Asset twinborn management method fusing indoor positioning and asset twinborn management server

Abstract

The invention discloses an asset twin management method fusing indoor positioning and an asset twin management server, and relates to the technical field of asset management, and the method comprises the steps: obtaining a to-be-managed asset list, carrying out the attribute classification and integration of all asset information, and obtaining an asset attribute parameter set; establishing an asset digital twinborn model; carrying out key position identification and positioning system deployment on the indoor area information to obtain an indoor positioning sensor network, and carrying out position interaction with the positioning installation labels of the asset information to obtain an asset indoor positioning sensing data stream; and carrying out fusion processing on the asset indoor positioning sensing data flow, determining asset synchronous position information, carrying out asset state updating on the asset digital twin model, obtaining an asset updated digital twin model, and carrying out asset twin management. According to the invention, the technical problems of insufficient asset positioning accuracy, dynamic state updating and real-time monitoring in the prior art are solved, and the technical effects of accurate asset state management and efficient monitoring are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of asset management, and in particular to an asset twin management method and an asset twin management server integrating indoor positioning. Background Art

[0002] As the demand for accurate monitoring and efficient management of assets in modern industry and enterprise management continues to increase, traditional asset management methods face many challenges. Most existing asset management systems rely on static data and regular manual updates, which leads to lags and inaccuracies in asset location and status information, and cannot reflect the actual use of assets and their dynamic changes in real time. Especially in complex indoor environments, traditional positioning technologies are difficult to provide sufficient accuracy and real-time performance, and the tracking and management efficiency of asset status is low. Summary of the invention

[0003] The present application provides an asset twin management method and an asset twin management server integrating indoor positioning, which are used to solve the technical problems of the prior art in terms of asset positioning accuracy, dynamic status update and real-time monitoring.

[0004] In view of the above problems, the present application provides an asset twin management method and an asset twin management server integrating indoor positioning.

[0005] In a first aspect of the present application, a method for asset twin management integrating indoor positioning is provided, the method comprising:

[0006] Obtain a list of assets to be managed, classify and integrate the attributes of each asset information in the list of assets to be managed, and obtain an asset attribute parameter set; perform twin simulation on the asset attribute parameter set to establish an asset digital twin model; obtain the indoor area information of the list of assets to be managed, perform key position identification and positioning system deployment on the indoor area information, and obtain an indoor positioning sensor network; perform position interaction with the positioning installation tags of each asset information through the indoor positioning sensor network to obtain an asset indoor positioning sensor data stream; perform fusion processing on the asset indoor positioning sensor data stream based on the indoor positioning sensor network to determine the asset synchronization position information; perform asset status update on the asset digital twin model based on the asset synchronization position information to obtain an asset update digital twin model, and perform asset twin management through the asset update digital twin model.

[0007] A second aspect of the present application provides an asset twin management server integrating indoor positioning, the server comprising:

[0008] An attribute classification integration module, wherein the attribute classification integration module obtains a list of assets to be managed, classifies and integrates the asset information in the list of assets to be managed, and obtains a set of asset attribute parameters; a twin simulation module, wherein the twin simulation module performs twin simulation on the set of asset attribute parameters to establish an asset digital twin model; a sensor network establishment module, wherein the sensor network establishment module obtains the indoor area information of the list of assets to be managed, performs key position identification and positioning system deployment on the indoor area information, and obtains an indoor positioning sensor network; a position interaction module, wherein the position interaction module performs position interaction with the positioning installation tags of the asset information through the indoor positioning sensor network to obtain an asset indoor positioning sensor data stream; a fusion processing module, wherein the fusion processing module performs fusion processing on the asset indoor positioning sensor data stream based on the indoor positioning sensor network to determine the asset synchronization position information; an asset twin management module, wherein the asset twin management module performs asset status update on the asset digital twin model based on the asset synchronization position information to obtain an asset update digital twin model, and performs asset twin management through the asset update digital twin model.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application obtains a list of assets to be managed, classifies and integrates the attributes of each asset information in the list of assets to be managed, and obtains an asset attribute parameter set; performs twin simulation on the asset attribute parameter set to establish an asset digital twin model; obtains the indoor area information of the list of assets to be managed, identifies key locations and deploys a positioning system for the indoor area information, and obtains an indoor positioning sensor network; performs position interaction with the positioning installation tags of each asset information through the indoor positioning sensor network to obtain an asset indoor positioning sensor data stream; performs fusion processing on the asset indoor positioning sensor data stream based on the indoor positioning sensor network to determine the asset synchronization location information; performs asset status update on the asset digital twin model based on the asset synchronization location information to obtain an asset update digital twin model, and performs asset twin management through the asset update digital twin model. The present invention solves the technical problems of the prior art in terms of asset positioning accuracy, dynamic status update and real-time monitoring. Through asset attribute classification integration and digital twin modeling, combined with indoor positioning sensor network deployment and positioning data fusion processing, it dynamically obtains asset synchronization location information and updates the digital twin model in real time, so as to achieve the technical effect of accurate management and efficient monitoring of asset status. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic diagram of the flow of an asset twin management method integrating indoor positioning provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of an asset twin management server integrating indoor positioning provided in an embodiment of the present application.

