Data processing method and device, acquisition equipment, beacon equipment and storage medium

Abstract

The embodiment of the invention discloses a data processing method and device, acquisition equipment, beacon equipment and a storage medium, and the method comprises the steps: obtaining first information of a first point location in a target region, and transmitting the first information to multiple pieces of beacon equipment meeting an observation condition; the first information comprises first signal model parameters of the plurality of beacon devices at the first point location; in the process of moving from the first point location to a second point location, second information of a plurality of position points is obtained, and the second information comprises the first signal receiving strength of each beacon device meeting the observation condition and received at each position point and the first distance between each position point and each beacon device; sending the second information to each beacon device, and receiving third information sent by each beacon device; the third information at least comprises second signal model parameters of the corresponding beacon equipment at a plurality of position points; and determining a target signal model based on third information sent by all beacon devices in the target area.

Description

Technical Field

[0001] The present invention relates to the field of positioning technology, and in particular to a data processing method, device, collection equipment, beacon equipment and storage medium. Background Art

[0002] There are many technical solutions for implementing indoor positioning technology. Among them, the Bluetooth Received Signal Strength Indication (RSSI) positioning solution based on the Bluetooth protocol stack is widely used in indoor ranging due to its advantages of low power consumption, low cost and high reliability. This solution performs positioning based on the attenuation law curve of RSSI and distance. The following attenuation formula is usually used to calculate the physical distance between the device and the Bluetooth beacon:

[0003] d = 10 (abs(RSSI)-A) / (10×n)

[0004] Among them, RSSI represents the Bluetooth signal reception strength, which is a negative value, abs(·) represents the calculated absolute value; d represents the distance estimated based on RSSI, A represents the signal reception strength at a distance of 1m from the Bluetooth beacon, and n represents the signal propagation factor. A and n are the empirical values ​​of the attenuation model in different environments. How to determine more accurate A and n is the key to improving the accuracy of Bluetooth positioning.

[0005] At present, the commonly used methods for measuring these two parameters include estimation, weighted average calculation and field measurement. Among them, the estimation method is a qualitative method. After the positioning system is deployed, the parameter A must be determined experimentally. Then the positioning node is placed in the center of the ranging surface. By continuously fine-tuning the signal propagation factor n, the corresponding n value is determined under accurate positioning conditions. The n value determined by this method is inaccurate for relatively mixed indoor positioning. It may happen that the positioning of a certain point is calibrated but the positioning of other points is inaccurate. The weighted average calculation method performs weighted calculations on multiple signal propagation factors n. This method is usually used to achieve a larger coverage space with as few beacon devices as possible. Often, multiple beacon devices are placed at close to equal distances, resulting in a relatively large actual sampling distance. Concentrated in a certain distance interval, the n value obtained by weighted calculation may have errors, and this method is a black box algorithm, and the operator cannot intuitively see the calculation accuracy of the n value; in order to measure the parameters A and n in the RSSI characteristic curve, the on-site measurement method generally requires the detection instrument to continuously send Bluetooth data packets to the coordinator, and the coordinator collects the data packets and sends them to the host computer. The operator needs to manually copy the data packets received by the serial port on the host computer, and classify the measured data into equal intervals, and arrange the equally spaced RSSI values ​​in sequence to obtain A and n values ​​based on the fitting code. This method is complicated to operate and the fitting process is not intuitive, and the workload is large. Summary of the invention

[0006] In order to solve the existing technical problems, the embodiments of the present invention provide a data processing method, device, collection equipment, beacon equipment and storage medium.

[0007] To achieve the above purpose, the technical solution of the embodiment of the present invention is implemented as follows:

[0008] In a first aspect, an embodiment of the present invention provides a data processing method, which is applied to a collection device; the method comprises:

[0009] Acquire first information of a first point in a target area, and send the first information to a plurality of beacon devices that meet observation conditions; the first information includes first signal model parameters of the plurality of beacon devices at the first point;

[0010] In the process of moving from the first point to the second point, second information of multiple points is obtained, wherein the second information includes a first signal reception strength of each beacon device that meets the observation condition at each point, and a first distance between each point and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area;

[0011] Sending the second information to each beacon device, and receiving third information sent by each beacon device; the third information at least includes second signal model parameters of the corresponding beacon device at the multiple location points;

[0012] The target signal model is determined based on the third information sent by all beacon devices in the target area.

[0013] In the above scheme, the third information also includes the first weight of the beacon device corresponding to each location point, and the first weight is determined based on the first distance; the target signal model is determined based on the third information sent by all beacon devices in the target area, including: determining the N beacon devices with the first signal reception strength ranked first at each location point, where N is a positive integer; determining the second weight of each location point according to the first weight of each of the N beacon devices; determining the third signal model parameters of each location point based on the second weight and the third information sent by all beacon devices, and determining the target signal model based on the third signal model parameters at all location points.

[0014] In the above scheme, the third signal model parameters of each location point are determined based on the second weight and the third information sent by all beacon devices, including: based on the second weights of multiple location points, weighted averaging the second signal model parameters of each of the N beacon devices at the multiple location points to obtain the third signal model parameters, wherein the third signal model parameters include the signal model parameters of each of the N beacon devices at each location point.

[0015] In the above scheme, the obtaining of the first information of the first point in the target area includes: determining the multiple beacon devices that meet the observation conditions at the first point; collecting multiple groups of signal data, each group of signal data includes the second signal reception strength received by each beacon device at the first point, and the second distance between the first point and each beacon device; each group of signal data is collected at a different height and / or at a different angle; and determining the first information based on the multiple groups of signal data.

[0016] In a second aspect, an embodiment of the present invention provides a data processing method, which is applied to a beacon device; the method comprises:

[0017] Receive first information and second information sent by a collection device, wherein the first information includes first signal model parameters of multiple beacon devices at a first point; the second information includes first signal reception strength of each beacon device that meets the observation condition received by the collection device at each position point among multiple positions between the first point and the second point, and a first distance between each position point and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area;

[0018] Training the first signal model parameters based on the second information to obtain third information, where the third information at least includes the second signal model parameters of the beacon device at the multiple locations;

[0019] The third information is sent to the acquisition device, where the third information is used by the acquisition device to determine a target signal model corresponding to the target area.

[0020] In the above scheme, the method also includes: determining the first weight corresponding to the beacon device based on all the first distances included in the second information; accordingly, the third information also includes the first weight, the first weight is used by the acquisition device to determine the second weight of each location point, and the second weight is used by the acquisition device to determine the third signal model parameters of each location point and determine the target signal model based on the third signal model parameters.

[0021] In a third aspect, an embodiment of the present invention provides a data processing device, which is applied to a collection device; the device includes an acquisition module, a first communication module and a first processing module; wherein,

[0022] The acquisition module is used to acquire first information of a first point in the target area, wherein the first information includes first signal model parameters of a plurality of beacon devices at the first point;

[0023] The first communication module is used to send the first information to multiple beacon devices that meet the observation condition;

[0024] The acquisition module is further used to acquire second information of multiple positions in the process of moving from the first point to the second point, wherein the second information includes a first signal reception strength of each beacon device that meets the observation condition received at each position, and a first distance between each position and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area;

[0025] The first communication module is further used to send the second information to each beacon device and receive third information sent by each beacon device; the third information at least includes second signal model parameters of the corresponding beacon device at the multiple location points;

[0026] The first processing module is used to determine the target signal model based on the third information sent by all beacon devices in the target area.

