CN117061998A - Data processing method and device - Google Patents
Data processing method and device Download PDFInfo
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- CN117061998A CN117061998A CN202311157454.5A CN202311157454A CN117061998A CN 117061998 A CN117061998 A CN 117061998A CN 202311157454 A CN202311157454 A CN 202311157454A CN 117061998 A CN117061998 A CN 117061998A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The embodiment of the invention discloses a data processing method and device. According to the method and the device provided by the embodiment of the invention, the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data collected by the target terminal are combined to realize comprehensive positioning in the target interest point, so that the positioning precision of the target terminal in the indoor environment can be improved. And the target terminal only needs to acquire the target positioning model corresponding to the target interest point and used for comprehensive positioning processing when the target terminal is about to enter the target interest point, so that the target terminal only downloads the related data of the target positioning model corresponding to the target interest point according to the travel information or the motion track of the target terminal, the data downloading amount of the target terminal is greatly reduced, and the operation load of the target terminal is reduced.
Description
Technical Field
The present invention relates to the field of positioning technologies, and in particular, to a data processing method and apparatus.
Background
With the rapid development of the mobile internet and the popularization of smart phones, the demands of people for the position location service of the smart phones in daily life are increasing. In an outdoor environment, a satellite positioning system is mainly used for providing a position positioning service, but in an indoor environment, the positioning effect of the satellite positioning system is poor due to satellite signal shielding and the like. Indoor positioning technology therefore typically uses a wireless communication network to determine the geographic location of a mobile terminal at a certain time by measuring some parameter of the received radio waves. Because of the paving cost and the positioning precision of the wireless radio frequency device, the indoor positioning is difficult to provide universal high-precision position service by only one positioning technology. Particularly, in the distribution scenario, how to reduce the energy consumption of the whole system while performing indoor positioning more accurately is also a problem to be solved.
Disclosure of Invention
In view of this, the embodiment of the invention provides a data processing method and device, so as to improve indoor positioning accuracy and reduce energy consumption of the whole system.
In a first aspect, a data processing method is provided, the method comprising:
responding to a target point of interest to be entered by a target terminal, and determining a target positioning model corresponding to the target point of interest;
respectively acquiring satellite positioning data, wireless network transmission positioning data and beacon positioning data of the target terminal;
and inputting the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data into the target positioning model, and determining the positioning information of the target terminal in the target interest point.
In a second aspect, there is provided a data processing apparatus, the apparatus comprising:
the first determining module is used for determining a target positioning model corresponding to a target interest point in response to the fact that the target terminal is about to enter the target interest point;
the acquisition module is used for respectively acquiring satellite positioning data, wireless network transmission positioning data and beacon positioning data of the target terminal;
and the second determining module is used for inputting the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data into the target positioning model and determining the positioning information of the target terminal in the target interest point.
In a third aspect, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method of any of the first aspects above.
In a fourth aspect, there is provided an electronic device, the device comprising:
a memory for storing one or more computer program instructions;
a processor, the one or more computer program instructions being executed by the processor to implement the method of any of the first aspects.
According to the method and the device provided by the embodiment of the invention, the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data collected by the target terminal are combined to realize comprehensive positioning in the target interest point, so that the positioning precision of the target terminal in the indoor environment can be improved. And the target terminal only needs to acquire the target positioning model corresponding to the target interest point and used for comprehensive positioning processing when the target terminal is about to enter the target interest point, so that the target terminal only downloads the related data of the target positioning model corresponding to the target interest point according to the travel information or the motion track of the target terminal, the data downloading amount of the target terminal is greatly reduced, and the operation load of the target terminal is reduced.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following description of embodiments of the present invention with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram of a data processing system according to an embodiment of the present invention;
FIG. 2 is a flow chart of a data processing method according to an embodiment of the invention;
FIG. 3 is a flowchart of a method for determining a target location model corresponding to a target point of interest according to an embodiment of the present invention;
FIG. 4 is a flowchart of another method for determining a target location model corresponding to a target point of interest according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a grouping of beacon transmitters according to an embodiment of the invention;
fig. 6 is a schematic diagram of another grouping of beacon transmitter groups according to an embodiment of the invention;
FIG. 7 is a flowchart of a method for determining location information of a target terminal according to an embodiment of the present invention;
FIG. 8 is a data flow diagram of determining target terminal location information according to an embodiment of the present invention;
FIG. 9 is a data flow diagram of another embodiment of determining target terminal location information;
FIG. 10 is a schematic diagram of a data processing apparatus according to an embodiment of the present invention;
fig. 11 is a schematic diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The present application is described below based on examples, but the present application is not limited to only these examples. In the following detailed description of the present application, certain specific details are set forth in detail. The present application will be fully understood by those skilled in the art without the details described herein. Well-known methods, procedures, flows, components and circuits have not been described in detail so as not to obscure the nature of the application.
Moreover, those of ordinary skill in the art will appreciate that the drawings are provided herein for illustrative purposes and that the drawings are not necessarily drawn to scale.
Unless the context clearly requires otherwise, the words "comprise," "comprising," and the like throughout the application are to be construed as including but not being exclusive or exhaustive; that is, it is the meaning of "including but not limited to".
In the description of the present application, it should be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
The solutions described in the present specification and the embodiments, if related to the personal information processing and the mapping information processing, are processed on the premise of having a legal basis (for example, obtaining the consent of the personal information body, or being necessary for executing the contract, or conforming to the rules of law and administration, etc.), and are processed only within the scope of the rules or agreements. The user refuses to process the personal information except the necessary information of the basic function, and the basic function is not influenced by the user.
In the following description, the position detection of take-out delivery terminals to store meal is taken as an example, and it should be understood that the embodiments of the present application may be applied to any scenario where indoor positioning is required.
