Device positioning method, device, Internet of Things device, storage medium and program product

Abstract

The present application relates to a device positioning method, apparatus, IoT device, storage medium and program product, which obtains signal data sent by multiple positioning base stations; performs position calculation processing on the target device according to the positioning algorithm and signal data, and obtains the positioning information of the target device at the target time. The present application can make full use of multi-source data for comprehensive analysis by obtaining signal data sent by multiple positioning base stations and performing position calculation processing on the target device according to the corresponding positioning algorithm. Compared with the positioning method that relies only on a single base station or a small amount of data, this multi-base station collaborative mode greatly improves the positioning accuracy.

Description

Technical Field

[0001] The present application relates to the technical field of Internet of Things, and in particular to a device positioning method, apparatus, Internet of Things device, storage medium and program product. Background Art

[0002] In today's digital age, the number of IT (Information Technology) equipment in various indoor scenarios (such as data centers, office buildings, factory workshops, etc.) is increasing and widely distributed, and its efficient operation and maintenance management has become a key requirement.

[0003] Traditional monitoring methods are difficult to accurately locate IT equipment in complex indoor environments. As an emerging indoor positioning method, Bluetooth positioning technology has certain advantages, such as relatively low equipment cost and easy deployment. However, in actual applications, Bluetooth signals are easily interfered by various factors during indoor propagation, which can lead to inaccurate positioning distance estimation. Summary of the invention

[0004] Based on this, it is necessary to provide a device positioning method, apparatus, Internet of Things device, storage medium and program product that can solve the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a device positioning method. The method comprises:

[0006] Acquire signal data sent by multiple positioning base stations; the signal data is generated by each positioning base station based on beacon signals sent by multiple Bluetooth beacons, and the beacon signals are generated based on Bluetooth signals sent by the target device to each Bluetooth beacon;

[0007] The position of the target device is calculated and processed according to the positioning algorithm and signal data to obtain the positioning information of the target device at the target time.

[0008] In one embodiment, the signal data includes the signal strength and signal arrival time of the Bluetooth signal sent by the target device to the Bluetooth beacon at multiple times; the position of the target device is calculated and processed according to the positioning algorithm and the signal data, and the positioning information of the target device at the target time is obtained, including:

[0009] Determine the first device position of the target device at the target time according to the signal strength positioning algorithm and the signal strength corresponding to each time;

[0010] Determine the second device position of the target device at the target time according to the time difference positioning algorithm and the signal arrival time corresponding to each time;

[0011] The positioning information of the target device at the target time is determined according to the first device position of the target device at the target time and the second device position of the target device at the target time.

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

[0013] Obtain environmental information; environmental information includes the material and distribution information of obstacles;

[0014] Input the environmental information into the pre-built signal attenuation model to perform attenuation calculation processing to obtain the signal attenuation amount;

[0015] The parameters of the positioning algorithm are adjusted according to the signal attenuation to obtain the optimized positioning information of the target device at the target time.

[0016] In one embodiment, the method further comprises:

[0017] Performing component identification processing on signal data to obtain multipath signal components;

[0018] Determine the positioning error of the signal data based on the multipath signal components;

[0019] Using a correction algorithm, the positioning error of the signal data is corrected to obtain corrected signal data;

[0020] Correspondingly, the position of the target device is calculated and processed according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time, including:

[0021] The position of the target device is calculated and processed according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target device at the target time.

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

[0023] Get the status information of the target device;

[0024] Visualize the location information and status information of the target device to generate a visualization interface;

[0025] Display a visualization interface; the visualization interface includes a map and the movement trajectory of the target device in the map.

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

[0027] Obtaining the location information of the target device within a preset period of time;

[0028] Generate a moving track of the target device according to the positioning information of the target device within a preset time period;

[0029] In response to the trajectory playback operation, the movement trajectory of the target device is displayed.

[0030] In a second aspect, the present application also provides a device positioning apparatus. The apparatus comprises:

[0031] A data acquisition module is used to acquire signal data sent by multiple positioning base stations; the signal data is generated by each positioning base station based on beacon signals sent by multiple Bluetooth beacons, and the beacon signals are generated based on Bluetooth signals sent by the target device to each Bluetooth beacon;

[0032] The position calculation module is used to perform position calculation processing on the target device according to the positioning algorithm and signal data to obtain the positioning information of the target device at the target time.

[0033] In a third aspect, the present application further provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in the first aspect when executing the computer program.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method in the first aspect when executed by a processor.

[0035] In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the method in the first aspect are implemented.

