Method and apparatus for analyzing device behavior, electronic device, and storage medium

Abstract

Embodiments of the present application disclose a device behavior analysis method and device, electronic equipment and storage medium, and relate to the technical field of computers, which comprises: obtaining unmarked grids of a target area, one unmarked grid comprising at least one working device; obtaining at least one aggregation group according to the unmarked grids; analyzing the device behavior of the at least one working device in the target area according to the aggregation attribute information of each aggregation group, the aggregation attribute information being obtained from the device attribute information of the at least one working device corresponding to the at least one unmarked grid. Embodiments of the present application divide the unmarked grids in the target area into at least one aggregation group by clustering, further obtain the aggregation attribute information of each aggregation group from the device attribute information of the working devices corresponding to the unmarked grids in each aggregation group, and analyze the device behavior of the working devices through the aggregation attribute information, thereby simplifying the workload and intuitively depicting the device behavior.

Description

Technical Field

[0001] The embodiments of the present invention relate to computer technology, and more particularly to a method, apparatus, electronic device, and storage medium for analyzing device behavior. Background Technology

[0002] With social development and progress, a Global Positioning System (GPS) device can be installed on each piece of engineering equipment to obtain the current location information of the engineering equipment based on each GPS device, and upload the location information of each piece of engineering equipment to a server to perform visual analysis of the equipment behavior in a certain area based on the location information of the engineering equipment.

[0003] When uploading the location information of each piece of engineering equipment, the GPS devices upload at pre-set fixed time intervals, such as once every hour or once per minute. The shorter the fixed time interval, the more GPS information is uploaded for each piece of engineering equipment. Because individual engineering equipment moves slowly and has a small working range, and multiple pieces of equipment may be working simultaneously within a small area, when analyzing equipment behavior based on the location information of each piece of equipment, the closer the equipment is, the higher the similarity of its behavior, leading to redundant analysis and a large workload. Furthermore, when visualizing the location information of multiple devices, the small range of location changes and the large number of uploaded location data points result in overlapping location points, hindering the operation of personnel to analyze the behavior of the engineering equipment. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for analyzing device behavior, which can improve existing solutions for analyzing device behavior.

[0005] In a first aspect, embodiments of the present invention provide a method for analyzing device behavior, comprising:

[0006] Acquire unmarked grids of a target area, wherein each unmarked grid includes at least one working device;

[0007] At least one aggregation group is obtained based on the unlabeled mesh, and one aggregation group includes at least one of the unlabeled meshes; when one aggregation group includes at least two of the unlabeled meshes, any one of the unlabeled meshes has adjacent unlabeled meshes.

[0008] The device behavior of at least one of the working devices in the target area is analyzed based on the aggregation attribute information of each of the aggregation groups, wherein the aggregation attribute information is obtained through the device attribute information of at least one of the working devices corresponding to at least one of the unmarked grids.

[0009] Secondly, embodiments of the present invention provide a device for analyzing device behavior, the device comprising:

[0010] A grid acquisition module is used to acquire unmarked grids in a target area, wherein each unmarked grid includes at least one working device;

[0011] An aggregation group obtaining module is used to obtain at least one aggregation group based on the unmarked meshes, wherein when an aggregation group includes at least two unmarked meshes, any unmarked mesh has adjacent unmarked meshes;

[0012] The behavior analysis module is used to analyze the device behavior of at least one of the working devices in the target area based on the aggregation attribute information of each of the aggregation groups, wherein the aggregation attribute information is obtained through the device attribute information of at least one of the working devices corresponding to at least one of the unmarked grids.

[0013] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the device behavior analysis method according to any embodiment of the present invention.

[0017] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the device behavior analysis method described in any embodiment of the present invention.

[0018] The device behavior analysis scheme provided in this embodiment of the invention first obtains unmarked grids in the target area, where each unmarked grid includes at least one working device; then, at least one aggregation group is obtained based on the unmarked grids, where each aggregation group includes at least one unmarked grid; when an aggregation group includes at least two unmarked grids, any unmarked grid has adjacent unmarked grids; finally, the device behavior of at least one working device in the target area is analyzed based on the aggregation attribute information of each aggregation group, wherein the aggregation attribute information is obtained through the device attribute information of at least one working device corresponding to at least one unmarked grid. The scheme provided in this embodiment, through clustering, can divide the unmarked grids in the target area into at least one aggregation group, and further obtain the aggregation attribute information of each aggregation group from the device attribute information of the working devices corresponding to the unmarked grids in each aggregation group, so as to analyze the device behavior of the working devices through the aggregation attribute information. This solves the problems of large workload and difficulties in analysis caused by the stacking of location points when performing behavior analysis on engineering equipment one by one in existing schemes, achieving the beneficial effects of simplifying workload and intuitively depicting device behavior.

