CN110320544B - Method, device, equipment and storage medium for identifying position of terminal equipment - Google Patents
Method, device, equipment and storage medium for identifying position of terminal equipment Download PDFInfo
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- CN110320544B CN110320544B CN201810294432.6A CN201810294432A CN110320544B CN 110320544 B CN110320544 B CN 110320544B CN 201810294432 A CN201810294432 A CN 201810294432A CN 110320544 B CN110320544 B CN 110320544B
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- 238000004590 computer program Methods 0.000 claims description 4
- 238000010586 diagram Methods 0.000 description 11
- 238000013461 design Methods 0.000 description 9
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/46—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being of a radio-wave signal type
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Abstract
The embodiment of the application provides a method, a device, equipment and a storage medium for identifying the position of terminal equipment.
Description
Technical Field
The embodiment of the application relates to the technical field of positioning, in particular to a method, a device, equipment and a storage medium for identifying the position of terminal equipment.
Background
In the prior art, detecting whether a terminal device is indoors or outdoors is one of terminal positioning. The existing detection method is generally distinguished based on whether the terminal device can receive the GPS signal, when the terminal device can receive the GPS signal, the terminal device is considered to be outdoors, and when the terminal device cannot receive the GPS signal, the terminal device is considered to be indoors.
However, since the terminal device may receive the GPS signal indoors, the accuracy of the conventional detection method is not high, and erroneous determination is serious.
Disclosure of Invention
The embodiment of the application provides a method, a device, equipment and a storage medium for identifying the position of terminal equipment, so as to accurately identify whether the terminal equipment is indoors or outdoors.
A first aspect of an embodiment of the present application provides a correction method for a sensor, including: acquiring positioning signal intensity information on target terminal equipment; and determining whether the target terminal equipment is in the target building or not based on the positioning signal strength information and a preset classification model.
A second aspect of the embodiments of the present application provides an apparatus for identifying a location of a terminal device, including: the first acquisition module is used for acquiring the strength information of the positioning signal on the target terminal equipment; and the classification identification module is used for determining whether the target terminal equipment is in the target building or not based on the positioning signal strength information and a preset classification model.
A third aspect of embodiments of the present application provides a computer device, including: one or more processors; the system comprises a GPS module and/or a WIFI module, wherein the GPS module is used for carrying out GPS positioning, and the WIFI module is used for carrying out WIFI network connection; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method according to the first aspect as described above.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the method according to the first aspect.
Based on the above aspects, the embodiment of the application determines whether the target terminal device is in the target building by acquiring the positioning signal strength information on the target terminal and based on the acquired positioning signal strength information and the preset classification model. According to the embodiment of the application, the positioning signal strength information of the terminal equipment is used as the input of the preset classification model to judge whether the terminal equipment is indoors or outdoors, and the judgment is not carried out according to whether the terminal equipment can receive the GPS signal, so that the problem of misjudgment caused by the fact that the terminal equipment can also receive the GPS signal indoors in the prior art can be solved, and the accuracy of distinguishing the position relation between the terminal equipment and a building is improved.
It should be understood that what is described in the summary section above is not intended to limit key or critical features of the embodiments of the application, nor is it intended to limit the scope of the application. Other features of the present disclosure will become apparent from the following description.
