CN119789204A - Device positioning method, device, internet of things device, storage medium and program product - Google Patents
Device positioning method, device, internet of things device, storage medium and program product Download PDFInfo
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Abstract
本申请涉及一种设备定位方法、装置、物联网设备、存储介质和程序产品，获取多个定位基站发送的信号数据；根据定位算法和信号数据对目标设备进行位置计算处理，得到目标设备在目标时刻的定位信息。本申请通过获取多个定位基站发送的信号数据，并依据相应的定位算法对目标设备进行位置计算处理，能够充分利用多源数据进行综合分析。相较于仅依靠单一基站或少量数据的定位方式，这种多基站协同的模式极大地提高了定位精度。
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
The application relates to the technical field of the internet of things, in particular to a device positioning method and device, internet of things device, storage medium and program product.
Background
In the present digital age, IT (Information Technology ) devices are increasingly and widely distributed in various indoor scenes (such as data centers, office buildings, factory workshops, etc.), and efficient operation and maintenance management thereof becomes a key requirement.
The traditional monitoring mode is difficult to realize accurate positioning of IT equipment in the face of a complex indoor ring. The Bluetooth positioning technology is used as an emerging indoor positioning means, and has certain advantages, such as relatively low equipment cost, easy deployment and the like. However, in practical applications, the bluetooth signal is susceptible to interference from various factors during indoor propagation, which may lead to inaccurate positioning distance estimation.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a device positioning method, an apparatus, an internet of things device, a storage medium, and a program product that can solve the foregoing problems.
In a first aspect, the present application provides a method for locating a device. The method comprises the following steps:
The method comprises the steps of obtaining signal data sent by a plurality of positioning base stations, wherein the signal data are generated by each positioning base station according to beacon signals sent by a plurality of Bluetooth beacons, and the beacon signals are generated based on Bluetooth signals sent by target equipment to each Bluetooth beacon;
And carrying out position calculation processing on the target equipment according to the positioning algorithm and the signal data to obtain the positioning information of the target equipment at the target moment.
In one embodiment, the signal data includes signal intensities and signal arrival times of bluetooth signals sent to the bluetooth beacons by the target device at a plurality of moments, and the step of performing position calculation processing on the target device according to a positioning algorithm and the signal data to obtain positioning information of the target device at the target moment includes:
Determining a first equipment position of target equipment at a target moment according to a signal strength positioning algorithm and signal strengths corresponding to all moments;
Determining a second equipment position of the target equipment at the target moment according to the time difference positioning algorithm and the signal arrival time corresponding to each moment;
and determining positioning information of the target equipment at the target moment according to the first equipment position of the target equipment at the target moment and the second equipment position of the target equipment at the target moment.
In one embodiment, the method further comprises:
acquiring environment information, wherein the environment information comprises material and distribution information of barriers;
inputting the environment information into a pre-constructed signal attenuation model for attenuation calculation processing to obtain the signal attenuation;
And adjusting parameters of a positioning algorithm according to the signal attenuation amount to obtain positioning information of the optimized target equipment at the target moment.
In one embodiment, 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;
Correcting the positioning error of the signal data by using a correction algorithm to obtain corrected signal data;
correspondingly, performing position calculation processing on the target equipment according to a positioning algorithm and signal data to obtain positioning information of the target equipment at a target moment, wherein the method comprises the following steps:
And carrying out position calculation processing on the target equipment according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target equipment at the target moment.
In one embodiment, the method further comprises:
acquiring state information of target equipment;
Performing visual processing on the positioning information and the state information of the target equipment to generate a visual interface;
and displaying a visual interface, wherein the visual interface comprises a map and a moving track of the target equipment in the map.
In one embodiment, the method further comprises:
acquiring positioning information of target equipment in a preset period;
Generating a moving track of the target equipment according to the positioning information of the target equipment in a preset period;
in response to the track playback operation, a movement track of the target device is presented.
In a second aspect, the application further provides a device positioning device. The device comprises:
The system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring signal data sent by a plurality of positioning base stations, the signal data are generated by each positioning base station according to beacon signals sent by a plurality of Bluetooth beacons, and the beacon signals are generated based on Bluetooth signals sent by target equipment to each Bluetooth beacon;
And the position calculation module is used for carrying out position calculation processing on the target equipment according to the positioning algorithm and the signal data to obtain the positioning information of the target equipment at the target moment.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the steps of the method of the first aspect described above when the processor executes the computer program.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method of the first aspect described above.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of the method of the first aspect described above.
The equipment positioning method, the equipment positioning device, the Internet of things equipment, the storage medium and the program product acquire signal data sent by a plurality of positioning base stations, and perform position calculation processing on target equipment according to a positioning algorithm and the signal data to acquire positioning information of the target equipment at a target moment. According to the application, the signal data sent by a plurality of positioning base stations are obtained, and the position of the target equipment is calculated according to the corresponding positioning algorithm, so that the multi-source data can be fully utilized for comprehensive analysis. Compared with a positioning mode which only depends on a single base station or a small amount of data, the multi-base station cooperative mode greatly improves positioning accuracy.