[0019] It should be understood that the description in this section is not intended to identify key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the embodiments of the present invention will become readily apparent from the following description. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating a device behavior analysis method provided in an embodiment of the present invention;

[0022] Figure 2 This is another flowchart illustrating the device behavior analysis method provided in this embodiment of the invention;

[0023] Figure 3 This is an illustrative diagram illustrating the acquisition of an aggregate group according to an embodiment of the present invention;

[0024] Figure 4 This is a schematic diagram of a device behavior analysis apparatus provided in an embodiment of the present invention;

[0025] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0028] Figure 1 This is a flowchart illustrating a device behavior analysis method provided in an embodiment of the present invention. This embodiment is applicable to the analysis of the working behavior of engineering equipment. The method can be executed by a device behavior analysis device, which can be implemented in hardware and / or software and can be configured in computer equipment such as servers. (Reference) Figure 1 The method may specifically include the following steps:

[0029] S110, Obtain the unmarked grid of the target area.

[0030] This embodiment is applicable to situations where the behavior of multiple working devices in a target area is analyzed. The current working devices can be engineering equipment used for construction, such as road machinery (e.g., asphalt mixers, asphalt pavers, stabilized soil mixers, and stone spreaders), lifting machinery (e.g., truck cranes, crawler cranes, truck-mounted cranes, and tower cranes), and concrete machinery (e.g., concrete mixers, trailer pumps, and truck-mounted pumps); they can also be smart devices, such as smartphones, smart robot vacuums, and other smart home devices. The specific type of working equipment is not limited here, but depends on the object to be analyzed by the technician.

[0031] Before acquiring the unmarked grid of the target area, the target area is first divided into multiple grids based on its latitude and longitude information. Each grid can be a square with a side length of 1 km, 2 km, or 5 km. The specific length of each grid is not limited here and is determined by a combination of the number of devices operating in the target area and the size of the target area.

[0032] The target area can be determined based on the scope of the technical personnel's analysis of the working equipment. For example, the target area can be the whole country, a certain province, a certain city, a certain district, a certain county, or a certain street, etc. The specific scope of the target area is not limited here.

[0033] When dividing the target area into multiple grids, each grid may contain working devices or not. This embodiment mainly obtains the device behavior of working devices in the target area by performing relevant analysis on the grids containing working devices.

[0034] When analyzing a target area containing working equipment, there are grids that have been analyzed and grids that have not been analyzed. Therefore, for ease of distinction, grids containing working equipment but not analyzed are called unmarked grids, and each unmarked grid includes at least one working device. Grids that have been analyzed are called marked grids.

[0035] S120. Obtain at least one aggregation group based on the unmarked mesh.

[0036] Clustering groups refer to the process of performing cluster analysis on multiple unlabeled grids, grouping the unlabeled grids that can be clustered together into one group, and then performing cluster analysis again on the remaining un-clustered unlabeled grids until all unlabeled grids in the target region are clustered, thus obtaining multiple clustering groups.

[0037] In this context, an aggregation group includes at least one unlabeled grid; when an aggregation group includes at least two unlabeled grids, any unlabeled grid has adjacent unlabeled grids.

[0038] When an aggregation group contains only one unlabeled grid, it indicates that there is no other unlabeled grid among the grids adjacent to the current unlabeled grid. Therefore, the current unlabeled grid can be considered as an aggregation group. Optionally, when an aggregation group contains only one unlabeled grid, the number of working devices in the current unlabeled grid can be further obtained. If the number of devices is small and the data analysis is not representative, the analysis of the current aggregation group can be discarded.

[0039] When an aggregation group includes at least two unlabeled grids, each unlabeled grid has adjacent unlabeled grids. For example, if the aggregation group includes two unlabeled grids A and B, then A and B must be adjacent. Among the multiple grids divided in the target area, the current adjacency relationship can be such that, with A as the center, there is one B among the eight grids adjacent to A; in this case, A and B can be considered adjacent. In this scenario, A and B can be grouped into one aggregation group.

[0040] Taking an aggregate group consisting of unlabeled grids A, B, C, and D as an example, first, an unlabeled grid A is determined. Among the eight grids adjacent to A, there are unlabeled grids B and C. Among the eight grids adjacent to B, there is an unlabeled grid D. Among the eight grids adjacent to C, there are no unlabeled grids. Among the eight grids adjacent to D, there are also no unlabeled grids. At this point, one clustering is completed, and an aggregate group consisting of A, B, C, and D is obtained.

