Data processing method and apparatus, electronic device, and storage medium

Abstract

The present disclosure relates to a data processing method and apparatus, an electronic device, and a storage medium. The method comprises: acquiring first location information flows of a plurality of target Internet of Things devices, wherein the first location information flows represent location information generated when the locations of the target Internet of Things devices change; generating second location information flows on the basis of the first location information flows, wherein the second location information flows represent location distributions of the plurality of target Internet of Things devices in areas of different levels; and aggregating location distribution information of the plurality of target Internet of Things devices in the areas of different levels to obtain virtual layer data of multiple levels. In this way, by means of the generated virtual layer data of multiple levels, the distribution conditions of the Internet of Things devices with changed locations can be conveniently and globally learnt, and the processing efficiency of location information of the Internet of Things devices can be improved to a great extent.

Description

Data processing method, device, electronic device and storage medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is based on the Chinese patent application with application number 202311600994.6 and application date of November 27, 2023, and claims the priority of the Chinese patent application. The entire content of the Chinese patent application is hereby introduced into this application as a reference. Technical Field

[0003] The present disclosure relates to the field of computer technology, and in particular to a data processing method, device, electronic device, and storage medium. Background Art

[0004] With the continuous development of technology, IoT devices have become widely popular. If we can perform near-real-time location distribution statistics on a large number of IoT cards and present the real-time location of IoT card devices in different industries and enterprises, it will provide enterprises and industries with highly timely decision-making support and promote the rapid development of their business.

[0005] In the related art, users in the IoT card industry mainly obtain the latitude and longitude information of the terminal's last Internet access location by calling the API (Application Programming Interface), and usually can only obtain it multiple times for a single card or batch of card numbers, which requires frequent requests to the platform, and the amount of data obtained is small, making it impossible to understand the global distribution of devices, resulting in low efficiency in processing the location information of IoT devices in the related art.

[0006] Summary of the Invention

[0007] To improve the processing efficiency of location information of IoT devices, the present disclosure provides a data processing method, device, electronic device and storage medium.

[0008] According to a first aspect of the present disclosure, there is provided a data processing method, which is executed by a server and includes:

[0009] Obtaining a first location information stream of a plurality of target IoT devices, where the first location information stream represents location information generated when a location of each of the target IoT devices changes;

[0010] generating a second location information stream based on the first location information stream, wherein the second location information stream represents the location distribution of the plurality of target IoT devices in areas at different levels;

[0011] Aggregate the location distribution information of the multiple target IoT devices in the areas of each level to obtain multi-level virtual layer data.

[0012] In one embodiment, the method further comprises:

[0013] Obtain log information when the multiple target IoT devices are connected to the Internet;

[0014] The location information of the multiple target IoT devices when they are connected to the network is obtained based on the log information.

[0015] In one embodiment, obtaining log information of the plurality of target IoT devices when connected to the network includes:

[0016] Obtain target network elements that are communicatively connected with the multiple target IoT devices within a target historical period;

[0017] Obtain log information generated when multiple target IoT devices communicate with the target network element.

[0018] In one embodiment, the method further comprises:

[0019] The target IoT card number and networking time of each target IoT device are obtained based on the log information, and a corresponding relationship between the target IoT card number, networking time and the location information is established.

[0020] In one embodiment, generating the second location information stream based on the first location information stream includes:

[0021] A multi-dimensional tag is added to the first location information stream to obtain a second location information stream, where the multi-dimensional tag includes regional location information and terminal information at different levels.

[0022] In one embodiment, the method further comprises:

[0023] Based on the target IoT card numbers corresponding to the target IoT devices, respectively, obtaining the terminal information corresponding to the target IoT devices;

[0024] Based on the location information corresponding to each of the target IoT devices, obtain location distribution information of each of the target IoT devices in the areas of each level; wherein the location distribution information includes the number of devices corresponding to the corresponding locations of each of the target IoT devices in the areas of each level;

[0025] The multi-dimensional label is obtained based on the terminal information and the location distribution information.

[0026] In one embodiment, the method further comprises:

[0027] receiving data request information sent by a terminal, wherein the data request information is used to request location distribution information of a plurality of the IoT devices in a target display area in a target virtual layer;

[0028] Based on the target virtual layer and the target display area, determining position distribution information of the plurality of IoT devices in the target display area from the target virtual layer;

[0029] The location distribution information is sent to the terminal.

[0030] According to a second aspect of the present disclosure, a data processing method is provided, which is executed by a terminal and includes:

[0031] Obtain target operation information for the target map;

[0032] In response to the target operation information, acquiring a target virtual layer corresponding to the target map and a target display area corresponding to the target virtual layer;

[0033] The location distribution information of the target IoT device is displayed in the target display area.

[0034] In one embodiment, obtaining the target virtual layer corresponding to the target map and the target display area corresponding to the target virtual layer includes:

[0035] Acquire zoom information and a display window of the target map based on the target operation information;

[0036] A target virtual layer currently corresponding to the target map is determined based on the zoom information, and a target display area in the target virtual layer is determined based on the display window.

[0037] In one embodiment, the target operation information includes zoom information generated when the target user performs a zoom-in operation or a zoom-out operation on the target map.

[0038] In one embodiment, displaying the location distribution information of the target IoT device in the target display area includes:

[0039] Sending data request information to a server, wherein the data request information includes the target virtual layer and the target display area;

[0040] Receive the location distribution information sent by the server, and display the location distribution information in a display window.