Drawings
FIG. 1 is a diagram of an application environment for a device location method in one embodiment;
FIG. 2 is a flow chart of a method of locating a device in one embodiment;
FIG. 3 is a flowchart of a method for obtaining positioning information of a target device at a target time according to an embodiment;
FIG. 4 is a flow chart of parameter adjustment of a positioning algorithm in one embodiment;
FIG. 5 is a flow chart of a positioning error correction process for signal data in one embodiment;
FIG. 6 is a flow diagram of visualization of location information and status information of a target device in one embodiment;
FIG. 7 is a flow diagram of generating a movement trajectory of a target device in one embodiment;
FIG. 8 is a block diagram of the device positioning apparatus in one embodiment;
fig. 9 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The device positioning method provided by the embodiment of the application can be applied to an application environment shown in figure 1. The internet of things platform 102 is communicatively coupled to the positioning base station 104, the positioning base station 104 is communicatively coupled to the bluetooth beacon 106, and the bluetooth beacon 106 is communicatively coupled to the target device 108. The internet of things platform 102 obtains signal data sent by a plurality of positioning base stations 104, the signal data are generated by each positioning base station 104 according to beacon signals sent by a plurality of Bluetooth beacons 106, the beacon signals are generated based on Bluetooth signals sent 108 by target equipment to each Bluetooth beacon, and position calculation processing is carried out on the target equipment according to a positioning algorithm and the signal data to obtain positioning information of the target equipment at target time. The target device 108 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The internet of things platform 102 may be implemented by a stand-alone server or a server cluster formed by a plurality of servers.
In an exemplary embodiment, as shown in fig. 2, an embodiment of the present application provides a device positioning method, which is illustrated by using the method applied to the internet of things platform 102 in fig. 1 as an example, and includes the following steps:
S201, signal data sent by a plurality of positioning base stations are acquired.
The signal data is generated by each positioning base station according to beacon signals sent by a plurality of Bluetooth beacons, and the beacon signals are generated based on Bluetooth signals sent to each Bluetooth beacon by target equipment.
In the embodiment of the application, the Internet of things platform firstly establishes communication connection with a plurality of positioning base stations, and the connection can be realized in a network mode such as Ethernet, wi-Fi and the like, so that the stability and timeliness of data transmission are ensured.
The positioning base station receives beacon signals transmitted by a plurality of Bluetooth beacons in real time in the coverage area of the positioning base station. For example, in an indoor office environment, bluetooth beacons are deployed at various corners and key locations, which continuously broadcast bluetooth signals containing information such as their own unique identification at a set power and period (e.g., broadcast once every 500 milliseconds). When a target device (such as a notebook computer) starts the Bluetooth function and is in the environment, the target device interacts with the Bluetooth beacon, and after receiving the Bluetooth signal from the target device, the Bluetooth beacon correspondingly adjusts and broadcasts a new beacon signal outwards.
After the positioning base station receives the beacon signals, key data information such as a timestamp (accurate to millisecond level, convenient for calculating signal propagation time related parameters), a received signal strength indicator (RSSI value, used for measuring strength condition of the signals after propagation attenuation and further calculating distance between the signals) and a corresponding Bluetooth beacon identifier (definitely from which specific beacon) of the signals are extracted and recorded, so as to generate signal data.
The positioning base station transmits the generated signal data to the Internet of things platform in real time through the established network connection. The internet of things platform is provided with a corresponding data receiving module, and received data are analyzed, verified and stored according to a preset data format and protocol, so that complete and accurate signal data from a plurality of positioning base stations are ensured to be obtained.
S202, performing position calculation processing on the target equipment according to a positioning algorithm and the signal data to obtain positioning information of the target equipment at a target moment.
In the embodiment of the application, after receiving signal data sent by a plurality of positioning base stations, the internet of things platform carries out preprocessing operation on the data. The method comprises the steps of data cleaning, data noise reduction, data standardization, unification of data formats and expression ranges transmitted by different positioning base stations and convenience for subsequent unified calculation, wherein the data cleaning is used for removing abnormal data (such as data with RSSI values exceeding a reasonable range) generated by signal interference, equipment temporary faults and the like, the data noise reduction is used for reducing noise influence in the data by technical means such as filtering and the like, so that the data can reflect real signal propagation conditions more.
And selecting according to the positioning scene and a pre-configured positioning algorithm. For example, if the indoor environment is relatively clear and the obstacles are fewer, the positioning algorithm based on RSSI may be preferentially selected, and if the positioning accuracy requirement is extremely high and the positioning base station has a high-accuracy time synchronization function, the TDOA algorithm is considered to be adopted.