[0041] In this embodiment, when performing the initial analysis on the grid containing the working equipment in the target area, all grids containing the working equipment are unlabeled grids. In the process of analyzing the unlabeled grids to obtain the aggregation group according to step S120, the unlabeled grids that have been aggregated (or the surrounding adjacent grids that have been analyzed above) can be labeled as labeled grids. The purpose of doing so is to prevent repeated analysis of adjacent unlabeled grids.

[0042] S130. Analyze the device behavior of at least one working device in the target area based on the aggregation attribute information of each aggregation group.

[0043] Aggregate attribute information represents the attribute information corresponding to each aggregate group. Aggregate attribute information is obtained through the device attribute information of at least one working device corresponding to at least one unmarked grid.

[0044] After the above step S120, the target area can be divided into multiple aggregation groups, wherein each aggregation group includes at least one unmarked grid, and each unmarked grid includes at least one working device. The grid attribute information of each unmarked grid can be obtained by analyzing the device attribute information of the working device contained in each unmarked grid. Furthermore, the aggregation attribute information of each aggregation group can be obtained by analyzing the grid attribute information corresponding to the multiple unmarked grids contained in each aggregation group.

[0045] The device attribute information of the working equipment may include: the location information of each working equipment uploaded to the server at fixed intervals; the grid attribute information of unmarked grids may include the number of working equipment, the starting position and ending position of each working equipment in the current grid, and the working time in the current grid; the aggregation attribute information may include: the number of unmarked grids, the total number of working equipment in the current aggregation group, the center coordinate position of the aggregation group, the earliest appearing working equipment and the latest leaving working equipment in the current aggregation group, etc. The specific device attribute information, grid attribute information, and aggregation attribute information are not limited here.

[0046] After obtaining at least one aggregation attribute, the device behavior of at least one working device in the target area can be analyzed in the following ways: the number of working device distribution locations can be analyzed based on the number of unmarked grids; the total number of working devices in the aggregation group can be analyzed to determine the number of devices required for the current project; the aggregation location of the host device can be analyzed based on the center coordinates of the aggregation group, so as to know the construction location at the remote end; the construction time of the working device can be obtained based on the earliest appearing working device and the latest leaving working device in the current aggregation group, etc. The specific method of analyzing device behavior based on the aggregation attribute information of each aggregation group is not limited here.

[0047] The device behavior analysis method provided in this embodiment of the invention first obtains unmarked grids in a target area, where each unmarked grid includes at least one working device; then, at least one aggregation group is obtained based on the unmarked grids, where each aggregation group includes at least one unmarked grid; when an aggregation group includes at least two unmarked grids, any unmarked grid has adjacent unmarked grids; finally, the device behavior of at least one working device in the target area is analyzed based on the aggregation attribute information of each aggregation group, wherein the aggregation attribute information is obtained through the device attribute information of at least one working device corresponding to at least one unmarked grid. The solution provided in this embodiment, through clustering, can divide the unmarked grids in the target area into at least one aggregation group, and further obtain the aggregation attribute information of each aggregation group from the device attribute information of the working devices corresponding to the unmarked grids in each aggregation group, so as to analyze the device behavior of the working devices through the aggregation attribute information. This solves the problems of large workload and difficulties in analysis caused by the stacking of location points when performing behavior analysis on engineering equipment one by one in existing solutions, achieving the beneficial effects of simplifying workload and intuitively depicting device behavior.

[0048] Figure 2 This is another flowchart illustrating the device behavior analysis method provided in this embodiment of the invention. The relationship between this embodiment and the above embodiments further refines the corresponding features of the above embodiments. Figure 2 As shown, the method may include the following steps:

[0049] S210 acquires the unmarked mesh of the target region.

[0050] An unmarked grid includes at least one working device.

[0051] S220. Obtain at least one location information uploaded by each working device in the unmarked grid.

[0052] When each working device is in operation, the GPS installed on the device will upload its current location information at fixed intervals. The current location information can include latitude and longitude coordinates and a timestamp, with the timestamp being the time corresponding to the upload of the latitude and longitude coordinates.

[0053] Since the latitude and longitude coordinates in the location information uploaded by GPS can be accurate to the meter, for example, the latitude and longitude coordinates of the center of Beijing are (116.41667, 39.91667), we can first perform reduction processing on each location information. For example, for latitude and longitude data, we can keep two decimal places. After reduction processing, the latitude and longitude coordinates of the center of Beijing are (116.41, 39.91).