FIG. 1 is a schematic diagram of a data processing system according to an embodiment of the present application. As shown in fig. 1, the data processing system includes a terminal 11, a server 12, a wireless network transmission signal transmitter 13, a beacon transmitter 14, and a satellite positioning signal transmitter 15. In this embodiment, the terminal 11 is a general-purpose terminal capable of running a takeout platform client application or applet, for example, the terminal 11 may be a terminal device such as a mobile phone, a computer, or a tablet computer. In some embodiments, the terminal 11 may also be a dedicated terminal with an application program that is cured in an application specific integrated circuit. Wherein the open platform allows third party developers to develop their own applets based on the open platform by providing application programming interfaces (Application Programming Interface, APIs) to the third party developers. The applet may be in particular a program developed on the basis of an application within the platform and adapted to perform the corresponding operations. Specifically, the terminal 11 is a terminal device for distributing resources for executing a distribution task by a platform. The distribution resource can be a person, or can be various unmanned equipment, such as a distribution unmanned vehicle, a distribution robot, a distribution unmanned aerial vehicle and the like. The server 12 may be a single server or a server cluster consisting of a plurality of servers. The wireless network transmission signal transmitter 13 is a general transmitter capable of transmitting a wireless network transmission signal, for example, the wireless network transmission signal transmitter may be a WIFI (wireless fidelity, wireless connection) transmitter, a UWB (Ultra wide band) transmitter, a ZigBee (ZigBee) transmitter, or the like. The beacon transmitter 14 is a general purpose transmitter that can transmit bluetooth beacon signals, and may be, for example, a beacon signal transmitter. The satellite positioning signal transmitter 15 is a satellite capable of transmitting satellite positioning signals, for example, a GPS (Global Positioning System) positioning system satellite, a gulonas (Global Navigation Sate) positioning system satellite, a galileo satellite positioning system satellite or a beidou satellite navigation system satellite, etc.
In this embodiment, the target interest point is a location to be accessed by the target terminal, and in the distribution task scene, the target interest point may be a building where a dining point is located, for example, a mall or an office building where a merchant is located. The target point of interest is provided with a plurality of wireless network transmission signal transmitters 13 and beacon transmitters 14. Since there are usually enough WIFI signal transmitters in the target points of interest such as malls and snack streets, the WIFI signal transmitter can be directly used as the wireless network transmission signal transmitter 13. The beacon transmitters 14 need to be laid in advance, and a plurality of beacon transmitters which are divided into a plurality of beacon transmission groups by location are present in the target interest point, wherein each of the beacon transmission groups includes at least one of the beacon transmitters.
When the terminal 11 is about to enter a target interest point, such as a mall, it requests to the server 12 to acquire a target positioning model corresponding to the target interest point through the internet. And collects the wireless network transmission signal transmitted by the wireless network transmission signal transmitter 13 and the beacon signal transmitted by the beacon transmitter 14 through the wireless local area network, respectively, and collects the satellite positioning signal transmitted by the satellite positioning signal transmitter 15. And finally, inputting the wireless network transmission signals, the beacon signals and the satellite positioning signals into a target positioning model to determine the positioning information of the target terminal in the target interest point. It should be understood that the stage of acquiring the target behavior model by the terminal 11 and the stage of acquiring the positioning data may be mutually isolated in time or may be mutually intersected, that is, after the terminal 11 enters the target interest point, if the target positioning model cannot be acquired in time due to poor network connection or other reasons, the various positioning data may be continuously acquired and stored, and then processed after the target positioning model is acquired. In this process, the server 12 needs to control the beacon transmission groups to transmit beacon signals according to a preset period, so that at least one beacon transmitter transmitting beacon signals exists in each beacon transmission group at the same time.
In the system provided by the embodiment of the invention, the integrated positioning in the target interest point is realized by combining the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data acquired by the target terminal, so that the positioning precision of the target terminal in the indoor can be improved. And the target terminal only needs to acquire the target positioning model corresponding to the target interest point and used for comprehensive positioning processing when the target terminal is about to enter the target interest point, so that the target terminal only downloads the related data of the target positioning model corresponding to the target interest point according to the travel information or the movement track of the target terminal, the data downloading amount of the target terminal is greatly reduced, the operation load of the target terminal is reduced, the beacon transmitters are controlled to transmit beacon signals in turn, the periodic scanning of the system can be realized, and the overall power consumption of all the beacon transmitters in the target interest point is reduced on the premise of ensuring the coverage range of the signals required for positioning in the inner chamber of the target interest point.
Fig. 2 is a flowchart of a data processing method according to an embodiment of the present invention. As shown in fig. 2, the data processing method according to the embodiment of the present invention includes the following steps:
in step S100, in response to the target terminal coming into the target interest point, a target positioning model corresponding to the target interest point is determined.
The point of interest (Point Of Interest, POI) refers to a place which needs to be reached when a person takes a meal, such as a restaurant, a hotel, a market, and the like. The target interest point is the interest point to be entered by the target terminal, and the target interest point is the position of the merchant in the distribution task under the distribution task scene. The target positioning model is a model for determining positioning information of the target terminal in the target interest point according to satellite positioning data, wireless network transmission positioning data and beacon positioning data, and in this embodiment, the type of the target positioning model is not limited, and the target positioning model may be a rule model, a machine learning model or other types of models.
