the maximum level grid and the minimum level grid;

Wherein, in each level grid between the minimum level grid and the intermediate level grid, the area of the grid area at this level is M times the area of the grid area at the next level, and in the intermediate level grid In each level grid between the maximum level grid, the area of the grid area at this level is N times the area of the grid area at the next level, the M is greater than N, and the M and N are integers greater than or equal to 0.

In a possible implementation, the real-time location includes real-time latitude and longitude information, and the first real-time characteristic data that determines that the real-time location is located within the regional location of the first grid is used as the real-time location of the geofence. Characteristic data, including:

If the longitudes in the real-time latitude and longitude information are located between the longitudes of the diagonal points of the first grid and the dimensions are between the latitudes of the diagonal points of the first grid, then the real-time latitude and longitude information is determined Located within the regional location of the first grid, the first real-time feature data corresponding to the real-time longitude and latitude information is determined to be the real-time feature data of the geofence.

In a second aspect, an embodiment of the present disclosure provides an information acquisition device.

Specifically, the information acquisition device includes:

The first acquisition module is configured to acquire and store each real-time feature data and its corresponding real-time location;

The second acquisition module is configured to acquire the regional location of each grid in the geofence;

The first determination module is configured to determine the real-time characteristic data that the real-time location is located within the regional position of the grid in the geo-fence as the real-time characteristic data of the geo-fence.

In a possible implementation, the second acquisition module is configured as:

Obtain the regional location of the geofence;

Based on the regional position of the geofence, the regional positions of the first grid and the second grid in the geofence are obtained, the first grid includes a grid completely covered by the geofence, and the second grid is The grid includes a grid partially covered by the geofence, and the first grid and the second grid are preset fixed-position grids.

In a possible implementation, the first determination module is configured as:

Determine the first real-time characteristic data in which the real-time position is located within the regional position of the first grid as the real-time characteristic data of the geofence;

The device also includes:

a second determination module configured to determine second real-time feature data where the real-time position is located within the regional position of the second grid;

A filtering module configured to filter third real-time feature data whose real-time location is within the regional location of the geofence from the second real-time feature data as real-time feature data of the geofence.

In a possible implementation, the filtering module is configured as:

Determine a ray using the real-time position corresponding to the second real-time feature data as a starting point;

If the number of intersections between the ray and the boundary of the geofence is an odd number, it is determined that the second real-time feature data is the third real-time feature data whose real-time position is within the regional position of the geofence;

If the number of intersections between the ray and the boundary of the geofence is an even number, it is determined that the real-time position corresponding to the second real-time feature data is located outside the regional position of the geofence.

In a possible implementation, each grid in the geofence includes a GeoHash grid, and the second acquisition module obtains the first network completely covered by the geofence based on the regional location of the geofence. The grid and the portion of the second grid partially covered by the geofence is configured as:

Based on the regional location of the geofence, the preset minimum level grid completely covered by the geofence is determined to be the first grid, and the preset minimum level grid partially covered by the geofence is determined to be the first layer part. Cover grid;

Traverse the next level grid in the first layer partially covered grid, determine the next level grid in the first layer partially covered grid that is fully covered by the geofence as the first grid, determine the The next level grid in the first layer of partially covered grids that is partially covered by the geofence is the next layer of partially covered grids, until the next level grid of the next layer of partially covered grids is the default the maximum level grid, then determine the maximum level grid that is fully covered by the geofence in the next layer of partially covered grids as the first grid, determine the maximum level grid that is partially covered by the area where the geofence is located Grid is the second grid;

Among them, the area of the grid at this level is larger than the area of the grid at the next level.

In a possible implementation, in the second acquisition module, based on the regional location of the geofence, it is determined that the preset minimum level grid completely covered by the geofence is the first grid, and it is determined that the grid is the first grid. The preset minimum level grid that is partially covered by the geofence is the first layer that partially covers the grid and is configured as:

Determine the minimum circumscribed rectangle of the geofence based on the regional location of the geofence;

Based on the longitude and latitude coordinates of the diagonal points of the minimum circumscribed rectangle, determine the preset minimum level grid that is fully or partially covered by the minimum circumscribed rectangle as the third grid;

The third grid is traversed, the third grid completely covered by the geofence is determined to be the first grid, and the third grid partially covered by the geofence is determined to be the first layer partially covered grid.

In a possible implementation, a preset intermediate level grid is included between the maximum level grid and the minimum level grid;

Wherein, in each level grid between the minimum level grid and the intermediate level grid, the area of the grid area at this level is M times the area of the grid area at the next level, and in the intermediate level grid In each level grid between the maximum level grid, the area of the grid area at this level is N times the area of the grid area at the next level, the M is greater than N, and the M and N are integers greater than or equal to 0.

In a possible implementation, the real-time location includes real-time latitude and longitude information, and the first real-time feature data that determines that the real-time location is located within the regional location of the first grid is used as the first real-time feature data. The section describing real-time feature data for geofences is configured as:

If the longitudes in the real-time latitude and longitude information are located between the longitudes of the diagonal points of the first grid and the dimensions are between the latitudes of the diagonal points of the first grid, then the real-time latitude and longitude information is determined Located within the regional location of the first grid, the first real-time feature data corresponding to the real-time longitude and latitude information is determined to be the real-time feature data of the geofence.

In a third aspect, embodiments of the present disclosure provide an electronic device, including a memory and a processor. The memory is used to store one or more computer instructions that support an information acquisition device to perform the above information acquisition method. The processor is configured for executing computer instructions stored in the memory. The information acquisition device may also include a communication interface for the information acquisition device to communicate with other devices or communication networks.

In a fourth aspect, embodiments of the present disclosure provide a computer-readable storage medium for storing computer instructions used by an information acquisition device, which includes computer instructions for executing the above information acquisition method for the information acquisition device.

In a fifth aspect, embodiments of the present disclosure provide a computer program product, including a computer program/instruction, wherein when the computer program/instruction is executed by a processor, the steps in the above information acquisition method are implemented.