[0041] In one embodiment, the method further comprises:

[0042] Obtaining a query request input by a target user; the query request includes distribution change information of a target IoT device within a target time period;

[0043] Obtaining location distribution information of the target IoT device at each time within the target time period;

[0044] The location distribution of the target IoT devices in the target display area is dynamically displayed according to the time sequence within the target time period.

[0045] According to a third aspect of the present disclosure, there is provided a data processing device, applied to a server, comprising:

[0046] A first location information stream acquisition module is configured to acquire first location information streams of a plurality of target IoT devices, wherein the first location information streams represent location information generated when the location of each of the target IoT devices changes;

[0047] A second location information stream acquisition module is configured to generate a second location information stream based on the first location information stream, wherein the second location information stream represents the location distribution of the plurality of target IoT devices in areas at different levels;

[0048] The aggregation module is used to aggregate the location distribution information of the multiple target IoT devices in the areas of each level to obtain multi-level virtual layer data.

[0049] According to a fourth aspect of the present disclosure, there is provided a data processing device, applied to a terminal, comprising:

[0050] An information acquisition module is used to obtain target operation information for a target map;

[0051] a layer data acquisition module, configured to acquire, in response to the target operation information, a target virtual layer corresponding to the target map and a target display area corresponding to the target virtual layer;

[0052] The display module is used to display the location distribution information of the target Internet of Things device in the target display area.

[0053] According to a fifth aspect of the present disclosure, an electronic device is provided, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor implements the above method when executing the program.

[0054] According to a sixth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the above method of the present disclosure is implemented.

[0055] The data processing method, device, electronic device and storage medium provided by the embodiments of the present disclosure obtain a first location information stream of multiple target IoT devices, and the first location information stream represents the location information generated when the location of each target IoT device changes. A second location information stream is generated based on the first location information stream. Since the second location information stream represents the location distribution of the multiple target IoT devices in areas of different levels, multi-level virtual layer data can be obtained by aggregating the location distribution information of multiple target IoT devices in areas of each level. In this way, the multi-level virtual layer data generated above facilitates a global understanding of the distribution of IoT devices whose locations have changed, and can greatly improve the processing efficiency of the location information of IoT devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Further details, features and advantages of the present disclosure are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0057] FIG1 is a schematic diagram of a virtual layer provided by an exemplary embodiment of the present disclosure;

[0058] FIG2 is a schematic diagram of a scenario provided by an exemplary embodiment of the present disclosure;

[0059] FIG3 is a flow chart of a data processing method provided by an exemplary embodiment of the present disclosure;

[0060] FIG4 is a flow chart of a data processing method provided by an exemplary embodiment of the present disclosure;

[0061] FIG5 is a schematic block diagram of functional modules of a data processing device provided by an exemplary embodiment of the present disclosure;

[0062] FIG6 is a structural block diagram of an electronic device provided by an exemplary embodiment of the present disclosure;

[0063] FIG7 is a structural block diagram of a computer system provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0064] The following describes embodiments of the present disclosure in more detail with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0065] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0066] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0067] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0068] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0069] It is understandable that before using the technical solutions disclosed in the various embodiments of this disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved in this disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0070] For example, in response to a user's active request, a prompt message is sent to the user to clearly inform the user that the operation requested will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the electronic device, application, server, storage medium, or other software or hardware that performs the operations of the disclosed technical solution based on the prompt message.

[0071] As an optional but non-limiting implementation method, in response to receiving the user's active request, the method of sending a prompt message to the user can be, for example, a pop-up window, and the prompt message can be presented in the form of text in the pop-up window. In addition, the pop-up window can also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device. It is understandable that the above notification and the process of obtaining user authorization are only illustrative and do not constitute a limitation on the implementation method of the present disclosure. Other methods that meet relevant laws and regulations can also be applied to the implementation method of the present disclosure.

[0072] The overall location distribution of IoT terminal devices can provide effective operational analysis and decision-making support for IoT enterprise users, such as targeted advertising, regional financial risk prevention and control, and regional business layout analysis. For example, POS (point of sale) users can quickly adjust operational strategies and POS resource allocation strategies based on the flow and location distribution of sold POS devices. In areas with abnormal POS concentrations, financial risk screening and disposal can be carried out promptly, such as identifying potential money laundering or fraud, to mitigate systemic risks.

[0073] Currently, the number of related connected cards has exceeded billions. We can conduct quasi-real-time location distribution statistics for massive IoT cards, and present enterprise-owned IoT card devices separately for different industries or enterprises in real time and smoothly. This can provide industries or enterprises with highly timely decision-making support, thereby greatly improving the ability of enterprises and industry users to control IoT card devices and support the rapid development of enterprises' businesses.

[0074] In the current IoT technology, the device location information is usually obtained through the API interface via the IoT card number, and then stored and analyzed. This places high demands on the platform's concurrent performance. Due to the small amount of single acquisition, the time required to obtain the location of millions of IoT devices may vary from several hours to several days, making it impossible to quickly grasp the device distribution situation.

[0075] To present location distribution, related technologies often use open-source front-end frameworks, such as HTML5 canvas and SVG (Scalable Vector Graphics) for raster heat maps, or WebGL (Web Graphics Library) for point heat maps in browsers. For average PC users, when the amount of location data exceeds approximately 20,000, significant lag, page unresponsiveness, and even browser crashes can occur due to the varying computing power requirements of data aggregation and rendering. This also places high demands on PC graphics cards and memory configurations, resulting in a poor user experience. For back-end services, a single query exceeding 1,000 data points can significantly impact database and network performance.