In a possible implementation manner, the target positioning model may be a machine learning model, and when determining the target positioning model, model related data of the target positioning model corresponding to the target point of interest needs to be acquired first, where the model related data is a machine learning model related parameter determined according to historical positioning data of the target point of interest, and then the target positioning model is determined based on the machine learning model related parameter. The training method of the target positioning model comprises the following steps: and acquiring multiple sets of training data, wherein one set of training data comprises historical input data and historical output data of each positioning position in the target interest point, the historical input data comprises historical GPS positioning data, historical WIFI positioning data and historical beacon positioning data, and the historical output data comprises historical accurate positioning and corresponding confidence. The training data generally needs to manually carry a test terminal and a high-precision positioning instrument to a target interest point for collection, and specifically, the historical GPS positioning data, the historical WIFI positioning data and the historical beacon positioning data are collected at each test positioning position of the target interest point. And then determining accurate positioning information of the test positioning position as historical accurate positioning by using a high-precision positioning instrument. And determining historical positioning information according to the historical GPS positioning data, the historical WIFI positioning data and the historical beacon positioning data, and then determining corresponding confidence coefficient according to the historical positioning data and the accurate positioning information. And repeating the acquisition process on enough test positioning positions to obtain training data of the target positioning model. The target positioning model is then trained using the training data.
Each point of interest has a corresponding positioning model. If the relevant positioning data in all the interest points are processed by using the same model, the data volume of the model processing is large and the processing speed is low, so that each interest point in the embodiment is provided with the corresponding positioning model for processing the indoor positioning data in the interest point, and the data volume of the model processing is less and the processing speed is higher.
Fig. 3 is a flowchart of a method for determining a target positioning model corresponding to a target interest point according to an embodiment of the present invention, as shown in fig. 3, step S100 may specifically include the following steps:
in step S111, the delivery state and the position information of the target terminal are determined.
Specifically, in the scenario of a delivery task, when the target terminal confirms that the delivery task is received, that is, the delivery track of the target terminal needs to be monitored to confirm the current delivery node, the delivery node may include: the delivery personnel receive the bill, the merchant takes the meal, the delivery personnel takes the meal to the store, the delivery personnel delivers the meal, the delivery is completed, and the like. In this embodiment, the target positioning model needs to be determined before entering the target point of interest, and preparation is made for indoor positioning, so that satellite positioning data can be used to determine the position information of the target terminal. Even if the target positioning model is not determined before entering the target interest point because of poor network connection and the like, the target positioning model can be determined according to satellite positioning data before the target terminal enters the target interest point. Specifically, if the satellite positioning signal is not received or the satellite positioning signal strength is too low in the preset time period, the position information of the target terminal is determined according to the satellite positioning signal with the signal strength meeting the requirement for the last time.
In step S112, a target positioning model corresponding to the target point of interest is determined in response to the delivery status being meal taking and/or the location information of the target terminal characterizing that the target terminal is about to enter the target point of interest.
Optionally, determining whether a target positioning model corresponding to the target interest point needs to be acquired according to the distribution state of the target terminal. When the delivery state is that a delivery person gets a meal to a store, and the target terminal is about to reach the target interest point, the target positioning model corresponding to the target type defect can be obtained in advance, so that preparation is made for positioning the target terminal in the target interest point. Or in order to avoid unsmooth network connection and influence the acquisition progress of the target positioning model, the acquisition of the target positioning model can be attempted for the delivery personnel to receive the order in the delivery state.
Optionally, whether the target positioning model corresponding to the target interest point needs to be acquired or not can also be determined according to the position information of the target terminal. Because the target terminal needs to be positioned indoors when entering the target interest point, and the target positioning model needs to be determined before entering indoors, the position information of the target terminal can be determined according to satellite positioning data before not entering the target interest point. The method comprises the specific steps of obtaining satellite positioning data of the target terminal, and then determining the position information of the target terminal based on the satellite positioning data. And when the position information characterizes that the target terminal is about to enter the target interest point, determining a target positioning model corresponding to the target interest point, and preparing for indoor positioning of the target terminal.
Because the target terminal still has the possibility of giving up the delivery task before taking the meal, the delivery state and the position information of the target terminal can be combined to determine whether the target positioning model corresponding to the target interest point needs to be acquired or not, namely, the target positioning model is determined only when the delivery state of the target terminal is taking the meal and the position information indicates that the target terminal is about to enter the target interest point.
Fig. 4 is a flowchart of another method for determining a target positioning model corresponding to a target interest point according to an embodiment of the present invention, as shown in fig. 4, step S100 may specifically include the following steps:
in step S121, trip information of the target terminal is acquired.
Specifically, in other scenes needing indoor positioning, whether the target positioning model corresponding to the target interest point needs to be acquired or not can be determined according to the travel information recorded in the target terminal. Specifically, the trip information of the target terminal may be obtained through a trip record, a calendar, a note, and the like in the target terminal.
In step S122, a target positioning model corresponding to the target point of interest is determined in response to the trip information characterizing that the target terminal is about to enter the target point of interest.
The method is used for determining the target positioning model, preparing for indoor positioning and waiting for collecting positioning related data.
In step S200, satellite positioning data, wireless network transmission positioning data, and beacon positioning data of the target terminal are acquired, respectively.
The satellite positioning data can be GPS positioning data, beidou positioning data or Galileo positioning data and the like. The satellite positioning data type may be determined based on the positioning system supported by the target terminal. The wireless network transmission positioning data comprise wireless network transmission signals, corresponding signal strength and other data, and the wireless network transmission signals can be WIFI signals, UWB signals, zigBee signals or the like. The Beacon positioning data includes data such as a Beacon signal and a corresponding signal strength, and the Beacon signal may be a Beacon signal. In order to realize wireless network transmission positioning and beacon positioning, the target interest point is provided with a plurality of wireless network transmission positioning devices and beacon positioning devices. Because a lot of WIFI signal transmitters are usually arranged in target interest points such as shopping malls and snack streets, the WIFI signal transmitters can be directly used as wireless network transmission positioning devices. The beacon positioning device needs to be laid in advance. There are a plurality of beacon transmitters that are divided into a plurality of beacon transmission groups by location within a target point of interest, wherein each of the beacon transmission groups includes at least one of the beacon transmitters.