Taking an RSSI-based positioning algorithm as an example, the internet of things platform uses an existing signal propagation model (such as a logarithmic distance path loss model, and parameters in the model, such as a signal attenuation index, are determined in advance by performing test calibration for multiple times in an actual positioning environment), substitutes the RSSI value corresponding to the beacon signal received by each positioning base station into the model, and calculates a distance estimation value between each bluetooth beacon and the corresponding positioning base station. And when a plurality of positioning base stations receive signals of the same Bluetooth beacon, a multilateration method is used for position calculation.
The equipment positioning method, the equipment positioning device, the Internet of things equipment, the storage medium and the program product acquire signal data sent by a plurality of positioning base stations, and perform position calculation processing on target equipment according to a positioning algorithm and the signal data to acquire positioning information of the target equipment at a target moment. According to the application, the signal data sent by a plurality of positioning base stations are obtained, and the position of the target equipment is calculated according to the corresponding positioning algorithm, so that the multi-source data can be fully utilized for comprehensive analysis. Compared with a positioning mode which only depends on a single base station or a small amount of data, the multi-base station cooperative mode greatly improves positioning accuracy.
In an exemplary embodiment, based on the foregoing embodiment, please refer to fig. 3, in which the signal data in the embodiment of the present application includes signal strengths and signal arrival times of bluetooth signals sent by a target device to a bluetooth beacon at a plurality of moments, the embodiment of the present application relates to a process for performing a position calculation process on the target device according to a positioning algorithm and the signal data to obtain positioning information of the target device at the target moment, including the following steps:
S301, determining the first equipment position of the target equipment at the target time according to a signal strength positioning algorithm and the signal strengths corresponding to the time.
In the embodiment of the application, the internet of things platform firstly extracts signal intensity information of Bluetooth signals sent to the Bluetooth beacons by target equipment at each moment from received signal data sent by a plurality of positioning base stations. The data are classified and stored according to different time, different Bluetooth beacons and corresponding positioning base stations. For example, in an indoor positioning scenario of a large mall, multiple bluetooth beacons are deployed in different areas in the mall, and each positioning base station receives bluetooth signal strength data from target devices (such as mobile phones of customers) forwarded by the beacons, and the internet of things platform integrates and combs the scattered data for subsequent unified processing.
Depending on the actual conditions of the internal environment (e.g. spatial layout, obstacle distribution, signal interference conditions, etc.), a suitable signal propagation model is selected, such as a logarithmic distance path loss model (PL (d) =pl (d_) -10nlg (d/d_) -n_0, where PL (d) represents the signal strength at the distance d from the transmitting node, PL (d_) is the signal strength at the reference distance d_n is the signal attenuation index, d is the actual distance between the nodes, n_0 is a gaussian random noise variable with mean 0 and standard deviation σ. Parameters of the model (e.g., n, PL (d_), etc.) have been calibrated by field testing to make it more fit to the actual environment prior to deployment of the system.
For each time, the signal strength (RSSI value) corresponding to each bluetooth beacon is substituted into the selected signal propagation model, and the distance estimation value between the target device and each bluetooth beacon is calculated. For example, at a certain moment, the positioning base station A receives the RSSI value of the corresponding target device from the Bluetooth beacon B as minus 60dB, and calculates the estimated distance value between the target device and the Bluetooth beacon B as 5 meters through the model and the calibrated parameters. And after the distance estimated values between the target device and the plurality of Bluetooth beacons (at least three) are acquired, calculating the position of the target device by utilizing a multilateration algorithm.
S302, determining a second equipment position of the target equipment at the target moment according to a time difference positioning algorithm and signal arrival time corresponding to each moment;
In the embodiment of the application, the internet of things platform firstly performs time synchronization state inspection on each positioning base station, ensures that the time synchronization precision between the positioning base stations meets the requirement of a time difference positioning algorithm (synchronization with microsecond level or even higher precision is generally required), and can be ensured by means of professional time synchronization technologies such as Network Time Protocol (NTP). And then, extracting time information of the Bluetooth signals transmitted by the target equipment at each moment to reach each positioning base station from the signal data, and classifying and sorting according to different positioning base stations. And aiming at the Bluetooth signals sent by the same target equipment, comparing the time of reaching different positioning base stations, and calculating the time difference. When a plurality of groups of positioning base stations participate in measurement (generally at least three groups), a plurality of hyperbolas exist, and the position of the target equipment is determined by solving the intersection points of the hyperbolas. And comprehensively considering the position relation, the error condition and the like of each hyperbola by utilizing a numerical calculation method and an optimization algorithm, and finally calculating the position coordinate of the second equipment of the target equipment at the target moment.
S303, determining positioning information of the target device at the target moment according to the first device position of the target device at the target moment and the second device position of the target device at the target moment.
In the embodiment of the application, the weight of the two in fusion positioning is determined by the Internet of things platform 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 some areas of a market (such as places close to elevators and more metal structures), signal strength is disturbed more, and the time difference positioning algorithm is relatively more reliable and is given higher weight, while in the areas with wide opening and less disturbance, the signal strength positioning algorithm is given proper weight. The weight can be dynamically adjusted according to actual experience, experimental test results and the like. And carrying out weighted average calculation on the first equipment position and the second equipment position by using the determined weight to obtain the final positioning information coordinate of the target equipment at the target moment.