[0076] Therefore, in order to solve the above technical problems, the embodiments of the present disclosure collect the Internet information logs of IoT devices in core network elements such as GGSN (Gateway GPRS Support Node), PGW (PDN GateWay), or SMF (Session Management Function) in real time or periodically. In the embodiment, the IoT device corresponds to an IoT card number, so the Internet information log corresponding to the IoT device can be obtained in the core network element based on the IoT card number. The IoT card number and Internet location information of the IoT device can be extracted from the Internet information log to form the original location of the IoT device, and the original location information constitutes information flow 1.

[0077] In the embodiments, online logs can be periodically and in batches pulled in near-real time. The time and corresponding location information points of IoT devices going online can be obtained from the logs to form an original location stream 1. It should be noted that the location information point in the embodiments refers to a piece of location information generated when the location of a terminal or device changes. The location information point includes at least the time of the location change and the location information at the time of the change, such as longitude and latitude information. It is understood that when the distance between the changed location of the terminal or device and the original location is greater than a threshold, the terminal or device's location can be considered to have changed. The threshold can be set as needed. In addition, the location information stream in the embodiments can be a data stream consisting of multiple location information points. For example, if there are 100 POS machines distributed in a certain area, when any POS machine undergoes a significant location change, a location information point is generated. When the location information points continuously generated by the 100 POS machines are transmitted through the data channel, a location information stream is formed. Therefore, the embodiments of the present disclosure mainly obtain the location information of IoT devices whose locations have changed over a period of time. The location information of IoT devices whose locations have not changed can be selectively included or discarded as needed. The embodiments are not limited to this.

[0078] In the embodiment, by obtaining the information stream 1 composed of the original location information as described above, relevant multi-dimensional tags can be added according to the needs of the business scenario to form a location information stream 2, and the location information stream 2 is processed in real time to generate virtual layer data of multiple dimensions. The multi-dimensional tags in the embodiment can exemplarily include one or more of the following combinations: enterprise code, IoT terminal type, terminal model, province, city, district, county, township, POI (Point of Information) and terminal specific location information. The multi-dimensional tags in the embodiment can also include other types of tags, which can be set and added according to the needs of the specific business scenario, and the embodiment is not limited to this.

[0079] It should be noted that in the virtual layers of the embodiments, a layer may only represent a location range of one level. The layer levels can be determined based on actual conditions, for example, including: country, province, city, district, county, township, POI, and the actual location coordinates of the terminal. For example, a province layer consists entirely of the closed boundaries of the province. The layer depth of the layers in the embodiments can be increased or decreased based on actual conditions, and the embodiments are not limited thereto.

[0080] For example, the virtual layers in the embodiment may have obvious geographical size distinctions between the layers. For example, the physical geographical location sizes of a province and a city may differ by about 5-10 times.

[0081] In the embodiment, the virtual layer may include elements, for example, the element may be a province, and the element has a clear and closed position boundary, that is, any position point in the layer must and can only belong to a unique element in the layer. The outline of the element is a fixed value and is static data. It can be silently loaded to the user end during the browser initialization process to achieve static outline preheating of the layer. In addition, an element in the layer can be composed of one or several closed areas, and each closed area can have an element coordinate point to represent the center position of the current element. When data information needs to be added to the element, the element's position coordinate point can be used as a mark. For example, the total number of terminals in the element can be displayed at the element's position coordinate point.

[0082] In an embodiment, the location coordinates of an element (which may be referred to as element coordinates) may include the precise latitude and longitude of the element and the statistical number of terminal location information within the element. For example, the element coordinates of a city A may include the latitude and longitude of the center coordinates of city A, the current real-time number of a certain type of terminal within city A, etc. The element coordinates in this embodiment may be dynamic data. Only during the actual interaction between the map and the user, the real-time data of the element coordinates within the corresponding range of the corresponding virtual layer is dynamically loaded based on the layer and the actual screen area.

[0083] In this embodiment, the most recent internet location information corresponding to the IoT terminal can be parsed from the above log information, and the full and latest log stream can be periodically pulled, for example, once per second. All location information points in the location information stream 1 can be marked with layer attributes according to the settings of the virtual layer. In this embodiment, the format of the location information point is shown in Table 1:

[0084] Table 1:

[0085] The information point identifier in Table 1 above may be the IoT card number of the IoT device.

[0086] In the embodiment, multi-dimensional tags can be added according to virtual layer information or business scenarios, and the above-mentioned location information points are marked by the multi-dimensional tags. The marked location information points form a new information flow, forming information flow 2, as shown in Table 2:

[0087] Table 2:

[0088] The location information stream 2 obtained through the above embodiment can periodically (for example, every second) pull new location information streams in batches through streaming computing. For each batch of stream data, each virtual layer performs real-time aggregation operations based on dimension labels, obtains the location information corresponding to the target element in real time (for example, the number information of IoT devices), and can update it to the corresponding virtual layer. In the embodiment, the virtual layer data can be maintained in a quasi-real-time state.