[0014] Explanation of the accompanying drawings: attribute classification integration module 11, twin simulation module 12, sensor network establishment module 13, location interaction module 14, fusion processing module 15, asset twin management module 16. DETAILED DESCRIPTION

[0015] This application provides an asset twin management method and an asset twin management server integrated with indoor positioning, aiming to solve the technical problems of the existing technology in terms of asset positioning accuracy, dynamic status update and real-time monitoring. Through asset attribute classification integration and digital twin modeling, combined with indoor positioning sensor network deployment and positioning data fusion processing, the asset synchronization position information is dynamically obtained and the digital twin model is updated in real time, so as to achieve the technical effect of accurate management and efficient monitoring of asset status.

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0017] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, server, product or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0018] Embodiment 1, as Figure 1 As shown, the present application provides an asset twin management method integrating indoor positioning, the method comprising:

[0019] Step S100: Obtain a list of assets to be managed, classify and integrate the asset information in the list of assets to be managed, and obtain a set of asset attribute parameters.

[0020] In the embodiment of the present application, in the process of obtaining the list of assets to be managed and classifying and integrating the attributes, the list of assets to be managed is first obtained from the asset management system, and this list contains all the assets that need to be managed. Each asset contains multiple aspects of information, such as the basic attributes, physical attributes, value attributes, usage attributes, and location attributes of the asset.

[0021] Next, the various attributes in these asset information are classified and integrated. For example, all basic information is classified as "basic attributes", all information related to asset use such as maintenance records is classified as "usage attributes", and information related to asset value such as price and depreciation value is classified as "value attributes".

[0022] After completing the attribute classification and integration, the final result is a set of asset attribute parameters containing information of various types of assets.

[0023] Furthermore, in the method provided in the embodiment of the application, the asset information in the list of assets to be managed is classified and integrated to obtain a set of asset attribute parameters, and further includes:

[0024] According to the asset management standard, asset management attribute factor information is obtained, and the asset management attribute factor information includes basic attributes, physical attributes, value attributes, usage attributes and location attributes; each attribute factor in the asset management attribute factor information is classified and analyzed in turn to obtain an asset management attribute factor content set; management record calls are made for each asset information in the list of assets to be managed to obtain an asset management record data set; based on the asset management attribute factor content set, the asset management record data set is attribute-classified and integrated to obtain the asset attribute parameter set.

[0025] In an embodiment of the present application, first, according to the pre-set asset management standards, the basic information of the assets to be managed is extracted from the asset management database. This step is completed by database query technology, and relevant data is extracted from the database using SQL query and other methods. The extracted asset management attribute factor information includes basic attributes, physical attributes, value attributes, usage attributes and location attributes. Among them, basic attributes include the name, number, type, manufacturer, production date, etc. of the asset. Physical attributes include the size, weight, color, material, etc. of the asset. Value attributes include purchase price, depreciation rate, current value, market valuation, etc. Usage attributes include service life, frequency of use, maintenance records, repair costs, etc. Location attributes include storage location, usage location, transportation route, etc.

[0026] Then, the attribute factors in the asset management attribute factor information are classified and analyzed. Through the rule analysis method, the relevant attributes of each asset (such as basic attributes, physical attributes, value attributes, etc.) are classified and sorted to form an asset management attribute factor content set. For example, all data such as size, weight, color, etc. will be classified into the physical attribute category, while all purchase price, depreciation rate, and market valuation will be classified into the value attribute category.

[0027] After completing the attribute classification, proceed to the asset management record call, that is, call the historical record data set of each asset from the asset management system. These data sets include dynamic data such as the actual use of the asset, maintenance records, and failure history. By combining with static attributes (such as physical attributes, value attributes, etc.), dynamic data provides information on changes in the asset life cycle, such as maintenance history, number of failures, etc., to help managers fully understand the current status of the asset.

[0028] Finally, attribute classification and integration are performed based on the asset management attribute factor content set and the asset management record data set. This process uses data integration technology to orderly integrate various static and dynamic data to obtain an asset attribute parameter set. For example, the name, type, size, value and other attributes of the asset are integrated together, and combined with dynamic data such as the asset's maintenance history and usage to form a complete asset information file.

[0029] Step S200: Perform twin simulation on the asset attribute parameter set to establish an asset digital twin model.

[0030] In the embodiment of the present application, firstly, various attribute information of the asset to be managed is obtained, then the various attributes of the asset are converted into numerical data by using the parametric modeling method, and virtual modeling is performed based on these data. In this step, all the collected asset attribute parameters (such as size, weight, material, etc.) are transferred to the modeling tool in digital form so as to be accurately represented in the virtual space.

[0031] These attribute parameters are then used to generate a digital twin model of the asset through the selected modeling method. The digital twin model converts the physical attributes and usage attributes of the asset into digital form through modeling tools such as CAD, and builds a virtual asset model based on this.

[0032] Through the above process, the asset digital twin model is obtained.

[0033] Step S300: Acquire the indoor area information of the to-be-managed asset list, perform key position identification and positioning system deployment on the indoor area information, and obtain an indoor positioning sensor network.

[0034] In an embodiment of the present application, first, the distribution of the indoor area where the assets to be managed are located is collected to generate an indoor area map. Then, based on the map, key locations are identified, such as equipment storage areas and entrances and exits, to form a key location set. Then, according to the positioning demand target, a suitable multi-source positioning technology (such as Wi-Fi, Bluetooth, UWB, etc.) is selected, and sensor parameters are parsed for key locations in the indoor area to obtain a sensor deployment parameter set. Finally, based on these parameters, positioning sensors are deployed at key locations to form an indoor positioning sensor network.