The embodiment of the application combines the signal strength positioning algorithm and the time difference positioning algorithm to determine the positioning information of the target equipment, and has obvious beneficial effects. Firstly, two positioning algorithms with different principles are fused, the advantages that the signal intensity data can reflect the relative distance relation and the signal arrival time data can accurately calculate the distance difference are fully utilized, the limitations of each positioning algorithm in different environments are mutually compensated, and the positioning accuracy and reliability are effectively improved.
In an exemplary embodiment, based on the foregoing embodiment, please refer to fig. 4, the method of the embodiment of the present application further includes the following steps:
s401, acquiring environment information.
The environment information comprises the material and distribution information of the barriers.
In the embodiment of the application, the internet of things platform firstly acquires environment information by establishing communication connection with various sensor devices. For example, the system is connected with laser radar sensors arranged at various key positions in a room, the laser radar can scan the surrounding environment to identify the outline, position and other information of different objects (namely barriers), the spatial coordinate data of the objects are transmitted to an internet of things platform through the algorithm processing of the system, and meanwhile, the system is interacted with a plurality of material identification sensors (which can be sensors based on the principles of radio frequency identification, ultrasonic waves and the like and judge materials according to the characteristic differences of reflection, penetration and the like of the objects of different materials) to obtain the material information of the barriers, such as the concrete materials of the wall of a certain area and the glass materials of a certain part of partitions. After receiving data from different sensors, the internet of things platform integrates the data, associates the position and material information about the same obstacle, marks the position and material information according to a coordinate system of an indoor space, and forms an environment information data set containing the material and distribution information of each obstacle, so that the environment information data set is convenient to input into a signal attenuation model for unified analysis. For example, in a floor positioning scene of an office building, relevant information of furniture such as a desk and a chair, a filing cabinet and the like in each office and building structures such as walls, columns and the like are all arranged on corresponding position coordinates, and the distribution condition of obstacles and the respective material condition of the whole floor are clearly presented.
S402, inputting environment information into a pre-constructed signal attenuation model for attenuation calculation processing to obtain signal attenuation;
In the embodiment of the application, according to the signal type adopted by the positioning system and the characteristics of the positioning scene (such as the approximate scale of an indoor environment, the type of a common obstacle and the like), the Internet of things platform selects an adaptive model from a plurality of signal attenuation models which are built and stored in advance. The models can be experience models constructed based on mathematical methods such as regression analysis after attenuation tests are carried out on Bluetooth signals by a large number of indoor experimental tests and by using barriers made of different materials, or theoretical models combined with electromagnetic theory to simulate the signal propagation attenuation process, and the models are stored for standby after actual verification and calibration. And inputting the integrated environment information into the selected signal attenuation model according to the format and parameter form required by the model. For example, the input parameters of the model may include the thickness of the obstacle of different materials, the relative position relation with the signal propagation path (and the distance from the target device and the bluetooth beacon (or positioning base station), etc., after the model receives these parameters, according to the algorithm rule set in the model, the model performs attenuation calculation processing, and outputs the corresponding signal attenuation value, for example, the attenuation of the bluetooth signal is 15dB calculated on a specific propagation path due to the shielding of a concrete wall and several wooden file cabinets.
S403, adjusting the parameters of the positioning algorithm according to the signal attenuation amount to obtain the positioning information of the optimized target equipment at the target moment.
In the embodiment of the application, the internet of things platform analyzes the positioning algorithm (such as a positioning algorithm based on Received Signal Strength Indication (RSSI), a time difference of arrival (TDOA) positioning algorithm and the like) in use to find out key parameters related to signal strength and propagation distance, and the parameters need to be correspondingly adjusted under different signal attenuation conditions to ensure positioning accuracy. After the parameters are adjusted, the positioning algorithm is used again to calculate the position of the target equipment, and the positioning information of the optimized target equipment at the target moment is obtained.
According to the embodiment of the application, the material and distribution conditions of the obstacles in the environment information are considered, the signal attenuation quantity is calculated through the signal attenuation model, the real propagation characteristics of Bluetooth signals and the like in the actual complex indoor environment can be reflected more accurately, the positioning error caused by the traditional positioning algorithm when the influence of environmental factors is ignored is made up, the positioning precision is effectively improved, and the acquired positioning information of the target equipment is closer to the real position of the target equipment.
In an exemplary embodiment, based on the foregoing embodiment, please refer to fig. 5, the method of the embodiment of the present application further includes the following steps:
s501, carrying out component identification processing on the signal data to obtain multipath signal components.