[0089] As shown in Figure 1, the location information of target elements in a virtual layer with multiple dimensions is aggregated to obtain the location distribution information of IoT terminals corresponding to each virtual layer. As shown in Figure 1, the location information of target elements in a virtual layer with six dimensions is aggregated, where the first dimension can include the total number of terminals in each province, the second dimension can include the total number of terminals in each city, the third dimension can include the total number of terminals in each district and county, the fourth dimension can include the total number of terminals in each township, the fifth dimension can include the total number of terminals within the range of each POI, where the POI can specifically be an important landmark, etc., and the sixth dimension can include the total number of all relevant IoT terminals.

[0090] The above embodiment can process the location information of each IoT terminal in the server. After obtaining the location distribution information of the IoT terminal corresponding to the virtual layer of each dimension, the above-mentioned related virtual layer data can be called through the terminal according to the user's relevant operations or input information.

[0091] In the embodiment, the browser of the terminal or the user end may receive user operations on the map, such as zoom-in or zoom-out operations, and may also receive query information input by the user.

[0092] Specifically, in the embodiments, operation events may include, but are not limited to, zooming in or out on a map interface using a mouse wheel, or zooming in or out on a map interface in electronic map software using a touch screen on a mobile operating system such as Android or Apple. Furthermore, the map scale can be determined based on the operation event input by the user. For example, if a user inputs information about a province, the map scale can be adjusted to display the map interface in the display window to that province. This allows for obtaining information about the corresponding virtual layer in the display window, such as the virtual layer number of the map corresponding to the current display window.

[0093] After obtaining the virtual layer information, the virtual layer information and the edge coordinate information of the currently displayed screen can be transmitted to the server side to obtain the location distribution information of all relevant IoT terminals in the screen display area. As shown in Figure 2, the screen display area in Figure 2 is illustrated by taking a rectangle as an example, and the embodiment is not limited thereto. The coordinates of the four vertices of the screen display area can be obtained, specifically the longitude and latitude information. In the rectangular screen display area, the coordinates of the first vertex are (longitude 1, latitude 1), the coordinates of the second vertex are (longitude 2, latitude 1), the coordinates of the third vertex are (longitude 1, latitude 2), and the coordinates of the first vertex are (longitude 2, latitude 2). By sending a request message to the server through the terminal, the IoT terminal distribution information of the display area in the virtual layer corresponding to the screen display area can be obtained, and the corresponding IoT terminal distribution information can be displayed in the screen display area. For example, after the terminal obtains all relevant IoT terminal data in the display screen area, it can perform relevant effect rendering and present the data to the user.

[0094] In an embodiment, a user terminal or browser may receive an input event input by a user and use the input event as query information. The dimension tag input by the user may include, but is not limited to, the terminal's enterprise code, terminal type, terminal model, or terminal industry code. In addition, after receiving the dimension tag input event input by the user, the user terminal or browser may, in conjunction with a zoom-in or zoom-out event on the map interface, request corresponding virtual layer data from the server, and display the terminal data with the corresponding dimension tag in the screen display area.

[0095] In the embodiments provided by the present disclosure, user-entered dimensional labels, such as enterprise codes, terminal types, or terminal models, can be received through a browser, APP (Application), or map display terminal, and dynamically switched to the corresponding virtual layer in real time, thereby enabling rapid positioning and viewing of the real-time location information distribution of diverse IoT terminal devices. This can enhance the company's insight into IoT terminal devices, support enterprise users in making rapid decisions and efficiently deploying their IoT field strategies, achieve rapid decision-making, real-time observation, and rapid results, and enable timely correction and adjustment of business strategies to optimize business development layouts.

[0096] The disclosed embodiment adds dimension tags to the original location information points of the IoT terminal and performs streaming aggregation calculations based on the dimension tags to form quasi-real-time virtual layers of different dimensions. In this way, when zooming in and out on the map, the virtual layers can be switched in real time to achieve the effect of obtaining the overall geographic location distribution information of the IoT terminal in quasi-real time. Compared with related technologies, the disclosed embodiment can obtain more real-time data, the dimensions of the acquired data are also richer, and the loading and rendering of the map page can be smoother.

[0097] Based on the above embodiment, in another embodiment provided by the present disclosure, a data processing method is provided, as shown in FIG3 , which may include the following steps:

[0098] In step S310, first location information streams of multiple target IoT devices are obtained.

[0099] Among them, the first location information flow represents the location information generated by each target IoT device when its location changes.

[0100] In the embodiment, the target IoT device may refer to a certain type of IoT device, such as a POS machine, or an IoT device belonging to a certain enterprise, etc., but the embodiment is not limited thereto.

[0101] When certain IoT devices transmit location changes, the location information of these IoT devices can be obtained, and the IoT devices with these location changes can be used as target devices. The location information of the target IoT devices can also be used as the first location information stream, which can specifically be location information stream 1 in the above embodiment. In this way, by obtaining location information stream 1 of the target IoT devices with location changes, it is convenient to timely grasp the location changes of these target IoT devices, and then take appropriate measures in a timely manner.

[0102] In step S320 , a second location information stream is generated based on the first location information stream.

[0103] The second location information flow represents the location distribution of multiple target IoT devices in areas at different levels.

[0104] In an embodiment, a multi-dimensional tag may be added to the first location information stream to obtain a second location information stream, the multi-dimensional tag including regional location information and terminal information at different levels. The second location information stream may specifically be location information stream 2 in the above embodiment.

[0105] Specifically, in this embodiment, the terminal information corresponding to each target IoT device can be obtained based on the target IoT card number corresponding to each target IoT device. Furthermore, based on the location information corresponding to each target IoT device, the location distribution information of each target IoT device in each level of area can be obtained. The location distribution information can include the number of devices corresponding to the corresponding location of each target IoT device in each level of area. In this way, a multi-dimensional label can be obtained based on the terminal information and location distribution information.