[0035] Furthermore, in the method provided in the embodiment of the application, the key position identification and positioning system deployment of the indoor area information to obtain the indoor positioning sensor network also includes:

[0036] The distribution of the indoor area information is collected and map modeled to generate an indoor area map, key positions are identified based on the indoor area map, and a set of indoor area key positions is obtained; a positioning requirement target is obtained, and a multi-source positioning technology is selected according to the positioning requirement target; sensor parameters of the indoor area key position set are analyzed in turn according to the multi-source positioning technology to obtain a sensor deployment parameter set; a positioning system is deployed for the indoor area key position set based on the sensor deployment parameter set to obtain the indoor positioning sensor network.

[0037] In the embodiment of the present application, firstly, the indoor area information of the asset to be managed is obtained from the preset database, including the building layout, functional zoning, channels, etc., and the distribution situation collection method is used to collect detailed spatial data of the area by means of laser scanning, two-dimensional drawings or sensor data, etc., to generate an indoor area map. Then, based on the generated indoor area map, key positions are identified, and the map analysis method is used to identify key positions such as equipment storage areas, entrances and exits, important channels, etc., and form a set of key positions in the indoor area.

[0038] Then, according to the positioning requirements (such as asset tracking, personnel positioning, etc.), select the appropriate multi-source positioning technology. For example, Wi-Fi, Bluetooth low energy and other positioning technologies are selected according to the needs, and these technologies are selected according to different positioning accuracy and environmental conditions.

[0039] Next, based on the selected positioning technology, sensor parameter analysis is performed for the key locations in the indoor area. This process determines the sensor type and deployment plan required for each location by analyzing the signal propagation model, coverage range, accuracy requirements, etc. The final set of sensor deployment parameters is the sensor type, quantity, and installation location required for each key location.

[0040] Finally, based on the sensor deployment parameter set, the positioning system is deployed at key locations in the indoor area. This step generates a deployment diagram through a computer-aided design (CAD) tool and installs the sensor network on site. After the deployment is completed, the sensors are connected to the central server through a wireless network (such as Wi-Fi, Zigbee, etc.) to ensure real-time data collection and transmission. Through this step, an indoor positioning sensor network is obtained.

[0041] Step S400: Performing position interaction with the positioning installation tags of each asset information through the indoor positioning sensor network to obtain the asset indoor positioning sensor data stream.

[0042] In the embodiment of the present application, a multi-source indoor positioning sensor set is first determined. Then, the assets to be managed are coded and identified, and an asset identification code is generated and written into the positioning installation tag. Then, the multi-source indoor positioning sensor is used to interact with the asset positioning tag to obtain a multi-sensor positioning interaction data stream. Finally, the data stream is diverted according to the asset identification code to obtain the asset indoor positioning sensor data stream.

[0043] Furthermore, in the method provided in the embodiment of the application, the indoor positioning sensor network interacts with the positioning installation tags of each asset information to obtain the asset indoor positioning sensor data stream, and further includes:

[0044] According to the indoor positioning sensor network, a multi-source indoor positioning sensor set is determined; each asset information in the list of assets to be managed is encoded and identified to obtain an asset identification code, and the asset identification code is written into the positioning installation tag; the multi-source indoor positioning sensor set is used to perform position interaction with the positioning installation tags of each asset information to obtain a multi-sensor positioning interaction data stream; the multi-sensor positioning interaction data stream is diverted by device identification according to the asset identification code to obtain the asset indoor positioning sensor data stream.

[0045] In an embodiment of the present application, firstly, a multi-source indoor positioning sensor set is determined based on an indoor positioning sensor network. The sensor set includes multiple sensors of different types, such as Wi-Fi, Bluetooth, etc.

[0046] Next, encode and identify each asset information in the list of assets to be managed. In this step, a unique asset identification code is assigned to each asset to be managed (such as equipment, tools, etc.). Usually, barcodes, QR codes or RFID tags are used to identify these assets. The asset identification code consists of a combination of numbers or letters and contains key information about the asset (such as model, production date, etc.). The identification code of the asset can be quickly obtained by scanning the device or RFID reader. The identification code is the basis for subsequent positioning and asset tracking, ensuring that the positioning data of each asset can be correctly associated with a specific asset.

[0047] Subsequently, the asset identification code is written into the positioning installation tag. In this step, the asset identification code generated above is written into the asset's positioning installation tag. Commonly used technologies are RFID tags (radio frequency identification technology) or QR code tags. RFID tags interact with sensors through wireless signals and can quickly obtain and transmit location information. QR code tags use cameras or scanners to identify and extract information. Each asset's positioning installation tag will be embedded with a unique identification code and tracked in real time through sensors.

[0048] Next, the multi-source indoor positioning sensor interacts with the asset tag. In this step, the selected set of multi-source indoor positioning sensors interacts with the positioning installation tag of the asset information. Specifically, when the RFID tag or QR code carried by the asset enters the coverage range of the positioning sensor, the sensor communicates with the tag in a two-way manner through data such as signal strength and time difference to obtain the relative position of the asset. For example, the Bluetooth sensor estimates the distance of the asset based on the signal strength (RSSI value), while the Wi-Fi access point calculates the location of the asset through triangulation between the access points. The sensor collects data in this process and generates a multi-sensor positioning interaction data stream, which contains the real-time positioning information of multiple sensors.