[0054] S221. Preprocess at least one location information uploaded by each working device to obtain the target location information of each working device in the unmarked grid.

[0055] Taking the application of this solution in engineering construction as an example, when the server collects the location information of each working device, it can be represented as a location point on the map corresponding to the target area, indicating the current location of the working device on the map. Because the moving speed of the working devices is slow and the working radius is small, each working device stays in the same unmarked grid for a long time. Since GPS devices upload location information at fixed time intervals, multiple location information for the same working device exists in the same unmarked grid. Furthermore, in the engineering field, multiple working devices often need to work simultaneously. When the moving range of each working device is small and the working positions of the devices overlap, the location points collected by the server regarding the current unmarked grid will overlap, making it difficult to perform intuitive analysis of the working devices.

[0056] Accordingly, when preprocessing at least one location information uploaded by each working device to obtain the target location information of each working device in the unmarked grid, the location information should also carry the identification information of the working device, so as to distinguish which location information was generated by the same working device when preprocessing the location information data in the unmarked grid.

[0057] Therefore, the location information uploaded by each working device is preprocessed to obtain the target location information of each working device appearing in the unmarked grid. The current target location information includes the start position and the end position; each location information includes a timestamp. Specifically, the above step S211 can be implemented as follows: obtain the start time and end time of each working device appearing in the target unmarked grid according to the timestamp, where the target unmarked grid is any unmarked grid in an aggregate group; and use the location information corresponding to the start time and end time respectively as the target location information of the working device appearing in the target unmarked grid.

[0058] The above process analyzes the historical location information uploaded by each working device in the target unmarked grid. Based on this historical location information, it obtains the earliest and end times of each working device's appearance in the target unmarked grid. Therefore, it retains only the start position corresponding to the start time and the end position corresponding to the end time of each working device in the target unmarked grid to obtain the target location information, filtering out intermediate location information. The advantage of this approach is that while reducing the amount of location information in the target unmarked grid, it allows for a clear understanding of the positional changes of each working device based on its start and end positions, and the duration of each working device's operation in the target unmarked grid based on its start and end times.

[0059] S230. Determine the target mesh from the unmarked meshes. If there are no unmarked meshes in the adjacent meshes of the target mesh, obtain an aggregate group.

[0060] The target grid indicates the first grid identified among all unlabeled grids in the target area, so as to obtain an aggregate group by analyzing the adjacent grids of the target grid.

[0061] The target grid can be determined in several ways: randomly selecting any unmarked grid as the target grid; determining the target grid from a region where unmarked grids are denser; or determining the target grid from a region far from marked grids (which have been divided into clusters). The specific method for determining the target grid is not limited here.

[0062] Please refer to Figure 3 , Figure 3 This is an illustrative diagram illustrating the acquisition of an aggregate group according to an embodiment of the present invention; the above step S220 can be specifically implemented by the following steps:

[0063] a) Identify at least one first grid from the neighboring grids of the target grid, wherein the first grid is an unmarked grid.

[0064] by Figure 3 In the example, the grids containing grids a through h are all unmarked grids containing working equipment. Taking grid a as the target grid, the adjacent grids of the target grid can be the eight grids centered on grid a and adjacent to grid a. Therefore, according to the diagram, the first grids are grids b and c.

[0065] b) Determine whether each first grid's adjacent grids include unmarked grids.

[0066] If each first grid's adjacent grids include unmarked grids, it indicates that the process of obtaining an aggregation group is not yet complete, and aggregation operations can still be performed. In this case, unmarked grids can be used as target grids in sequence, and the operation of step a) above can be repeated until each first grid's adjacent grids do not include unmarked grids, thus obtaining an aggregation group.

[0067] For example, please continue to refer to Figure 3 In step a) above, the first grid obtained are grid b and grid c. In the current step, it is necessary to determine whether the adjacent grids of grid b and grid c contain unmarked grids. Figure 3 For example, the unlabeled grids adjacent to grid b are grids h and a. Since grid a has already been analyzed, the unlabeled grids adjacent to grid b are grid h. Similarly, the unlabeled grids adjacent to grid c are grids a and f. Since grid a has already been analyzed, the unlabeled grids adjacent to grid c are grid f. Further, to determine whether the adjacent grids of grids h and f include unlabeled grids, based on… Figure 3 For example, if grids h and f do not include unlabeled grids, it indicates that the current clustering has ended, and an aggregate group is obtained based on a, b, c, h, f.