Drawings
Fig. 1 is a schematic diagram of a scene for distinguishing whether a terminal device is indoors or outdoors according to the prior art;
fig. 2 is a flowchart of a method for identifying a location of a terminal device according to an embodiment of the present application;
FIG. 3 is a flowchart of a method for training a classification model according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a training scenario of a classification model provided in an embodiment of the present application;
FIG. 5 is a flowchart of a training method of an outdoor category identification model according to an embodiment of the present disclosure;
fig. 6 is a flowchart of a method for determining a first preset threshold in the embodiment of fig. 3 according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an apparatus 70 for identifying a location of a terminal device according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a second obtaining module 73 according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an apparatus for identifying a location of a terminal device according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of an apparatus for identifying a location of a terminal device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are for illustration purposes only and are not intended to limit the scope of the present application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the embodiments of the application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In the existing positioning technology, whether the terminal device is indoors or outdoors can be distinguished based on the location of the terminal device, and then some specific services are implemented according to the result of the distinction. For example, in some scenarios, some specific services may be implemented based on the positional relationship between the terminal device and the building. For example, in a shopping scenario, when the terminal device is detected to be in a shopping mall, the purpose of marketing can be achieved by pushing advertisement information to the terminal device. For another example, in a positioning scenario, because the indoor GPS signal strength is generally weak, when it is detected that the user is indoors, the terminal device may be positioned through WIFI or other methods, and then the GPS module of the terminal device may be temporarily turned off to achieve the purpose of saving power. Therefore, for some specific scenarios, it is important to accurately distinguish whether the terminal device is indoors or outdoors.
Fig. 1 is a schematic view of a scene for distinguishing whether a terminal device is indoors or outdoors in the prior art, as shown in fig. 1, fig. 1 includes a GPS positioning satellite 10, a terminal device 11, a terminal device 12, a building 13, and a cloud server 14, where the terminal device 11 is outside the building 13, the terminal device 12 is inside the building 13, the terminal device 11 and the terminal device 12 are equipped with GPS modules (not shown in fig. 1), and receive a GPS signal including the GPS positioning satellite 10 through the GPS modules, and report signal strength information of the received GPS signal to the cloud server 14. Since the terminal device located indoors cannot receive the GPS signal, the cloud server 14 determines whether the terminal device is indoors or outdoors according to whether the terminal device can receive the GPS signal. Therefore, referring to fig. 1, in general, the terminal device 11 can receive the GPS signal, the terminal device 12 cannot receive the GPS signal, and the cloud server determines that the terminal device 11 is outdoors and the terminal device 12 is indoors, however, in some cases, even if the terminal device 12 is indoors, the terminal device 12 cannot receive the GPS signal at all, and the determining method according to the prior art may determine that the terminal device 12 is outdoors by mistake. Therefore, the existing method for distinguishing whether the terminal equipment is indoors is low in accuracy.
In view of the foregoing problems in the prior art, an embodiment of the present application provides a method for identifying a location of a terminal device. According to the method, the positioning signal intensity information on the terminal equipment is acquired and is used as the input of a preset classification model, so that whether the terminal equipment is in a building or not is judged through the output of the classification model, wherein the positioning signal intensity information comprises GPS signal intensity information and/or WIFI signal intensity information. According to the method and the device, whether the terminal device is in the building or not is judged through the preset classification model, and the judgment is not carried out according to whether the terminal device can receive the GPS signal or not, so that the problem of misjudgment caused by the fact that the terminal device can also receive the GPS signal indoors in the prior art can be solved, and the accuracy of distinguishing the position relation between the terminal device and the building is improved.
In the following, with reference to the drawings, the embodiment of the present application will be described in detail by taking the positioning signal strength information as GPS signal strength information as an example, but in some other embodiments, the GPS signal strength information to be referred to in the following embodiment may also be replaced by WIFI signal strength information, or GPS signal strength information and WIFI signal strength information, and the positioning signal strength information is WIFI signal strength information, or a case where the positioning signal strength information includes GPS signal strength information and WIFI signal strength information is similar to a case where the positioning signal strength information is GPS signal strength information, and a detailed description will not be described in the embodiment of the present application.
Embodiments of the present application will be described below in detail with reference to the accompanying drawings.
Fig. 2 is a flowchart of a method for identifying a location of a terminal device according to an embodiment of the present disclosure, where the method may be performed by a cloud server. Referring to FIG. 2, the method includes steps S11-S12:
and S11, acquiring the GPS signal intensity information of the target terminal equipment. The name of the "target terminal device" is defined only to distinguish the terminal device to be identified from other terminal devices, and is not limited. The terminal device related in this embodiment is equipped with a GPS module, receives a GPS signal of a GPS positioning satellite through the GPS module, and reports strength information of the received GPS signal to the cloud server.