The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects:

The above technical solution only needs to store each real-time feature data and its corresponding real-time location. When querying the real-time feature data of the geofence, it only needs to be based on the regional location of each grid in the geofence, and the queried real-time data can be directly retrieved. The real-time feature data located within the regional location of the grid in the geo-fence is used as the real-time feature data of the geo-fence; in this way, there is no need to store the specific geo-fence and its corresponding real-time feature data in advance, only each real-time feature needs to be stored The data and its corresponding real-time location greatly reduce storage costs and are highly scalable. For new geofences, the above solution can also be used to query and obtain them in real time.

It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and do not limit the embodiments of the present disclosure.

Description of the drawings

Other features, objects, and advantages of embodiments of the present disclosure will become more apparent from the following detailed description of the non-limiting embodiments in conjunction with the accompanying drawings. In the attached picture:

Figure 1 shows a flow chart of an information acquisition method according to an embodiment of the present disclosure;

Figure 2 shows a schematic diagram of a scene for obtaining grids in a geofence according to an embodiment of the present disclosure;

Figure 3 shows a schematic diagram of a location determination scenario inside and outside a geo-fence according to an embodiment of the present disclosure;

Figure 4 shows a schematic diagram of a scene for obtaining grids in a geofence according to an embodiment of the present disclosure;

Figure 5 shows a schematic diagram of the existing scenario for obtaining grids in geofences;

Figure 6 shows a schematic diagram of a scene for obtaining grids in a geofence according to an embodiment of the present disclosure;

Figure 7 shows a schematic diagram of a comparison scene of grids in a geofence obtained in two ways according to an embodiment of the present disclosure;

Figure 8 shows a schematic diagram of a location query scenario inside and outside the grid according to an embodiment of the present disclosure;

Figure 9 shows a structural block diagram of an information acquisition device according to an embodiment of the present disclosure;

Figure 10 shows a structural block diagram of an electronic device according to an embodiment of the present disclosure;

FIG. 11 is a schematic structural diagram of a computer system suitable for implementing an information acquisition method according to an embodiment of the present disclosure.

Detailed ways

Hereinafter, exemplary implementations of embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Furthermore, for the sake of clarity, parts irrelevant to describing the exemplary embodiments are omitted in the drawings.

In the embodiments of the present disclosure, it should be understood that terms such as "comprising" or "having" are intended to indicate the presence of features, numbers, steps, acts, components, portions, or combinations thereof disclosed in this specification, and are not intended to indicate Excludes the possibility that one or more other features, numbers, steps, acts, parts, portions or combinations thereof exist or are added.

In addition, it should be noted that the embodiments and features in the embodiments of the present disclosure can be combined with each other as long as there is no conflict. The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

As mentioned above, at present, the main solution for obtaining real-time feature data of geofences is: when receiving real-time feature data, determine the geofence to which it belongs based on the longitude and latitude in the real-time feature data, and then, use the real-time feature data to Store it in the geofence to which it belongs, bind it to the geofence to which it belongs, and then provide query services for real-time characteristic data of the geofence to the outside world. However, this method needs to store each geofence and its corresponding real-time feature data in advance, so the storage cost increases linearly with the increase in the number of fences; if a new geofence is added, the real-time feature data of the geofence must be in that geofence. The real-time feature data can only be obtained after the geofence is added, and the real-time feature data of the newly added geofence is not supported. In addition, since the geofence and its corresponding real-time feature data need to be stored, it needs to rely heavily on the management of the geofence. and determination services. These two services involve business life cycle management of geofences, fence determination algorithms, etc., and the cost of business understanding and maintenance is high.

In order to solve the above problems, the present disclosure provides an information acquisition solution. This solution only needs to store each real-time feature data and its corresponding real-time location. When querying the real-time feature data of a geofence, it only needs to be based on each feature in the geofence. If the regional location of the grid is determined, the queried real-time feature data located within the regional location of the grid in the geofence can be directly used as the real-time feature data of the geofence; in this way, there is no need to store specific geofences in advance. and its corresponding real-time feature data. It only needs to store each real-time feature data and its corresponding real-time location, which greatly reduces storage costs and has strong scalability. Moreover, for new geofences, the above solution can also be used to query and obtain them in real time.

Figure 1 shows a flow chart of an information acquisition method according to an embodiment of the present disclosure. As shown in Figure 1, the information acquisition method includes the following steps S101-S103:

In step S101, obtain and store each real-time feature data and its corresponding real-time location;

In step S102, obtain the regional location of each grid in the geofence;

In step S103, real-time feature data whose real-time location is within the regional location of the grid in the geo-fence is determined as the real-time feature data of the geo-fence.

In an embodiment of the present disclosure, the information acquisition method may be applicable to computers, computing devices, electronic devices, servers, service clusters, etc. that can perform acquisition of real-time feature data of geofences.

In an embodiment of the present disclosure, the real-time feature data refers to real-time streaming data of various entities, such as real-time streaming data of vehicles, real-time streaming data of orders, real-time streaming data of work orders, etc., and the real-time location refers to It is the positioning position when the real-time feature data is generated. The real-time position can be the longitude and latitude position.

In one embodiment of the present disclosure, a geofence refers to a virtual geographical boundary surrounded by a virtual fence, and its shape can be any polygon. As an example, FIG. 2 shows a method of obtaining geographic information according to an embodiment of the present disclosure. The scene diagram of the grid in the fence, as shown in Figure 2, may be the shape of the geofence 201.

In one embodiment of the present disclosure, the electronic map area is divided into non-intersecting network grids according to a certain shape, such as triangles/quadrangles/hexagons, etc., and these grids are called grids. The geofence covers multiple grids, and the regional positions of these grids belong to the regional positions of the geofence. Therefore, in this embodiment, the regional position of each grid in the geofence can be used to represent the regional scope of the geofence.