[0068] If each first grid's adjacent grids do not include unmarked grids, it indicates that an aggregation group can be obtained based on the target grid and the first grids, and the current aggregation operation ends.

[0069] S231. Determine whether all unmarked grids in the target area have been assigned to the corresponding aggregation group.

[0070] If so, it indicates that the clustering operation on the unlabeled grids of the target region is complete, and at least one clustered group can be obtained, then step S240 can be executed.

[0071] If not, it indicates that there are still un-analyzed unlabeled meshes in the target area. Then repeat S230 above until all unlabeled meshes in the target area are assigned to the corresponding aggregation group, and at least one aggregation group is obtained.

[0072] Please continue to refer to Figure 3 In S230, an aggregate group is obtained comprising a, b, c, h, and f. Figure 3 For example, if there are also grids e, d, and g that have not been assigned to the corresponding aggregation group, then the target grid e is redefined, and at least one first grid d is determined from the adjacent grids of the target grid e. If there are no unmarked grids in the adjacent grids of d, then another aggregation group is obtained based on d and e. If there are also unmarked grids g in the target region, and there are no unmarked grids in the adjacent grids of grid g, then another aggregation group can be obtained based on g.

[0073] S240, Obtain at least one aggregation group.

[0074] Using the example above, then Figure 3 Aggregate groups 1 (a, b, c, h, and f), aggregate group 2 (d and e), and aggregate group 3 (g) can be obtained.

[0075] S250. Obtain the grid attribute information corresponding to at least one unmarked grid in each aggregation group.

[0076] The aforementioned grid attribute information is obtained through the device attribute information of at least one working device included in the unmarked grid. After preprocessing at least one location information uploaded by each working device in step S221, the device attribute information of each working device may include: the device position of each working device (the starting position and the ending position generated in the current unmarked grid), the time of generation of each device position (the time of generation of the starting position and the time of generation of the ending position), etc.

[0077] The grid attribute information obtained for the currently unmarked grid may include: number of devices, device location, time corresponding to each device location, and grid center coordinates.

[0078] The number of devices mentioned above is obtained by summing all the working devices appearing in the current grid; the device positions represent the starting and ending positions of the current unmarked grid. The starting position is obtained by comparing the time when each working device generates its starting position in the current grid, and taking the position corresponding to the earliest time as the starting position of the current unmarked grid; the ending position is obtained by comparing the time when each working device generates its ending position in the current grid, and taking the position corresponding to the latest time as the ending position of the current unmarked grid; the grid center coordinates are obtained by averaging the position coordinates corresponding to the starting and ending positions of each working device, and taking the result as the grid center coordinates of the current unmarked grid.

[0079] S251. Obtain the aggregation attribute information of each aggregation group based on at least one grid attribute information.

[0080] In one implementation, step S25 can be implemented as follows: obtain the total number of working devices in each aggregation group based on the number of working devices contained in the attribute information of each grid; obtain the aggregation center coordinates of each aggregation group based on the center coordinates of each grid; obtain the time information of each aggregation group based on the time corresponding to the location of each device; and obtain the aggregation attribute information corresponding to each aggregation group based on the number of unmarked grids, the total number of working devices, the coordinate information, and the time information in each aggregation group.

[0081] For any aggregation group, the number of unmarked grids can be obtained. Further, the number of devices contained in each unmarked grid can be used to obtain the total number of working devices in the current aggregation group. The average of the grid center coordinates of each unmarked grid can be used to obtain the aggregation center coordinates of the current aggregation group. The time corresponding to the location information contained in each grid attribute can be compared to obtain the time of the aggregation group (the earliest and latest time when the devices in the current aggregation group appear), etc.

[0082] S252. Analyze the device behavior of at least one working device in the target area based on each aggregate attribute information.

[0083] Before analyzing device behavior based on aggregate attribute information, data can be stored for each aggregate attribute. For attributes such as the aggregation center coordinates, total number of working devices, number of unmarked grids, earliest time and latest time, a data model can be established and stored using a relational database management system (MySQL-Get-Proto-Info, or MYSQL for short). Read-write separation can be achieved through master-slave configuration.

[0084] Furthermore, based on the data stored in MySQL, the backend uses the Springboard (an application development architecture) framework, and the frontend uses the Vue (another application development architecture) framework to display the coordinates of the aggregation center for each aggregation group on a map. At the same time, the total number of working devices, the number of unmarked grids, the earliest time and the latest time for each aggregation group are mapped to the coordinates of the aggregation center as attributes for visualization.