[0049] Finally, the multi-sensor positioning interaction data stream is diverted by device identification. In this step, the multi-sensor positioning interaction data stream is diverted by device identification according to the unique identification code of each asset. That is, according to the identification code of the asset, the data streams from different sensors are matched and classified to ensure that each positioning information in the data stream can correspond to the correct asset. For example, the asset data scanned by the RFID tag will be extracted and matched with the identification code in the asset management database to generate accurate asset positioning information. Through diversion, the location information of different assets can be clearly distinguished, and the location changes of each asset can be monitored in real time, and finally an accurate asset indoor positioning sensor data stream is obtained.

[0050] Through the above steps, accurate asset indoor positioning sensor data stream is obtained.

[0051] Step S500: Based on the indoor positioning sensor network, the asset indoor positioning sensor data stream is fused and processed to determine the asset synchronization position information.

[0052] In an embodiment of the present application, the asset indoor positioning sensor data stream is first wirelessly transmitted to the data processing center through a wireless communication link for preprocessing and analysis to obtain preliminary processing results. Then, the data stream is further preprocessed based on the data preprocessing step to standardize all positioning data and generate a standard asset indoor positioning sensor data stream. Subsequently, a characteristic analysis is performed on each sensor in the multi-source indoor positioning sensor set to obtain a characteristic parameter set of the positioning sensor. Finally, based on these characteristic parameter sets, the standard asset indoor positioning sensor data stream is subjected to position fusion processing to ultimately determine the synchronous position information of the asset.

[0053] Furthermore, in the method provided in the embodiment of the application, the determining of the asset synchronization location information further includes:

[0054] The asset indoor positioning sensor data stream is wirelessly transmitted to a data processing center for preprocessing and analysis using a wireless communication link to obtain a data preprocessing step; the asset indoor positioning sensor data stream is preprocessed based on the data preprocessing step to obtain a standard asset indoor positioning sensor data stream; characteristics analysis is performed on each positioning sensor in the multi-source indoor positioning sensor set to obtain a positioning sensor characteristic parameter set; position fusion processing is performed on the standard asset indoor positioning sensor data stream based on the positioning sensor characteristic parameter set to determine the asset synchronization position information.

[0055] In an embodiment of the present application, when a wireless communication link is used to wirelessly transmit the indoor positioning sensor data stream of the asset to the data processing center for preprocessing and analysis, the data collected by the sensor is first analyzed to determine the appropriate preprocessing steps. Specifically, after the data collected by the sensor is transmitted to the data processing center, a preliminary analysis is performed based on the characteristics of the data (such as completeness, accuracy, noise, etc.) and the processing target requirements. For example, if there are missing values ​​in the data, data interpolation is required; if the data contains noise, filtering processing is required; if the data format is not uniform, standardization processing is required. Therefore, a set of data preprocessing steps will be generated through the process of preprocessing and analysis.

[0056] Once the preprocessing steps that need to be performed are determined, the data processing center preprocesses the asset indoor positioning sensor data stream according to these steps. In this process, data cleaning is first performed to delete invalid data points or outliers, including missing or duplicate positioning data. Next, the data format is standardized to convert the positioning data output by different sensors into a unified format (such as a unified timestamp, coordinate system or unit). After data standardization, noise filtering is performed, usually using methods such as Kalman filtering and mean filtering to remove noise caused by external environment or sensor failure. Finally, data normalization is performed to convert sensor data from different sources to a unified range according to certain rules for unified comparison during subsequent processing. After these steps, the original sensor data is preprocessed and converted into a standard asset indoor positioning sensor data stream that meets subsequent requirements.

[0057] Next, the characteristics of each sensor in the multi-source indoor positioning sensor set are analyzed. In this step, the data processing center analyzes the performance of each sensor in historical operation in order to determine its characteristic parameters. The characteristic parameters of these sensors include positioning accuracy, response time, signal strength, working stability, anti-interference ability, etc. By analyzing the historical data of the sensor in different environments and usage conditions, the reliability and performance of each sensor are evaluated. For example, by comparing the positioning errors of each sensor in different scenarios, the positioning accuracy parameters of each sensor are obtained. Based on these analyses, the data processing center will obtain a positioning sensor characteristic parameter set, which reflects the performance level that each sensor can achieve in actual operation.

[0058] Then, based on the positioning sensor characteristic parameter set, the data processing center performs position fusion processing on the standard asset indoor positioning sensor data stream. The core of position fusion is to use the positioning data from different sensors and weight the data according to the performance and accuracy of each sensor. Specifically, the weight of each sensor is determined according to its positioning accuracy. Sensors with higher accuracy will be given higher weights, and sensors with lower accuracy will be given lower weights. The weight calculation method can be based on the ratio of errors or assigned through specific accuracy values. For example, if the positioning error of a sensor is 1 meter and the positioning error of another sensor is 2 meters, the weight of the first sensor may be twice that of the second. To ensure that the sum of the weights is 1, the weights of all sensors are normalized so that their sum is 1.

[0059] In this way, data from multiple sensors are weighted and fused according to their positioning accuracy, resulting in a comprehensive and accurate synchronized asset location information.