In one possible implementation, a plurality of beacon transmitters that enable any location of the target point of interest to receive a beacon transmission signal at any time may be determined as a set of beacon transmitter groups according to the signal coverage of each of the beacon transmitters. And combining all the beacon transmitters in the target interest point to obtain a plurality of beacon transmitter groups. And in the positioning process, controlling each beacon transmitter group to transmit beacon signals in turn according to a preset period. The preset period can be determined according to the actual positioning requirement, the shorter the preset period is, the shorter the positioning interval is, the more positioning information is, and the more accurate the obtained motion trail is.
Fig. 5 is a schematic diagram of a grouping of beacon transmitters according to an embodiment of the invention. As shown in fig. 5, all beacon transmitters in the target interest point are divided into four groups of beacon transmission groups according to the signal coverage range of the beacon transmitters, the beacon transmitters in each group of beacon transmission groups are uniformly distributed in the target interest point, the interval between the beacon transmitters is determined according to the signal coverage range of the beacon transmitters, and it is ensured that any position of the target interest point receives the beacon transmission signals.
Fig. 6 is a schematic diagram of another grouping of beacon transmitters according to an embodiment of the invention. The beacon transmitters within the same location area are determined as a group of beacon transmitter groups according to the pre-defined location area. As shown in fig. 6, the target point of interest is divided into four partitions, namely partition 61, partition 62, partition 63 and partition 64, and the beacon transmitters in the same partition are a set of beacon transmission groups. The beacon transmitters within a partition are evenly distributed. And controlling the beacon transmitters in the beacon transmitter groups to transmit beacon signals in turn according to a preset period so that any position of the target region of interest point can receive the beacon transmission signals. That is, at the same time, one beacon transmitter each transmits a beacon signal in each of the different beacon transmission groups.
The method controls the beacon transmitters to transmit the beacon signals in turn, so that the periodic scanning of the system can be realized, and the overall power consumption of all the beacon transmitters in the target interest point is reduced on the premise of ensuring the positioning of the required signal coverage range in the inner chamber of the target interest point.
In step S300, the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data are input into the target positioning model, and positioning information of the target terminal in the target interest point is determined. In one possible implementation, the target location model includes a signal fingerprint database including signal fingerprints received at each location position within the target point of interest, the signal fingerprints including at least two of satellite positioning signals, wireless network transmission signals, or beacon signal fingerprints.
The fingerprint database is a database for providing positioning basis for indoor positioning technology. The fingerprint database is established by measuring the signal strength from the respective wireless network device at each of the predetermined location points within the set range, including the signal fingerprint data corresponding to each of the predetermined location points within the set range. The set range refers to a range for providing positioning service, and in this embodiment, the set range is within the target point of interest. For example, a channel in a mall may be divided into grids of a set size, and a center point of each grid is taken as a preset position point, which may be simply referred to as a positioning position. Before the indoor positioning is performed by using the target positioning model, a fingerprint database corresponding to the target interest point needs to be established. The fingerprint database is built by measuring the signal strengths from the various wireless network transmission signal transmitters and beacon transmitters at each location of the target point of interest. The fingerprint database comprises signal fingerprints corresponding to each positioning position, and the signal fingerprints corresponding to each positioning position comprise position information of the positioning position and signal intensity values corresponding to each wireless network transmission signal transmitter and each beacon transmitter on the positioning position. Illustratively, the signal fingerprint may take the form of: longitude, latitude, floor |mac1, RSSI1; MAC2, RSSI2; … …; MACn, RSSIn. Wherein, (longitude, latitude, floor) is the location information of the positioning location, MAC is the identification of the wireless network transmission signal transmitter or the beacon transmitter, and RSSI (Received Signal Strength Index, received signal strength) is the signal strength value of the wireless network transmission signal or the beacon transmission signal at the positioning location. Notably, the signal fingerprint information base needs to be updated periodically, such as once a day, once a week, once every two weeks, etc. When updating the signal fingerprint information base, signals transmitted by the trusted wireless network transmission signal transmitter and the beacon transmitter need to be collected. When a wireless network transmission signal transmitter or beacon transmitter is detected a plurality of times in succession, and the detected signal strength is higher than a preset strength, the wireless network transmission signal transmitter or beacon transmitter can be determined to be trusted. The trusted wireless network transmits a signal or beacon signal to update the signal fingerprint information base. In this embodiment, the signal fingerprint may be one of satellite positioning data, satellite positioning data transmitted by a wireless network, and beacon positioning data, or may be integrated positioning data of satellite positioning data, satellite positioning data transmitted by a wireless network, and beacon positioning data.
Fig. 7 is a flowchart of a method for determining positioning information of a target terminal according to an embodiment of the present invention, as shown in fig. 7, step S300 may specifically include the following steps:
in step S310, according to the satellite positioning data, the satellite positioning data transmitted by the wireless network, and the beacon positioning data, the target fingerprint positioning information and the target confidence level are determined from the signal fingerprint database corresponding to the target interest point.
Alternatively, the satellite positioning data, the wireless network satellite positioning data and the beacon positioning data corresponding to a positioning position can be processed and then stored in the fingerprint database as a signal fingerprint. Thus, the integrated positioning data of the target terminal may be determined first from the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data. And then determining fingerprint positioning information with highest similarity with the comprehensive positioning data from a signal fingerprint database corresponding to the target interest point, determining the fingerprint positioning information with the highest similarity with the comprehensive positioning data as the target fingerprint positioning information, and determining the similarity between the comprehensive positioning data and the target fingerprint positioning information as the target confidence level.