In the embodiment of the application, the internet of things platform firstly extracts the part of signal data related to the positioning of the target equipment from the original signal data collected by each positioning base station, wherein the data comprise information such as signal strength, signal arrival time and the like received at different moments. Then, a basic preprocessing operation is performed on the data, such as removing noise in the data, normalizing the data, and the like, so that the data quality is ensured for better component recognition processing. Aiming at the preprocessed signal data, the Internet of things platform extracts relevant parameters capable of reflecting multipath signal characteristics by using a signal processing technology, recognizes and extracts each multipath signal component from the mixed signal data by using a pattern recognition algorithm and a multipath propagation model according to the extracted characteristic parameters, respectively collates the multipath signal components, and confirms the key parameter information such as the amplitude, the phase, the delay time and the like of each multipath signal component so as to prepare for the subsequent analysis of positioning errors.
S502, determining the positioning error of the signal data according to the multipath signal components.
In the embodiment of the application, the internet of things platform constructs a corresponding positioning error analysis model according to a specific algorithm adopted by positioning (such as a positioning algorithm based on RSSI, a TDOA positioning algorithm and the like) and the characteristics of the current indoor environment (such as known barrier distribution, spatial layout and the like). The model takes relevant parameters of multipath signal components (such as amplitude, phase, delay time and relative relation between the multipath signal components and a direct path signal) as input variables, establishes a mathematical association relation with positioning errors through theoretical derivation and empirical analysis based on historical positioning data, for example, in RSSI positioning, multipath signal superposition can cause abnormal change of received signal strength, further influences the distance calculated based on the signal strength and the final positioning result, and the model quantifies the situation of the positioning errors corresponding to the influence. Substituting the specific parameters for identifying the extracted multipath signal components into a constructed positioning error analysis model, and calculating the positioning error caused by the influence of the multipath signals according to the calculation rules set in the model.
S503, correcting the positioning error of the signal data by using a correction algorithm to obtain corrected signal data.
In the embodiment of the application, the internet of things platform selects a proper algorithm from a plurality of pre-stored correction algorithms to correct errors according to the overall architecture of a positioning system, the adopted positioning technology and the specific condition 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 intensity information, a correction algorithm based on ray tracing principle may be selected, the signal intensity abnormality caused by the multipath is reversely corrected through the real propagation path of the analog signal in the indoor environment, and if TDOA positioning is adopted and the multipath interference shows a certain periodicity rule, a correction algorithm based on filtering and phase adjustment is selected to remove the influence of the multipath on the signal arrival time difference.
The selected correction algorithm is used to process the original signal data in the presence of multipath interference. Taking a correction algorithm based on a ray tracing principle as an example, according to an indoor environment map and an identified multipath signal propagation path, calculating the theoretical signal strength under the condition of no multipath interference again, then correcting a signal strength value of deviation generated by multipath superposition in original signal data by using the theoretical value, and for the correction algorithm based on filtering and phase adjustment, removing abnormal phase components which do not accord with a normal propagation rule in multipath signals by filtering operation, adjusting the phase of the signals to enable the phases to be closer to an ideal state without multipath interference, thereby finishing correction processing of the signal data, and obtaining corrected signal data so as to enable the corrected signal data to reflect the real position information of target equipment.
Correspondingly, the position calculation processing is carried out on the target equipment according to the positioning algorithm and the signal data to obtain the positioning information of the target equipment at the target moment, and the position calculation processing is carried out on the target equipment according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target equipment at the target moment.
In the embodiment of the application, the internet of things platform sorts and format-converts the signal data corrected by the correction algorithm according to the input requirement of the positioning algorithm, replaces original signal data with multipath interference, provides the new input data for the positioning algorithm, and performs position calculation processing on the corrected signal data by using the positioning algorithm. For example, in the polygonal positioning based on the RSSI, the distance between the target equipment and each base station is estimated again according to the signal intensity value of the target equipment received by each positioning base station after correction, and then the coordinate position of the target equipment at the target moment is calculated by solving an equation set formed by the distances, so that more accurate positioning information is obtained, and the influence of positioning errors caused by multipath signals is effectively reduced.
In the embodiment of the application, the interference condition generated by the multipath effect when the wireless signal propagates in the actual complex indoor environment can be deeply known by accurately identifying the multipath signal component and analyzing the positioning error brought by the multipath signal component, so that the signal data is corrected by using a correction algorithm in a targeted manner, and the positioning precision is greatly improved.
In an exemplary embodiment, based on the foregoing embodiment, please refer to fig. 6, the method of the embodiment of the present application further includes the following steps:
s601, acquiring state information of target equipment;
The status information refers to data of various running, using and other aspects related to the target device, such as whether the device is in a power-on state, a residual electric quantity condition and a task being executed by the device.
In the embodiment of the application, the internet of things platform firstly determines the mode and the corresponding interface of the target equipment capable of providing the state information, and for the traditional equipment, the gateway equipment can be used for carrying out data conversion and transmission so as to acquire the state information. And then, configuring a data receiving module according to the corresponding communication protocol and data format requirements, and ensuring that the state information actively pushed or sent by the target equipment according to a certain period can be stably received. And after receiving the original state information from the target equipment, the Internet of things platform analyzes the original state information. In order to ensure timeliness and accuracy of the state information, the internet of things platform also sets a timing inquiry mechanism or monitors state change notification of the equipment to continuously acquire the latest state information. For example, a state query request is sent to the target device every few minutes, or when the key states of the device such as electric quantity and working mode change, the device actively pushes update notification to the platform of the internet of things, and the platform timely receives and updates the stored corresponding state information so as to display the latest device state condition to the user.