[0036] The above-mentioned device positioning method, apparatus, IoT device, storage medium and program product obtain signal data sent by multiple positioning base stations; perform position calculation and processing on the target device according to the positioning algorithm and signal data, and obtain the positioning information of the target device at the target time. This application can make full use of multi-source data for comprehensive analysis by obtaining signal data sent by multiple positioning base stations and performing position calculation and processing on the target device according to the corresponding positioning algorithm. Compared with the positioning method that relies only on a single base station or a small amount of data, this multi-base station collaborative mode greatly improves the positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A diagram of an application environment of a device positioning method in an embodiment;

[0038] Figure 2 A schematic diagram of a flow chart of a device positioning method in an embodiment;

[0039] Figure 3 A schematic diagram of a process for obtaining positioning information of a target device at a target time in one embodiment;

[0040] Figure 4 A schematic diagram of a flow chart of parameter adjustment of a positioning algorithm in an embodiment;

[0041] Figure 5 A schematic diagram of a flow chart of positioning error correction processing of signal data in one embodiment;

[0042] Figure 6 A schematic diagram of a process for visualizing the location information and status information of a target device in one embodiment;

[0043] Figure 7 A schematic diagram of a process of generating a moving trajectory of a target device in one embodiment;

[0044] Figure 8 is a structural block diagram of a device positioning apparatus in one embodiment;

[0045] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] The device positioning method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. The Internet of Things platform 102 is connected to the positioning base station 104 in communication; the positioning base station 104 is connected to the Bluetooth beacon 106 in communication, and the Bluetooth beacon 106 is connected to the target device 108 in communication. The Internet of Things platform 102 obtains the signal data sent by multiple positioning base stations 104; the signal data is generated by each positioning base station 104 according to the beacon signal sent by multiple Bluetooth beacons 106, and the beacon signal is generated based on the Bluetooth signal sent by the target device 108 to each Bluetooth beacon; the position of the target device is calculated and processed according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time. Among them, the target device 108 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The Internet of Things platform 102 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0048] In an exemplary embodiment, Figure 2 As shown, the embodiment of the present application provides a device positioning method, which is applied to Figure 1Taking the IoT platform 102 in the example as an example, the method includes the following steps:

[0049] S201, obtaining signal data sent by multiple positioning base stations.

[0050] Among them, the signal data is generated by each positioning base station according to the beacon signals sent by multiple Bluetooth beacons, and the beacon signals are generated based on the Bluetooth signals sent by the target device to each Bluetooth beacon.

[0051] In the embodiment of the present application, the Internet of Things platform first establishes communication connections with multiple positioning base stations. These connections can be achieved through Ethernet, Wi-Fi and other network methods to ensure the stability and timeliness of data transmission.

[0052] The positioning base station receives beacon signals sent by multiple Bluetooth beacons in real time within its coverage area. For example, in an indoor office environment, Bluetooth beacons are deployed in various corners and key locations. They continuously broadcast Bluetooth signals containing their own unique identification information at a set power and period (such as broadcasting once every 500 milliseconds). When the target device (such as a laptop) turns on the Bluetooth function and is in this environment, it will interact with the Bluetooth beacon. After receiving the Bluetooth signal from the target device, the Bluetooth beacon will adjust accordingly and broadcast a new beacon signal.

[0053] After receiving these beacon signals, the positioning base station will extract and record key data information, such as the timestamp of the received signal (accurate to the millisecond level, which is convenient for the subsequent calculation of parameters related to the signal propagation time), the received signal strength indication (RSSI value, which is used to measure the strength of the signal after propagation attenuation, and then calculate the distance to the beacon) and the corresponding Bluetooth beacon identification (to clearly indicate which specific beacon it comes from), etc., to generate signal data.

[0054] The positioning base station transmits the generated signal data to the IoT platform in real time through the established network connection. The IoT platform sets up a corresponding data receiving module to parse, verify and store the received data according to the predetermined data format and protocol to ensure that complete and accurate signal data from multiple positioning base stations is obtained.

[0055] S202: Perform position calculation processing on the target device according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time.

[0056] In the embodiment of the present application, after receiving the signal data sent by multiple positioning base stations, the IoT platform first performs preprocessing operations on the data. This includes data cleaning, removing abnormal data (such as data whose RSSI value exceeds a reasonable range) caused by signal interference, temporary equipment failure, etc.; data noise reduction, using filtering and other technical means to reduce the impact of noise in the data so that the data can better reflect the actual signal propagation situation; data standardization, unifying the data format and representation range transmitted from different positioning base stations, to facilitate subsequent unified calculations.

[0057] The selection is based on the positioning scenario and pre-configured positioning algorithms. For example, if the indoor environment is relatively open and has few obstacles, the RSSI-based positioning algorithm may be preferred; if the positioning accuracy requirement is extremely high and the positioning base station has a high-precision time synchronization function, the TDOA algorithm will be considered.

[0058] Taking the RSSI-based positioning algorithm as an example, the IoT platform uses existing signal propagation models (such as the logarithmic distance path loss model, which is pre-calibrated by multiple tests in the actual positioning environment to determine the parameters in the model, such as the signal attenuation index, etc.), substitutes the RSSI value corresponding to the beacon signal received by each positioning base station into the model, and calculates the estimated distance between each Bluetooth beacon and the corresponding positioning base station. When multiple positioning base stations receive the signal of the same Bluetooth beacon, the multi-lateral positioning method is used to calculate the position.

[0059] The above-mentioned device positioning method, apparatus, IoT device, storage medium and program product obtain signal data sent by multiple positioning base stations; perform position calculation and processing on the target device according to the positioning algorithm and signal data, and obtain the positioning information of the target device at the target time. This application can make full use of multi-source data for comprehensive analysis by obtaining signal data sent by multiple positioning base stations and performing position calculation and processing on the target device according to the corresponding positioning algorithm. Compared with the positioning method that relies only on a single base station or a small amount of data, this multi-base station collaborative mode greatly improves the positioning accuracy.