Fig. 8 is a data flow chart of determining positioning information of a target terminal according to an embodiment of the present invention, as shown in fig. 8, and it is assumed that satellite positioning data 801 is 54.031757e, 11.2957825 n,5. The wireless network transmits positioning data 802 at 54.121524E,11.284578N,4|MAC11,2 Bei Haowa (dBm), MAC12,5dBm, MAC13, -76dBm. The beacon location data 803 is 54.12358E, 11.236589N,4|MAC21, -20dBm, MAC22,7dBm, MAC23, -48dBm. And then determining the comprehensive positioning data 804 of the target terminal to be 54.1200254E,11.250215N,4 according to a preset comprehensive positioning algorithm. The integrated position data 804 may be converted into a corresponding integrated position vector 805, the integrated position vector 805 being (1,1,0,1,0,1,0,1,0). Fingerprint positioning information (1,1,0,1,0,1,0,1,1) with highest similarity with the integrated positioning vector 805 is searched and determined from the signal fingerprint database, then the fingerprint positioning information is determined to be target positioning information 806 of the target terminal, the similarity between the integrated positioning vector 805 and the corresponding vector of the target positioning information 806 is calculated to be 87%, and the similarity is taken as target confidence 807. The similarity between the integrated positioning vector 805 and the corresponding vector of the target positioning information 806 may be determined by cosine similarity, euclidean distance, manhattan distance, chebyshev distance, and the like. It should be noted that, the object location information 806 with the highest similarity may also be determined from the signal fingerprint database according to the integrated location data 804, specifically, a text similarity algorithm may be used to determine the similarity between the integrated location data 804 and the object location information 806, such as TF-IDF (Term frequency-inverse word frequency), BM25 (Best Match 25), simHash algorithm, and the like.
Alternatively, the satellite positioning data, the wireless network satellite positioning data and the beacon positioning data corresponding to one positioning position can be respectively processed and then stored in the fingerprint database as three different signal fingerprints. Therefore, first fingerprint positioning information, second fingerprint positioning information and third fingerprint positioning information can be respectively determined from a signal fingerprint database corresponding to the target interest point according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data, wherein the first fingerprint positioning information is positioning information with the highest similarity with the satellite positioning data, the second fingerprint positioning information is positioning information with the highest similarity with the wireless network transmission positioning data, and the third fingerprint positioning information is positioning information with the highest similarity with the beacon positioning data. And then determining the target fingerprint positioning information and the target confidence according to the first fingerprint positioning information and the corresponding first confidence, the second fingerprint positioning information and the corresponding second confidence and the third fingerprint positioning information and the corresponding third confidence, wherein the first confidence is the similarity of the first fingerprint positioning information and the satellite positioning data, the second confidence is the similarity of the second fingerprint positioning information and the wireless network transmission positioning data, and the third confidence is the similarity of the third fingerprint positioning information and the beacon positioning data. Specifically, fingerprint positioning information with the highest confidence coefficient can be selected as target positioning information by comparing the first confidence coefficient, the second confidence coefficient and the third confidence coefficient. Or fusing the first fingerprint positioning information, the second fingerprint positioning information and the third fingerprint positioning information to obtain target fingerprint positioning information, and carrying out weighted summation on the first confidence coefficient, the second confidence coefficient and the third confidence coefficient to obtain target confidence coefficient, wherein the weight corresponding to each confidence coefficient can be determined according to the average positioning precision of the satellite positioning technology, the wireless network transmission positioning technology and the beacon positioning technology.
Fig. 9 is a data flow chart of another embodiment of determining positioning information of a target terminal, as shown in fig. 9, assuming that satellite positioning data 901 is 54.031757e, 11.2957825 n,5. The wireless network transmits positioning data 902 at 54.121524E,11.284578N,4|MAC11, -74 Bei Haowa (dBm), MAC12, -71dBm, MAC13, -20dBm. The beacon location data 903 is 54.12358E, 11.236589N,4|MAC21, -20dBm, MAC22,7dBm, MAC23,3dBm. A first positioning vector 904 corresponding to satellite positioning data 901 (1,1,1,1,0,1,0,1,1), a second positioning vector 905 corresponding to wireless network transmission positioning data (1,1,0,1,0,5,0,2,0), and a third positioning vector 906 corresponding to beacon positioning data 903 (1,1,0,1,0,2,0,1,1) are determined, respectively. Then, the first fingerprint positioning information 907 with the highest similarity to the first positioning vector 904 is determined from the signal fingerprint database, for example, (1,1,1,1,0,1,0,1,2), the similarity between the first positioning vector 904 and the corresponding vector of the first fingerprint positioning information 907 is determined to be 90%, and the similarity is determined to be the first confidence 910. The second fingerprint positioning information 908 having the highest similarity to the second positioning vector 905 is determined from the signal fingerprint database, for example, (1,1,0,1,0,5,0,3,1), and the similarity between the second positioning vector 905 and the corresponding vector of the second fingerprint positioning information 908 is determined to be 80%, and is determined to be the second confidence 911. Third fingerprint positioning information 909, such as (1,1,0,1,0,2,2,1,2), having the highest similarity to the third positioning vector 906 is determined from the signal fingerprint database, and the similarity between the third positioning vector 906 and the corresponding vector of the third fingerprint positioning information 909 is determined to be 85%, and is determined to be a third confidence 912. Finally, the fingerprint positioning information with the highest confidence level can be selected as the target fingerprint positioning information 913 by comparing the first confidence level 910, the second confidence level 911 and the third confidence level 912. And the confidence corresponding to the target location information is determined as the target confidence 914, i.e., 90%. Or the first fingerprint positioning information 907, the second fingerprint positioning information 908 and the third fingerprint positioning information 909 may be fused to obtain the target fingerprint positioning information 913, and the first confidence coefficient 910, the second confidence coefficient 911 and the third confidence coefficient 912 may be weighted and summed to obtain the target confidence coefficient 914. The weight corresponding to each confidence coefficient may be determined according to the average positioning accuracy of the satellite positioning technology, the wireless network transmission positioning technology and the beacon positioning technology, for example, the first weight is 0.1, the second weight is 0.3, and the third weight is 0.6, and the target confidence coefficient 914 is 90% by 0.1+80% by 0.3+85% by 0.6=0.84.