[0027] In the above scheme, the third information also includes the first weight of the beacon device corresponding to each location point, and the first weight is determined based on the first distance; the first processing module is used to determine the N beacon devices with the first signal reception strength ranked first at each location point, where N is a positive integer; determine the second weight of each location point according to the first weight of each of the N beacon devices, and determine the third signal model parameters of each location point based on the second weight and the third information sent by all beacon devices, and determine the target signal model based on the third signal model parameters at all location points.

[0028] In the above scheme, the acquisition module is used to determine the multiple beacon devices that meet the observation conditions at the first point position, and collect multiple groups of signal data, each group of signal data includes the second signal reception strength of each beacon device received at the first point position and the second distance between each beacon device; each group of signal data has a different collection height and / or collection angle; and the first information is determined based on the multiple groups of signal data.

[0029] In the above scheme, the first processing module is used to perform weighted averaging on the second signal model parameters of each of the N beacon devices at the multiple location points based on the second weights of the multiple location points to obtain the third signal model parameters, wherein the third signal model parameters include the signal model parameters of each of the N beacon devices at each location point.

[0030] In a fourth aspect, an embodiment of the present invention provides a data processing device, which is applied to a beacon device; the device includes a second communication module and a second processing module; wherein,

[0031] The second communication module is used to receive first information and second information sent by the acquisition device, wherein the first information includes first signal model parameters of multiple beacon devices at a first point; the second information includes the first signal reception strength of each beacon device that meets the observation condition received by the acquisition device at each position point of multiple positions between the first point and the second point, and the first distance between each position point and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area;

[0032] The second processing module is used to train the first signal model parameters based on the second information to obtain third information, where the third information at least includes the second signal model parameters of the beacon device at the multiple location points;

[0033] The second communication module is further used to send the third information to the acquisition device, and the third information is used by the acquisition device to determine the target signal model corresponding to the target area.

[0034] In the above scheme, the second processing module is also used to determine the first weight corresponding to the beacon device based on all the first distances included in the second information; accordingly, the third information also includes the first weight, and the first weight is used by the acquisition device to determine the second weight of each location point, and the second weight is used by the acquisition device to determine the third signal model parameters of each location point and to determine the target signal model based on the third signal model parameters.

[0035] In a fifth aspect, an embodiment of the present invention provides a collection device, including a detection module, a collection module and a first processing module; wherein:

[0036] The detection module is used to determine the beacon device that meets the observation conditions;

[0037] The acquisition module is used to collect the signal reception strength of the beacon device and the distance between the acquisition module and the beacon device;

[0038] The first processing module includes a processor and a memory for storing a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, the steps of the method described in the first aspect are executed.

[0039] In the above scheme, the acquisition device includes two groups of acquisition modules with fixed relative postures, and each group of acquisition modules includes a ranging module and a signal measurement module; wherein the ranging module is used to determine the distance between the acquisition module and the beacon device; and the ranging module is used to collect the signal reception strength of the beacon device.

[0040] In a sixth aspect, an embodiment of the present invention provides a beacon device, comprising a signal sending module and a second processing module; wherein:

[0041] The signal sending module is used to send signals;

[0042] The second processing module includes a processor and a memory for storing a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, the steps of the method described in the second aspect are executed.

[0043] In the seventh aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the steps of the method described in the first aspect are performed; or, when the program is executed by a processor, the steps of the method described in the second aspect are performed.

[0044] The data processing method, device, acquisition device, beacon device and storage medium provided by the embodiment of the present invention, the acquisition device acquires first information of a first point in the target area, the first information includes first signal model parameters of multiple beacon devices at the first point, and can analyze data in real time during the sampling process to provide an accurate local fitting model (i.e., first signal model parameters); at the same time, the acquisition device acquires second information of multiple position points in the process of moving from the first point to the second point, sends the second information to each beacon device and receives third information sent by each beacon device, the third information at least includes the second signal model parameters of the corresponding beacon device at multiple position points, this embodiment is based on the idea of ​​federal aggregation, does not require the host computer to perform data processing, expands each beacon device as a computing unit, and can make full use of the distributed computing capabilities of the beacon device; further, the acquisition device determines the target signal model based on the third information sent by all beacon devices in the target area, and can form an overall more refined global fitting model through the local fitting model. Compared with the related art based on a set of signal model parameters for the entire positioning area, this embodiment can improve the positioning accuracy of the global area by improving the accuracy of the signal fitting model in each local area, the method is simple and easy to implement, and can effectively reduce the workload. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 The data processing method of the present invention is shown in FIG. Figure 1 ;

[0046] Figure 2 A schematic diagram of a collection device moving in a target area according to an embodiment of the present invention;

[0047] Figure 3 The data processing method of the present invention is shown in FIG. Figure 2 ;

[0048] Figure 4 A schematic diagram of the structure of a collection device according to an embodiment of the present invention;

[0049] Figure 5 A schematic diagram of the structure of a beacon device according to an embodiment of the present invention;

[0050] Figure 6 A schematic diagram of an exemplary structure of a collection device according to an embodiment of the present invention;

[0051] Figure 7 A schematic diagram of a collection device according to an embodiment of the present invention;

[0052] Figure 8 An exemplary flow chart of the data processing solution of an embodiment of the present invention applied to Bluetooth data processing;

[0053] Fig. 9 The structure diagram of the data processing device according to the embodiment of the present invention is shown in FIG. Figure 1 ;

[0054] Fig.10 The structure diagram of the data processing device according to the embodiment of the present invention is shown in FIG. Figure 2 . DETAILED DESCRIPTION

[0055] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] In the description of the present invention, it should be noted that the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. These terms are only used to distinguish one element (or threshold or application or instruction or operation) from another element (or threshold or application or instruction or operation). For example, a first operation can be called a second operation, and a second operation can also be called a first operation without departing from the scope of the present invention. Both the first operation and the second operation are operations, but they are not the same operation.

[0057] The term "and / or" in the embodiments of the present invention refers to any and all possible combinations of one or more of the associated enumerated items. It should also be noted that when used in this specification, "include / comprise" specifies the existence of the stated features, integers, steps, operations, elements and / or components, but does not exclude the existence or addition of one or more other features, integers, steps, operations, elements and / or components and / or their groups.

[0058] The steps in the embodiments of the present invention do not necessarily have to be processed in the order of the described steps. The steps can be selectively rearranged, or the steps in the embodiments can be deleted, or the steps in the embodiments can be added as needed. The step description in the embodiments of the present invention is only an optional sequence combination and does not represent all step sequence combinations in the embodiments of the present invention. The step order in the embodiments cannot be regarded as a limitation of the present invention.

[0059] An embodiment of the present invention provides a data processing method, which is applied to a collection device; Figure 1 The data processing method of the present invention is shown in FIG. Figure 1 ,like Figure 1 As shown, the method includes:

[0060] Step 101: Acquire first information of a first point in a target area, and send the first information to a plurality of beacon devices that meet observation conditions; the first information includes first signal model parameters of the plurality of beacon devices at the first point;

[0061] Step 102: in the process of moving from the first point to the second point, obtaining second information of a plurality of points, the second information including a first signal reception strength of each beacon device meeting the observation condition received at each point, and a first distance between each point and each beacon device; wherein the first point and the second point are any two adjacent points among the plurality of points included in the target area;

[0062] Step 103: Send the second information to each beacon device, and receive third information sent by each beacon device; the third information at least includes second signal model parameters of the corresponding beacon device at the multiple locations;

[0063] Step 104: Determine a target signal model based on the third information sent by all beacon devices in the target area.