[0060] In an exemplary embodiment, based on the above embodiment, see Figure 3 The signal data of the embodiment of the present application includes the signal strength and signal arrival time of the Bluetooth signal sent by the target device to the Bluetooth beacon at multiple times; the embodiment of the present application involves a process of calculating the position of the target device according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time, including the following steps:

[0061] S301, determining a first device position of a target device at a target time according to a signal strength positioning algorithm and the signal strength corresponding to each time.

[0062] In the embodiment of the present application, the IoT platform first extracts the signal strength information of the Bluetooth signal sent by the target device to the Bluetooth beacon at each moment from the signal data sent by the multiple positioning base stations. These data are classified and stored according to different moments, different Bluetooth beacons and corresponding positioning base stations. For example, in the indoor positioning scenario of a large shopping mall, multiple Bluetooth beacons are deployed in different areas of the mall. Each positioning base station will receive the Bluetooth signal strength data of the target device (such as the customer's mobile phone) forwarded by these beacons. The IoT platform integrates and sorts these scattered data for subsequent unified processing.

[0063] According to the actual situation of the internal environment (such as spatial layout, obstacle distribution, signal interference, etc.), select an appropriate signal propagation model, such as the logarithmic distance path loss model (PL(d)=PL(d_)-10nlg(d / d_)-N_0, where PL(d) represents the signal strength at a distance d from the sending node, PL(d_) is the signal strength at a reference distance d_, n is the signal attenuation index, d is the actual distance between nodes, and N_0 is a Gaussian random noise variable with a mean of 0 and a standard deviation of σ). Before deploying the system, the parameters of the model (such as n, PL(d_), etc.) have been calibrated through field tests to make it more suitable for the actual environment.

[0064] For each moment, the signal strength (RSSI value) corresponding to each Bluetooth beacon is substituted into the selected signal propagation model to calculate the estimated distance between the target device and each Bluetooth beacon. For example, at a certain moment, the RSSI value of the corresponding target device received by positioning base station A from Bluetooth beacon B is -60dB. The estimated distance between the target device and Bluetooth beacon B is calculated to be 5 meters through the model and calibrated parameters. After obtaining the estimated distance between the target device and multiple Bluetooth beacons (at least three), the multi-lateration algorithm is used to calculate the position of the target device.

[0065] S302, determining a second device position of the target device at the target time according to a time difference positioning algorithm and the signal arrival time corresponding to each time;

[0066] In the embodiment of the present application, the Internet of Things platform first checks the time synchronization status of each positioning base station to ensure that the time synchronization accuracy between them meets the requirements of the time difference positioning algorithm (generally requiring synchronization at the microsecond level or even higher precision), which can be guaranteed by means of professional time synchronization technologies such as the Network Time Protocol (NTP). Then, the time information of the Bluetooth signal sent by the target device at each moment arriving at each positioning base station is extracted from the signal data, and the information is also classified and sorted according to different positioning base stations. For the Bluetooth signal sent by the same target device, the time of arrival at different positioning base stations is compared to calculate the time difference. Combined with the signal propagation speed, the distance difference between the target device and different positioning base stations is calculated according to the time difference. When there are multiple groups of positioning base stations involved in the measurement (generally at least three groups), there will be multiple hyperbolas, and the location of the target device is determined by solving the intersection of these hyperbolas. Using numerical calculation methods and optimization algorithms, the position relationship and error conditions of each hyperbola are comprehensively considered, and the second device position coordinates of the target device at the target time are finally calculated.

[0067] S303: Determine positioning information of the target device at the target time according to a first device position of the target device at the target time and a second device position of the target device at the target time.

[0068] In an embodiment of the present application, the Internet of Things platform determines the weights of the signal strength positioning algorithm and the time difference positioning algorithm in the fusion positioning according to the accuracy and reliability of the signal strength positioning algorithm and the time difference positioning algorithm in the current environment. For example, through statistical analysis of historical positioning data, it is found that in certain areas of the shopping mall (such as near elevators and places with more metal structures), the signal strength is greatly interfered. At this time, the time difference positioning algorithm is relatively more reliable, so it is given a higher weight; in open areas with less interference, the signal strength positioning algorithm has good accuracy, so it is given an appropriate weight. The weights can be dynamically adjusted according to actual experience, experimental test results, etc. Using the determined weights, the weighted average calculation of the first device position and the second device position is performed to obtain the final positioning information coordinates of the target device at the target time.

[0069] The embodiment of the present application combines the signal strength positioning algorithm and the time difference positioning algorithm to determine the positioning information of the target device, which has significant beneficial effects. First, the integration of two positioning algorithms based on different principles fully utilizes the advantages of signal strength data that can reflect the relative distance relationship and signal arrival time data that can accurately calculate the distance difference, and makes up for each other's limitations in different environments, effectively improving the accuracy and reliability of positioning.