In the embodiment of the present disclosure, when you need to query the real-time feature data of a certain geofence (it can be an existing geofence or a new geofence), you can directly query the real-time location corresponding to each stored real-time feature data. For real-time feature data whose real-time location is within the regional location of the grid in the geofence, the queried real-time feature data will be used as the real-time feature data of the geofence; in this way, there is no need to store specific geofences and their corresponding real-time features in advance. Data only needs to store each real-time feature data and its corresponding real-time location, which greatly reduces storage costs and has strong scalability. It also supports the acquisition of real-time feature data for new geofences. In addition, this solution does not need to be bound to geofence storage, so it does not rely on service components such as fence management and fence determination to provide geofences. Geofences of any shape can be obtained to query their real-time characteristic data.

In an embodiment of the present disclosure, obtaining the regional location corresponding to each grid in the geofence includes:

Obtain the regional location of the geofence;

Based on the regional position of the geofence, the regional positions of the first grid and the second grid in the geofence are obtained, the first grid includes a grid completely covered by the geofence, and the second grid is The grid includes a grid partially covered by the geofence, and the first grid and the second grid are preset fixed-position grids.

In this embodiment, the regional location of the geofence can be the latitude and longitude information of the boundary of the geofence. Each grid on the map is a pre-divided grid with a fixed position. It can be based on the regional location of the geofence and The regional position of each grid is determined to determine the grid in the geofence, and then the regional position of each grid in the geofence is obtained.

In this embodiment, the geofence can be an arbitrary polygon, so there may be some grids at the boundary of the geofence, with one part inside the geofence and the other part outside the geofence. These parts can be described as The grid covered by the geofence is recorded as the second grid, and the grids all within the geofence can be recorded as the first grid.

In an embodiment of the present disclosure, determining the real-time feature data that the real-time location is within the regional location of the grid in the geo-fence, as the real-time feature data of the geo-fence, includes:

Determine the first real-time characteristic data in which the real-time position is located within the regional position of the first grid as the real-time characteristic data of the geofence;

The method also includes:

Determining that the real-time position is located in the second real-time feature data within the regional position of the second grid;

Third real-time feature data whose real-time location is within the regional location of the geofence is selected from the second real-time feature data as the real-time feature data of the geofence.

In this implementation, since the first grid is completely covered by the geofence, the first real-time feature data whose real-time location is located in the first grid area must be the real-time feature data within the geofence.

In this implementation, since the second grid is partially covered by a geofence, the second real-time feature data whose real-time location is within the first grid area may be the real-time feature data within the geofence, or It may not be the real-time feature data within the geo-fence. If the second real-time feature data is directly used as the real-time feature data of the geo-fence, it will cause the real-time feature data within the geo-fence to be inaccurate, and the subsequent calculation of the real-time feature data for the specific business will be inaccurate. Errors may also occur in characteristics. In order to improve accuracy, after obtaining the second real-time characteristic data, the third real-time characteristic data whose real-time location is within the regional location of the geofence can be filtered out from the second real-time characteristic data. The third real-time feature data is used as the real-time feature data of the geofence.

This implementation can make a second accurate determination of the real-time feature data located in the second grid located at the boundary of the geofence, and can realize accurate query of the real-time feature data of any polygonal geofence.

In an embodiment of the present disclosure, filtering the third real-time feature data whose real-time location is within the regional location of the geofence from the second real-time feature data may include the following steps:

Determine a ray using the real-time position corresponding to the second real-time feature data as a starting point;

If the number of intersections between the ray and the boundary of the geofence is an odd number, it is determined that the second real-time feature data is the third real-time feature data whose real-time position is within the regional position of the geofence;

If the number of intersections between the ray and the boundary of the geofence is an even number, it is determined that the real-time position corresponding to the second real-time feature data is located outside the regional position of the geofence.

In this implementation manner, a ray method can be used to filter out the third real-time feature data from the second real-time feature data.

For example, Figure 3 shows a schematic diagram of a location determination scenario inside and outside a geofence according to an embodiment of the present disclosure. As shown in Figure 3, there are multiple second grids 302 at the boundary 301 of the geofence. These second grids 302 Part is located within the geo-fence, and part is located outside the geo-fence. The first real-time position 303 and the second real-time position 304 corresponding to each second real-time characteristic data are used as an example for illustration. Taking the first real-time position 303 and the second real-time position 304 respectively. For the second real-time position 304, select any direction as the starting point to create the first ray and the second ray. The number of intersections between the first ray and the boundary of the geofence is 1, which is an odd number. Then determine the first ray corresponding to the first real-time position 303. The second real-time feature data is the third real-time feature data; the number of intersections between the second ray and the boundary of the geofence is 2, which is an even number. Then it is determined that the second real-time feature data corresponding to the second real-time position 304 is not the third real-time feature data. Real-time feature data.

It can be clearly seen from Figure 3 that the first real-time position 303 is located within the geo-fence, and the second real-time position 304 is located outside the geo-fence. Therefore, the ray method can be used to accurately filter out the third real-time feature data from the second real-time feature data. Feature data enables accurate query of real-time feature data of any geofence.

In a possible implementation, in the above information acquisition method, each grid in the geofence includes a GeoHash grid, and based on the regional location of the geofence, the first grid completely covered by the geofence is obtained. A grid and a second grid partially covered by said geofence, including:

Based on the regional location of the geofence, the preset minimum level grid completely covered by the geofence is determined to be the first grid, and the preset minimum level grid partially covered by the geofence is determined to be the first layer part. Cover grid;

Traverse the next level grid in the first layer partially covered grid, determine the next level grid in the first layer partially covered grid that is fully covered by the geofence as the first grid, determine the The next level grid in the first layer of partially covered grids that is partially covered by the geofence is the next layer of partially covered grids, until the next level grid of the next layer of partially covered grids is the default the maximum level grid, then determine the maximum level grid that is fully covered by the geofence in the next layer of partially covered grids as the first grid, determine the maximum level grid that is partially covered by the area where the geofence is located Grid is the second grid;

Among them, the area of the grid at this level is larger than the area of the grid at the next level.