[0064] In this embodiment, a plurality of beacon devices are deployed in the target area, and the beacon devices may be, for example, Bluetooth beacon devices. The signal models involved in the embodiments of the present invention may be, for example, Bluetooth received signal strength indication (RSSI) models, and the corresponding signal model parameters may include a first parameter (A) representing the signal receiving strength value at 1 meter (m) from the beacon device, and a second parameter (n) representing the signal propagation factor. The target area may also include a plurality of points, which may be pre-divided or determined by the regular movement of the acquisition device, such as when the acquisition device travels along a specific route in the target area, it stays in place at intervals or every time it travels a certain distance, thereby obtaining a plurality of points in the target area.

[0065] Figure 2 FIG. 1 is a schematic diagram of the movement of the acquisition device in the target area according to an embodiment of the present invention. Figure 2 As shown, the target area may be pre-deployed with multiple beacon devices, and the acquisition device of this embodiment may collect signal strength data at multiple points in the target area and / or at positions between multiple points. Exemplarily, the acquisition device may automatically travel along a feasible route in the target area, and sample the signal reception strength emitted by the beacon device during the driving process. For example, the sampling device stops to collect data every time it reaches a point after traveling a certain distance (e.g., one meter). After the collection is completed, it continues to move forward, and in the process of traveling from any point to another adjacent point, it collects data every time (e.g., 20 milliseconds), thereby completing the signal data collection of the entire target area.

[0066] In this embodiment, the first information includes first signal model parameters of multiple beacon devices that meet the observation conditions at the first point. Exemplarily, each beacon device is a Bluetooth beacon device, and the corresponding signal model is a Bluetooth RSSI signal model. The first information can characterize the relationship between the reception strength of the Bluetooth signals sent by each of the multiple beacon devices and the distance from the receiving point to the transmitting point. The first signal model parameters may, for example, include a first parameter (A) characterizing the signal reception strength value of the beacon device at 1 meter (m) away from the beacon device, and a second parameter (n) characterizing the signal propagation factor.

[0067] As an example, the first information may include a first parameter and a second parameter of each beacon device corresponding to a first point.

[0068] In some embodiments, satisfying the observation condition may include: the collection device is within the communication range of the beacon device, and / or the beacon device is within the communication range of the collection device.

[0069] In some embodiments, the acquisition device is provided with a detection module, which can be used to detect beacon devices within a preset range; the sending of the first information to multiple beacon devices that meet the observation conditions may include: the acquisition device determines multiple beacon devices that meet the observation conditions based on the detection module, and sends the first information to the multiple beacon devices. Optionally, the detection module may include, for example, a camera component and a data processing module, and detects multiple beacon devices that meet the observation conditions through image recognition technology; or, the detection module may also include a distance measurement module, which may be implemented based on time of flight (TOF) technology, and determines multiple beacon devices that meet the observation conditions through distance.

[0070] In step 102, the plurality of position points are the plurality of position points that the acquisition device passes through during the process of moving from the first point to the second point. For example, the acquisition device determines a position point at intervals of time or at intervals of distance during the process of moving from the first point to the second point, thereby obtaining a plurality of position points, such as Figure 2 As shown, during the process of the collection device moving from the first point to the second point, the first signal reception strength of each beacon device that meets the observation conditions and the first distance between the current point and each beacon device can be collected every 20 milliseconds.

[0071] It should be noted that, in this embodiment, the first point and the second point represent any two adjacent points that the acquisition device passes through when moving in the target area according to a preset motion trajectory.

[0072] In step 103, the acquisition device sends the second information to each beacon device, and the second information is used for each beacon device to train the first signal model parameters to obtain the second signal model parameters of each beacon device at multiple locations.

[0073] In some embodiments, each beacon device can determine the signal model parameters of each location point based on the first signal reception strength and the first distance corresponding to each location point, and train the first signal model parameters based on the signal model parameters of each location point to obtain the second signal model parameters of the beacon device at each location point.

[0074] In step 104, the acquisition device aggregates the third information sent by all beacon devices to obtain a target signal model corresponding to the target area. The target signal model may include signal model parameters of each beacon device corresponding to each position point in the target area, such as the first parameter and the second parameter of each beacon device corresponding to each position point.

[0075] In some embodiments, step 104 may include: the acquisition device fuses the second signal model parameters of each beacon device at the corresponding location point based on the contribution value of each beacon device at each location point, obtains the target signal model parameters corresponding to each location point, and determines the target signal model based on the target signal model parameters of all location points. In this embodiment, the second signal model parameters of all beacon devices at each location point can be aggregated by federated learning.

[0076] According to the data processing method of the embodiment of the present invention, the acquisition device first obtains the first signal model parameters of multiple beacon devices at the first point, which can realize real-time data analysis during the sampling process and provide an accurate local fitting model (i.e., the first signal model parameters); at the same time, the second information of multiple position points is obtained in the process of moving from the first point to the second point, the second information is sent to each beacon device and the third information sent by each beacon device is received, and the third information at least includes the second signal model parameters of the corresponding beacon device at multiple position points. This embodiment is based on the idea of ​​federal aggregation and does not require the host computer to perform data processing. Each beacon device is expanded as a computing unit, which can make full use of the distributed computing capabilities of the beacon device; further, the acquisition device determines the target signal model based on the third information sent by all beacon devices in the target area, and a more refined global fitting model can be formed as a whole through the local fitting model. Compared with the related art based on a set of signal model parameters for the entire positioning area, this embodiment can improve the positioning accuracy of the global area by improving the accuracy of the signal fitting model in each local area. The method is simple and easy to implement and can effectively reduce the workload.

[0077] In an optional embodiment of the present invention, the third information also includes a first weight of the beacon device corresponding to each location point, and the first weight is determined based on the first distance; determining the target signal model based on the third information sent by all beacon devices in the target area may include: determining the N beacon devices with the first signal reception strength ranked first at each location point, where N is a positive integer; determining the second weight of each location point according to the first weight of the N beacon devices; determining the third signal model parameters of each location point based on the second weight and the third information sent by all beacon devices, and determining the target signal model based on the third signal model parameters at all location points.

[0078] In this embodiment, the third information sent by each beacon device to the collection device also includes a first weight of each beacon device corresponding to each location point, and the first weight can be determined based on the first distance between all beacon devices and the location point.

[0079] In some embodiments, the first weight can be obtained in the following manner: For example, there are x beacon devices that meet the observation condition at a certain location point, and the first distance between each beacon device and the location point is s. 1 、s 2 ,…,s x , the first weight of x beacon devices corresponding to each location point can be Q 1 =1-s 1 / (s 1 +s 2 +…+s x ), Q 2 =1-s 2 / (s 1 +s 2 +…+s x ),…,Q x =1-s x / (s 1 +s 2 +…+s x ). Thus, for each position point from the first position to the second position, the first weight of each beacon device that meets the observation condition at the position point can be determined.

[0080] As an optional implementation, the first weights of the N beacon devices corresponding to a certain location point are Q 1 , Q 2 ,…,Q N , the corresponding second weight may be, for example, G=1-(Q 1 +Q 2 +…+Q N ). For example, N can be 3, that is, the second weight corresponding to each location point can be obtained according to the first weights of the three beacon devices ranked first by the first signal reception strength at the location point, that is, G = 1-(Q 1 +Q 2 +Q 3 ).