[0070] In an exemplary embodiment, based on the above embodiment, see Figure 4 , the method of the embodiment of the present application further includes the following steps:

[0071] S401, obtaining environmental information.

[0072] The environmental information includes the material and distribution information of obstacles.

[0073] In the embodiment of the present application, the IoT platform first obtains environmental information by establishing communication connections with a variety of sensor devices. For example, the IoT platform is connected to the laser radar sensors deployed at various key locations indoors. The laser radar can scan the surrounding environment, identify the contours, positions and other information of different objects (i.e. obstacles), and transmit the spatial coordinate data of these objects to the IoT platform through its own algorithm processing; at the same time, it interacts with some material recognition sensors (which can be sensors based on principles such as radio frequency identification and ultrasound, and judge the material based on the differences in reflection, penetration and other characteristics of objects of different materials) to obtain the material information of the obstacle, such as the wall of a certain area is made of concrete, and a certain part of the partition is made of glass. After receiving the data from different sensors, the IoT platform integrates and processes it, associates the location and material information of the same obstacle, and marks it according to the coordinate system of the indoor space, forming an environmental information data set containing the material and distribution information of each obstacle, which is convenient for subsequent input into the signal attenuation model for unified analysis. For example, in a positioning scenario on a certain floor of an office building, the relevant information of furniture such as tables, chairs, filing cabinets, and building structures such as walls and columns in each office are organized into corresponding location coordinates, clearly presenting the distribution of obstacles on the entire floor and their respective materials.

[0074] S402, inputting the environmental information into a pre-built signal attenuation model to perform attenuation calculation processing to obtain a signal attenuation amount;

[0075] In the embodiment of the present application, according to the signal type used by the positioning system and the characteristics of the positioning scene (such as the approximate size of the indoor environment, the type of common obstacles, etc.), the Internet of Things platform selects an adaptive model from a plurality of pre-built and stored signal attenuation models. These models may be empirical models constructed based on mathematical methods such as regression analysis after a large number of indoor experimental tests and attenuation tests of Bluetooth signals using obstacles of different materials, or theoretical models that combine electromagnetic theory to simulate the signal propagation attenuation process, which are stored for standby after actual verification and calibration. The integrated environmental information is input into the selected signal attenuation model in the format and parameter form required by the model. For example, the input parameters of the model may include the thickness of obstacles of different materials, the relative position relationship with the signal propagation path (and the distance from the target device and the Bluetooth beacon (or positioning base station), etc. After receiving these parameters, the model performs attenuation calculation processing according to the algorithm rules set internally, and outputs the corresponding signal attenuation value. For example, it is calculated that on a certain propagation path, due to the obstruction of a concrete wall and several wooden filing cabinets, the attenuation of the Bluetooth signal is 15dB.

[0076] S403: Adjust the parameters of the positioning algorithm according to the signal attenuation to obtain optimized positioning information of the target device at the target time.

[0077] In the embodiment of the present application, the IoT platform analyzes the positioning algorithm being used (such as the positioning algorithm based on the received signal strength indication (RSSI) and the time difference of arrival (TDOA) positioning algorithm) to find out the key parameters related to the signal strength and propagation distance. These parameters need to be adjusted accordingly under different signal attenuation conditions to ensure the positioning accuracy. After such parameter adjustment, the positioning algorithm is used again to calculate the position of the target device to obtain the optimized positioning information of the target device at the target time.

[0078] The embodiment of the present application takes into account the material and distribution of obstacles in the environmental information, and calculates the signal attenuation through a signal attenuation model, which can more accurately reflect the actual propagation characteristics of Bluetooth signals in actual complex indoor environments, and make up for the positioning errors caused by traditional positioning algorithms when the influence of environmental factors is ignored, thereby effectively improving the positioning accuracy and making the acquired target device positioning information closer to its actual position.

[0079] In an exemplary embodiment, based on the above embodiment, see Figure 5 , the method of the embodiment of the present application further includes the following steps:

[0080] S501, performing component identification processing on signal data to obtain multipath signal components.

[0081] In the embodiment of the present application, the Internet of Things platform first extracts the signal data related to the positioning of the target device from the original signal data collected by each positioning base station. These data contain information such as the signal strength received at different times and the signal arrival time. Then, basic preprocessing operations are performed on it, such as removing noise from the data, normalizing the data, etc., to ensure data quality so as to better perform component identification and processing. For the preprocessed signal data, the Internet of Things platform uses signal processing technology to extract relevant parameters that can reflect the characteristics of multipath signals. According to the extracted characteristic parameters, the pattern recognition algorithm and the multipath propagation model are used to identify and extract each multipath signal component from the mixed signal data, sort them out separately, and clarify the key parameter information such as the amplitude, phase, and delay time of each multipath signal component, so as to prepare for the subsequent analysis of positioning errors.

[0082] S502: Determine the positioning error of the signal data according to the multipath signal components.