In this implementation, GeoHash is essentially a way of spatial indexing. Its basic principle is to understand the earth as a two-dimensional plane and recursively decompose the plane into smaller sub-blocks. Each sub-block has a certain range of longitude and latitude. Same encoding. GeoHash converts two-dimensional longitude and latitude into strings. Each string represents a rectangular area. All coordinates within the rectangular range share the string. The longer the string, the higher the accuracy. The corresponding rectangular range The smaller. Each rectangular area is a GeoHash grid.

For example, the positioning position is usually represented by longitude and latitude. For example, the target longitude and latitude (39.923201, 116.390705) represents a location. It does not represent a specific point, but generally refers to an area. The range of the area is related to the value accuracy of the longitude and latitude. D. The area represented by the longitude and latitude can be calculated through the GeoHash algorithm to obtain a comparable string. The specific calculation process is as follows:

S1. Divide the interval (latitude initial interval range [-90,90], longitude initial interval range [-180,180]) in half into left and right intervals, and calculate whether the target longitude and latitude fall in the left interval or the right interval, and whether they fall in the left interval Then it takes 0, and the right interval takes 1, and the first bit of binary code is obtained;

S2. Then divide the interval where the target longitude and latitude is located in half to update the left and right intervals, and continue to calculate whether the target longitude and latitude fall in the left interval or the right interval. If it falls in the left interval, it will be taken as 0, and if it falls in the right interval, it will be taken as 1, to get the next digit. Binary encoding.

S3. When the encoding length reaches the length requirement of the business, such as 20 bits, the binary representation of longitude 39.923201 is: 10111000110001111001, and the binary representation of latitude 116.390705 is: 11010010110001000100.

S4. According to the rule of "put longitude in even-numbered bits and latitude in odd-numbered bits", intersperse and combine the obtained binary codes to obtain a new binary string: 11100 11101 00100 01111 00000 01101 01011 00001.

S5. According to the comparison table of base32, translate every 5 bits of the binary string into a string to obtain the target GeoHash string 45EPANLB corresponding to the target longitude and latitude (39.923201, 116.390705). The length of the string is 8 bits, indicating the level of the GeoHash grid. It is 8 floors.

It can be seen from the above that if each character in the Geohash string is composed of 5 bits, these 5 bits can have 32 different combinations (0 ~ 31), so that we can divide the entire map area into 32 areas, Geohash string For each bit increase, the level of the GeoHash grid corresponding to the Geohash string increases by one level. The rectangular size of each level of grid is 32 times the rectangular size of the next level of grid.

For example, Figure 4 shows a schematic diagram of a scene for obtaining grids in a geofence according to an embodiment of the present disclosure. As shown in Figures 2 and 4, the preset minimum level grid may be the 5th level grid. After obtaining the regional location of the geofence 201, it is possible to first determine that the preset minimum level grid covered by the geofence 201 is the first grid. As shown in Figure 2, there is no first grid, and it is determined that the grid is the first grid. The preset minimum level grids partially covered by the geofence are the first layer partially covered grids, namely Grid A, Grid B, Grid C, Grid E, Grid F, Grid G, in Figure 2. Grid J, Grid K and Grid L.

Then, the next level grid in the first layer partially covered grid, that is, the 6th level grid, can be traversed. Taking grid F in the first layer partially covered grid as an example, as shown in Figure 4, you can Traverse the 32 sixth-level grids in the grid F, determine the sixth-level grids in the grid F that are all covered by the geographical fence as the first grid 2021, and set the grid in the grid F that is covered by the geographical fence. The sixth-level grid partially covered by the fence is determined as the next partially covered grid 2022. Of course, all sixth-level grids in grid F located outside the geofence are discarded.

In this way, for the partial coverage grid of the next layer, it can be divided into 32 equal parts of the next-level grid, and the traversal to the next-level grid continues.

At the same time, the maximum level grid is set. If the next level grid of the next layer partially covered grid is the preset maximum level grid such as the 8th level grid, then the next layer partially covered grid is determined. The 8th-level grid that is fully covered by the geofence is the first grid. It is determined that the 8th-level grid that is partially covered by the area where the geofence is located is the second grid. No need to remove the next-level grid. .

In this way, multiple first grids and second grids within the geofence can be obtained. From the above, it can be seen that each first grid has a different grid level, and the area areas of the first grids at different levels are different.

In a possible implementation, based on the regional position of the geofence, the preset minimum level grid that is fully covered by the geofence is determined to be the first grid, and the preset minimum level grid that is partially covered by the geofence is determined. The default minimum level grid is the first layer partial coverage grid, including:

determining a minimum enclosing rectangle of the boundary of the geofence based on the regional location of the geofence;

Based on the longitude and latitude coordinates of the diagonal points of the minimum circumscribed rectangle, determine the preset minimum level grid that is fully or partially covered by the minimum circumscribed rectangle as the third grid;

The third grid is traversed, the third grid completely covered by the geofence is determined to be the first grid, and the third grid partially covered by the geofence is determined to be the first layer partially covered grid.

In this embodiment, after obtaining the regional location of the geofence, the minimum circumscribed rectangle of the geofence can be obtained. The minimum circumscribed rectangle refers to the maximum size of the polygonal geofence represented by two-dimensional coordinates (such as latitude and longitude coordinates). The range is the rectangle whose lower boundary is determined by the maximum abscissa, minimum abscissa, maximum ordinate, and minimum ordinate of each vertex of the given polygonal geofence. For example, as shown in FIG. 2 or FIG. 4 , the rectangle 203 is the smallest circumscribed rectangle of the geofence 201 .

In this embodiment, based on the longitude and latitude coordinates of the diagonal points of the minimum circumscribed rectangle, that is, the maximum abscissa, minimum abscissa, maximum ordinate, and minimum ordinate of each vertex of the above-mentioned polygonal geofence, it can be calculated from the lower left corner Go to the upper right corner and start to calculate the preset minimum level grid that is fully covered or partially covered by the minimum circumscribed rectangle, that is, grid A-grid L is the third grid.

In this implementation, the third grid is traversed, and the third grid completely covered by the geofence is determined to be the first grid (there is no first grid in the scene shown in Figure 2), and it is determined that the third grid is covered by the geofence. The third grid partially covered by the geofence is grid A, grid B, grid C, grid E, grid F, grid G, grid J, grid K and grid L in Figure 2 Partially cover the mesh for the first layer.