[0081] In some embodiments, determining the third signal model parameters of each location point based on the second weight and the third information sent by all beacon devices may include: performing weighted averaging on the second signal model parameters of each of the N beacon devices at the multiple location points based on the second weights of the multiple location points to obtain the third signal model parameters, wherein the third signal model parameters include the signal model parameters of each of the N beacon devices at each location point.

[0082] Exemplarily, taking weighted averaging at three location points as an example, the signal model parameters of any beacon device at each location point can be obtained by weighted averaging the second signal model parameters of multiple location points near the location point of the beacon device according to the second weights of each of the multiple location points. For example, for location point 1, the second signal model parameters of any beacon device at location point 1, location point 2 and location point 3 are (A1, n1), (A2, n2), and (A3, n3), respectively, where A1, A2, and A3 are the first parameters of the beacon device at location point 1, location point 2, and location point 3, respectively, and n1, n2, and n3 are the second parameters of the beacon device at location point 1, location point 2, and location point 3, respectively. The first parameter and the second parameter are weighted averaged according to the second weights G1, G2, and G3 corresponding to the above three location points, respectively, to obtain the third signal model parameters of location point 1, where the first parameter A=G1×A1+G2×A2+G3×A3, and the second parameter n=G1×n1+G2×n2+G3×n3. The second parameters corresponding to the remaining location points can be obtained with reference to location point 1, thereby obtaining the third signal model parameters of each location point.

[0083] In an optional embodiment of the present invention, the acquisition of first information of a first point in the target area may include: determining the multiple beacon devices that meet the observation conditions at the first point; collecting multiple groups of signal data, each group of signal data including the second signal reception strength received by each beacon device at the first point, and the second distance between the first point and each beacon device; each group of signal data has a different collection height and / or collection angle; and determining the first information based on the multiple groups of signal data.

[0084] As an optional implementation, an identifier may be set at each location where a beacon device is deployed in the target area or on each beacon device, so that the acquisition device can identify the multiple beacon devices that meet the observation conditions. For example, a paper with a corresponding beacon device number mark may be pasted or hung at each location where a beacon device is placed or on each beacon device, and the multiple beacon devices that meet the observation conditions may be determined through the camera and image recognition program in the acquisition device. As another optional implementation, the multiple beacon devices that meet the observation conditions may be determined through communication between the acquisition device and each beacon device.

[0085] It should be noted that each set of signal data may include multiple sets of second signal reception strengths and second distances at different times. That is to say, this embodiment can collect multiple sets of second signal reception strengths and second distances at the same collection height and the same collection angle to reduce collection errors.

[0086] As an example, the collection of multiple groups of signal data may include: collecting at least two groups of signal data at different collection heights and / or different collection angles. Exemplarily, the collection device may include a collection module with adjustable height and angle, firstly collecting multiple groups of signal data (e.g., 10 groups) at a first height and a first angle, each group of signal data is, for example, {{beacon device number x1, signal reception strength z1, distance s1}, {beacon device number x2, signal reception strength z2, distance s2}, ..., {beacon device number xn, signal reception strength zn, distance sn}}; then adjusting the collection height to the second height, adjusting the collection angle to the second angle, and obtaining multiple groups of signal data at the first height and the second angle, the second height and the first angle, and the second height and the second angle. Optionally, the first height is greater than the second height, for example, the first height is the average height of the first user, and the second height is the average height of the second user, respectively simulating the signal data of the beacon device that users of different heights can receive at the first point.

[0087] In some embodiments, the first signal model parameter includes a first parameter representing a signal reception strength value of a beacon device 1m away from the beacon device, and a second parameter representing a signal propagation factor; the first information may be obtained in the following manner:

[0088] First, the first parameter A and the second parameter n corresponding to the first beacon device are calculated according to the following formula based on any two sets of signal data:

[0089]

[0090]

[0091] Among them, RSSI1 and RSSI2 are respectively the second received signal strengths of the first beacon device respectively included in any two groups of signal data in the multiple groups of signal data, d1 and d2 are respectively the second distances of the first beacon device respectively included in any two groups of signal data in the multiple groups of signal data, and the first beacon device is any beacon device in the multiple beacon devices; abs(·) represents the calculation of the absolute value, and lg represents the logarithm with the base of 10. Then, the average values ​​of all the first parameters and all the second parameters obtained are calculated respectively to determine the first information.

[0092] Exemplarily, the data for the same beacon device in multiple groups of signal data are combined in pairs, and the A and n corresponding to the two combined groups of signal data are calculated according to the above formulas. Then, the average values ​​of all the obtained A and n are calculated to determine the A and n corresponding to the first point of the beacon device, thereby obtaining the first information.

[0093] In some embodiments, the acquisition device includes two groups of acquisition modules with fixed relative postures, and the multiple groups of signal data also include multiple groups of first signal data collected by the first group of acquisition modules at different acquisition heights and / or different acquisition angles, and multiple groups of second signal data collected by the second group of acquisition modules at different acquisition heights and / or different acquisition angles. In this embodiment, multiple first parameters A and multiple second parameters n corresponding to the beacon device can be determined according to the above formula based on the multiple groups of first signal data and the multiple groups of second signal data, and then the average value is calculated based on all the first parameters A corresponding to the two groups of signal data, and the average value is calculated based on all the second parameters n corresponding to the two groups of signal data, thereby obtaining the first information.

[0094] The embodiment of the present invention also provides a data processing method, which is applied to a beacon device; Figure 3 The data processing method of the present invention is shown in FIG. Figure 2 ,like Figure 3 As shown, the method includes:

[0095] Step 201, receiving first information and second information sent by a collection device, wherein the first information includes first signal model parameters of multiple beacon devices at a first point; the second information includes the first signal reception strength of each beacon device that meets the observation condition received by the collection device at each of multiple positions between the first point and the second point and the first distance between the collection device and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area;

[0096] Step 202: Train the first signal model parameters based on the second information to obtain third information, where the third information at least includes the second signal model parameters of the beacon device at the multiple locations;

[0097] Step 203: Send the third information to the acquisition device, where the third information is used by the acquisition device to determine a target signal model corresponding to the target area.

[0098] In this embodiment, the beacon device can be, for example, a Bluetooth beacon device, and multiple beacon devices are deployed in the target area. When the collection device moves to the observation range corresponding to each beacon device, each beacon device can receive the first information and the second information sent by the collection device.

[0099] In some embodiments, step 202 may include: the beacon device may determine the signal model parameters at each location point based on the second information, and train the first signal model parameters based on the signal model parameters at each location point to obtain the second signal model parameters of the beacon device at each location point.

[0100] In the data processing method of the embodiment of the present invention, a beacon device receives first information and second information sent by a collection device, wherein the first information includes first signal model parameters of multiple beacon devices at a first point, and the second information includes the first signal reception strength of each beacon device that meets the observation conditions received by the collection device at each position point of multiple positions between the first point and the second point, and the first distance between each position point and each beacon device. This embodiment can be based on the idea of ​​federal aggregation, does not require a host computer to perform data processing, and expands each beacon device as a computing unit, which can fully utilize the distributed computing capabilities of the beacon device; the beacon device trains the first signal model parameters based on the second information to obtain third information, wherein the third information includes the second signal model parameters of the beacon device at multiple positions, and sends the third information to the collection device. After receiving the third information, the collection device can form a more sophisticated global fitting model as a whole through a local fitting model. Compared with the related art in which a set of signal model parameters is used for the entire positioning area, this embodiment can improve the positioning accuracy of the global area by improving the accuracy of the signal fitting model in each local area.