S602, performing visualization processing on positioning information and state information of target equipment to generate a visualization interface;
In the embodiment of the application, the internet of things platform selects the map data matched with the target equipment according to the positioning area where the target equipment is located, and the map can be an electronic map stored in a platform database in advance or can be map information acquired by calling a third-party map service. And then loading the selected map into a visual processing frame, and setting basic interaction functions such as zooming, translation and the like of the map to enable the basic interaction functions to serve as a basic background for displaying the information of the target equipment. And corresponding the positioning information of the target equipment at the target moment to the corresponding position on the map, and identifying the current position of the target equipment by using a specific icon. Meanwhile, different visualization modes are adopted for displaying the state information of the target equipment. For example, the electric quantity condition of the equipment is represented by different icon colors, and the current working mode of the equipment is displayed by adding a text prompt box beside the icon, so that a user can intuitively know the state of the equipment at a glance. If the target equipment moves, the internet of things platform records positioning information of different moments, the position coordinate points are sequentially connected according to time sequence, a moving track of the target equipment is drawn on a map, the track can be represented by lines with different colors and thickness, so that visual effect and distinguishing degree are enhanced, and a user can conveniently and clearly observe the moving path and the historical position change condition of the equipment. The map, the positioning information and the state information are comprehensively processed to generate a complete visual interface, so that the complete visual interface can comprehensively and intuitively display the related conditions of the target equipment.
S603, displaying a visual interface. The visual interface comprises a map and a moving track of the target device in the map.
In the embodiment of the application, the Internet of things platform issues the generated visual interface through the network service, so that the visual interface can be accessed by authorized users.
Considering that a user can access the visual interface through different terminal devices (such as a computer browser, a mobile phone, a tablet personal computer and the like), the internet of things platform can perform multi-port adaptation processing, so that the interface can be normally displayed under different screen sizes and resolutions, and the layout is reasonable and attractive. Meanwhile, interactive functions are provided for the user, such as supporting to view detailed state information of the device through mouse clicking or touch operation (a clicking device icon pops up a detailed information frame to display more state parameters), enlarging or shrinking a map to view device distribution and moving tracks in different ranges, switching different device groups or screening conditions to view information of a specific device subset, and the like, so that convenience and experience of the user for viewing and managing the device are improved.
The embodiment of the application combines the positioning information and the state information and presents the positioning information and the state information in a visual interface, so that a user can intuitively and comprehensively know the real-time condition of the target equipment, including key information such as where the equipment is and what operating state the equipment is, and the like, does not need to check complicated text data or perform complex data analysis, greatly improves the efficiency of information acquisition, and is convenient for the user to quickly make decisions about equipment management, scheduling, operation and maintenance and the like.
In an exemplary embodiment, based on the foregoing embodiment, please refer to fig. 7, the method of the embodiment of the present application further includes the following steps:
s701, positioning information of target equipment in a preset period is acquired;
In the embodiment of the application, the internet of things platform firstly accesses a database storing positioning information, and extracts all positioning information of the target equipment in a preset period from massive positioning data records according to preset time screening conditions. The queried positioning information is sorted according to the time sequence, so that the position change sequence of the target equipment in the preset period can be accurately reflected. And meanwhile, checking the integrity and accuracy of the data, and checking whether the condition of key data missing or data abnormality exists. If the problem data is found, processing is carried out according to a data backup mechanism or a related data restoration strategy, so that the data quality of the subsequently generated moving track is ensured to be reliable.
S702, generating a moving track of the target equipment according to the positioning information of the target equipment in a preset period;
In the embodiment of the application, the platform of the internet of things selects a proper movement track construction algorithm according to the environmental characteristics of the target equipment and the data format of the positioning information. For example, in a simple two-dimensional indoor plane positioning scene, a linear interpolation algorithm is adopted to sequentially connect position coordinate points of target equipment at adjacent moments according to a time sequence to form a continuous moving track, and for the outdoor positioning condition involving complex terrain and three-dimensional space, an algorithm based on spline curve fitting can be applied, so that the generated moving track can be more smoothly and naturally attached to the actual terrain and the motion path of the equipment, and the problems of discontinuous track or unattractive track and the like caused by coordinate dispersion are reduced. The selected track construction algorithm can be used for processing the positioning information of the sorted target equipment in a preset period of time to generate corresponding movement track data. The data structure may contain information such as the start point and end point coordinates of the track, key coordinate points passing through the middle, and time stamps corresponding to the points, so as to completely describe the moving process of the device. And then, the generated moving track data is stored in a special track database or a storage area associated with the positioning information, so that the subsequent quick retrieval and display can be conveniently carried out according to the track playback operation of the user.