The method for reporting the GPS signal strength information to the cloud server by the terminal device according to this embodiment may be multiple:
in one possible design, the terminal device only reports the strength information of the received GPS signal to the cloud server.
In another possible design, the terminal device reports a User Generated Content (UGC) location log to the cloud server periodically or in real time, where the UGC location log includes WIFI signal characteristics (e.g., MAC address, signal strength, etc.) of a location where the terminal device is located and GPS information, where the GPS information includes GPS signal strength information. In the design, the cloud server acquires the GPS signal intensity information of the target terminal device from the UGC positioning log reported by the terminal device.
And S12, determining whether the target terminal equipment is in the target building or not based on the GPS signal strength information and a preset classification model.
The name of the "target building" is defined only to distinguish the building to be identified from other buildings, and is not limited thereto.
The classification model in this embodiment is obtained by training using a machine learning algorithm according to the GPS signal strength information of the plurality of terminal devices located outside the target building and the GPS signal strength information of the plurality of terminal devices located inside the target building (for example, a binary model, but not limited to a binary model), that is, the method for establishing the classification model in this embodiment may be exemplarily expressed as: acquiring GPS signal intensity information of a plurality of first terminal devices positioned in a target building and acquiring GPS signal intensity information of a plurality of second terminal devices positioned outside the target building; and training and obtaining a classification model for identifying whether the terminal equipment is in the target building or not based on the GPS signal strength information of the plurality of first terminal equipments and the GPS signal strength information of the plurality of second terminal equipments. The names of the "first terminal device" and the "second terminal device" are defined only to distinguish from other terminal devices, and are not limited.
The classification model according to this embodiment takes GPS signal strength information as input, and outputs a result of determination that the terminal device is indoors or outdoors, or a probability that the terminal device is located indoors and/or outdoors. For example, in one possible design, the classification model may output the probability that the terminal device is indoors and the probability that the terminal device is outdoors at the same time, and if the probability that the terminal device is outdoors is greater than the probability that the terminal device is indoors, it is determined that the terminal device is outdoors, and if the probability that the terminal device is indoors is opposite, it is determined that the terminal device is indoors. In another possible design, the output of the classification model is the probability that the terminal device is located indoors or outdoors, and when the probability value is greater than a preset threshold, the terminal device is correspondingly judged to be located indoors or outdoors. Of course, the foregoing is illustrative only and is not intended to be the only limitation on the present application.
In this embodiment, whether the target terminal device is in the target building is determined by acquiring the GPS signal strength information of the target terminal and based on the acquired GPS signal strength information and the preset classification model. In the embodiment, the GPS signal strength information of the terminal device is used as the input of the preset classification model to judge whether the terminal device is indoors or outdoors, rather than judging according to whether the terminal device can receive the GPS signal, so that the problem of erroneous judgment caused by the fact that the terminal device can also receive the GPS signal indoors in the prior art can be avoided, and the accuracy of distinguishing the position relationship between the terminal device and the building is improved.
Fig. 3 is a flowchart of a training method of a classification model provided in an embodiment of the present application, and as shown in fig. 3, on the basis of the embodiment of fig. 2, the classification model may be obtained based on the training of steps S31-S35:
and S31, acquiring the GPS signal intensity information of a plurality of third terminal devices located in a preset range around the target building.
And S32, inputting the GPS signal intensity information of each third terminal device into a preset outdoor category identification model.
And S33, if the output result of the outdoor type identification model is larger than a first preset threshold value, marking the corresponding third terminal device as a second terminal device, wherein the second terminal device is positioned outside the target building.
And S34, if the output result of the identification type identification model is smaller than a first preset threshold value, marking the corresponding third terminal device as a first terminal device, wherein the first terminal device is positioned in the target building.
And S35, training and obtaining a classification model for identifying whether the terminal device is in the target building or not based on the GPS signal strength information of the first terminal devices and the GPS signal strength information of the second terminal devices.