[0101] In an optional embodiment of the present invention, the method may also include: determining the first weight corresponding to the beacon device based on all the first distances included in the second information; accordingly, the third information also includes the first weight, the first weight is used by the acquisition device to determine the second weight of each location point, the second weight is used by the acquisition device to determine the third signal model parameters of each location point and determine the target signal model based on the third signal model parameters.

[0102] In some embodiments, the second information is, for example, {{beacon device number x1, signal reception strength z1, distance s1}, {beacon device number x2, signal reception strength z2, distance s2}, ...}. Exemplarily, the second information received by the beacon device includes data corresponding to x beacon devices, and the first distance between each beacon device and the location point is s. 1 、s 2 ,…,s x , the first weight of x beacon devices corresponding to each location point can be, for example, Q 1 =1-s 1 / (s 1 +s 2 +…+s x ), Q 2 =1-s 2 / (s 1 +s 2 +…+s x ),…,Q x =1-sx / (s 1 +s 2 +…+s x ). Thus, the beacon device can determine a first weight corresponding to each position point from the first point to the second point.

[0103] The embodiment of the present invention also provides a collection device. Figure 4 FIG. 1 is a schematic diagram of the structure of a collection device according to an embodiment of the present invention. Figure 4 As shown, the acquisition device 300 includes a detection module 301, a collection module 302 and a first processing module 303; wherein,

[0104] The detection module 301 is used to determine the beacon device that meets the observation conditions;

[0105] The acquisition module 302 is used to collect the signal reception strength of the beacon device and the distance between the acquisition module and the beacon device;

[0106] The first processing module 303 includes a processor and a memory for storing a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, it executes the steps of the data processing method in the aforementioned embodiment in which the execution subject is the acquisition device.

[0107] In some embodiments, the first processing module 303 is used to obtain first information of a first point in the target area, and send the first information to multiple beacon devices that meet the observation conditions; the first information includes first signal model parameters of multiple beacon devices at the first point; and in the process of moving from the first point to the second point, obtain second information of multiple position points, the second information includes the first signal reception strength of each beacon device that meets the observation conditions received at each position point, and the first distance between each position point and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area; send the second information to each beacon device, receive the third information sent by each beacon device, the third information at least includes the second signal model parameters of the corresponding beacon device at the multiple position points; determine the target information model based on the third information sent by all beacon devices in the target area.

[0108] In some embodiments, the third information also includes a first weight of each beacon device corresponding to each location point, and the first weight is determined based on the first distance; the first processing module 303 is used to determine the N beacon devices with the first signal reception strength ranked first at each location point, where N is a positive integer; determine the second weight of each beacon device corresponding to each location point according to the first weights of each of the N beacon devices; determine the third signal model parameters of each location point based on the second weight and the third information sent by all beacon devices, and determine the target signal model based on the third signal model parameters at all location points.

[0109] In some embodiments, the detection module 301 is used to determine the multiple beacon devices that meet the observation conditions at the first point; the acquisition module 302 is used to collect multiple groups of signal strength data, each group of signal data includes the second signal reception strength received by each beacon device at the first point, and the second distance between the first point and each beacon device; each group of signal data has a different collection height and / or collection angle; the first processing module 303 is used to determine the first information based on the multiple groups of signal data.

[0110] In an optional embodiment of the present invention, the acquisition device 300 includes two groups of acquisition modules 302 with fixed relative postures, and each group of acquisition modules 302 includes a ranging module and a signal measurement module; wherein the ranging module is used to determine the distance between the acquisition module and the beacon device; and the signal measurement module is used to collect the signal reception strength of the beacon device.

[0111] In some embodiments, the first processing module 303 includes a motion module for controlling the movement of the acquisition device. Exemplarily, the motion module can be used to control the acquisition device to move between different points in the target area according to a set route, such as controlling the movement trajectory of the acquisition device in the target area, controlling the acquisition device to stay at a first point to collect signal data, and controlling the trajectory and speed of the acquisition device moving from the first point to the second point.

[0112] In some embodiments, the acquisition device 300 also includes a display module, which may include a camera component and a display component. The camera component can be used to capture images or video data of the acquisition device during driving, and the display component can be used to display the images or video data captured by the camera component.

[0113] The data processing method for the acquisition device disclosed in the above embodiment of the present invention can be applied to the first processing module 303, or implemented by the first processing module 303. The processor in the first processing module 303 may be an integrated circuit chip with data processing capabilities. In the implementation process, the steps of the data processing method for the acquisition device can be completed by the hardware integrated logic circuit or software instructions in the processor. The above processor can be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general processor can be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in the memory of the first processing module 303. The processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0114] An embodiment of the present invention also provides a beacon device. Figure 5 FIG. 1 is a schematic diagram of the structure of a beacon device according to an embodiment of the present invention. Figure 5 As shown, the beacon device 400 includes a signal sending module 401 and a second processing module 402; wherein the signal sending module 401 is used to send a signal;

[0115] The second processing module 402 includes a processor and a memory for storing a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, it executes the steps of the data processing method in the aforementioned embodiment in which the execution subject is a beacon device.

[0116] In some embodiments, the second processing module 402 is used to receive first information and second information sent by a collection device, the first information including first signal model parameters of multiple beacon devices at a first point; the second information includes the first signal reception strength of each beacon device that meets the observation conditions received by the collection device at each of multiple positions between the first point and the second point and the first distance between the collection device and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area; the first signal model parameters are trained based on the second information to obtain third information, the third information at least including the second signal model parameters of the beacon device at the multiple positions; and the third information is sent to the collection device, and the third information is used by the collection device to determine the target signal model corresponding to the target area.

[0117] In some embodiments, the second processing module 402 is also used to determine the first weight corresponding to the beacon device based on all the first distances included in the second information; accordingly, the third information also includes the first weight, and the first weight is used by the acquisition device to determine the second weight of each location point, and the second weight is used by the acquisition device to determine the third signal model parameters of each location point and determine the target signal model based on the third signal model parameters.

[0118] The data processing method for a beacon device disclosed in the above embodiment of the present invention can be applied to the second processing module 402, or implemented by the second processing module 402. The processor in the second processing module 402 may be an integrated circuit chip with data processing capabilities. In the implementation process, each step of the data processing method for a beacon device can be completed by an integrated logic circuit of hardware in the processor or instructions in software form. The above processor may be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, which is located in the memory of the second processing module 402. The processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0119] The data processing scheme of the embodiment of the present invention is described below in conjunction with specific application scenarios.

[0120] This example takes the construction of the Bluetooth RSSI signal model as an example. In this example, the collection device includes a Bluetooth transceiver module, which is used to collect Bluetooth signal data sent by a beacon device. The beacon device is a Bluetooth beacon device. Figure 6 FIG. 1 is a schematic diagram of an exemplary structure of a collection device according to an embodiment of the present invention. Figure 6 As shown, the acquisition device 500 may include a detection module 510, an acquisition module 520, a communication module 530, a display module 540, a motion module 550, a power module 560, a storage module 570 and a processing module 580, etc.; wherein the detection module 510 may include a camera module and an image processing module for detecting beacon devices that meet the observation conditions; the acquisition module 520 may include a Bluetooth module (i.e., the signal measurement module in the aforementioned embodiment) and a distance measurement module, the Bluetooth module is used to receive Bluetooth signals and measure Bluetooth signal reception strength data, and the distance measurement module is used to measure the distance between the beacon device; the communication module 530 is used to communicate with the beacon device; the display module 540 is used to display the acquisition data, motion trajectory, processing process data and other related data; the motion module 550 is used to control the movement to acquire data, for example, controlling the acquisition device to move along a preset trajectory with a certain degree of freedom; the power module 560 is used to supply power, the storage module 570 is used to store the acquisition data, motion trajectory data, processing process data and other related data, and the processing module 580 is used to implement the steps of the data processing method in the aforementioned embodiment in which the execution subject is the acquisition device.