[0085] When analyzing the device behavior of at least one working device in the target area based on the aggregated attribute information displayed in the visualization interface, the construction location can be obtained based on the coordinates of the aggregation center, the construction scale can be obtained based on the total number of working devices, the construction area can be obtained based on the number of unmarked grids, and the construction duration can be analyzed based on the earliest and latest times, etc. The specific method of analyzing device behavior is not limited here.

[0086] The device behavior analysis provided in this embodiment of the invention reduces data storage by dividing the target area into grids and clustering the unlabeled grids containing working devices. Furthermore, by determining at least one first grid from the neighboring grids of the target grid and judging whether each first grid's neighboring grids include unlabeled grids, a breadth-first traversal is used to cluster the grids in the target area, resulting in multiple cluster groups. Finally, by obtaining the aggregation attributes of each cluster group, the device behavior is visualized, allowing for intuitive observation of the aggregation status of working devices and facilitating direct analysis of their behavior.

[0087] Figure 4This is a schematic diagram of a device behavior analysis apparatus provided in an embodiment of the present invention. This apparatus is suitable for executing the device behavior analysis method provided in an embodiment of the present invention. Figure 4 As shown, the device may specifically include: a mesh acquisition module 410, an aggregation group acquisition module 420, and a behavior analysis module 430, wherein:

[0088] The grid acquisition module 410 is used to acquire unmarked grids in a target area, wherein each unmarked grid includes at least one working device;

[0089] Aggregation group obtaining module 420 is used to obtain at least one aggregation group based on the unmarked mesh, wherein an aggregation group includes at least one unmarked mesh; when the aggregation group includes at least two unmarked meshes, any unmarked mesh has adjacent unmarked meshes.

[0090] The behavior analysis module 430 is used to analyze the device behavior of at least one of the working devices in the target area based on the aggregation attribute information of each of the aggregation groups, wherein the aggregation attribute information is obtained through the device attribute information of at least one of the working devices corresponding to at least one of the unmarked grids.

[0091] The device behavior analysis apparatus provided in this embodiment first acquires unmarked grids in a target area, where each unmarked grid includes at least one working device. Then, it obtains at least one aggregation group based on the unmarked grids, where each aggregation group includes at least one unmarked grid. When an aggregation group includes at least two unmarked grids, any unmarked grid has adjacent unmarked grids. Finally, it analyzes the device behavior of at least one working device in the target area based on the aggregation attribute information of each aggregation group. The aggregation attribute information is obtained through the device attribute information of at least one working device corresponding to at least one unmarked grid. The solution provided in this embodiment, through clustering, divides the unmarked grids in the target area into at least one aggregation group. Furthermore, it obtains the aggregation attribute information of each aggregation group from the device attribute information of the working devices corresponding to the unmarked grids in each aggregation group, thereby analyzing the device behavior of the working devices through the aggregation attribute information. This solves the problems of large workload and difficulties in analysis caused by the stacking of location points when performing behavior analysis on engineering equipment one by one in existing solutions, achieving the beneficial effects of simplifying workload and intuitively depicting device behavior.

[0092] In one embodiment, the aggregation group obtaining module 420 is specifically used to determine a target grid from the unmarked grids, and to obtain an aggregation group when there are no unmarked grids in the adjacent grids of the target grid; to determine whether all the unmarked grids in the target area are assigned to the corresponding aggregation group; and to repeatedly perform the operation of determining the target grid from the unmarked grids until all the unmarked grids in the target area are assigned to the corresponding aggregation group, thereby obtaining at least one aggregation group.

[0093] In one embodiment, the aggregation group obtaining module 420 is specifically used to determine at least one first grid from the neighboring grids of the target grid, wherein the first grid is the unmarked grid; determine whether the neighboring grids of each first grid include the unmarked grid; if so, then sequentially use the unmarked grid as the target grid, and repeatedly perform the operation of determining at least one first grid from the neighboring grids of the target grid until the neighboring grids of each first grid do not include the unmarked grid, thereby obtaining an aggregation group.

[0094] In one embodiment, the behavior analysis module 430 includes: a mesh attribute acquisition unit, an aggregate attribute acquisition unit, and a device behavior analysis unit, wherein:

[0095] A grid attribute acquisition unit is used to acquire grid attribute information corresponding to at least one unmarked grid in each of the aggregation groups, wherein the grid attribute information is obtained through device attribute information of at least one working device included in the unmarked grid;

[0096] An aggregation attribute obtaining unit is configured to obtain aggregation attribute information for each of the aggregation groups based on at least one of the grid attribute information.