In step S320, positioning information of the target terminal in the target point of interest is determined according to the target fingerprint positioning information and the target confidence level.
Specifically, the target fingerprint positioning information can be directly used as the positioning information of the target terminal in the target interest point. Or the last positioning information of the target terminal and the target confidence coefficient can be combined to correct the target fingerprint positioning information so as to obtain the positioning information of the target terminal in the target interest point. For example, when the target confidence is smaller, whether the current positioning position is reasonable or not can be judged according to the time interval between the last positioning information and the two times of positioning of the target terminal, and if the distance between the position represented by the target fingerprint positioning information and the position represented by the last positioning information obviously exceeds the reasonable displacement range of the target terminal, the target fingerprint positioning information is corrected to a certain extent. Assuming that the preset confidence coefficient is 80%, if the target confidence coefficient is greater than or equal to 80%, the target positioning information is considered to be a trusted positioning result, and the positioning information of the target terminal in the target interest point is directly determined according to the target fingerprint positioning information and the target confidence coefficient. If the target positioning information is less than 80%, the target positioning information is not a reliable positioning result and needs to be corrected. Specifically, the current motion state, including the motion direction and the motion speed, is determined by combining the previous positioning information, and then the current estimated positioning information is determined by combining the last positioning information. And correcting the target positioning information according to the current estimated positioning information. In addition, the correction can be performed in combination with the actual environment in the target interest point, that is, in the actual situation, there are areas in the target interest point that are not reachable by the person, and when the target is located in these areas, the target location information is corrected to the nearest reachable area. For example, if the target positioning information shows that the target terminal is located in the wall of the merchant, the positioning information of the target terminal is corrected, and the target positioning information is corrected to be beside the wall. Or determining the motion trail of the target terminal according to the plurality of positioning information of the target terminal, matching the motion trail with the road in the target interest point, correcting the target positioning information of the target terminal when the motion trail of the target terminal deviates from a certain degree, and matching the target terminal to a similar road.
In one possible implementation, the object localization model is a machine learning model. The target positioning model is obtained after history positioning data training. Satellite positioning data, wireless network transmission positioning data, and beacon positioning data are input into the target positioning model. And outputting the corresponding target positioning information and target confidence. When the target confidence is smaller, the similar method is used for correcting the target positioning information, and the satellite positioning data, the wireless network transmission positioning data, the beacon positioning data and the corrected target positioning information are used as training data to train the target positioning model, so that the trained target positioning model can output more accurate positioning information.
In the method provided by the embodiment of the invention, the integrated positioning in the target interest point is realized by combining the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data acquired by the target terminal, so that the positioning precision of the target terminal in the indoor can be improved. And the target terminal only needs to acquire the target positioning model corresponding to the target interest point and used for comprehensive positioning processing when the target terminal is about to enter the target interest point, so that the target terminal only downloads the related data of the target positioning model corresponding to the target interest point according to the travel information or the movement track of the target terminal, the data downloading amount of the target terminal is greatly reduced, the operation load of the target terminal is reduced, the beacon transmitters are controlled to transmit beacon signals in turn, the periodic scanning of the system can be realized, and the overall power consumption of all the beacon transmitters in the target interest point is reduced on the premise of ensuring the coverage range of the signals required for positioning in the inner chamber of the target interest point.
FIG. 10 is a schematic diagram of a data processing apparatus according to an embodiment of the present invention, as shown in FIG. 10, the data processing apparatus includes the following modules:
a first determining module 1001, configured to determine, in response to a target terminal going to enter a target interest point, a target positioning model corresponding to the target interest point;
an acquiring module 1002, configured to acquire satellite positioning data, wireless network transmission positioning data, and beacon positioning data of the target terminal respectively;
a second determining module 1003, configured to input the satellite positioning data, the wireless network transmission positioning data, and the beacon positioning data into the target positioning model, and determine positioning information of the target terminal in the target interest point.
In the device provided by the embodiment of the invention, the integrated positioning in the target interest point is realized by combining the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data acquired by the target terminal, so that the positioning precision of the target terminal in the indoor can be improved. And the target terminal only needs to acquire the target positioning model corresponding to the target interest point and used for comprehensive positioning processing when the target terminal is about to enter the target interest point, so that the target terminal only downloads the related data of the target positioning model corresponding to the target interest point according to the travel information or the motion track of the target terminal, the data downloading amount of the target terminal is greatly reduced, and the operation load of the target terminal is reduced.
Fig. 11 is a schematic diagram of an electronic device according to an embodiment of the present invention. In this embodiment, the electronic device includes a server, a terminal, and the like. As shown in fig. 11, the electronic device includes at least one processor 1101; and a memory 1102 communicatively coupled to the at least one processor 1101; and a communication unit 1103 in communication connection with the scanning apparatus, the communication unit 1103 receiving and transmitting data under the control of the processor 1101; the memory 1102 stores instructions executable by the at least one processor 1101, and the instructions are executed by the at least one processor 1101 to implement the unlocking method.