[0121] In this example, the distance measurement module can be based on laser positioning technology to achieve distance measurement, for example, it can be a TOF sensor. The detection module 510 can be combined with artificial intelligence based on deep learning to identify the beacon device mark within the scene line of sight, and measure the physical distance between the acquisition device and the mark (i.e., the beacon device) through the TOF sensor in the distance measurement module.

[0122] Figure 7 A schematic diagram of a collection device according to an embodiment of the present invention is shown in FIG. Figure 7 As shown, the acquisition device 500 may include two head devices 610, a crossbar 620, a vertical pole 630, and a body 640, wherein the vertical pole 630 is fixed above the body 640, the crossbar 620 is vertically liftable and installed on the vertical pole 630, and can rotate in a plane perpendicular to the vertical pole 630; the two head devices 610 are respectively installed at both ends of the crossbar 620, and the positions are kept fixed by the crossbar 620.

[0123] In this example, a group of acquisition modules 520 are integrated in each head device 610, and the acquisition modules 520 can collect data at different heights and / or different angles by lifting and rotating the crossbar 620.

[0124] In some examples, a camera module may also be integrated into each head device 610. Optionally, the camera module may rotate 360 ​​degrees to detect beacon devices within the scene viewing range.

[0125] by Figure 7 Taking the collection device 500 shown as an example, this example also provides a data processing flow. Figure 8 FIG. 1 is an exemplary flow chart of the data processing solution of an embodiment of the present invention applied to Bluetooth data processing. Figure 8 As shown, the process includes:

[0126] Step 701: The collection device determines multiple beacon devices that meet the observation conditions at the first point in the target area, and collects multiple groups of signal data, each group of signal data includes the second signal reception strength received by each beacon device at the first point, and the second distance between the first point and each beacon device; each group of signal data has a different collection height and / or collection angle.

[0127] As an implementation method, in this example, a piece of paper with a beacon number mark may be pasted or hung at the location of each Bluetooth beacon in the target area, and the beacon number information may be entered into the collection device. The collection device 500 is started, and the collection device 500 is controlled to automatically drive along a feasible route in the target area to sample the Bluetooth signal reception strength data. Optionally, the collection device 500 may be controlled to automatically move forward for a certain distance (such as one meter), and then stop to start data sampling.

[0128] During specific sampling, the camera module 511 in the sampling device 500 can rotate 360 ​​degrees, and use the computer vision algorithm to find the marking point where the Bluetooth beacon is placed. When the mark of the Bluetooth beacon is found, the distance to the beacon mark is measured and recorded through the distance measurement module 522. At the same time, the Bluetooth module 521 collects the Bluetooth signal reception strength value at the corresponding position, which can be stored as a group in the form of {{beacon number x1, RSSIz1, distance s1}, {beacon number x2, RSSIz2, distance s2}, {beacon number xn, RSSIzn, distance sn}}. At the same time, the camera module 511 continues to rotate until the installation mark of the Bluetooth beacon can no longer be obtained within the field of view. Finally, the signal reception strength and distance of all the Bluetooth beacons obtained are stored. This example takes sampling to obtain 10 groups of data as an example. Therefore, the two groups of acquisition modules of the sampling device 500 perform the above sampling respectively and obtain 10 groups of data respectively.

[0129] Further, the height of the crossbar 620 in the sampling device 500 is adjusted, for example, it is lowered by 20 cm to simulate the height of a person with a shorter height, and the two collection modules repeat the above sampling process to obtain 10 sets of data respectively; the angle of the crossbar 620 in the sampling device 500 is adjusted, for example, the crossbar is rotated 90 degrees, and the above sampling process (including the sampling process of height adjustment) collects 40 sets of data. Thus, each collection module obtains 10 sets of data at two heights and two angles respectively, and the sampling device obtains a total of 80 sets of data.

[0130] Step 702: The acquisition device determines first information based on the multiple groups of signal data, and sends the first information to the multiple beacon devices that meet the observation conditions; the first information includes the first signal model parameters of the multiple beacon devices at the first point. In this example, for a fixed point (such as the first point), the 80 groups of data obtained by the above sampling are weighted averaged to obtain the average value as the A and n parameters of a beacon corresponding to the point.

[0131] Exemplarily, the 80 sets of data obtained include 40 sets of data obtained by the first acquisition module and 40 sets of data obtained by the second acquisition module. For any acquisition module, any two sets of the 40 sets of data are a pair of data, and the following formulas are used to calculate the values ​​of n and A:

[0132]

[0133]

[0134] Among them, RSSI1 and RSSI2 are the received signal strengths of the same beacon device contained in any two sets of signal data in the 40 sets of signal data, and d1 and d2 are the distances of the same beacon device contained in any two sets of signal data in the 40 sets of signal data. Then the average values ​​of the 40 sets of A and n values ​​obtained by the two acquisition modules are the A and n values ​​corresponding to the beacon device at the point.

[0135] It should be noted that the first point in this example is any point in the target area. By collecting data from multiple points in the target area and fitting model parameters, the RSSI fitting model of different points (the curve model determined by parameters A and n) can be obtained.

[0136] Step 703: When the acquisition device moves from the first point to the second point, it obtains second information of multiple positions and sends corresponding second information to each beacon device; the second information includes the first signal reception strength of each beacon device that meets the observation conditions at each position, and the first distance between each position and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area.

[0137] Exemplarily, when the collection device moves from a first point to an adjacent second point, it collects current data (i.e., the second information) every 20 milliseconds, including signal reception strength and distance, such as {{beacon number x1, RSSIz1, distance s1}, {beacon number x2, RSSIz2, distance s2}…}, and sends the collected data to a discoverable Bluetooth beacon device.

[0138] Step 704: The beacon device receives the first information and the second information sent by the collection device, trains the first signal model parameters based on the second information to obtain third information, wherein the third information at least includes the second signal model parameters of the beacon device at the multiple location points; and sends the third information to the collection device.

[0139] Exemplarily, each Bluetooth beacon analyzes the received data packet (i.e., the first information and the second information), and can calculate the corresponding A and n for each pairwise combination of the signal reception strength and the distance according to the above formula, thereby determining the A and n (i.e., the second signal model parameter) corresponding to each Bluetooth beacon at each location point; at the same time, each Bluetooth beacon can also determine the weight corresponding to each location point according to the distance (i.e., the first weight). Specifically, the weight of each Bluetooth beacon corresponding to each location point can be determined according to the number of Bluetooth beacons in the received data packet and the corresponding distance. For example, the distances between x Bluetooth beacons and a certain location point are s respectively. 1 、s 2 ,…,s x , the weight of these x Bluetooth beacons corresponding to the location point can be Q 1 =1-s 1 / (s 1 +s 2 +…+s x ), Q 2 =1-s 2 / (s 1 +s 2 +…+s x ),…,Q x =1-s x / (s 1 +s 2 +…+s x ).