[0060] Furthermore, in the method provided in the embodiment of the application, the position fusion processing is performed on the standard asset indoor positioning sensor data stream based on the positioning sensor characteristic parameter set to determine the asset synchronization position information, and further includes:

[0061] Perform accuracy verification analysis on each positioning sensor in the multi-source indoor positioning sensor set to obtain a multi-source sensor accuracy factor set; select a matching position fusion algorithm set based on the positioning sensor characteristic parameter set; perform a positioning test on the matching position fusion algorithm set, and when the positioning test result does not meet the preset accuracy rate, initialize the particle swarm parameters, and the particle swarm parameters include particle position and particle velocity; define a fitness loss function to evaluate and iteratively update the particle swarm parameters until the preset iteration conditions are met, and determine the particle with the largest fitness as the optimal parameter solution; optimize the matching position fusion algorithm set based on the optimal parameter solution to obtain a position fusion optimization algorithm set; perform positioning fusion on the indoor positioning sensor data streams of the standard assets based on the position fusion optimization algorithm set to obtain a multi-algorithm fusion positioning set; perform weighted fusion processing on the multi-algorithm fusion positioning set based on the multi-source sensor accuracy factor set to determine the asset synchronization position information.

[0062] In an embodiment of the present application, firstly, each positioning sensor in the multi-source indoor positioning sensor set is subjected to accuracy verification analysis. By comparing with a known reference position, the positioning error of each sensor is calculated. The root mean square error (RMSE) is usually used to measure the positioning accuracy of each sensor. By analyzing historical data, the error value of each sensor in different environments is calculated, and the calculated error value is used as the accuracy factor of the sensor. Through the above process, a multi-source sensor accuracy factor set is obtained.

[0063] Next, according to the positioning sensor characteristic parameter set, select the matching position fusion algorithm set. This algorithm set contains a variety of positioning fusion algorithms to choose from, such as Kalman filtering, particle filtering, weighted averaging, etc. Each sensor will be matched to a most suitable algorithm based on its precision factor and characteristic parameters. For example, a sensor with higher accuracy may choose the weighted averaging method, while a sensor with lower accuracy may choose the Kalman filtering algorithm. The purpose of this step is to select the most suitable fusion method for each sensor to ensure that the data of each sensor can be optimally fused. What is finally obtained is a matching positioning fusion algorithm set.

[0064] After selecting the appropriate matching position fusion algorithm, the positioning test phase begins. The accuracy of the current fusion algorithm is tested by comparing the positioning data of each sensor with the known standard position. If the positioning test results do not meet the preset accuracy standard, the algorithm parameters need to be further optimized. At this time, particle swarm optimization is used to initialize and optimize the parameters of the fusion algorithm. Particle swarm optimization is a global optimization method based on swarm intelligence, which is suitable for solving parameter optimization problems. During the initialization process, the particle swarm parameters include the position and velocity of each particle, which together determine the position and search step of the particle in the search space. The particle swarm algorithm explores the optimal solution by simulating swarm behavior, gradually adjusting the position and velocity of the particles, and finding the optimal parameters that minimize the positioning error.

[0065] After the particle swarm is initialized, a fitness loss function is defined, which is used to evaluate the quality of each particle solution. The fitness loss function is usually determined by calculating the error between the output position of the positioning algorithm and the standard position. The fitness value of each particle reflects the quality of the solution. The particle swarm is iteratively updated according to the fitness value, and the particle speed and position are updated each time, moving towards the optimal solution until the preset iteration conditions are met (such as the error is less than a certain threshold or the maximum number of iterations is reached).

[0066] In each round of iteration, the particle is adjusted according to its historical optimal position and the global optimal position. Finally, the particle with the largest fitness value (minimum error) is found, and the position of this particle is the optimal parameter solution.

[0067] Then, based on the optimal parameter solution obtained by particle swarm optimization, the selected matching position fusion algorithm set is optimized and configured. This process involves applying the optimal parameters to each fusion algorithm and adjusting the algorithm's parameter settings to better adapt to the characteristics of the sensor data. The optimized fusion algorithm can improve the accuracy of data fusion and reduce errors caused by insufficient sensor accuracy or external interference. Through this optimization configuration step, the position fusion optimization algorithm set is obtained.

[0068] Next, the optimized position fusion optimization algorithm set is put into practical application to generate a multi-algorithm fusion positioning set. In this process, the data of different sensors are processed according to the optimized algorithm and the positioning results are fused. For example, for sensors with higher accuracy, the weighted average method is used for fusion, while for sensors with lower accuracy, the Kalman filter is used for data processing. The data of each sensor is processed by the corresponding fusion algorithm to generate a multi-algorithm fusion positioning set.

[0069] Finally, the multi-algorithm fusion positioning set is weighted fused based on the multi-source sensor precision factor set. The weighted fusion process assigns different weights based on the precision factor of each sensor. The sensor results with higher precision factors will receive larger weights, indicating that the data of the sensor is more reliable and should have a greater impact on the final position calculation; the sensor results with lower precision factors will receive smaller weights. Through this weighted fusion method, the positioning results of all sensors are synthesized into a comprehensive asset synchronization position information to ensure the high accuracy of the final result. Through this step, the final asset synchronization position information is obtained. The sum of the weights of each sensor is 1, and the weight of each sensor is obtained by dividing the sum of the precision factors of all sensors by the precision factor corresponding to the sensor.