[0106] In an embodiment, the multi-dimensional tag may include one or more of the following: enterprise code, IoT terminal type, terminal model, province, city, district, county, township, POI, and terminal location information. The multi-dimensional tag can be set accordingly as needed, and the embodiment is not limited thereto.

[0107] In step S330 , the location information of multiple target IoT devices in the regions of each level is aggregated to obtain multi-level virtual layer data.

[0108] In this embodiment, by adding multi-dimensional tags to location information stream 1 to obtain location information stream 2, the location information of IoT devices corresponding to each dimension can be aggregated to obtain the number of IoT devices corresponding to each dimension and the corresponding location distribution information. For example, by aggregating the location information of IoT devices under a certain enterprise code, the location distribution information of IoT devices corresponding to that enterprise code can be obtained, such as the number of devices in each province.

[0109] The data processing method provided by the embodiment of the present disclosure obtains a first location information stream of multiple target IoT devices, and the first location information stream represents the location information generated when the location of each target IoT device changes. A second location information stream is generated based on the first location information stream. Since the second location information stream represents the location distribution of the multiple target IoT devices in areas of different levels, multi-level virtual layer data can be obtained by aggregating the location distribution information of multiple target IoT devices in areas of each level. In this way, the multi-level virtual layer data generated above facilitates a global understanding of the distribution of IoT devices whose locations have changed, and can greatly improve the processing efficiency of the location information of IoT devices.

[0110] Based on the above embodiment, in another embodiment provided by the present disclosure, the method further includes the following steps:

[0111] In step S340, log information of multiple target IoT devices when connected to the Internet is obtained.

[0112] In step S350, location information of multiple target IoT devices when connected to the network is obtained based on the log information.

[0113] In this embodiment, target network elements that were connected to multiple target IoT devices during a target historical period are obtained, and log information generated when multiple target IoT devices communicated with the target network element is obtained. For example, log information about IoT device connections can be collected in real time or periodically from core network elements such as GGSN, PGW, or SMF network elements. In this embodiment, IoT devices are associated with IoT card numbers, so the corresponding Internet access information logs can be obtained from the core network element based on the IoT card numbers. The IoT card numbers and Internet access location information of the IoT devices can be extracted from the log information.

[0114] In an embodiment, the target IoT card number and networking time of each target IoT device can be obtained based on the above-mentioned log information, and a correspondence between the target IoT card number, networking time and location information can be established, so that the networking time and networking location information of the target IoT device can be obtained according to the target IoT card number.

[0115] Based on the above embodiment, in another embodiment provided by the present disclosure, the method may further include the following steps:

[0116] In step S360, data request information sent by the receiving terminal is used to request location distribution information of multiple IoT devices in the target display area in the target virtual layer.

[0117] In step S370, based on the target virtual layer and the target display area, position distribution information of multiple Internet of Things devices in the target display area is determined from the target virtual layer.

[0118] In step S380, the location distribution information is sent to the terminal.

[0119] In an embodiment, when a user performs a related operation on a target map in a terminal, such as zooming in or out on the map, or when the terminal receives related query information input by the user, it sends a data request message to the server. Upon receiving the data request message from the terminal, the server determines the location distribution information of multiple IoT devices in the target display area from the generated virtual layer data, and sends this location distribution information to the terminal, so that upon receiving this location distribution information, the terminal can display information such as the number of related IoT devices in the area display window of the map.

[0120] Based on the above embodiment, in another embodiment provided by the present disclosure, a data processing method is further provided. The method can be applied to a terminal. As shown in FIG4 , the method may include the following steps:

[0121] In step S410, target operation information for the target map is obtained.

[0122] In an embodiment, the target operation information may include zoom information generated when the target user performs a zoom operation or a zoom operation on the target map. The target operation information may also be an input event input by the user in the above embodiment. For details, please refer to the description of the above embodiment and will not be repeated here.

[0123] In an embodiment, when a user zooms in or out on a map, the layer can be automatically switched according to the map scale rules. The layer switching provides the user with location distribution information within the corresponding layer selection range, thereby always ensuring that the number of location elements within the layer of the current map page is within the range that can be smoothly rendered by the terminal, and ensuring that in scenarios with massive location data, the location information of the map can still be presented in real time and smoothly.

[0124] In step S420 , in response to the target operation information, a target virtual layer corresponding to the target map and a target display area corresponding to the target virtual layer are acquired.

[0125] In this embodiment, the zoom information and area display window of the target map can be obtained based on the target operation information, and the target virtual layer currently corresponding to the target map can be determined based on the zoom information. Then, the target display area in the target virtual layer can be determined based on the display window. In this way, the location distribution data of the target display area in the target virtual layer can be requested from the server, so that the location distribution data corresponding to the target display area can be displayed in the display window.

[0126] In step S430, the location distribution information of the target IoT device is displayed in the target display area.

[0127] In an embodiment, the terminal may send data request information to the server, where the data request information may include a target virtual layer and a target display area, receive the position distribution information sent by the server, and display the position distribution information in a display window.

[0128] In this embodiment, when displaying the location distribution information of target IoT terminals on a target map, virtual layer outline data of different dimensions can be pre-loaded and pre-loaded. Based on different business needs, such as those for different enterprises, industries, or regional levels, the map layers can be freely switched, and the real-time coordinate point data of the elements in the virtual layer within the screen area can be obtained and presented to the user terminal for rendering. This can accelerate the response efficiency and smoothness during map zooming, improving the user experience.