[0140] In this example, the acquisition device can continue to move along a preset trajectory within the target area, and during the movement, the first signal model parameters corresponding to each point (a coarse-grained fitting model can be constructed) and the second signal model parameters at the position points between the points (a local fine-grained fitting model can be constructed) can be continuously determined according to the above steps 701 to 704.

[0141] Step 705: The collection device receives the third information sent by each beacon device, and determines a target signal model based on the third information sent by all beacon devices in the target area.

[0142] In some examples, the acquisition device may determine the top three beacon devices in terms of Bluetooth signal reception strength at each location point between the points, determine the second weight of each location point based on the first weight of each of the three beacon devices at each location point corresponding to the location point, perform weighted averaging based on the second weights of multiple location points and the second signal model parameters of each of the three beacon devices corresponding to the multiple location points, obtain the third signal model parameters of all location points, and determine the target signal model based on the third signal model parameters. Exemplarily, the second weight of a certain location point may be based on the weights Q of the top three Bluetooth beacons in terms of signal reception strength at the location point. 1 , Q 2 , Q 3 Obtain, for example, the second weight G=1-(Q 1 +Q 2 +Q 3 ); then the second signal model parameters can be fused based on the second weights of multiple location points. For example, for location point 1, the second signal model parameters (A1, n1), (A2, n2), and (A3, n3) corresponding to the same Bluetooth beacon at location point 1 and nearby location point 2 and the location point can be weighted averaged according to the second weights corresponding to each location point, that is, the third signal model parameter of location point 1 corresponding to the Bluetooth beacon is A=G1×A1+G2×A2+G3×A3, n=G1×n1+G2×n2+G3×n3, thereby obtaining the third signal model parameters of all location points corresponding to the top three Bluetooth beacons in signal reception strength ranking, and further obtaining the target signal model.

[0143] This example calculates the aggregation weight (i.e., the second weight) during federal aggregation based on the contribution of each Bluetooth beacon corresponding to each location point, and fuses each local fine-grained fitting model (which can be constructed by the second signal model parameters) according to the aggregation weight to obtain a global model (i.e., the target signal model); wherein the global model is a fine-grained fitting parameter model.

[0144] The acquisition device in this example is an autonomously moving device that can quickly collect data such as Bluetooth RSSI and beacon distance in the environment. The flexibility of the structure allows the acquisition of Bluetooth RSSI at different heights and directions, solving the problems of slow RSSI acquisition speed and heavy workload in traditional Bluetooth RSSI fitting. On the other hand, this example uses a federal aggregation fitting method that does not require a host computer to process data. At the same time, each Bluetooth beacon is expanded as a computing unit, which can make full use of the distributed computing power of the beacon, analyze data in real time during the sampling process, provide a more accurate local fitting curve model, and form an overall accurate fitting model through the local model, avoiding the use of a set of model parameters (such as A, n) for the entire positioning area in the traditional method. At the same time, this example can also improve the calculation accuracy of the distance value in each Bluetooth beacon through TOF technology, thereby improving the overall positioning accuracy.

[0145] The embodiment of the present invention further provides a data processing device, which is applied to a collection device; Fig. 9 The structure diagram of the data processing device according to the embodiment of the present invention is shown in FIG. Figure 1 ,like Fig. 9 As shown, the data processing device 800 includes an acquisition module 801, a first communication module 802 and a first processing module 803; wherein,

[0146] The acquisition module 801 is used to acquire first information of a first point in the target area, where the first information includes first signal model parameters of multiple beacon devices at the first point;

[0147] The first communication module 802 is used to send the first information to multiple beacon devices that meet the observation condition;

[0148] The acquisition module 801 is further configured to acquire second information of a plurality of positions in the process of moving from the first position to the second position, wherein the second information includes a first signal reception strength of each beacon device satisfying the observation condition received at each position and a first distance to each beacon device; wherein the first position and the second position are any two adjacent positions among the plurality of positions included in the target area;

[0149] The first communication module 802 is further configured to send the second information to each beacon device and receive third information sent by each beacon device; the third information at least includes second signal model parameters of the corresponding beacon device at the multiple locations;

[0150] The first processing module 803 is configured to determine a target signal model based on third information sent by all beacon devices in the target area.

[0151] In an optional embodiment of the present invention, the third information also includes a first weight of the beacon device corresponding to each location point, and the first weight is determined based on the first distance; the first processing module 803 is used to determine the N beacon devices with the first signal reception strength ranked first at each location point, where N is a positive integer; determine the second weight of each location point according to the first weight of the N beacon devices, and determine the third signal model parameters of each location point based on the second weight and the third information sent by all beacon devices, and determine the target signal model based on the third signal model parameters at all location points.

[0152] In an optional embodiment of the present invention, the acquisition module 801 is also used to determine the multiple beacon devices that meet the observation conditions at the first point; collect multiple groups of signal data, each group of signal data includes the second signal reception strength of each beacon device received at the first point and the second distance between each beacon device; each group of signal data has a different collection height and / or collection angle; and determine the first information based on the multiple groups of signal data.

[0153] In an optional embodiment of the present invention, the acquisition module is used to determine the multiple beacon devices that meet the observation conditions at the first point position, collect multiple groups of signal data, each group of signal data includes the second signal reception strength of each beacon device received at the first point position and the second distance between each beacon device; each group of signal data has a different collection height and / or collection angle; and determine the first information based on the multiple groups of signal data.

[0154] In an optional embodiment of the present invention, the first processing module 803 is used to perform weighted averaging of the second signal model parameters of each of the N beacon devices at the multiple location points based on the second weights of the multiple location points to obtain the third signal model parameters, wherein the third signal model parameters include the signal model parameters of each of the N beacon devices at each location point.

[0155] In some embodiments, the first processing module 303 in the aforementioned embodiments may be implemented based on the data processing device 800 .

[0156] In the embodiment of the present invention, the acquisition module 801 and the first processing module 803 in the data processing device 800 can be implemented by the central processing unit (CPU), digital signal processor (DSP), microcontroller unit (MCU) or programmable gate array (FPGA) in the acquisition device in actual applications; the first communication module 802 in the data processing device can be implemented by a communication module (including: basic communication kit, operating system, communication module, standardized interface and protocol, etc.) and a transceiver antenna in actual applications.

[0157] It should be noted that: when the data processing device provided in the above embodiment performs data processing, only the division of the above program modules is used as an example. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above. In addition, the data processing device provided in the above embodiment and the data processing method embodiment in which the execution subject is the acquisition device belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0158] The embodiment of the present invention further provides a data processing device, which is applied in a beacon device; Fig.10 The structure diagram of the data processing device according to the embodiment of the present invention is shown in FIG. Figure 2 ,like Fig.10 As shown, the data processing device 900 includes a second communication module 901 and a second processing module 902; wherein,

[0159] The second communication module 901 is used to receive the first information and the second information sent by the acquisition device, wherein the first information includes the first signal model parameters of multiple beacon devices at a first point; the second information includes the first signal reception strength of each beacon device that meets the observation condition received by the acquisition device at each of the multiple positions between the first point and the second point and the first distance between the acquisition device and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area;

[0160] The second processing module 902 is used to train the first signal model parameters based on the second information to obtain third information, where the third information at least includes the second signal model parameters of the beacon device at the multiple locations;

[0161] The second communication module 901 is further used to send the third information to the acquisition device, and the third information is used by the acquisition device to determine the target signal model corresponding to the target area.