[0097] The device behavior analysis unit is used to analyze the device behavior of at least one of the working devices in the target area based on each of the aggregated attribute information.

[0098] In one embodiment, one of the grid attribute information includes the number of devices, device locations, time corresponding to each device location, and grid center coordinates, wherein one of the grid center coordinates is obtained through the device locations of at least one of the working devices.

[0099] The aggregation attribute obtaining unit is specifically used to obtain the total number of working devices in each aggregation group based on the number of working devices included in each grid attribute information; obtain the aggregation center coordinates of each aggregation group based on the center coordinates of each grid; obtain the time information of each aggregation group based on the time corresponding to the location of each device; and obtain the aggregation attribute information corresponding to each aggregation group based on the number of unmarked grids, the total number of working devices, the aggregation center coordinates, and the time information in each aggregation group.

[0100] In one embodiment, the device further includes: a location information acquisition module and an information preprocessing module, wherein:

[0101] A location information acquisition module is used to acquire at least one location information uploaded by each of the working devices in the unmarked grid;

[0102] An information preprocessing module is used to preprocess at least one of the location information uploaded by each of the working devices to obtain the target location information of each of the working devices in the unmarked grid.

[0103] In one embodiment, the target location information includes a start location and an end location; each location information includes a timestamp;

[0104] The information preprocessing module is specifically used to obtain the start time and end time of each working device appearing in the target unmarked grid according to the timestamp, wherein the target unmarked grid is any unmarked grid in the aggregation group; and to use the location information corresponding to the start time and the end time as the target location information of the working device appearing in the target unmarked grid.

[0105] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is merely an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0106] This invention also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the device behavior analysis method described in any embodiment of this invention.

[0107] This invention also provides a computer-readable medium storing computer instructions that, when executed by a processor, implement the device behavior analysis method described in any embodiment of this invention.

[0108] The following is for reference. Figure 5 It shows a schematic diagram of the structure of a computer system 500 suitable for implementing an electronic device according to embodiments of the present invention. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0109] like Figure 5 As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 502 or programs loaded from storage section 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the system 500. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0110] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 510 as needed so that computer programs read from it can be installed into storage section 508 as needed.

[0111] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs the functions defined above in the system of this invention.

[0112] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0113] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0114] The modules and / or units described in the embodiments of this invention can be implemented in software or hardware. The described modules and / or units can also be housed in a processor; for example, a processor can be described as including a mesh acquisition module, an aggregation group acquisition module, and a behavior analysis module. The names of these modules do not necessarily limit the module itself.

[0115] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs that, when executed by the device, cause the device to include: acquiring unmarked grids of a target area, each unmarked grid including at least one working device; obtaining at least one aggregation group based on the unmarked grids, each aggregation group including at least one of the unmarked grids; when an aggregation group includes at least two of the unmarked grids, any unmarked grid has adjacent unmarked grids; and analyzing the device behavior of at least one working device in the target area based on aggregation attribute information of each aggregation group, the aggregation attribute information being obtained through device attribute information of at least one working device corresponding to at least one of the unmarked grids.

[0116] According to the technical solution of this invention, unlabeled grids in the target area can be divided into at least one cluster group by clustering. Furthermore, the cluster attribute information of each cluster group is obtained from the equipment attribute information of the working equipment corresponding to the unlabeled grids in each cluster group, so as to analyze the equipment behavior of the working equipment through the cluster attribute information. This solves the problems of large workload and difficulty for workers to analyze due to the stacking of location points when performing behavior analysis on engineering equipment one by one in existing solutions, achieving the beneficial effects of simplifying workload and intuitively depicting equipment behavior.

[0117] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for analyzing equipment behavior, characterized in that, include: Acquire unmarked grids of a target area, wherein each unmarked grid includes at least one working device; Obtain at least one location information uploaded by each of the working devices in the unmarked grid, each location information including a timestamp; The start and end times of the appearance of each working device at the target unmarked grid are obtained based on the timestamp, wherein the target unmarked grid is any unmarked grid in an aggregate group; The location information corresponding to the start time and the end time is used as the target location information of the working device in the target unmarked grid; wherein, the target location information includes the start position and the end position; At least one aggregation group is obtained based on the unlabeled mesh, and one aggregation group includes at least one of the unlabeled meshes; when one aggregation group includes at least two of the unlabeled meshes, any one of the unlabeled meshes has adjacent unlabeled meshes. Based on the aggregation attribute information of each aggregation group, analyze the device behavior of at least one of the working devices in the target area. The aggregation attribute information is obtained through the device attribute information of at least one of the working devices corresponding to at least one of the unmarked grids. The device behavior includes the number of distribution locations of the working devices, the number of devices required for the current project, the clustering location of the host devices, and the construction time of the working devices. Wherein, obtaining at least one aggregation group based on the unlabeled grid includes: The target grid is determined from the unmarked grids. If the unmarked grid does not exist in the adjacent grids of the target grid, an aggregation group is obtained. It is determined whether all the unmarked grids in the target area are assigned to the corresponding aggregation group. If not, the operation of determining the target grid from the unmarked grids is repeated until all the unmarked grids in the target area are assigned to the corresponding aggregation group, and at least one aggregation group is obtained. The adjacent grids of the target grid are the eight grids that are adjacent to the target grid with the target grid as the center.