The outdoor type identification model can only identify whether the terminal device is outdoors according to the GPS signal intensity of the terminal device, but cannot identify whether the terminal device is indoors. In this embodiment, the GPS signal strength information of the terminal device located within the preset range around the target building is used as sample data, and according to the outdoor category identification model, it is identified which terminal devices corresponding to the GPS signal strength information are located outside the target building from the sample data, that is, which terminal devices are second terminal devices located outside the target building, and the terminal devices corresponding to other GPS signal strength information in the sample are marked as terminal devices located inside the target building, that is, first terminal devices.
For example, fig. 4 is a schematic view of a training scenario of a classification model provided in an embodiment of the present application, as shown in fig. 4, fig. 4 includes a cloud server 40, a target building 41, and a plurality of third terminal devices 42 located within a preset range 43 (for example, within a range of 50-100 meters) around the target building 41. The third terminal device 42 reports its UGC positioning log to the cloud server 40 in real time or periodically, and the cloud server 40 determines that the third terminal device 42 is located within a preset range of the target building 41 according to WIFI positioning information or GPS positioning information in the UGC positioning log, and extracts GPS signal intensity information of the third terminal device 42 from the UGC positioning log.
Further, the cloud server 40 inputs GPS signal strength information of the third terminal device 42 into a preset outdoor category identification model, and if an output result of the outdoor category identification model is greater than a first preset threshold, marks the corresponding third terminal device as a second terminal device, where a name of the "second terminal device" is defined to indicate that the terminal device is located outdoors in the target building. And if the output result of the identification type identification model is smaller than a first preset threshold value, marking the corresponding third terminal device as the first terminal device, wherein the name definition of the first terminal device is used for indicating that the terminal device is positioned indoors of the target building.
Further, the cloud server 40 trains and obtains the classification model based on the GPS signal strength information of the first terminal device and the GPS signal strength information of the second terminal device.
In this embodiment, by using GPS signal intensity data of terminal devices within a preset range near a target building as sample data, identifying terminal devices located outdoors in the target building through a preset outdoor category identification model, and marking other terminal devices in the sample data as terminal devices located outside the target building, a binary model is trained and obtained based on the GPS signal intensity information of the terminal devices located outdoors and the GPS signal intensity information of the terminal devices located indoors. Whether the terminal equipment is indoors or outdoors can be identified through the binary classification model. Compared with a preset outdoor category identification model, the output result of the two-category model is more visual.
Fig. 5 is a flowchart of a training method for an outdoor category identification model according to an embodiment of the present application, and as shown in fig. 5, on the basis of the embodiment of fig. 3, the method includes steps S51-S52:
and S51, based on the acquired GPS signal intensity information of the plurality of third terminal devices, marking the terminal device of which the GPS signal intensity exceeds a second preset threshold value in the third terminal devices as a fourth terminal device located outside the target building.
And S52, training and obtaining an outdoor category identification model for identifying the terminal equipment outside the target building based on the GPS signal strength information of the fourth terminal equipment and the GPS signal strength information of the terminal equipment left after the fourth terminal equipment is removed from the plurality of third terminal equipment.
In this embodiment, on the basis of the embodiment shown in fig. 3, a terminal device whose GPS signal intensity exceeds a second preset threshold value in an obtained third terminal device is marked as a fourth terminal device located outside a target building, an outdoor category identification model is trained by using GPS signal intensity information of the fourth terminal device and GPS signal intensity information of terminal devices remaining after the fourth terminal device is removed from all the third terminal devices, the third terminal devices are re-screened based on the outdoor category identification model obtained by training, which ones of the third terminal devices are located indoors are identified, and then a second classification model with higher accuracy can be obtained based on the GPS signal intensity information of the terminal devices located outdoors and the GPS signal intensity information of the terminal devices located indoors. The accuracy of model training is improved.
Fig. 6 is a flowchart of a method for determining the first preset threshold in the embodiment of fig. 3 according to an embodiment of the present application, and as shown in fig. 6, on the basis of the embodiment, the method includes steps S61-S62:
and S61, inputting the GPS signal intensity information of the fourth terminal equipment into the outdoor category identification model, and determining the probability of each fourth terminal equipment outside the target building.