[0070] Step S600: Update the asset status of the asset digital twin model based on the asset synchronization position information, obtain the asset update digital twin model, and perform asset twin management through the asset update digital twin model.

[0071] In an embodiment of the present application, the asset status of the asset digital twin model is updated based on the asset synchronization position information to ensure that the asset location and status in the virtual model are consistent with the operating status of the actual asset. Through this update process, the asset digital twin model is adjusted and optimized in real time to reflect the current real status of the asset. Next, based on the updated digital twin model of the asset, more accurate asset twin management is performed. Specifically, through the updated digital twin model, the management personnel can monitor the asset status in real time, perform fault warning, performance analysis and optimization decision-making, improve the asset's operational efficiency and maintenance level, and thus achieve more scientific asset management.

[0072] Furthermore, the method provided in the application embodiment also includes:

[0073] If the target asset is in a moving state, monitor and obtain the asset movement speed change information; based on the asset movement speed change information, construct an asset movement prediction model, and perform movement state prediction based on the asset movement prediction model to obtain the asset predicted movement state; according to the asset predicted movement state, obtain the position real-time offset parameter, and perform position update correction on the asset synchronization position information based on the position real-time offset parameter.

[0074] In the embodiment of the present application, if the target asset is in a moving state, the target asset is monitored by the established indoor positioning sensor network to obtain the asset movement speed change information, including the asset's instantaneous speed, acceleration and direction change data. Among them, the target asset refers to a mobile entity in the list of assets to be managed that needs to be located, tracked and dynamically managed in a specific environment, such as cargo pallets in logistics warehousing, mobile equipment in production lines, transportation tools, etc.

[0075] Next, based on the collected information on asset movement speed changes, an asset movement prediction model is constructed. In order to build this prediction model, historical data is used for training. The training data includes information such as the speed, acceleration, direction of the asset at different time points, and external environmental factors (such as slope, obstacles, etc.). These data are used as inputs to learn the movement laws of assets and their behavioral characteristics in different environments through machine learning algorithms, such as support vector machine training models. During the training process, the model automatically adjusts parameters based on historical data to obtain accurate movement prediction capabilities. Through this step, a constructed asset movement prediction model is obtained.

[0076] Next, the constructed asset movement prediction model is used to predict the movement status of the asset. The asset movement speed change information is input into the asset movement prediction model to predict the movement status of the asset, and the predicted movement status of the asset is obtained, including the predicted position, speed and direction.

[0077] Then, based on the predicted movement state of the asset, the real-time offset parameter of the position is calculated. Specifically, the offset parameter refers to the difference between the predicted position and the current actual position. Since the asset is always in motion, the model generates a correction parameter based on the deviation value between the predicted future position and the current actual position. This offset parameter reflects the difference between the current predicted position and the actual position, and can be dynamically adjusted over time, thereby updating and correcting the current position of the asset in real time.

[0078] Finally, the synchronized position information of the asset is corrected based on the calculated real-time offset parameter. Since the future position predicted by the model is often one step ahead of the actual position, this offset parameter can be used to adjust the synchronized position information and correct the current position information to align with the predicted result. Through this step, the updated synchronized position information of the asset is obtained, completing the position update and correction of the synchronized position information of the asset.

[0079] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0080] This application obtains a list of assets to be managed, classifies and integrates the attributes of each asset information in the list of assets to be managed, and obtains an asset attribute parameter set; performs twin simulation on the asset attribute parameter set to establish an asset digital twin model; obtains the indoor area information of the list of assets to be managed, identifies key locations and deploys a positioning system for the indoor area information, and obtains an indoor positioning sensor network; performs position interaction with the positioning installation tags of each asset information through the indoor positioning sensor network to obtain an asset indoor positioning sensor data stream; performs fusion processing on the asset indoor positioning sensor data stream based on the indoor positioning sensor network to determine the asset synchronization location information; performs asset status update on the asset digital twin model based on the asset synchronization location information to obtain an asset update digital twin model, and performs asset twin management through the asset update digital twin model. The present invention solves the technical problems of the prior art in terms of asset positioning accuracy, dynamic status update and real-time monitoring. Through asset attribute classification integration and digital twin modeling, combined with indoor positioning sensor network deployment and positioning data fusion processing, it dynamically obtains asset synchronization location information and updates the digital twin model in real time, so as to achieve the technical effect of accurate management and efficient monitoring of asset status.

[0081] Embodiment 2 is based on the same inventive concept as the asset twin management method integrating indoor positioning in the above embodiment. Figure 2 As shown, the present application provides an asset twin management server integrating indoor positioning, and the server in the embodiment of the present application and the method embodiment are based on the same inventive concept. Among them, the server includes:

[0082] The attribute classification integration module 11 obtains the list of assets to be managed, classifies and integrates the asset information in the list of assets to be managed, and obtains a set of asset attribute parameters; the twin simulation module 12 performs twin simulation on the asset attribute parameter set to establish an asset digital twin model; the sensor network establishment module 13 obtains the indoor area information of the list of assets to be managed, identifies the key positions of the indoor area information and deploys the positioning system to obtain an indoor positioning sensor network; the position interaction module 14 The location interaction module 14 performs location interaction with the location installation tags of each asset information through the indoor positioning sensor network to obtain the asset indoor positioning sensor data stream; the fusion processing module 15, the fusion processing module 15 performs fusion processing on the asset indoor positioning sensor data stream based on the indoor positioning sensor network to determine the asset synchronization location information; the asset twin management module 16, the asset twin management module 16 updates the asset status of the asset digital twin model based on the asset synchronization location information, obtains the asset update digital twin model, and performs asset twin management through the asset update digital twin model.