2. The method according to claim 1, characterized in that, The step of determining the target mesh from the unmarked meshes, and obtaining an aggregate group when the unmarked meshes do not exist in the neighboring meshes of the target mesh, includes: Determine at least one first grid from the neighboring grids of the target grid, wherein the first grid is the unmarked grid; Determine whether each of the adjacent grids of the first grid includes the unmarked grid; If so, the unmarked grid is used as the target grid in sequence, and the operation of determining at least one first grid from the neighboring grids of the target grid is repeated until the neighboring grids of each first grid do not include the unmarked grid, thus obtaining an aggregate group.

3. The method according to claim 1, characterized in that, The step of analyzing the device behavior of at least one of the working devices in the target area based on the aggregation attribute information of each of the aggregation groups includes: Obtain grid attribute information corresponding to at least one unmarked grid in each of the aggregation groups, wherein the grid attribute information is obtained through device attribute information of at least one working device included in the unmarked grid; The aggregation attribute information of each aggregation group is obtained based on at least one of the grid attribute information; Analyze the device behavior of at least one of the working devices in the target area based on each of the aggregated attribute information.

4. The method according to claim 3, characterized in that, One of the grid attribute information includes the number of devices, device locations, time corresponding to each device location, and grid center coordinates, wherein the grid center coordinates are obtained through the device locations of at least one of the working devices; Obtaining the aggregation attribute information of each aggregation group based on at least one of the grid attribute information includes: Based on the number of devices contained in each of the grid attribute information, the total number of devices in each aggregation group is obtained; The aggregation center coordinates of each aggregation group are obtained based on the center coordinates of each grid. The time information of each aggregation group is obtained based on the time corresponding to each device location; Based on the number of unmarked grids in each aggregation group, the total number of working devices, the coordinates of the aggregation center, and the time information, the aggregation attribute information corresponding to each aggregation group is obtained.

5. An analysis device for equipment behavior, characterized in that, include: A grid acquisition module is used to acquire unmarked grids in a target area, wherein each unmarked grid includes at least one working device; A location information acquisition module is used to acquire at least one location information uploaded by each of the working devices in the unmarked grid, wherein each location information includes a timestamp; The information preprocessing module is used to obtain the start time and end time of the appearance of each working device in the target unmarked grid according to the timestamp, wherein the target unmarked grid is any unmarked grid in an aggregate group; The location information corresponding to the start time and the end time is used as the target location information of the working device in the target unmarked grid; wherein, the target location information includes the start position and the end position; An aggregation group obtaining module is configured to obtain at least one aggregation group based on the unmarked meshes, wherein an aggregation group includes at least one unmarked mesh; when the aggregation group includes at least two unmarked meshes, any unmarked mesh has adjacent unmarked meshes. The behavior analysis module is used to analyze the device behavior of at least one of the working devices in the target area based on the aggregation attribute information of each aggregation group. The aggregation attribute information is obtained through the device attribute information of at least one of the working devices corresponding to at least one of the unmarked grids. The device behavior includes the number of working devices in distribution locations, the number of devices required for the current project, the clustering location of the host devices, and the construction time of the working devices. The aggregation group acquisition module is specifically used to determine the target grid from the unmarked grids, and to obtain an aggregation group when the unmarked grids do not exist in the adjacent grids of the target grid; to determine whether all the unmarked grids in the target area are assigned to the corresponding aggregation group; and to repeatedly perform the operation of determining the target grid from the unmarked grids until all the unmarked grids in the target area are assigned to the corresponding aggregation group, thereby obtaining at least one aggregation group; wherein the adjacent grids of the target grid are the eight grids centered on the target grid and adjacent to the target grid.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the device behavior analysis method according to any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the device behavior analysis method as described in any one of claims 1-4.

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