In this implementation, it is possible to calculate how many of the four corners of the third grid are located inside the geographical fence. If all four corners are located within the geographical fence, it is determined that the third grid is located within the geographical fence. If the fence is completely covered, it is the first grid; if only one, two or three corners are located within the geofence, it is determined that the third grid is partially covered by the geofence, which is the first layer of partially covered grid. If none of the four corners are within the geofence, the third grid is discarded.

In a possible implementation, a preset intermediate level grid is included between the maximum level grid and the minimum level grid;

Wherein, in each level grid between the minimum level grid and the intermediate level grid, the area of the grid area at this level is M times the area of the grid area at the next level, and at the intermediate level In each level grid between the grid and the maximum level grid, the area of the grid area at this level is N times the area of the grid area at the next level. The M is greater than N, and the M and N are greater than or equal to 0. integer.

In this embodiment, on the next-level partial coverage grid of the geofence boundary, the rectangle of the next-level grid needs to be used for judgment. Removing the next-level grid means that the current partial coverage grid of the next level needs to be equally divided into 32 next-level grids before making a judgment. However, for some grids where most of the area is inside the geofence, continuing to remove the next level of grid will generate a large number of grids, but the benefits are not obvious. Figure 5 shows a schematic diagram of the existing scenario of obtaining a grid in a geofence, illustrating the above situation. As shown in Figure 5, the next layer in grid F partially covers the grid 2022 and continues to be divided into 32 next levels. After gridding, a large number of grids inside the geofence were generated, and only two grids that were not inside the geofence were excluded, so the fitting efficiency was relatively low.

Therefore, this embodiment can use a mixture of 5-bit and 1-bit lengths as segmentation. After a preset length such as 30-bit length (here is the business experience value), every 1 bit is used for encoding, and the above binary 11100 1110100100 is used. 01111 00000 01101 0 1 0 1 1 0 0 0 0 1 is used as an example to illustrate. The first 30 bits are encoded with 5 bits, and the last 10 bits are encoded with 1 bit. The string 45EPANABABBAAAAB is obtained. If the default length is 30 bits, then the middle level grid is the 6th level grid. The first 6 bits of the string are still encoded with 5 bits. Then between the first 6 levels, the area of this level grid is It is M = 32 times the area of the grid area at the next level. After the 6th bit of the string, it is encoded with 1 bit. Then between the grids at each level after the 6th level, the area of the grid area at this level is N=2 times the area of the first-level grid area. For example, Figure 6 shows a schematic diagram of a scene for obtaining a grid in a geofence according to an embodiment of the present disclosure. As shown in Figure 6, 5 bits and 1 bit After mixed encoding, 1-bit encoding once means that if the current grid is at the edge of the geofence, when taking down the next level, it only needs to be divided into two grids for determination, instead of being divided into 32 grids for determination as shown in Figure 5.

By way of example, Figure 7 shows a schematic diagram of a comparison scene of grids in a geofence obtained in two ways according to an embodiment of the present disclosure, as shown in Figures A and B in Figure 7 , Figure A in Figure 7 shows The grid in the geofence 701 obtained by the GeoHash polygon fitting algorithm shown in Figure 5 is shown. Figure B in Figure 7 shows the grid in the geofence 701 obtained by the GeoHash hybrid coding polygon fitting algorithm shown in Figure 6. Grid, under the same geofence and the same fitting accuracy (binary length after merging longitude and latitude), the geofence 701 in Figure 7 A contains 4047 rectangles, and the geofence 701 in Figure B contains 4047 rectangles. Containing 1818 polygons, it can be seen that the number of grids in the geofence determined by the GeoHash hybrid coding polygon fitting algorithm is only half that of the original GeoHash algorithm, which can improve the efficiency of subsequent queries of real-time feature data.

In this implementation, the fitting algorithm based on optimized GeoHash hybrid coding can effectively improve the efficiency of querying real-time feature data while ensuring the fitting accuracy.

In a possible implementation, the real-time location includes real-time latitude and longitude information, and the first real-time characteristic data that determines that the real-time location is located within the regional location of the first grid is used as the real-time location of the geofence. Characteristic data, including:

If the longitudes in the real-time latitude and longitude information are located between the longitudes of the diagonal points of the first grid and the dimensions are between the latitudes of the diagonal points of the first grid, then the real-time latitude and longitude information is determined Located within the regional location of the first grid, the first real-time feature data corresponding to the real-time longitude and latitude information is determined to be the real-time feature data of the geofence.

In this embodiment, the real-time location corresponding to the real-time feature data includes real-time longitude and latitude information, and the real-time longitude and latitude information can be used as an index for query.

In this embodiment, each GeoHash grid is a rectangle. Figure 8 shows a schematic diagram of a location query scenario inside and outside the grid according to an embodiment of the present disclosure. As shown in Figure 8, the GeoHash grid 801 can be composed of The two longitudes and latitudes of the diagonal points of the rectangle are represented by the first corner point 8011 (LatMin, LngMax) and the second corner point 8012 (LatMax, LngMin). When querying whether the real-time position 802 (lat, lng) of a certain real-time feature data Within the area of the GeoHash grid, the specific SQL (Structured Query Language) query template can be:

select*

from db.table

where lng>LngMin and lng<LngMax and lat>LatMin and lat<LatMax.

If the longitudes in the real-time latitude and longitude information are located between LngMin and LngMax of the first grid and the dimensions are between LatMin and LatMax of the first grid, then it is determined that the real-time latitude and longitude information is located between LngMin and LngMax of the first grid. Within the regional location, it is determined that the first real-time feature data corresponding to the real-time latitude and longitude information is the real-time feature data of the geofence.

This implementation can quickly query the latitude and longitude information to obtain real-time feature data whose real-time location is located in the geofence.

The following are device embodiments of the present disclosure, which can be used to perform method embodiments of the present disclosure.