[0129] In an embodiment, when heat maps with different degrees of precision need to be presented, appropriate multiple dimensional layers can be selected, and based on the location element information, different forms of rendering of features such as brightness or color can be achieved through layer overlay or layer combination, so as to achieve a flexibly adjustable location heat map. This can help users understand the geographical location distribution of enterprise IoT terminals more intuitively and accurately. For example, through virtual layer overlay, heat map presentation with different accuracy requirements can be achieved.

[0130] In the embodiment provided by the present disclosure, a query request input by a target user can be obtained, and the query request can include distribution change information of the target IoT device within the target time period. And the location distribution information corresponding to each moment within the target time period is obtained. In this way, the location distribution of the target IoT device in the target display area can be dynamically displayed according to the time sequence within the target time period. For example, the user inputs a query request for the target IoT devices in various cities in Province A within Time Period B. By loading the location distribution information of the corresponding area of ​​Province A within Time Period B in the corresponding virtual layer, the distribution changes of the IoT devices from the start time of Time Period B to the end time of Time Period B can be dynamically displayed in the display window of the map, including the dynamic changes in location and the changes in the number of related IoT devices in various cities.

[0131] The data processing method provided by the embodiment of the present disclosure can add multi-dimensional tags to the location information points in the original location information stream of the IoT device based on dimensions such as region or business, to form a new secondary location stream, and based on the secondary location information stream carrying dimension tags, periodically batch pull streaming data to perform streaming calculations to obtain quasi-real-time multi-dimensional location aggregation statistical information, which can provide real-time hot data for different businesses and different location needs. For example, different dimensional regional layers can be presented through regional dimension tags. It is also possible to provide location services for different field scenarios through industry dimension tags, and it is also possible to provide differentiated location customization services for different types of IoT enterprises through enterprise dimension tags.

[0132] Furthermore, the disclosed embodiments can aggregate information points on the location changes of discrete IoT terminals to form a real-time location information stream. This, combined with mature streaming computing in the big data field, can periodically pull location change information point data sets for batch streaming computing to obtain quasi-real-time location data. Compared with separate calculations for each location information point, this can greatly improve computing efficiency, reduce the consumption of computing resources, and improve the real-time performance of data processing.

[0133] In the case of dividing each functional module according to each function, an embodiment of the present disclosure provides a data processing device, which can be a server or a chip applied to a server. Figure 5 is a schematic block diagram of the functional modules of the data processing device provided by an exemplary embodiment of the present disclosure. As shown in Figure 5, the data processing device includes:

[0134] A first location information stream acquisition module 10 is configured to acquire first location information streams of a plurality of target IoT devices, wherein the first location information streams represent location information generated when the location of each target IoT device changes;

[0135] A second location information stream acquisition module 20 is configured to generate a second location information stream based on the first location information stream, wherein the second location information stream represents the location distribution of the plurality of target IoT devices in areas at different levels;

[0136] The aggregation module 30 is used to aggregate the location distribution information of the multiple target IoT devices in the areas of each level to obtain multi-level virtual layer data.

[0137] In another embodiment provided by the present disclosure, the apparatus further includes:

[0138] A log information acquisition module, used to obtain log information when the multiple target IoT devices are connected to the Internet;

[0139] A location information acquisition module is used to obtain the location information of the multiple target Internet of Things devices when they are connected to the network based on the log information.

[0140] In another embodiment provided by the present disclosure, the log information acquisition module is specifically configured to:

[0141] Obtain target network elements that are communicatively connected with the multiple target IoT devices within a target historical period;

[0142] Obtain log information generated when multiple target IoT devices communicate with the target network element.

[0143] In another embodiment provided by the present disclosure, the apparatus further includes:

[0144] The relationship determination module is used to obtain the target IoT card number and networking time of each target IoT device based on the log information, and establish a corresponding relationship between the target IoT card number, networking time and the location information.

[0145] In another embodiment provided by the present disclosure, the second location information flow acquisition module includes:

[0146] A multi-dimensional tag is added to the first location information stream to obtain a second location information stream, where the multi-dimensional tag includes regional location information and terminal information at different levels.

[0147] In another embodiment provided by the present disclosure, the apparatus further includes:

[0148] A terminal information acquisition module, configured to acquire terminal information corresponding to each target IoT device based on a target IoT card number corresponding to each target IoT device;

[0149] A location information determination module, configured to obtain location distribution information of each target IoT device in each level of area based on the location information corresponding to each target IoT device; wherein the location distribution information includes the number of devices corresponding to the corresponding location of each target IoT device in each level of area;

[0150] A multi-dimensional label acquisition module is used to obtain the multi-dimensional label based on the terminal information and the location distribution information.

[0151] In another embodiment provided by the present disclosure, the apparatus further includes:

[0152] A data request information receiving module is used to receive data request information sent by a terminal, wherein the data request information is used to request location distribution information of the plurality of IoT devices in a target display area in a target virtual layer;

[0153] a position distribution information acquisition module, configured to determine, from the target virtual layer and the target display area, position distribution information of the plurality of IoT devices in the target display area;

[0154] An information sending module is used to send the location distribution information to the terminal.