[0083] In the embodiment of the present application, the IoT platform constructs a corresponding positioning error analysis model based on the specific positioning algorithm (such as RSSI-based positioning algorithm, TDOA positioning algorithm, etc.) and the current indoor environment characteristics (such as known obstacle distribution, spatial layout, etc.). The model will take the relevant parameters of the multipath signal components (such as the amplitude, phase, delay time of each multipath signal component and their relative relationship with the direct path signal, etc.) as input variables, and establish a mathematical correlation relationship with the positioning error through theoretical deduction and empirical analysis based on historical positioning data. For example, in RSSI positioning, the superposition of multipath signals may cause abnormal changes in the received signal strength, thereby affecting the distance calculated based on the signal strength and the final positioning result. The model will quantify the positioning error corresponding to this impact. Substitute the specific parameters of the identified and extracted multipath signal components into the constructed positioning error analysis model, and calculate the size of the positioning error caused by the influence of the multipath signal according to the calculation rules set in the model.

[0084] S503, using a correction algorithm to correct the positioning error of the signal data to obtain corrected signal data.

[0085] In the embodiment of the present application, the IoT platform selects a suitable algorithm from a variety of pre-stored correction algorithms to perform error correction based on the overall architecture of the positioning system, the positioning technology used, and the specific situation of the current multipath signal interference. For example, if the multipath signal is mainly caused by indoor wall reflection, and the positioning is based on RSSI signal strength information, a correction algorithm based on the ray tracing principle may be selected to reversely correct the signal strength anomaly caused by multipath by simulating the real propagation path of the signal in the indoor environment; if TDOA positioning is used and the multipath interference shows a certain periodic law, a correction algorithm based on filtering and phase adjustment is selected to remove the influence of multipath on the signal arrival time difference, etc.

[0086] The selected correction algorithm is used to process the original signal data with multipath interference. Taking the correction algorithm based on the ray tracing principle as an example, it will recalculate the theoretical signal strength in the absence of multipath interference based on the indoor environment map and the identified multipath signal propagation path, and then use this theoretical value to correct the signal strength value in the original signal data that is deviated due to multipath superposition; for the correction algorithm based on filtering and phase adjustment, the abnormal phase components in the multipath signal that do not conform to the normal propagation law are removed through filtering operations, and the phase of the signal is adjusted to make it closer to the ideal state without multipath interference, thereby completing the correction processing of the signal data and obtaining the corrected signal data, so that it can better reflect the real location information of the target device.

[0087] Correspondingly, the position of the target device is calculated and processed according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time, including: the position of the target device is calculated and processed according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target device at the target time.

[0088] In the embodiment of the present application, the IoT platform organizes and converts the signal data corrected by the correction algorithm according to the input requirements of the positioning algorithm, replaces the original signal data with multipath interference, and provides it to the positioning algorithm as new input data. The positioning algorithm is used to perform position calculation processing on the corrected signal data. For example, in the multilateral positioning based on RSSI, the distance between the target device and each base station is re-estimated according to the corrected signal strength value of the target device received by each positioning base station, and then the coordinate position of the target device at the target time is calculated by solving the equation group composed of these distances, so as to obtain more accurate positioning information, which effectively reduces the influence of positioning error caused by multipath signals.

[0089] In the embodiment of the present application, by accurately identifying the multipath signal components and analyzing the positioning errors caused by them, it is possible to gain an in-depth understanding of the interference caused by the multipath effect when the wireless signal propagates in an actual complex indoor environment, and then use correction algorithms to correct the signal data in a targeted manner, thereby greatly improving the positioning accuracy.

[0090] In an exemplary embodiment, based on the above embodiment, see Figure 6 , the method of the embodiment of the present application further includes the following steps:

[0091] S601, obtaining status information of a target device;

[0092] The status information refers to data related to various operations and usage of the target device, such as whether the device is powered on, the remaining power, and the tasks the device is performing.

[0093] In the embodiment of the present application, the IoT platform first determines the way in which the target device can provide status information and the corresponding interface; for traditional devices, data conversion and transmission may be performed with the help of a gateway device to obtain its status information. Then, according to the corresponding communication protocol and data format requirements, the data receiving module is configured to ensure that the status information actively pushed by the target device or sent at a certain period can be stably received. After receiving the original status information from the target device, the IoT platform performs parsing operations on it. In order to ensure the timeliness and accuracy of the status information, the IoT platform will also set up a timed query mechanism or monitor the status change notification of the device to continuously obtain the latest status information. For example, a status query request is sent to the target device every few minutes, or when the key status of the device such as the power or working mode changes, the device actively pushes an update notification to the IoT platform, and the platform promptly receives and updates the corresponding stored status information so that the latest device status is displayed to the user later.

[0094] S602, visualizing the location information and status information of the target device to generate a visual interface;

[0095] In the embodiment of the present application, the Internet of Things platform selects the map data that matches the location area of ​​the target device according to the location area where the target device is located. The map can be an electronic map stored in the platform database in advance, or it can be map information obtained by calling a third-party map service. Then the selected map is loaded into the framework of visualization processing, and the basic interactive functions such as zooming and panning of the map are set up to make it the basic background for displaying the target device information. The location information of the target device at the target time corresponds to the corresponding position on the map, and the current position of the target device is identified by a specific icon. At the same time, different visualization methods are used to display the status information of the target device. For example, different icon colors are used to indicate the power status of the device, and a text prompt box is added next to the icon to display the current working mode of the device, so that the user can intuitively understand the device status at a glance. If the target device moves, the Internet of Things platform will record its location information at different times, connect these location coordinate points in sequence in chronological order, and draw the moving trajectory of the target device on the map. The trajectory can be represented by lines of different colors and thicknesses to enhance the visual effect and differentiation, so that the user can clearly observe the moving path and historical position changes of the device. Through comprehensive processing of maps, positioning information and status information, a complete visual interface is generated, which can comprehensively and intuitively display the relevant situation of the target device.