Figure 9 shows a structural block diagram of an information acquisition device according to an embodiment of the present disclosure. The device can be implemented as part or all of an electronic device through software, hardware, or a combination of both. As shown in Figure 9, the information acquisition device includes:

The first acquisition module 901 is configured to acquire and store each real-time feature data and its corresponding real-time location;

The second acquisition module 902 is configured to acquire the regional location of each grid in the geofence;

The first determination module 903 is configured to determine the real-time feature data that the real-time location is located within the regional location of the grid in the geo-fence as the real-time feature data of the geo-fence.

In a possible implementation, the second acquisition module 902 is configured as:

Obtain the regional location of the geofence;

Based on the regional position of the geofence, the regional positions of the first grid and the second grid in the geofence are obtained, the first grid includes a grid completely covered by the geofence, and the second grid is The grid includes a grid partially covered by the geofence, and the first grid and the second grid are preset fixed-position grids.

In a possible implementation, the first determination module 903 is configured as:

Determine the first real-time characteristic data in which the real-time position is located within the regional position of the first grid as the real-time characteristic data of the geofence;

The device also includes:

a second determination module configured to determine second real-time feature data where the real-time position is located within the regional position of the second grid;

A filtering module configured to filter third real-time feature data whose real-time location is within the regional location of the geofence from the second real-time feature data as real-time feature data of the geofence.

In a possible implementation, the filtering module is configured as:

Determine a ray using the real-time position corresponding to the second real-time feature data as a starting point;

If the number of intersections between the ray and the boundary of the geofence is an odd number, it is determined that the second real-time feature data is the third real-time feature data whose real-time position is within the regional position of the geofence;

If the number of intersections between the ray and the boundary of the geofence is an even number, it is determined that the real-time position corresponding to the second real-time feature data is located outside the regional position of the geofence.

In a possible implementation, each grid in the geofence includes a GeoHash grid, and the second acquisition module 902 obtains the first grid completely covered by the geofence based on the regional location of the geofence. The grid and the portion of the second grid partially covered by the geofence are configured as:

Based on the regional location of the geofence, the preset minimum level grid completely covered by the geofence is determined to be the first grid, and the preset minimum level grid partially covered by the geofence is determined to be the first layer part. Cover grid;

Traverse the next level grid in the first layer partially covered grid, determine the next level grid in the first layer partially covered grid that is fully covered by the geofence as the first grid, determine the The next level grid in the first layer of partially covered grids that is partially covered by the geofence is the next layer of partially covered grids, until the next level grid of the next layer of partially covered grids is the default the maximum level grid, then determine the maximum level grid that is fully covered by the geofence in the next layer of partially covered grids as the first grid, determine the maximum level grid that is partially covered by the area where the geofence is located Grid is the second grid;

Among them, the area of the grid at this level is larger than the area of the grid at the next level.

In a possible implementation, the second acquisition module 902 determines, based on the regional location of the geofence, that the preset minimum level grid that is fully covered by the geofence is the first grid, and determines that the grid is the first grid. The preset minimum level grid partially covered by the geofence is configured as: The first layer partially covered grid is configured as:

Determine the minimum circumscribed rectangle of the geofence based on the regional location of the geofence;

Based on the longitude and latitude coordinates of the diagonal points of the minimum circumscribed rectangle, determine the preset minimum level grid that is fully or partially covered by the minimum circumscribed rectangle as the third grid;

The third grid is traversed, the third grid completely covered by the geofence is determined to be the first grid, and the third grid partially covered by the geofence is determined to be the first layer partially covered grid.

In a possible implementation, a preset intermediate level grid is included between the maximum level grid and the minimum level grid;

Wherein, in each level grid between the minimum level grid and the intermediate level grid, the area of the grid area at this level is M times the area of the grid area at the next level, and in the intermediate level grid In each level grid between the maximum level grid, the area of the grid area at this level is N times the area of the grid area at the next level, the M is greater than N, and the M and N are integers greater than or equal to 0.

In a possible implementation, the real-time location includes real-time latitude and longitude information, and the first real-time feature data determined in the first determination module 903 that the real-time location is located within the regional location of the first grid is as The geofence real-time feature data portion is configured as:

If the longitudes in the real-time latitude and longitude information are located between the longitudes of the diagonal points of the first grid and the dimensions are between the latitudes of the diagonal points of the first grid, then the real-time latitude and longitude information is determined Located within the regional location of the first grid, the first real-time feature data corresponding to the real-time longitude and latitude information is determined to be the real-time feature data of the geofence.

In this embodiment, the information acquisition device corresponds to the above-mentioned information acquisition method. For specific details, please refer to the above description of the information acquisition method, which will not be described again here.

The present disclosure also discloses an electronic device. Figure 10 shows a structural block diagram of an electronic device according to an embodiment of the present disclosure. As shown in Figure 10, the electronic device 1000 includes a memory 1001 and a processor 1002; wherein,

The memory 1001 is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 1002 to implement the above method steps.

FIG. 11 is a schematic structural diagram of a computer system suitable for implementing an information acquisition method according to an embodiment of the present disclosure.

As shown in Figure 11, the computer system 1100 includes a processing unit 1101, which can perform the above-described implementation according to a program stored in a read-only memory (ROM) 1102 or loaded from a storage portion 1108 into a random access memory (RAM) 1103. Various processing methods. In the RAM 1103, various programs and data required for the operation of the system 1100 are also stored. The processing unit 1101, ROM 1102 and RAM 1103 are connected to each other via a bus 1104. An input/output (I/O) interface 1105 is also connected to bus 1104.

The following components are connected to the I/O interface 1105: an input section 1106 including a keyboard, a mouse, etc.; an output section 1107 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., speakers, etc.; and a storage section 1108 including a hard disk, etc. ; and a communication section 1109 including a network interface card such as a LAN card, a modem, etc. The communication section 1109 performs communication processing via a network such as the Internet. Driver 1110 is also connected to I/O interface 1105 as needed. Removable media 1111, such as magnetic disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on the drive 1110 as needed, so that a computer program read therefrom is installed into the storage portion 1108 as needed. Wherein, the processing unit 1101 can be implemented as a processing unit such as CPU, GPU, TPU, FPGA, NPU, etc.