Specifically, the electronic device includes: one or more processors 1101, and a memory 1102, one processor 1101 being illustrated in fig. 11. The processor 1101, memory 1102 may be connected by a bus or otherwise, as exemplified by the bus connection in fig. 11. Memory 1102 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The processor 1101 executes various functional applications of the device and data processing, i.e., implements the unlocking method described above, by running non-volatile software programs, instructions, and modules stored in the memory 1102.
Memory 1102 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store a list of options, etc. In addition, memory 1102 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 1102 may optionally include memory located remotely from the processor 1101, which may be connected to an external device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in the memory 1102 that, when executed by the one or more processors 1101, perform the unlocking method of any of the method embodiments described above.
The product may perform the method provided by the embodiment of the present application, and has the corresponding functional module and beneficial effect of the performing method, and technical details not described in detail in the embodiment of the present application may be referred to the method provided by the embodiment of the present application.
In the embodiment of the invention, the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data acquired by the target terminal are combined to realize comprehensive positioning in the target interest point, so that the positioning precision of the target terminal in the indoor environment can be improved. And the target terminal only needs to acquire the target positioning model corresponding to the target interest point and used for comprehensive positioning processing when the target terminal is about to enter the target interest point, so that the target terminal only downloads the related data of the target positioning model corresponding to the target interest point according to the travel information or the movement track of the target terminal, the data downloading amount of the target terminal is greatly reduced, the operation load of the target terminal is reduced, the beacon transmitters are controlled to transmit beacon signals in turn, the periodic scanning of the system can be realized, and the overall power consumption of all the beacon transmitters in the target interest point is reduced on the premise of ensuring the coverage range of the signals required for positioning in the inner chamber of the target interest point.
Another embodiment of the present invention is directed to a non-volatile storage medium storing a computer readable program for causing a computer to perform some or all of the method embodiments described above.
The embodiment of the invention discloses A1, a data processing method, which comprises the following steps:
responding to a target point of interest to be entered by a target terminal, and determining a target positioning model corresponding to the target point of interest;
respectively acquiring satellite positioning data, wireless network transmission positioning data and beacon positioning data of the target terminal;
and inputting the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data into the target positioning model, and determining the positioning information of the target terminal in the target interest point.
A2, according to the data processing method of A1, the determining a target positioning model corresponding to the target interest point in response to the target terminal going to enter the target interest point comprises the following steps:
determining distribution state and position information of the target terminal;
and determining a target positioning model corresponding to the target interest point according to the fact that the delivery state is meal taking and/or the position information of the target terminal represents that the target terminal is about to enter the target interest point.
A3, determining the distribution state and the position information of the target terminal according to the data processing method of A2, wherein the method comprises the following steps:
Acquiring satellite positioning data of the target terminal;
and determining the position information of the target terminal based on the satellite positioning data.
A4, according to the data processing method of A1, the determining a target positioning model corresponding to the target interest point in response to the target terminal going to enter the target interest point comprises the following steps:
acquiring travel information of the target terminal;
and responding to the travel information to represent that the target terminal is about to enter the target interest point, and determining a target positioning model corresponding to the target interest point.
A5, the data processing method according to A1, wherein the target positioning model comprises a signal fingerprint database, the signal fingerprint database comprises signal fingerprints received by each positioning position in the target interest point, and the signal fingerprints comprise at least two of satellite positioning signals, wireless network transmission signals or beacon signal fingerprints;
the step of inputting the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data into the target positioning model to determine the positioning information of the target terminal in the target interest point comprises the following steps:
determining target fingerprint positioning information and target confidence from a signal fingerprint database corresponding to the target interest point according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data;
And determining the positioning information of the target terminal in the target interest point according to the target fingerprint positioning information and the target confidence coefficient.
A6, according to the data processing method of A5, the determining target fingerprint positioning information and target confidence from the signal fingerprint database corresponding to the target interest point according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data comprises:
determining comprehensive positioning data of the target terminal according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data;
determining fingerprint positioning information with highest similarity with the comprehensive positioning data from a signal fingerprint database corresponding to the target interest point;
determining the fingerprint positioning information with the highest similarity with the comprehensive positioning data as the target fingerprint positioning information;
and determining the similarity between the comprehensive positioning data and the target fingerprint positioning information as target confidence.
A7, according to the data processing method of A5, the determining target fingerprint positioning information and target confidence from the signal fingerprint database corresponding to the target interest point according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data comprises:
According to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data, respectively determining first fingerprint positioning information, second fingerprint positioning information and third fingerprint positioning information from a signal fingerprint database corresponding to the target interest point, wherein the first fingerprint positioning information is positioning information with highest similarity with the satellite positioning data, the second fingerprint positioning information is positioning information with highest similarity with the wireless network transmission positioning data, and the third fingerprint positioning information is positioning information with highest similarity with the beacon positioning data;
determining the target fingerprint positioning information and the target confidence according to the first fingerprint positioning information and the corresponding first confidence, the second fingerprint positioning information and the corresponding second confidence and the third fingerprint positioning information and the corresponding third confidence, wherein the first confidence is the similarity of the first fingerprint positioning information and the satellite positioning data, the second confidence is the similarity of the second fingerprint positioning information and the wireless network transmission positioning data, and the third confidence is the similarity of the third fingerprint positioning information and the beacon positioning data.
A8, the data processing method according to the A1, wherein the target positioning model is a machine learning model;
the determining, in response to the target terminal going to enter the target interest point, a target positioning model corresponding to the target interest point includes:
responding to a target point of interest to be entered by a target terminal, and acquiring model related data of a target positioning model corresponding to the target point of interest, wherein the model related data are machine learning model related parameters determined according to historical positioning data of the target point of interest;
the target positioning model is determined based on the machine learning model related parameters.