[0096] S603: Display a visualization interface, wherein the visualization interface includes a map and a moving track of the target device in the map.

[0097] In the embodiment of the present application, the Internet of Things platform publishes the generated visualization interface through a network service so that it can be accessed by authorized users.

[0098] Considering that users may access the visualization interface through different terminal devices (such as computer browsers, mobile phones, tablets, etc.), the IoT platform will perform multi-terminal adaptation processing to ensure that the interface can be displayed normally and the layout is reasonable and beautiful under different screen sizes and resolutions. At the same time, it provides users with interactive functions, such as supporting the use of mouse clicks or touch operations on the visualization interface to view detailed status information of the device (click the device icon to pop up a detailed information box to display more status parameters), zooming in or out on the map to view the distribution and movement trajectory of devices in different ranges, switching different device groups or filtering conditions to view information of a specific device subset, etc., to improve the convenience and experience of users in viewing and managing devices.

[0099] The embodiment of the present application combines positioning information with status information and presents them in a visual interface, so that users can intuitively and comprehensively understand the real-time situation of the target device, including key information such as where the device is and what operating status the device is in. There is no need to view complicated text data or perform complex data analysis, which greatly improves the efficiency of information acquisition and facilitates users to quickly make decisions on equipment management, scheduling, operation and maintenance, etc.

[0100] In an exemplary embodiment, based on the above embodiment, see Figure 7 , the method of the embodiment of the present application further includes the following steps:

[0101] S701, obtaining positioning information of a target device within a preset period of time;

[0102] In the embodiment of the present application, the IoT platform first accesses the database storing the positioning information, and extracts all the positioning information of the target device within the preset time period from the massive positioning data records according to the preset time screening conditions. The queried positioning information is sorted and sorted in chronological order to ensure that it can accurately reflect the order of the position changes of the target device within the preset time period. At the same time, the integrity and accuracy of the data are verified to check whether there is any missing key data or data anomalies. If problematic data is found, it is processed according to the data backup mechanism or related data repair strategy to ensure that the data quality of the subsequent generated mobile trajectory is reliable.

[0103] S702, generating a moving track of the target device according to the positioning information of the target device within a preset time period;

[0104] In the embodiment of the present application, the Internet of Things platform selects a suitable mobile trajectory construction algorithm according to the environmental characteristics of the target device and the data format of the positioning information. For example, in a simple two-dimensional indoor plane positioning scenario, a linear interpolation algorithm is used to connect the position coordinate points of the target device at adjacent moments in chronological order to form a continuous mobile trajectory; for outdoor positioning involving complex terrain and three-dimensional space, an algorithm based on spline curve fitting may be used so that the generated mobile trajectory can fit the actual terrain and the motion path of the device more smoothly and naturally, reducing the problems of discontinuous or unsightly trajectories caused by discrete coordinates. The selected trajectory construction algorithm can be used to process the sorted positioning information of the target device within a preset period of time to generate corresponding mobile trajectory data. The data structure may contain information such as the starting point and end point coordinates of the trajectory, the key coordinate points passed in the middle, and the timestamps corresponding to each point, so as to fully describe the movement process of the device. Then, the generated mobile trajectory data is stored in a special trajectory database or a storage area associated with the positioning information, which is convenient for subsequent rapid retrieval and display according to the user's trajectory playback operation.

[0105] S703: In response to the trajectory playback operation, display the movement trajectory of the target device.

[0106] In the embodiment of the present application, the IoT platform is provided with an interactive interface specifically for receiving trajectory playback operations. When a user initiates a trajectory playback operation through a client, such as clicking the "Trajectory Playback" button on the interface or selecting a specific preset time period range on the timeline, the platform's interactive interface will receive the corresponding operation instructions and parameter information in real time, and parse and verify them to ensure that the operation instructions are legal and meet system requirements. According to the received trajectory playback operation instructions, the corresponding target device movement trajectory data is retrieved from the storage area, converted into a visualization element, and then displayed on the visualization interface. At the same time, according to the playback speed and other parameters set by the user, the complete movement trajectory of the target device within the preset time period is presented through animation effects, allowing the user to clearly observe the position change of the device, and can provide interactive functions such as pause, fast forward, and rewind, so that the user can flexibly view different parts and details of the trajectory.

[0107] The embodiment of the present application obtains the positioning information of the target device within a preset time period and generates a movement trajectory, which can completely record the movement history of the device and provide comprehensive data support for subsequent analysis. The trajectory playback operation and corresponding display function facilitate users to review the past movement of the device at any time, which helps to discover potential problems in the operation of the device, summarize the usage patterns of the device, and predict future device behavior.