S703, in response to the track playback operation, displaying the movement track of the target device.
In the embodiment of the application, the internet of things platform is provided with the interaction interface which is specially used for receiving the track playback operation, when a user initiates the track playback operation through the client, for example, clicks a track playback button on the interface or selects a specific preset time period range on a time axis, the interaction interface of the platform can receive corresponding operation instructions and parameter information in real time and analyze and verify the corresponding operation instructions, so that the operation instructions are legal and meet the system requirements. And according to the received track playback operation instruction, the corresponding target equipment movement track data is called from the storage area, converted into the visual element and then displayed on the visual interface. Meanwhile, according to parameters such as playback speed and the like set by a user, a complete moving track of the target device in a preset period is displayed through an animation effect, so that the user can clearly observe the position change condition of the device, interaction functions such as pause, fast forward, reverse and the like can be provided, and the user can conveniently and flexibly check different parts and detail contents of the track.
The embodiment of the application acquires the positioning information of the target equipment in the preset period and generates the movement track, can completely record the movement history of the equipment, provides comprehensive data support for subsequent analysis, has track playback operation and corresponding display functions, is convenient for users to review the past movement condition of the equipment at any time, and is beneficial to finding potential problems in the running process of the equipment, summarizing the use rule of the equipment and predicting the future equipment behaviors.
In an exemplary embodiment, based on the above embodiment, the method according to the embodiment of the present application further includes the following steps:
The method comprises the steps of 1, acquiring signal data sent by a plurality of positioning base stations by an Internet of things platform, carrying out component identification processing on the signal data to obtain multipath signal components, determining positioning errors of the signal data according to the multipath signal components, and carrying out correction processing on the positioning errors of the signal data by utilizing a correction algorithm to obtain signal intensities corresponding to corrected moments and signal arrival times corresponding to the moments;
Step 2, obtaining environment information, adjusting parameters of a positioning algorithm according to the signal attenuation amount to obtain an adjusted signal strength positioning algorithm and an adjusted time difference positioning algorithm;
Determining a first equipment position of the target equipment at the target moment according to the adjusted signal strength positioning algorithm and the corrected signal strength corresponding to each moment, determining a second equipment position of the target equipment at the target moment according to the adjusted time difference positioning algorithm and the corrected signal arrival time corresponding to each moment, and determining positioning information of the target equipment at the target moment according to the first equipment position of the target equipment at the target moment and the second equipment position of the target equipment at the target moment;
Step 4, acquiring state information of the target equipment, carrying out visual processing on the positioning information and the state information of the target equipment to generate a visual interface, and displaying the visual interface, wherein the visual interface comprises a map and a moving track of the target equipment in the map;
Step 5, obtaining positioning information of the target equipment in a preset period, generating a moving track of the target equipment according to the positioning information of the target equipment in the preset period, and displaying the moving track of the target equipment in response to track playback operation.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a device positioning device for realizing the above-mentioned device positioning method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiment of one or more device positioning devices provided below may refer to the limitation of the device positioning method hereinabove, and will not be repeated herein.
In one embodiment, as shown in fig. 9, there is provided a device positioning apparatus 800 comprising:
The data acquisition module 801 is configured to acquire signal data sent by a plurality of positioning base stations, where the signal data is generated by each positioning base station according to beacon signals sent by a plurality of bluetooth beacons, and the beacon signals are generated based on bluetooth signals sent by a target device to each bluetooth beacon;
The location calculation module 802 is configured to perform location calculation processing on the target device according to the location algorithm and the signal data, so as to obtain location information of the target device at the target moment.
In one embodiment, the signal data includes signal strength and signal arrival time of bluetooth signals transmitted to the bluetooth beacon by the plurality of time target devices, and the position calculation module includes:
the first position determining unit is used for determining a first equipment position of the target equipment at the target moment according to the signal strength positioning algorithm and the signal strengths corresponding to the moments;
The second position determining unit is used for determining the second equipment position of the target equipment at the target moment according to the time difference positioning algorithm and the signal arrival time corresponding to each moment;
And the position information determining unit is used for determining the positioning information of the target equipment at the target moment according to the first equipment position of the target equipment at the target moment and the second equipment position of the target equipment at the target moment.
In one embodiment, the apparatus further includes:
The information acquisition module is used for acquiring environmental information, wherein the environmental information comprises the material and distribution information of the barrier;
the attenuation calculation module is used for inputting the environmental information into a pre-constructed signal attenuation model to carry out attenuation calculation processing so as to obtain the signal attenuation;
And the parameter adjustment module is used for adjusting the parameters of the positioning algorithm according to the signal attenuation amount to obtain the positioning information of the optimized target equipment at the target moment.