And S62, determining the first preset threshold value based on the probability of each fourth terminal device outside the target building.
Among these, those skilled in the art will appreciate that: the present embodiment is only an example, and the GPS signal strength information of all the fourth terminal devices acquired in the embodiment of fig. 5 is used as an input of the outdoor category identification model to determine the probability that each fourth terminal device is outside the target building. In an actual scene, the GPS signal strength information of a part of the fourth terminal devices may be used as an input of the outdoor category identification model to determine the probability of the part of the fourth terminal devices outside the target building, and then an average value of the probabilities of the part of the fourth terminal devices outside the target building may be used as the first preset threshold.
In this embodiment, the accuracy of identifying the outdoor terminal device by the outdoor category identification model can be improved by inputting the GPS signal strength information of the fourth terminal device acquired in the embodiment of fig. 5 into the outdoor category identification model, determining the probability of each fourth terminal device outside the target building, and determining the first preset threshold value based on the probability of each fourth terminal device outside the target building.
Fig. 7 is a schematic structural diagram of an apparatus 70 for identifying a location of a terminal device according to an embodiment of the present application, where as shown in fig. 7, the apparatus 70 includes:
a first obtaining module 71, configured to obtain strength information of a positioning signal on a target terminal device;
a classification identification module 72, configured to determine whether the target terminal device is in the target building based on the positioning signal strength information and a preset classification model.
In one possible design, the positioning signal strength information includes GPS signal strength information and/or WIFI signal strength information.
In one possible design, the first obtaining module 71 includes:
and the first obtaining submodule is used for obtaining the positioning signal intensity information on the target terminal equipment from the UGC positioning log reported by the target terminal equipment.
In one possible design, the apparatus further comprises:
a second obtaining module 73, configured to obtain positioning signal strength information on a plurality of first terminal devices located inside the target building, and obtain positioning signal strength information on a plurality of second terminal devices located outside the target building;
a first model training module 74, configured to train and obtain a classification model for identifying whether the terminal device is in the target building based on the positioning signal strength information on the plurality of first terminal devices and the positioning signal strength information on the plurality of second terminal devices.
The apparatus 70 provided in this embodiment can be used to execute the method in the embodiment of fig. 2, and its execution manner and beneficial effect are similar, and are not described herein again.
Fig. 8 is a schematic structural diagram of a second obtaining module 73 according to an embodiment of the present application, and as shown in fig. 8, on the basis of the embodiment of fig. 7, the second obtaining module 73 includes:
a second obtaining submodule 731, configured to obtain strength information of positioning signals on a plurality of third terminal devices located in a preset range around the target building;
the data input sub-module 732 is configured to input the positioning signal strength information on each third terminal device into a preset outdoor category identification model;
the first labeling sub-module 733, configured to label, when an output result of the outdoor category identification model is greater than a first preset threshold, a corresponding third terminal device as a second terminal device, where the second terminal device is located outside the target building;
the second labeling submodule 734 is configured to label, when an output result of the identification class identification model is smaller than a first preset threshold, the corresponding third terminal device as a first terminal device, where the first terminal device is located in the target building.
The apparatus provided in this embodiment can be used to execute the method in the embodiment of fig. 3, and the execution manner and the beneficial effects are similar, which are not described herein again.
Fig. 9 is a schematic structural diagram of an apparatus for identifying a location of a terminal device according to an embodiment of the present application, and as shown in fig. 9, on the basis of the embodiment of fig. 8, the apparatus 70 may further include:
a marking module 75, configured to mark, based on the obtained information on the strength of the positioning signals on the plurality of third terminal devices, a terminal device, of the third terminal devices, whose strength of the positioning signal exceeds a second preset threshold, as a fourth terminal device located outside the target building;
a second model training module 76, configured to train to obtain an outdoor category identification model for identifying the terminal device outside the target building based on the positioning signal strength information on the fourth terminal device and the positioning signal strength information of the terminal devices remaining after the fourth terminal device is removed from the plurality of third terminal devices.