[0083] Furthermore, the server is also used to implement the following functions:

[0084] According to the asset management standard, asset management attribute factor information is obtained, and the asset management attribute factor information includes basic attributes, physical attributes, value attributes, usage attributes and location attributes; each attribute factor in the asset management attribute factor information is classified and analyzed in turn to obtain an asset management attribute factor content set; management record calls are made for each asset information in the list of assets to be managed to obtain an asset management record data set; based on the asset management attribute factor content set, the asset management record data set is attribute-classified and integrated to obtain the asset attribute parameter set.

[0085] Furthermore, the server is also used to implement the following functions:

[0086] The distribution of the indoor area information is collected and map modeled to generate an indoor area map, key positions are identified based on the indoor area map, and a set of indoor area key positions is obtained; a positioning requirement target is obtained, and a multi-source positioning technology is selected according to the positioning requirement target; sensor parameters of the indoor area key position set are analyzed in turn according to the multi-source positioning technology to obtain a sensor deployment parameter set; a positioning system is deployed for the indoor area key position set based on the sensor deployment parameter set to obtain the indoor positioning sensor network.

[0087] Furthermore, the server is also used to implement the following functions:

[0088] According to the indoor positioning sensor network, a multi-source indoor positioning sensor set is determined; each asset information in the list of assets to be managed is encoded and identified to obtain an asset identification code, and the asset identification code is written into the positioning installation tag; the multi-source indoor positioning sensor set is used to perform position interaction with the positioning installation tags of each asset information to obtain a multi-sensor positioning interaction data stream; the multi-sensor positioning interaction data stream is diverted by device identification according to the asset identification code to obtain the asset indoor positioning sensor data stream.

[0089] Furthermore, the server is also used to implement the following functions:

[0090] The asset indoor positioning sensor data stream is wirelessly transmitted to a data processing center for preprocessing and analysis using a wireless communication link to obtain a data preprocessing step; the asset indoor positioning sensor data stream is preprocessed based on the data preprocessing step to obtain a standard asset indoor positioning sensor data stream; characteristics analysis is performed on each positioning sensor in the multi-source indoor positioning sensor set to obtain a positioning sensor characteristic parameter set; position fusion processing is performed on the standard asset indoor positioning sensor data stream based on the positioning sensor characteristic parameter set to determine the asset synchronization position information.

[0091] Furthermore, the server is also used to implement the following functions:

[0092] Perform accuracy verification analysis on each positioning sensor in the multi-source indoor positioning sensor set to obtain a multi-source sensor accuracy factor set; select a matching position fusion algorithm set based on the positioning sensor characteristic parameter set; perform a positioning test on the matching position fusion algorithm set, and when the positioning test result does not meet the preset accuracy rate, initialize the particle swarm parameters, and the particle swarm parameters include particle position and particle velocity; define a fitness loss function to evaluate and iteratively update the particle swarm parameters until the preset iteration conditions are met, and determine the particle with the largest fitness as the optimal parameter solution; optimize the matching position fusion algorithm set based on the optimal parameter solution to obtain a position fusion optimization algorithm set; perform positioning fusion on the indoor positioning sensor data streams of the standard assets based on the position fusion optimization algorithm set to obtain a multi-algorithm fusion positioning set; perform weighted fusion processing on the multi-algorithm fusion positioning set based on the multi-source sensor accuracy factor set to determine the asset synchronization position information.

[0093] Furthermore, the server is also used to implement the following functions:

[0094] If the target asset is in a moving state, monitor and obtain the asset movement speed change information; based on the asset movement speed change information, construct an asset movement prediction model, and perform movement state prediction based on the asset movement prediction model to obtain the asset predicted movement state; according to the asset predicted movement state, obtain the position real-time offset parameter, and perform position update correction on the asset synchronization position information based on the position real-time offset parameter.

[0095] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0096] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0097] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. The asset twin management method integrating indoor positioning is characterized by: The method comprises: Obtain a list of assets to be managed, classify and integrate the asset information in the list of assets to be managed, and obtain a set of asset attribute parameters; Performing twin simulation on the asset attribute parameter set to establish an asset digital twin model; Acquire indoor area information of the list of assets to be managed, perform key position identification and positioning system deployment on the indoor area information, and obtain an indoor positioning sensor network; The indoor positioning sensor network interacts with the positioning installation tags of each asset information to obtain the asset indoor positioning sensor data stream; Based on the indoor positioning sensor network, the asset indoor positioning sensor data stream is fused and processed to determine the asset synchronization position information; The asset status of the asset digital twin model is updated based on the asset synchronization position information to obtain the asset update digital twin model, and the asset twin management is performed through the asset update digital twin model.

2. The asset twin management method integrating indoor positioning according to claim 1, characterized in that: The asset information in the list of assets to be managed is classified and integrated to obtain a set of asset attribute parameters, including: According to the asset management standard, asset management attribute factor information is obtained, wherein the asset management attribute factor information includes basic attributes, physical attributes, value attributes, usage attributes, and location attributes; Performing classification content analysis on each attribute factor in the asset management attribute factor information in turn to obtain an asset management attribute factor content set; Performing management record call on each asset information in the list of assets to be managed to obtain an asset management record data set; The asset management record data set is attribute-classified and integrated based on the asset management attribute factor content set to obtain the asset attribute parameter set.