[0155] In the case of dividing each functional module into corresponding functional modules, the embodiment of the present disclosure provides a data processing device, which can be a terminal. The data processing device includes:

[0156] An information acquisition module is used to obtain target operation information for a target map;

[0157] a layer data acquisition module, configured to acquire, in response to the target operation information, a target virtual layer corresponding to the target map and a target display area corresponding to the target virtual layer;

[0158] The display module is used to display the location distribution information of the target Internet of Things device in the target display area.

[0159] In another embodiment provided by the present disclosure, the layer data acquisition module is specifically configured to:

[0160] Acquire zoom information and a display window of the target map based on the target operation information;

[0161] A target virtual layer currently corresponding to the target map is determined based on the zoom information, and a target display area in the target virtual layer is determined based on the display window.

[0162] In another embodiment provided by the present disclosure, the target operation information includes zoom information generated when the target user performs a zoom-in operation or a zoom-out operation on the target map.

[0163] In another embodiment provided by the present disclosure, the display module is specifically configured to:

[0164] Sending data request information to a server, wherein the data request information includes the target virtual layer and the target display area;

[0165] Receive the location distribution information sent by the server, and display the location distribution information in the display window.

[0166] In another embodiment provided by the present disclosure, the apparatus further includes:

[0167] A distribution change information acquisition module is used to obtain a query request input by a target user; the query request includes distribution change information of a target IoT device within a target time period;

[0168] A location distribution information acquisition module is used to obtain the location distribution information of the target IoT device at each moment within the target time period;

[0169] The dynamic display module is used to dynamically display the location distribution of the target Internet of Things devices in the target display area according to the time sequence within the target time period.

[0170] The relevant device part corresponds to the method embodiment. Please refer to the corresponding description of the method embodiment for details and will not be repeated here.

[0171] The data processing device provided by the embodiment of the present disclosure obtains a first location information stream of multiple target IoT devices, and the first location information stream represents the location information generated when the location of each target IoT device changes. A second location information stream is generated based on the first location information stream. Since the second location information stream represents the location distribution of the multiple target IoT devices in areas of different levels, multi-level virtual layer data can be obtained by aggregating the location distribution information of multiple target IoT devices in areas of each level. In this way, the multi-level virtual layer data generated above facilitates a global understanding of the distribution of IoT devices whose locations have changed, and can greatly improve the processing efficiency of the location information of IoT devices.

[0172] An embodiment of the present disclosure further provides an electronic device, comprising: at least one processor; a memory for storing instructions executable by the at least one processor; wherein the at least one processor is configured to execute the instructions to implement the above method disclosed in the embodiment of the present disclosure.

[0173] Figure 6 is a schematic diagram of the structure of an electronic device provided by an exemplary embodiment of the present disclosure. As shown in Figure 6, the electronic device 1800 includes at least one processor 1801 and a memory 1802 coupled to the processor 1801. The processor 1801 can execute the corresponding steps of the above method disclosed in the embodiment of the present disclosure.

[0174] The processor 1801 can also be referred to as a central processing unit (CPU), which can be an integrated circuit chip with signal processing capabilities. Each step in the method disclosed in the embodiments of the present disclosure can be completed by hardware integrated logic circuits in the processor 1801 or by software instructions. The processor 1801 can be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present disclosure can be directly implemented as being executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in the memory 1802, such as a storage medium mature in the art, such as a random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The processor 1801 reads the information in the memory 1802 and, in conjunction with its hardware, completes the steps of the method.

[0175] In addition, when various operations / processes according to the present disclosure are implemented via software and / or firmware, the programs constituting the software can be installed from a storage medium or a network to a computer system having a dedicated hardware structure, such as computer system 1900 shown in FIG7 . When the various programs are installed, the computer system can perform various functions, including those described above. FIG7 is a block diagram of the structure of a computer system provided by an exemplary embodiment of the present disclosure.

[0176] Computer system 1900 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are intended to be examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0177] As shown in FIG7 , computer system 1900 includes a computing unit 1901, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1902 or a computer program loaded from a storage unit 1908 into a random access memory (RAM) 1903. Various programs and data required for the operation of computer system 1900 may also be stored in RAM 1903. Computing unit 1901, ROM 1902, and RAM 1903 are connected to each other via a bus 1904. An input / output (I / O) interface 1905 is also connected to bus 1904.

[0178] Several components within computer system 1900 are connected to I / O interface 1905, including an input unit 1906, an output unit 1907, a storage unit 1908, and a communication unit 1909. Input unit 1906 can be any type of device capable of inputting information into computer system 1900. Input unit 1906 can receive input numeric or character information and generate key input signals related to user settings and / or function control of an electronic device. Output unit 1907 can be any type of device capable of presenting information and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. Storage unit 1908 may include, but is not limited to, a magnetic disk or an optical disk. Communication unit 1909 allows computer system 1900 to exchange information / data with other devices over a network, such as the Internet, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver and / or chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0179] The computing unit 1901 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1901 performs the various methods and processes described above. For example, in some embodiments, the above-mentioned methods disclosed in the embodiments of the present disclosure may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 1908. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 1900 via the ROM 1902 and / or the communication unit 1909. In some embodiments, the computing unit 1901 may be configured to perform the above-mentioned methods disclosed in the embodiments of the present disclosure by any other appropriate means (e.g., by means of firmware).

[0180] An embodiment of the present disclosure further provides a computer-readable storage medium, wherein, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the above method disclosed in the embodiment of the present disclosure.