The apparatus provided in this embodiment can be used to execute the method in the embodiment of fig. 5, and the execution manner and the beneficial effects are similar, which are not described herein again.
Fig. 10 is a schematic structural diagram of an apparatus for identifying a location of a terminal device according to an embodiment of the present application, and as shown in fig. 10, on the basis of the embodiment of fig. 9, the apparatus 70 may further include:
a first determining module 77, configured to input the positioning signal strength information on the fourth terminal device into the outdoor category identification model, and determine a probability that each fourth terminal device is outside the target building;
a second determining module 78, configured to determine the first preset threshold based on a probability that each of the fourth terminal devices is outside the target building.
In one possible design, the second determining module 78 may include:
and the determining submodule is used for determining that the average value of the probabilities of all the fourth terminal devices outside the target building is a first preset threshold value.
The apparatus provided in this embodiment can be used to execute the method in the embodiment of fig. 6, and the execution manner and the beneficial effects are similar, which are not described herein again.
An embodiment of the present application further provides a computer device, including: one or more processors;
the system comprises a GPS module and/or a WIFI module, wherein the GPS module is used for carrying out GPS positioning, and the WIFI module is used for carrying out WIFI network connection;
a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of any of the above embodiments.
The present application also provides a computer readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to implement the method of any one of the above embodiments.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a load programmable logic device (CPLD), and the like.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Further, while operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Claims (14)
1. A method for identifying a location of a terminal device, the method being used in a server, the method comprising:
acquiring positioning signal intensity information on target terminal equipment;
determining whether the target terminal device is in a target building based on the positioning signal strength information and a preset classification model;
before the obtaining of the strength information of the positioning signal on the target terminal device, the method further includes:
the method comprises the steps of obtaining positioning signal strength information on a plurality of first terminal devices located inside a target building and obtaining positioning signal strength information on a plurality of second terminal devices located outside the target building;
training to obtain a classification model for identifying whether the terminal device is in the target building or not based on the positioning signal strength information on the plurality of first terminal devices and the positioning signal strength information on the plurality of second terminal devices;
the acquiring of the strength information of the positioning signals on the plurality of first terminal devices located inside the target building and the acquiring of the strength information of the positioning signals on the plurality of second terminal devices located outside the target building include:
acquiring positioning signal intensity information on a plurality of third terminal devices located in a preset range around a target building;
inputting the positioning signal intensity information on each third terminal device into a preset outdoor category identification model;
if the output result of the outdoor category identification model is larger than a first preset threshold value, marking a corresponding third terminal device as a second terminal device, wherein the second terminal device is positioned outside the target building;
if the output result of the outdoor category identification model is smaller than a first preset threshold value, marking a corresponding third terminal device as a first terminal device, wherein the first terminal device is located in the target building.
2. The method of claim 1, wherein the positioning signal strength information comprises GPS signal strength information and/or WIFI signal strength information.
3. The method of claim 1, wherein the obtaining of the positioning signal strength information on the target terminal device comprises:
and acquiring the positioning signal intensity information on the target terminal equipment from the UGC positioning log of the user generated content reported by the target terminal equipment.
4. The method according to claim 1, wherein before inputting the positioning signal strength information of each third terminal device into the preset outdoor category identification model, the method further comprises:
on the basis of the acquired positioning signal intensity information on the plurality of third terminal devices, marking the terminal device of which the positioning signal intensity exceeds a second preset threshold value in the third terminal devices as a fourth terminal device located outside the target building;
training and obtaining an outdoor category identification model for identifying the terminal equipment outside the target building based on the positioning signal strength information on the fourth terminal equipment and the positioning signal strength information of the terminal equipment left after the fourth terminal equipment is removed from the plurality of third terminal equipment.
5. The method of claim 4, wherein after training to obtain an outdoor category identification model for identifying the terminal device outside the target building based on the positioning signal strength information on the fourth terminal device and the positioning signal strength information of the terminal devices of the plurality of third terminal devices except the fourth terminal device, the method further comprises:
inputting the positioning signal intensity information of the fourth terminal equipment into the outdoor category identification model, and determining the probability of each fourth terminal equipment outside the target building;
and determining the first preset threshold value based on the probability of each fourth terminal device outside the target building.