[0162] In an optional embodiment of the present invention, the second processing module 902 is also used to determine the first weight corresponding to the beacon device based on all the first distances included in the second information; accordingly, the third information also includes the first weight, and the first weight is used by the acquisition device to determine the second weight of each location point, and the second weight is used by the acquisition device to determine the third signal model parameters of each location point and to determine the target signal model based on the third signal model parameters.

[0163] In some embodiments, the second processing module 402 in the aforementioned embodiments can be implemented based on the data processing device 900 .

[0164] In an embodiment of the present invention, the second processing module 902 in the data processing device 900 can be implemented by the CPU, DSP, MCU or FPGA in the beacon device in actual applications; the second communication module 901 in the data processing device can be implemented by a communication module (including: basic communication kit, operating system, communication module, standardized interface and protocol, etc.) and a transceiver antenna in actual applications.

[0165] It should be noted that: when the data processing device provided in the above embodiment performs data processing, only the division of the above program modules is used as an example. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above. In addition, the data processing device provided in the above embodiment and the data processing method embodiment whose execution subject is a beacon device belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0166] In an exemplary embodiment, the embodiment of the present invention further provides a computer-readable storage medium, such as a memory including a computer program, and the computer program can be executed by the processor of the acquisition device 300 or the beacon device 400 to complete the steps of the above method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disk, or CD-ROM; it can also be various devices including one or any combination of the above memories, such as a mobile phone, a computer, a tablet device, a personal digital assistant, etc.

[0167] The methods disclosed in several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0168] The features disclosed in several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0169] The features disclosed in several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0170] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0171] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0172] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0173] A person skilled in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, etc. Various media that can store program codes.

[0174] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0175] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A data processing method, It is characterized in that The method is applied to a collection device; the method comprises: Acquire first information of a first point in a target area, and send the first information to a plurality of beacon devices that meet observation conditions; the first information includes first signal model parameters of the plurality of beacon devices at the first point; In the process of moving from the first point to the second point, second information of multiple points is obtained, wherein the second information includes a first signal reception strength of each beacon device that meets the observation condition received at each point, and a first distance between each point and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area; Sending the second information to each beacon device, and receiving third information sent by each beacon device; the third information at least includes second signal model parameters of the corresponding beacon device at the multiple location points; The target signal model is determined based on the third information sent by all beacon devices in the target area.

2. The method according to claim 1, It is characterized in that The third information also includes a first weight of each beacon device corresponding to each location point, where the first weight is determined based on the first distance; and determining the target signal model based on the third information sent by all beacon devices in the target area includes: Determine N beacon devices ranked top in terms of the first signal reception strength at each location point, where N is a positive integer; Determine a second weight of each location point according to the first weights of the N beacon devices; The third signal model parameter of each location point is determined based on the second weight and the third information sent by all beacon devices, and the target signal model is determined based on the third signal model parameters at all location points.

3. The method according to claim 2, It is characterized in that The determining the third signal model parameter of each location point based on the second weight and the third information sent by all beacon devices includes: Based on the second weights of the multiple location points, the second signal model parameters of the N beacon devices at the multiple location points are weighted averaged to obtain the third signal model parameters, wherein the third signal model parameters include the signal model parameters of the N beacon devices at each location point.

4. The method according to claim 1, It is characterized in that The step of obtaining first information of a first point in the target area includes: Determine the plurality of beacon devices that meet the observation condition at the first point; Collecting multiple groups of signal data, each group of signal data includes the second signal reception strength received by each beacon device at the first point, and the second distance between the first point and each beacon device; each group of signal data is collected at a different height and / or at a different angle; The first information is determined based on the multiple sets of signal data.

5. A data processing method, It is characterized in that The method is applied to a beacon device; the method comprises: Receive first information and second information sent by a collection device, wherein the first information includes first signal model parameters of multiple beacon devices at a first point; the second information includes first signal reception strength of each beacon device that meets the observation condition received by the collection device at each of multiple positions between the first point and the second point, and a first distance between each position and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area; Training the first signal model parameters based on the second information to obtain third information, where the third information at least includes the second signal model parameters of the beacon device at the multiple locations; The third information is sent to the acquisition device, where the third information is used by the acquisition device to determine a target signal model corresponding to the target area.

6. The method according to claim 5, It is characterized in that The method further comprises: Determine a first weight corresponding to the beacon device according to all first distances included in the second information; Correspondingly, the third information also includes the first weight, the first weight is used by the acquisition device to determine the second weight of each location point, the second weight is used by the acquisition device to determine the third signal model parameters of each location point and determine the target signal model based on the third signal model parameters.

7. A data processing device, It is characterized in that The device is applied to a collection device; the device comprises an acquisition module, a first communication module and a first processing module; wherein, The acquisition module is used to acquire first information of a first point in the target area, wherein the first information includes first signal model parameters of a plurality of beacon devices at the first point; The first communication module is used to send the first information to multiple beacon devices that meet the observation condition; The acquisition module is further used to acquire second information of multiple positions in the process of moving from the first point to the second point, wherein the second information includes a first signal reception strength of each beacon device that meets the observation condition received at each position, and a first distance between each position and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area; The first communication module is further used to send the second information to each beacon device and receive third information sent by each beacon device; the third information at least includes second signal model parameters of the corresponding beacon device at the multiple location points; The first processing module is used to determine the target signal model based on the third information sent by all beacon devices in the target area.

8. A data processing device, It is characterized in that The device is applied to a beacon device; the device comprises a second communication module and a second processing module; wherein, The second communication module is used to receive first information and second information sent by the acquisition device, wherein the first information includes first signal model parameters of multiple beacon devices at a first point; the second information includes the first signal reception strength of each beacon device that meets the observation condition received by the acquisition device at each position point of multiple positions between the first point and the second point, and the first distance between each position point and each beacon device; wherein the first point and the second point are any two adjacent points among the multiple points included in the target area; The second processing module is used to train the first signal model parameters based on the second information to obtain third information, where the third information at least includes the second signal model parameters of the beacon device at the multiple location points; The second communication module is further used to send the third information to the acquisition device, and the third information is used by the acquisition device to determine the target signal model corresponding to the target area.

9. A collection device, It is characterized in that The acquisition device includes a detection module, an acquisition module and a first processing module; wherein, The detection module is used to determine the beacon device that meets the observation conditions; The acquisition module is used to collect the signal reception strength of the beacon device and the distance between the acquisition module and the beacon device; The first processing module includes a processor and a memory for storing a computer program that can be run on the processor; wherein, when the processor is used to run the computer program, the steps of the method described in any one of claims 1 to 4 are executed.

10. The acquisition device according to claim 9, It is characterized in that The acquisition device includes two groups of acquisition modules with fixed relative positions, each group of acquisition modules includes a distance measurement module and a signal measurement module; wherein, The distance measuring module is used to determine the distance between the acquisition module and the beacon device; The signal measurement module is used to collect the signal reception strength of the beacon device.

11. A beacon device, It is characterized in that The beacon device includes a signal sending module and a second processing module; wherein, The signal sending module is used to send signals; The second processing module includes a processor and a memory for storing a computer program that can be run on the processor; wherein the processor executes the steps of the method according to claim 5 or 6 when running the computer program.

12. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the program is executed by a processor, the steps of the method described in any one of claims 1 to 4 are implemented; or, when the program is executed by a processor, the steps of the method described in claim 5 or 6 are implemented.

Images