In one embodiment, the apparatus further includes:
The component recognition module is used for carrying out component recognition processing on the signal data to obtain multipath signal components;
the error determining module is used for determining the positioning error of the signal data according to the multipath signal components;
The error correction module is used for correcting the positioning error of the signal data by using a correction algorithm to obtain corrected signal data;
Correspondingly, the position calculation module includes:
and the positioning correction module is used for carrying out position calculation processing on the target equipment according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target equipment at the target moment.
In one embodiment, the apparatus further includes:
the information acquisition module is used for acquiring the state information of the target equipment;
the interface generation module is used for carrying out visual processing on the positioning information and the state information of the target equipment to generate a visual interface;
The system comprises an interface display module, a display module and a display module, wherein the interface display module is used for displaying a visual interface, and the visual interface comprises a map and a moving track of target equipment in the map.
In one embodiment, the apparatus further includes:
The positioning acquisition module is used for acquiring positioning information of the target equipment in a preset period;
The track generation module is used for generating a moving track of the target equipment according to the positioning information of the target equipment in a preset period;
And the track display module is used for responding to the track playback operation and displaying the moving track of the target equipment.
The various modules in the device positioning apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, an internet of things device is provided, which may be a server, and an internal structure diagram thereof may be as shown in fig. 9. The internet of things device comprises a processor, a memory, an Input/Output interface (I/O for short) and a communication interface. 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. The processor of the Internet of things device is used for providing computing and control capabilities. The memory of the Internet of things device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the internet of things device is used for exchanging information between the processor and the external device. The communication interface of the Internet of things device is used for communicating with an external terminal through network connection. The computer program is executed by a processor to implement a device positioning method.
It will be appreciated by those skilled in the art that the structure shown in fig. 9 is merely a block diagram of a portion of the structure related to the present application, and does not constitute a limitation of the internet of things device to which the present application is applied, and that a specific internet of things device may include more or less components than those shown in the drawings, or may combine some components, or have a different arrangement of components.
In one embodiment, there is provided an internet of things device comprising a memory and a processor, the memory storing a computer program, the processor when executing the computer program implementing the steps of:
The method comprises the steps of obtaining signal data sent by a plurality of positioning base stations, wherein the signal data are generated by each positioning base station according to beacon signals sent by a plurality of Bluetooth beacons, and the beacon signals are generated based on Bluetooth signals sent by target equipment to each Bluetooth beacon;
And carrying out position calculation processing on the target equipment according to the positioning algorithm and the signal data to obtain the positioning information of the target equipment at the target moment.
In one embodiment, the processor when executing the computer program further performs the steps of:
Determining a first equipment position of target equipment at a target moment according to a signal strength positioning algorithm and signal strengths corresponding to all moments;
Determining a second equipment position of the target equipment at the target moment according to the time difference positioning algorithm and the signal arrival time corresponding to each moment;
and determining positioning information of the target equipment at the target moment according to the first equipment position of the target equipment at the target moment and the second equipment position of the target equipment at the target moment.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring environment information, wherein the environment information comprises material and distribution information of barriers;
inputting the environment information into a pre-constructed signal attenuation model for attenuation calculation processing to obtain the signal attenuation;
And adjusting parameters of a positioning algorithm according to the signal attenuation amount to obtain positioning information of the optimized target equipment at the target moment.
In one embodiment, the processor when executing the computer program further performs the steps of:
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;
Correcting the positioning error of the signal data by using a correction algorithm to obtain corrected signal data;
correspondingly, performing position calculation processing on the target equipment according to a positioning algorithm and signal data to obtain positioning information of the target equipment at a target moment, wherein the method comprises the following steps:
And carrying out position calculation processing on the target equipment according to the positioning algorithm and the corrected signal data to obtain the positioning information of the target equipment at the target moment.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring state information of target equipment;
Performing visual processing on the positioning information and the state information of the target equipment to generate a visual interface;
and displaying a visual interface, wherein the visual interface comprises a map and a moving track of the target equipment in the map.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring positioning information of target equipment in a preset period;
Generating a moving track of the target equipment according to the positioning information of the target equipment in a preset period;
in response to the track playback operation, a movement track of the target device is presented.
According to some embodiments of the present application, there is also provided a computer program product, which, when executed by a processor, can implement the above-mentioned method. The computer program product includes one or more computer instructions. When loaded and executed on a computer, these computer instructions may implement some or all of the methods described above, in whole or in part, in accordance with the processes or functions described in embodiments of the present application.
According to some embodiments of the present application, there is also provided a non-transitory computer-readable storage medium, such as a memory, comprising instructions executable by a processor of an electronic device to perform the above-described method. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magneto-resistive random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (PHASE CHANGE Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN120416896A (en) * | 2025-07-04 | 2025-08-01 | 山西中维信息工程股份有限公司 | Internet of Things intelligent analysis and early warning system and method based on intelligent gateway |
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| CN120416896A (en) * | 2025-07-04 | 2025-08-01 | 山西中维信息工程股份有限公司 | Internet of Things intelligent analysis and early warning system and method based on intelligent gateway |
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