In particular, according to embodiments of the present disclosure, the method described above may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product including a computer program tangibly embodied on a readable medium thereof, the computer program including program code for executing the information acquisition method. In such embodiments, the computer program may be downloaded and installed from the network via communications portion 1109 and/or installed from removable media 1111 .

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the roadmap or block diagram may represent a module, segment, or portion of code that contains one or more functions for implementing the specified logical function. Executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown one after another may actually execute substantially in parallel, or they may sometimes execute in the reverse order, depending on the functionality involved. It will also be noted that each block of the block diagram and/or flowchart illustration, and combinations of blocks in the block diagram and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or operations. , or can be implemented using a combination of specialized hardware and computer instructions.

The units or modules described in the embodiments of the present disclosure may be implemented in software or hardware. The described units or modules may also be provided in the processor, and the names of these units or modules do not constitute a limitation on the units or modules themselves under certain circumstances.

As another aspect, embodiments of the present disclosure also provide a computer-readable storage medium. The computer-readable storage medium may be the computer-readable storage medium included in the device described in the above embodiments; it may also exist independently. , a computer-readable storage medium that is not installed in the device. The computer-readable storage medium stores one or more programs, which are used by one or more processors to execute the methods described in the embodiments of the present disclosure.

The embodiment of the present application discloses TS1, an information acquisition method, which is characterized in that the method includes:

Obtain and store each real-time feature data and its corresponding real-time location;

Get the regional location of each grid in the geofence;

Real-time feature data whose real-time location is within the regional location of the grid in the geo-fence is determined as the real-time feature data of the geo-fence.

TS2. The method as described in TS1, wherein,

The method of obtaining the regional location corresponding to each grid in the geofence includes:

Obtain the regional location of the geofence;

Based on the regional position of the geofence, the regional positions of the first grid and the second grid in the geofence are obtained, the first grid includes a grid completely covered by the geofence, and the second grid is The grid includes a grid partially covered by the geofence, and the first grid and the second grid are preset fixed-position grids.

TS3. The method as described in TS2, wherein determining the real-time feature data that the real-time location is located within the regional location of the grid in the geo-fence as the real-time feature data of the geo-fence includes:

Determine the first real-time characteristic data in which the real-time position is located within the regional position of the first grid as the real-time characteristic data of the geofence;

The method also includes:

Determining that the real-time position is located in the second real-time feature data within the regional position of the second grid;

Third real-time feature data whose real-time location is within the regional location of the geofence is selected from the second real-time feature data as the real-time feature data of the geofence.

TS4. The method as described in TS3, wherein filtering the third real-time feature data whose real-time location is within the regional location of the geo-fence from the second real-time feature data includes:

Determine a ray using the real-time position corresponding to the second real-time feature data as a starting point;

If the number of intersections between the ray and the boundary of the geofence is an odd number, it is determined that the second real-time feature data is the third real-time feature data whose real-time position is within the regional position of the geofence;

If the number of intersections between the ray and the boundary of the geofence is an even number, it is determined that the real-time position corresponding to the second real-time feature data is located outside the regional position of the geofence.

TS5. The method according to any one of TS2 to TS4, wherein each grid in the geofence includes a GeoHash grid, and based on the regional position of the geofence, the first grid completely covered by the geofence is obtained. A grid and a second grid partially covered by said geofence, including:

Based on the regional location of the geofence, the preset minimum level grid completely covered by the geofence is determined to be the first grid, and the preset minimum level grid partially covered by the geofence is determined to be the first layer part. Cover grid;

Traverse the next level grid in the first layer partially covered grid, determine the next level grid in the first layer partially covered grid that is fully covered by the geofence as the first grid, determine the The next level grid in the first layer of partially covered grids that is partially covered by the geofence is the next layer of partially covered grids, until the next level grid of the next layer of partially covered grids is the default the maximum level grid, then determine the maximum level grid that is fully covered by the geofence in the next layer of partially covered grids as the first grid, determine the maximum level grid that is partially covered by the area where the geofence is located Grid is the second grid;

Among them, the area of the grid at this level is larger than the area of the grid at the next level.

TS6. The method as described in TS5, wherein based on the regional position of the geofence, it is determined that the preset minimum level grid completely covered by the geofence is the first grid, and the part covered by the geofence is determined The default minimum level grid covered is the first layer partial coverage grid, including:

Determine the minimum circumscribed rectangle of the geofence based on the regional location of the geofence;

Based on the longitude and latitude coordinates of the diagonal points of the minimum circumscribed rectangle, determine the preset minimum level grid that is fully or partially covered by the minimum circumscribed rectangle as the third grid;

The third grid is traversed, the third grid completely covered by the geofence is determined to be the first grid, and the third grid partially covered by the geofence is determined to be the first layer partially covered grid.

TS7. The method as described in TS5, wherein a preset intermediate level grid is included between the maximum level grid and the minimum level grid;

Wherein, in each level grid between the minimum level grid and the intermediate level grid, the area of the grid area at this level is M times the area of the grid area at the next level, and in the intermediate level grid In each level grid between the maximum level grid, the area of the grid area at this level is N times the area of the grid area at the next level, the M is greater than N, and the M and N are integers greater than or equal to 0.

TS8. The method as described in TS5, wherein the real-time location includes real-time latitude and longitude information, and the first real-time feature data that determines that the real-time location is located within the regional location of the first grid is used as the geofence real-time feature data, including:

If the longitudes in the real-time latitude and longitude information are located between the longitudes of the diagonal points of the first grid and the dimensions are between the latitudes of the diagonal points of the first grid, then the real-time latitude and longitude information is determined Located within the regional location of the first grid, the first real-time feature data corresponding to the real-time longitude and latitude information is determined to be the real-time feature data of the geofence.

TS9. An information acquisition device, characterized in that the device includes:

The first acquisition module is configured to acquire and store each real-time feature data and its corresponding real-time location;

The second acquisition module is configured to acquire the regional location of each grid in the geofence;

The determining module is configured to determine the real-time feature data that the real-time location is located within the regional location of the grid in the geo-fence as the real-time feature data of the geo-fence.