6. The method according to claim 5, wherein the determining the first preset threshold based on the probability of the fourth terminal devices being outside the target building comprises:
and determining the average value of the probabilities of all the fourth terminal devices outside the target building as a first preset threshold value.
7. An apparatus for identifying a location of a terminal device, the apparatus being used in a server, comprising:
the first acquisition module is used for acquiring the strength information of the positioning signal on the target terminal equipment;
the classification identification module is used for determining whether the target terminal equipment is in a target building or not based on the positioning signal intensity information and a preset classification model;
the second acquisition module is used for acquiring the positioning signal strength information on a plurality of first terminal devices positioned in the target building and acquiring the positioning signal strength information on a plurality of second terminal devices positioned outside the target building;
a first model training module, configured to train and obtain a classification model for identifying whether a terminal device is in a target building based on the positioning signal strength information on the plurality of first terminal devices and the positioning signal strength information on the plurality of second terminal devices;
the second obtaining module includes:
the second acquisition submodule is used for acquiring the strength information of the positioning signals on a plurality of third terminal devices located in a preset range around the target building;
the data input submodule is used for inputting the positioning signal intensity information on each third terminal device into a preset outdoor category identification model;
the first marking submodule is used for marking the corresponding third terminal equipment as second terminal equipment when the output result of the outdoor category identification model is larger than a first preset threshold value, and the second terminal equipment is positioned outside the target building;
and the second marking submodule is used for marking the corresponding third terminal equipment as the first terminal equipment when the output result of the outdoor category identification model is smaller than a first preset threshold value, and the first terminal equipment is positioned in the target building.
8. The apparatus of claim 7, wherein the positioning signal strength information comprises GPS signal strength information and/or WIFI signal strength information.
9. The apparatus of claim 7, wherein the first obtaining module comprises:
and the first obtaining submodule is used for obtaining the positioning signal intensity information on the target terminal equipment from the UGC positioning log reported by the target terminal equipment.
10. The apparatus of claim 7, further comprising:
the marking module is used for marking the terminal equipment of which the positioning signal intensity exceeds a second preset threshold value in the third terminal equipment as fourth terminal equipment positioned outside the target building based on the acquired positioning signal intensity information on the plurality of third terminal equipment;
and the second model training module is used for training to obtain an outdoor category identification model for identifying the terminal equipment outside the target building based on the positioning signal strength information on the fourth terminal equipment and the positioning signal strength information of the terminal equipment left after the fourth terminal equipment is removed from the plurality of third terminal equipment.
11. The apparatus of claim 10, further comprising:
a first determining module, configured to input the positioning signal strength information of the fourth terminal device into the outdoor category identification model, and determine a probability that each fourth terminal device is outside the target building;
a second determining module, configured to determine the first preset threshold based on a probability that each of the fourth terminal devices is outside the target building.
12. The apparatus of claim 11, wherein the second determining module comprises:
and the determining submodule is used for determining that the average value of the probabilities of all the fourth terminal devices outside the target building is a first preset threshold value.
13. A computer device, comprising:
one or more processors;
the system comprises a GPS module and/or a WIFI module, wherein the GPS module is used for carrying out GPS positioning, and the WIFI module is used for carrying out WIFI network connection;
storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method of any one of claims 1-6.
14. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-6.
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| CN113630713A (en) * | 2020-05-08 | 2021-11-09 | 中兴通讯股份有限公司 | Indoor and outdoor position identification method and device, computer equipment and medium |
| CN112130187A (en) * | 2020-09-18 | 2020-12-25 | 上海钧正网络科技有限公司 | Positioning method, positioning device and computer readable storage medium |
| CN113259851A (en) * | 2021-05-17 | 2021-08-13 | 东莞市小精灵教育软件有限公司 | Indoor and outdoor detection method and system based on mobile terminal |
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