[0181] The computer-readable storage medium in the embodiments of the present disclosure can be a tangible medium that can contain or store a program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. The above-mentioned computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specifically, the above-mentioned computer-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0182] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0183] The embodiments of the present disclosure further provide a computer program product, including a computer program, wherein when the computer program is executed by a processor, the method disclosed in the embodiments of the present disclosure is implemented.

[0184] In embodiments of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or combinations thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer.

[0185] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0186] The modules, components, or units described in the embodiments of the present disclosure may be implemented in software or hardware. The names of the modules, components, or units do not necessarily limit the modules, components, or units themselves.

[0187] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, and without limitation, exemplary hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0188] The above descriptions are merely some embodiments of the present disclosure and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in the present disclosure.

[0189] Although some specific embodiments of the present disclosure have been described in detail by way of examples, those skilled in the art will appreciate that the above examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Those skilled in the art will appreciate that modifications may be made to the above embodiments without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A data processing method, executed by a server, comprising: Acquire a first location information stream of a plurality of target IoT devices, where the first location information stream represents location information generated when a location of each of the target IoT devices changes; Generate a second location information stream based on the first location information stream, where the second location information stream represents the location distribution of the multiple target IoT devices in areas at different levels; Aggregate the location distribution information of the multiple target IoT devices in the regions of each level to obtain multi-level virtual layer data.

2. The method according to claim 1, wherein: The method further comprises: Obtain log information when the multiple target IoT devices are connected to the Internet; Based on the log information, location information of the multiple target IoT devices when they are connected to the Internet is obtained.

3. The method according to claim 2, wherein: The obtaining log information when the multiple target IoT devices are connected to the Internet includes: Acquire a target network element that is communicatively connected with the plurality of target IoT devices within a target historical period; Obtain log information generated when multiple target IoT devices communicate with the target network element.

4. The method according to claim 2, wherein: The method further comprises: Based on the log information, the target IoT card number and networking time of each target IoT device are obtained, and a corresponding relationship between the target IoT card number, networking time and the location information is established.

5. The method according to claim 1, wherein: The generating a second location information stream based on the first location information stream comprises: A multi-dimensional tag is added to the first location information stream to obtain a second location information stream, wherein the multi-dimensional tag includes regional location information and terminal information at different levels.

6. The method according to claim 5, wherein: The method further comprises: Based on the target IoT card numbers respectively corresponding to the target IoT devices, obtaining the terminal information respectively corresponding to the target IoT devices; Based on the location information corresponding to each of the target IoT devices, respectively, obtaining the location distribution information of each of the target IoT devices in the regions of each level; wherein the location distribution information includes the number of devices corresponding to the corresponding positions of each of the target IoT devices in the regions of each level; The multi-dimensional label is obtained based on the terminal information and the location distribution information.

7. The method according to claim 1, wherein: The method further comprises: The data request information sent by the receiving terminal is used to request the location distribution information of the plurality of IoT devices in the target display area in the target virtual layer; Based on the target virtual layer and the target display area, determining location distribution information of a plurality of the Internet of Things devices in the target display area from the target virtual layer; The location distribution information is sent to the terminal.

8. A data processing method, executed by a terminal, comprising: Obtain target operation information for the target map; In response to the target operation information, acquiring a target virtual layer corresponding to the target map and a target display area corresponding to the target virtual layer; The location distribution information of the target IoT device is displayed in the target display area.

9. The method according to claim 8, wherein: The step of obtaining a target virtual layer corresponding to the target map and a target display area corresponding to the target virtual layer includes: Acquire the zoom information and display window of the target map based on the target operation information; A target virtual layer currently corresponding to the target map is determined based on the zoom information, and a target display area in the target virtual layer is determined based on the display window.

10. The method according to claim 8, wherein: The target operation information includes zoom information generated when the target user performs a zoom-in operation or a zoom-out operation on the target map.

11. The method according to claim 8, wherein: Displaying the location distribution information of the target IoT device in the target display area includes: Sending data request information to a server, wherein the data request information includes the target virtual layer and the target display area; The location distribution information sent by the server is received, and the location distribution information is displayed in a display window.

12. The method according to claim 8, wherein: The method further comprises: Obtaining a query request input by a target user; the query request includes distribution change information of a target IoT device within a target time period; Obtain location distribution information of the target IoT device at each time within the target time period; The location distribution of the target IoT devices in the target display area is dynamically displayed according to the time sequence within the target time period.

13. A data processing device, applied to a server, comprising: A first location information stream acquisition module, used to acquire first location information streams of multiple target IoT devices, wherein the first location information streams represent location information generated when the location of each of the target IoT devices changes; A second location information stream acquisition module, configured to generate a second location information stream based on the first location information stream, wherein the second location information stream represents the location distribution of the plurality of target IoT devices in areas of different levels; The aggregation module is used to aggregate the location distribution information of the multiple target IoT devices in the areas of each level to obtain multi-level virtual layer data.

14. A data processing device, applied to a terminal, comprising: An information acquisition module, used to acquire target operation information for a target map; A layer data acquisition module, used for acquiring a target virtual layer corresponding to the target map and a target display area corresponding to the target virtual layer in response to the target operation information; The display module is used to display the location distribution information of the target Internet of Things device in the target display area.

15. An electronic device, comprising: at least one processor; a memory for storing the at least one processor-executable instruction; The at least one processor is configured to execute the instructions to implement the method as described in any one of claims 1-7 or 8-12. 16 . A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method according to claim 1 .

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