[0108] In an exemplary embodiment, based on the above embodiment, the method of the embodiment of the present application further includes the following steps:

[0109] Step 1: The IoT platform obtains signal data sent by multiple positioning base stations; performs component identification processing on the signal data to obtain multipath signal components; determines the positioning error of the signal data based on the multipath signal components; uses a correction algorithm to correct the positioning error of the signal data to obtain the corrected signal strength corresponding to each moment and the signal arrival time corresponding to each moment;

[0110] Step 2: Acquire environmental information; adjust the parameters of the positioning algorithm according to the signal attenuation to obtain an adjusted signal strength positioning algorithm and an adjusted time difference positioning algorithm;

[0111] Step 3: Determine the first device position of the target device at the target time according to the adjusted signal strength positioning algorithm and the corrected signal strength corresponding to each moment; determine the second device position of the target device at the target time according to the adjusted time difference positioning algorithm and the corrected signal arrival time corresponding to each moment; determine the positioning information of the target device at the target time according to the first device position of the target device at the target time and the second device position of the target device at the target time;

[0112] Step 4: Obtain the status information of the target device; visualize the location information and status information of the target device to generate a visualization interface; display the visualization interface; the visualization interface includes a map and the movement trajectory of the target device in the map;

[0113] Step 5: Acquire the positioning information of the target device within a preset period of time; generate a movement trajectory of the target device according to the positioning information of the target device within the preset period of time; and display the movement trajectory of the target device in response to a trajectory playback operation.

[0114] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0115] Based on the same inventive concept, the embodiment of the present application also provides a device positioning device for implementing the device positioning method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more device positioning device embodiments provided below can refer to the limitations on the device positioning method above, and will not be repeated here.

[0116] In one embodiment, Fig. 9 As shown, a device positioning apparatus 800 is provided, comprising:

[0117] The data acquisition module 801 is used to acquire signal data sent by multiple positioning base stations; the signal data is generated by each positioning base station according to the beacon signals sent by multiple Bluetooth beacons, and the beacon signals are generated based on the Bluetooth signals sent by the target device to each Bluetooth beacon;

[0118] The position calculation module 802 is used to perform position calculation processing on the target device according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time.

[0119] In one embodiment, the signal data includes the signal strength and signal arrival time of the Bluetooth signal sent by the target device to the Bluetooth beacon at multiple times; the location calculation module includes:

[0120] A first position determination unit, configured to determine a first device position of a target device at a target time according to a signal strength positioning algorithm and a signal strength corresponding to each time;

[0121] A second position determination unit, used to determine a second device position of the target device at a target time according to a time difference positioning algorithm and a signal arrival time corresponding to each time;

[0122] The position information determining unit is used to determine the positioning information of the target device at the target time according to the first device position of the target device at the target time and the second device position of the target device at the target time.

[0123] In one embodiment, the above device further comprises:

[0124] The information acquisition module is used to obtain environmental information; the environmental information includes the material and distribution information of obstacles;

[0125] An attenuation calculation module is used to input environmental information into a pre-built signal attenuation model for attenuation calculation processing to obtain a signal attenuation amount;

[0126] The parameter adjustment module is used to adjust the parameters of the positioning algorithm according to the signal attenuation to obtain the optimized positioning information of the target device at the target time.

[0127] In one embodiment, the above device further comprises:

[0128] A component identification module is used to perform component identification processing on signal data to obtain multipath signal components;

[0129] An error determination module, used to determine the positioning error of the signal data according to the multipath signal components;

[0130] The error correction module is used to correct the positioning error of the signal data by using a correction algorithm to obtain corrected signal data;

[0131] Correspondingly, the position calculation module includes:

[0132] The positioning correction module is used to calculate the position of the target device according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target device at the target time.

[0133] In one embodiment, the above device further comprises:

[0134] An information acquisition module is used to obtain the status information of the target device;

[0135] An interface generation module is used to visualize the location information and status information of the target device and generate a visualization interface;

[0136] The interface display module is used to display the visual interface; the visual interface includes a map and the movement trajectory of the target device in the map.

[0137] In one embodiment, the above device further comprises:

[0138] A positioning acquisition module is used to obtain the positioning information of the target device within a preset time period;

[0139] A trajectory generation module, used to generate a moving trajectory of a target device according to the positioning information of the target device within a preset time period;

[0140] The trajectory display module is used to display the movement trajectory of the target device in response to the trajectory playback operation.

[0141] Each module in the above-mentioned device positioning apparatus can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module above.

[0142] In one embodiment, an Internet of Things device is provided. The Internet of Things device may be a server, and its internal structure diagram may be as follows: Fig. 9As shown. The IoT device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the IoT device is used to provide computing and control capabilities. The memory of the IoT device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the IoT device is used to exchange information between the processor and an external device. The communication interface of the IoT device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a device positioning method is implemented.