3. The asset twin management method integrating indoor positioning as claimed in claim 1, characterized in that: The step of identifying key positions of the indoor area information and deploying a positioning system to obtain an indoor positioning sensor network includes: Collecting distribution information of the indoor area and performing map modeling to generate an indoor area map, identifying key locations based on the indoor area map, and obtaining a set of key locations of the indoor area; Obtaining a positioning requirement target, and selecting a multi-source positioning technology according to the positioning requirement target; According to the multi-source positioning technology, sensor parameters are analyzed for the key positions of the indoor area in sequence to obtain a sensor deployment parameter set; A positioning system is deployed on the indoor area key location set based on the sensor deployment parameter set to obtain the indoor positioning sensor network.

4. The asset twin management method integrating indoor positioning as claimed in claim 1, characterized in that: The method of performing position interaction with the positioning installation tags of each asset information through the indoor positioning sensor network to obtain the asset indoor positioning sensor data stream includes: Determining a multi-source indoor positioning sensor set according to the indoor positioning sensor network; Encoding and identifying each asset information in the list of assets to be managed to obtain an asset identification code, and writing the asset identification code into the positioning installation tag; The multi-source indoor positioning sensor set is used to perform position interaction with the positioning installation tags of each asset information to obtain a multi-sensor positioning interaction data stream; The multi-sensor positioning interactive data stream is separated by device identification according to the asset identification code to obtain the asset indoor positioning sensor data stream.

5. The asset twin management method integrating indoor positioning as claimed in claim 4, characterized in that: The determining of the asset synchronization location information includes: Using a wireless communication link to wirelessly transmit the asset indoor positioning sensor data stream to a data processing center for preprocessing and analysis, obtaining a data preprocessing step; Preprocessing the asset indoor positioning sensor data stream based on the data preprocessing step to obtain a standard asset indoor positioning sensor data stream; Performing characteristic analysis on each positioning sensor in the multi-source indoor positioning sensor set to obtain a positioning sensor characteristic parameter set; Based on the positioning sensor characteristic parameter set, position fusion processing is performed on the standard asset indoor positioning sensor data stream to determine the asset synchronization position information.

6. The asset twin management method integrating indoor positioning as claimed in claim 5, characterized in that: The performing position fusion processing on the standard asset indoor positioning sensor data stream based on the positioning sensor characteristic parameter set to determine the asset synchronization position information includes: Performing accuracy verification analysis on each positioning sensor in the multi-source indoor positioning sensor set to obtain a multi-source sensor precision factor set; According to the positioning sensor characteristic parameter set, selecting a matching position fusion algorithm set; Performing a positioning test on the matching position fusion algorithm set, and when the positioning test result does not meet the preset accuracy, initializing the particle swarm parameters, the particle swarm parameters including particle position and particle velocity; Define a fitness loss function to evaluate and iteratively update the particle swarm parameters until a preset iteration condition is met, and optimize and determine the particle with the largest fitness as the optimal parameter solution; Optimizing the matching position fusion algorithm set based on the optimal parameter solution to obtain a position fusion optimization algorithm set; Based on the position fusion optimization algorithm set, the standard asset indoor positioning sensor data streams are respectively positioned and fused to obtain a multi-algorithm fusion positioning set; The multi-algorithm fusion positioning set is weightedly fused based on the multi-source sensor precision factor set to determine the asset synchronization position information.

7. The asset twin management method integrating indoor positioning as claimed in claim 1, characterized in that: The method comprises: If the target asset is in a moving state, monitor and obtain information on changes in the asset's moving speed; Based on the asset movement speed change information, an asset movement prediction model is constructed, and a movement state prediction is performed based on the asset movement prediction model to obtain an asset predicted movement state; According to the predicted movement state of the asset, a real-time position offset parameter is obtained, and based on the real-time position offset parameter, a position update correction is performed on the asset synchronization position information.

8. Asset twin management server integrating indoor positioning, characterized in that: The server implements the asset twin management method integrating indoor positioning according to any one of claims 1 to 7, and the server includes: An attribute classification integration module, wherein the attribute classification integration module obtains a list of assets to be managed, classifies and integrates the asset information in the list of assets to be managed, and obtains an asset attribute parameter set; A twin simulation module, wherein the twin simulation module performs twin simulation on the asset attribute parameter set to establish an asset digital twin model; A sensor network establishment module, wherein the sensor network establishment module obtains indoor area information of the list of assets to be managed, performs key position identification and positioning system deployment on the indoor area information, and obtains an indoor positioning sensor network; A location interaction module, wherein the location interaction module performs location interaction with the location installation tags of each asset information through the indoor positioning sensor network to obtain an asset indoor positioning sensor data stream; A fusion processing module, wherein the fusion processing module performs fusion processing on the asset indoor positioning sensor data stream based on the indoor positioning sensor network to determine the asset synchronization position information; An asset twin management module, wherein the asset twin management module updates the asset status of the asset digital twin model based on the asset synchronization position information, obtains the asset update digital twin model, and performs asset twin management through the asset update digital twin model.

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