A9, according to the data processing method of A1, the target interest point is provided with a plurality of beacon transmitters which are divided into a plurality of beacon transmission groups according to positions, wherein each beacon transmission group comprises at least one beacon transmitter;
the method further comprises the steps of:
and controlling the beacon transmitting groups to transmit beacon signals according to a preset period, so that at least one beacon transmitter for transmitting the beacon signals exists in each beacon transmitting group at the same moment.
The embodiment of the invention discloses a B1 data processing device, which comprises:
the first determining module is used for determining a target positioning model corresponding to a target interest point in response to the fact that the target terminal is about to enter the target interest point;
The acquisition module is used for respectively acquiring satellite positioning data, wireless network transmission positioning data and beacon positioning data of the target terminal;
and the second determining module is used for inputting the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data into the target positioning model and determining the positioning information of the target terminal in the target interest point.
Embodiments of the application disclose C1, a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method as claimed in any of A1-A9.
The embodiment of the application discloses D1 and electronic equipment, wherein the equipment comprises:
a memory for storing one or more computer program instructions;
a processor, the one or more computer program instructions being executed by the processor to implement the method of any of A1-A9.
That is, it will be understood by those skilled in the art that all or part of the steps in implementing the methods of the embodiments described above may be implemented by a program stored in a storage medium, where the program includes several instructions for causing a device (which may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps in the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, and various modifications and variations may be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of data processing, the method comprising:
responding to a target point of interest to be entered by a target terminal, and determining a target positioning model corresponding to the target point of interest;
respectively acquiring satellite positioning data, wireless network transmission positioning data and beacon positioning data of the target terminal;
and inputting the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data into the target positioning model, and determining the positioning information of the target terminal in the target interest point.
2. The method according to claim 1, wherein the determining, in response to the target terminal coming into the target point of interest, a target positioning model corresponding to the target point of interest includes:
determining distribution state and position information of the target terminal;
And determining a target positioning model corresponding to the target interest point according to the fact that the delivery state is meal taking and/or the position information of the target terminal represents that the target terminal is about to enter the target interest point.
3. The data processing method according to claim 2, wherein the determining the delivery status and the location information of the target terminal includes:
acquiring satellite positioning data of the target terminal;
and determining the position information of the target terminal based on the satellite positioning data.
4. The method according to claim 1, wherein the determining, in response to the target terminal coming into the target point of interest, a target positioning model corresponding to the target point of interest includes:
acquiring travel information of the target terminal;
and responding to the travel information to represent that the target terminal is about to enter the target interest point, and determining a target positioning model corresponding to the target interest point.
5. The data processing method of claim 1, wherein the target location model comprises a signal fingerprint database comprising signal fingerprints received at each location position within the target point of interest, the signal fingerprints comprising at least two of satellite positioning signals, wireless network transmission signals, or beacon signal fingerprints;
The step of inputting the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data into the target positioning model to determine the positioning information of the target terminal in the target interest point comprises the following steps:
determining target fingerprint positioning information and target confidence from a signal fingerprint database corresponding to the target interest point according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data;
and determining the positioning information of the target terminal in the target interest point according to the target fingerprint positioning information and the target confidence coefficient.
6. The data processing method according to claim 5, wherein determining target fingerprint positioning information and target confidence from a signal fingerprint database corresponding to the target point of interest according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data comprises:
determining comprehensive positioning data of the target terminal according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data;
determining fingerprint positioning information with highest similarity with the comprehensive positioning data from a signal fingerprint database corresponding to the target interest point;
Determining the fingerprint positioning information with the highest similarity with the comprehensive positioning data as the target fingerprint positioning information;
and determining the similarity between the comprehensive positioning data and the target fingerprint positioning information as target confidence.
7. The data processing method according to claim 5, wherein determining target fingerprint positioning information and target confidence from a signal fingerprint database corresponding to the target point of interest according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data comprises:
according to the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data, respectively determining first fingerprint positioning information, second fingerprint positioning information and third fingerprint positioning information from a signal fingerprint database corresponding to the target interest point, wherein the first fingerprint positioning information is positioning information with highest similarity with the satellite positioning data, the second fingerprint positioning information is positioning information with highest similarity with the wireless network transmission positioning data, and the third fingerprint positioning information is positioning information with highest similarity with the beacon positioning data;
Determining the target fingerprint positioning information and the target confidence according to the first fingerprint positioning information and the corresponding first confidence, the second fingerprint positioning information and the corresponding second confidence and the third fingerprint positioning information and the corresponding third confidence, wherein the first confidence is the similarity of the first fingerprint positioning information and the satellite positioning data, the second confidence is the similarity of the second fingerprint positioning information and the wireless network transmission positioning data, and the third confidence is the similarity of the third fingerprint positioning information and the beacon positioning data.
8. A data processing apparatus, the apparatus comprising:
the first determining module is used for determining a target positioning model corresponding to a target interest point in response to the fact that the target terminal is about to enter the target interest point;
the acquisition module is used for respectively acquiring satellite positioning data, wireless network transmission positioning data and beacon positioning data of the target terminal;
and the second determining module is used for inputting the satellite positioning data, the wireless network transmission positioning data and the beacon positioning data into the target positioning model and determining the positioning information of the target terminal in the target interest point.
9. A computer readable storage medium, on which computer program instructions are stored, which computer program instructions, when executed by a processor, implement the method of any of claims 1-7.
10. An electronic device, the device comprising:
a memory for storing one or more computer program instructions;
a processor, the one or more computer program instructions being executed by the processor to implement the method of any of claims 1-7.
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