[0143] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is only a block diagram of a partial structure related to the present application scheme, and does not constitute a limitation on the Internet of Things device to which the present application scheme is applied. The specific Internet of Things device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0144] In one embodiment, an Internet of Things device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0145] Acquire signal data sent by multiple positioning base stations; the signal data is generated by each positioning base station based on beacon signals sent by multiple Bluetooth beacons, and the beacon signals are generated based on Bluetooth signals sent by the target device to each Bluetooth beacon;

[0146] The position of the target device is calculated and processed according to the positioning algorithm and signal data to obtain the positioning information of the target device at the target time.

[0147] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0148] Determine the first device position of the target device at the target time according to the signal strength positioning algorithm and the signal strength corresponding to each time;

[0149] Determine the second device position of the target device at the target time according to the time difference positioning algorithm and the signal arrival time corresponding to each time;

[0150] The positioning information of the target device at the target time is determined according to the first device position of the target device at the target time and the second device position of the target device at the target time.

[0151] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0152] Obtain environmental information; environmental information includes the material and distribution information of obstacles;

[0153] Input the environmental information into the pre-built signal attenuation model to perform attenuation calculation processing to obtain the signal attenuation amount;

[0154] The parameters of the positioning algorithm are adjusted according to the signal attenuation to obtain the optimized positioning information of the target device at the target time.

[0155] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0156] Performing component identification processing on signal data to obtain multipath signal components;

[0157] Determine the positioning error of the signal data based on the multipath signal components;

[0158] Using a correction algorithm, the positioning error of the signal data is corrected to obtain corrected signal data;

[0159] Correspondingly, the position of the target device is calculated and processed according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time, including:

[0160] The position of the target device is calculated and processed according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target device at the target time.

[0161] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0162] Get the status information of the target device;

[0163] Visualize the location information and status information of the target device to generate a visualization interface;

[0164] Display a visualization interface; the visualization interface includes a map and the movement trajectory of the target device in the map.

[0165] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0166] Obtaining the location information of the target device within a preset period of time;

[0167] Generate a moving track of the target device according to the positioning information of the target device within a preset time period;

[0168] In response to the trajectory playback operation, the movement trajectory of the target device is displayed.

[0169] According to some embodiments of the present application, a computer program product is also provided, and when the computer program is executed by a processor, the above method can be implemented. The computer program product includes one or more computer instructions. When these computer instructions are loaded and executed on a computer, part or all of the above method can be implemented in whole or in part according to the process or function described in the embodiment of the present application.

[0170] According to some embodiments of the present application, there is also provided a non-transitory computer-readable storage medium including instructions, such as a memory including instructions, and the above instructions can be executed by a processor of an electronic device to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0171] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0172] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0173] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0174] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A device positioning method, characterized in that: The method comprises: Acquire signal data sent by multiple positioning base stations; the signal data is generated by each positioning base station according to a beacon signal sent by multiple Bluetooth beacons, and the beacon signal is generated based on a Bluetooth signal sent by a target device to each Bluetooth beacon; The position of the target device is calculated and processed according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time.

2. The method according to claim 1, characterized in that The signal data includes the signal strength and signal arrival time of the Bluetooth signal sent by the target device to the Bluetooth beacon at multiple times; the position calculation processing of the target device according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time includes: Determine a first device position of the target device at a target time according to a signal strength positioning algorithm and the signal strength corresponding to each of the time moments; Determine the second device position of the target device at the target time according to the time difference positioning algorithm and the signal arrival time corresponding to each of the said moments; The positioning information of the target device at the target time is determined according to the first device position of the target device at the target time and the second device position of the target device at the target time.

3. The method according to claim 1, characterized in that The method further comprises: Obtaining environmental information; the environmental information includes material and distribution information of obstacles; Inputting the environmental information into a pre-built signal attenuation model to perform attenuation calculation processing to obtain a signal attenuation amount; The parameters of the positioning algorithm are adjusted according to the signal attenuation to obtain optimized positioning information of the target device at the target time.

4. The method according to claim 1, characterized in that: The method further comprises: Performing component identification processing on the signal data to obtain multipath signal components; Determining a positioning error of the signal data according to the multipath signal component; Using a correction algorithm, the positioning error of the signal data is corrected to obtain corrected signal data; Correspondingly, performing position calculation processing on the target device according to the positioning algorithm and the signal data to obtain positioning information of the target device at the target time includes: The position of the target device is calculated and processed according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target device at the target time.

5. The method according to claim 4, characterized in that The method further comprises: Acquire status information of the target device; Visualize the location information and status information of the target device to generate a visualization interface; The visualization interface is displayed; the visualization interface includes a map and a movement track of the target device in the map.

6. The method according to claim 5, characterized in that The method further comprises: Obtaining location information of the target device within a preset time period; Generate a movement trajectory of the target device according to the positioning information of the target device within a preset time period; In response to the trajectory playback operation, the movement trajectory of the target device is displayed.

7. A device positioning device, characterized in that: The device comprises: A data acquisition module, used to acquire signal data sent by multiple positioning base stations; the signal data is generated by each positioning base station according to a beacon signal sent by multiple Bluetooth beacons, and the beacon signal is generated based on a Bluetooth signal sent by a target device to each Bluetooth beacon; The position calculation module is used to perform position calculation processing on the target device according to the positioning algorithm and the signal data to obtain the positioning information of the target device at the target time.

8. An Internet of Things device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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