TS10. An electronic device, including a memory and a processor; the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement any one of TS1 to TS8 The method steps described.

TS11. A computer-readable storage medium on which computer instructions are stored. When the computer instructions are executed by a processor, the method steps described in any one of TS1 to TS8 are implemented.

TS12. A computer program product, including a computer program/instruction, wherein the computer program/instruction implements the method steps described in any one of TS1 to TS8 when executed by a processor.

The above description is only a description of the preferred embodiments of the present disclosure and the technical principles applied. Persons skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to technical solutions composed of specific combinations of the above technical features, but should also cover the above-mentioned technical solutions without departing from the inventive concept. Other technical solutions formed by any combination of technical features or their equivalent features. For example, a technical solution is formed by replacing the above features with technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to).

Claims (12)

1. An information acquisition method, characterized by including: Obtain and store each real-time feature data and its corresponding real-time location; Get the regional location of each grid in the geofence; Real-time feature data whose real-time location is within the regional location of the grid in the geo-fence is determined as the real-time feature data of the geo-fence. 2. The method according to claim 1, characterized in that obtaining the regional location corresponding to each grid in the geofence includes: Obtain the regional location of the geofence; Based on the regional position of the geofence, the regional positions of the first grid and the second grid in the geofence are obtained, the first grid includes a grid completely covered by the geofence, and the second grid is The grid includes a grid partially covered by the geofence, and the first grid and the second grid are preset fixed-position grids. 3. The method according to claim 2, wherein determining the real-time feature data that the real-time location is located within the regional location of the grid in the geo-fence as the real-time feature data of the geo-fence includes: Determine the first real-time characteristic data in which the real-time position is located within the regional position of the first grid as the real-time characteristic data of the geofence; The method also includes: Determining that the real-time position is located in the second real-time feature data within the regional position of the second grid; Third real-time feature data whose real-time location is within the regional location of the geofence is selected from the second real-time feature data as the real-time feature data of the geofence. 4. The method according to claim 3, wherein filtering the third real-time feature data whose real-time location is within the regional location of the geo-fence from the second real-time feature data includes: Determine a ray using the real-time position corresponding to the second real-time feature data as a starting point; If the number of intersections between the ray and the boundary of the geofence is an odd number, it is determined that the second real-time feature data is the third real-time feature data whose real-time position is within the regional position of the geofence; If the number of intersections between the ray and the boundary of the geofence is an even number, it is determined that the real-time position corresponding to the second real-time feature data is located outside the regional position of the geofence. 5. The method according to any one of claims 2 to 4, characterized in that each grid in the geofence includes a GeoHash grid, and the region location based on the geofence is obtained. The first grid completely covered by the geofence and the second grid partially covered by the geofence include: Based on the regional location of the geofence, the preset minimum level grid completely covered by the geofence is determined to be the first grid, and the preset minimum level grid partially covered by the geofence is determined to be the first layer part. Cover grid; Traverse the next level grid in the first layer partially covered grid, determine the next level grid in the first layer partially covered grid that is fully covered by the geofence as the first grid, determine the The next level grid in the first layer of partially covered grids that is partially covered by the geofence is the next layer of partially covered grids, until the next level grid of the next layer of partially covered grids is the default the maximum level grid, then determine the maximum level grid that is fully covered by the geofence in the next layer of partially covered grids as the first grid, determine the maximum level grid that is partially covered by the area where the geofence is located Grid is the second grid; Among them, the area of the grid at this level is larger than the area of the grid at the next level. 6. The method according to claim 5, characterized in that, based on the regional position of the geofence, it is determined that the preset minimum level grid completely covered by the geofence is the first grid, and it is determined that the grid is the first grid. The default minimum level grid for partial coverage of the above geofence is the first layer partial coverage grid, including: Determine the minimum circumscribed rectangle of the geofence based on the regional location of the geofence; Based on the longitude and latitude coordinates of the diagonal points of the minimum circumscribed rectangle, determine the preset minimum level grid that is fully or partially covered by the minimum circumscribed rectangle as the third grid; The third grid is traversed, the third grid completely covered by the geofence is determined to be the first grid, and the third grid partially covered by the geofence is determined to be the first layer partially covered grid. 7. The method according to claim 5, wherein a preset intermediate level grid is included between the maximum level grid and the minimum level grid; Wherein, in each level grid between the minimum level grid and the intermediate level grid, the area of the grid area at this level is M times the area of the grid area at the next level, and in the intermediate level grid In each level grid between the maximum level grid, the area of the grid area at this level is N times the area of the grid area at the next level, the M is greater than N, and the M and N are integers greater than or equal to 0. 8. The method according to claim 5, wherein the real-time location includes real-time latitude and longitude information, and the first real-time feature data determining that the real-time location is located within the regional location of the first grid is as The real-time characteristic data of the geofence includes: If the longitudes in the real-time latitude and longitude information are located between the longitudes of the diagonal points of the first grid and the dimensions are between the latitudes of the diagonal points of the first grid, then the real-time latitude and longitude information is determined Located within the regional location of the first grid, the first real-time feature data corresponding to the real-time longitude and latitude information is determined to be the real-time feature data of the geofence. 9. An information acquisition device, characterized in that it includes: The first acquisition module is configured to acquire and store each real-time feature data and its corresponding real-time location; The second acquisition module is configured to acquire the regional location of each grid in the geofence; The determining module is configured to determine the real-time feature data that the real-time location is located within the regional location of the grid in the geo-fence as the real-time feature data of the geo-fence. 10. An electronic device, including a memory and a processor; characterized in that the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the claims The method steps described in any one of 1 to 8. 11. A computer-readable storage medium, characterized in that computer instructions are stored thereon, and when the computer instructions are executed by a processor, the method steps of any one of claims 1-8 are implemented. 12. A computer program product, comprising a computer program/instruction, characterized in that, when executed by a processor, the computer program/instruction implements the method steps of any one of claims 1-8.