Fixed asset checking method and device and medium

Abstract

The invention provides a fixed asset checking method and device and a medium, and relates to the technical field of data. The method comprises the following steps: acquiring first identification fixed asset information of a first fixed asset in a first range acquired by a mobile terminal, and second identification fixed asset information of the first fixed asset and a second fixed asset in a second range acquired by a fixed terminal; and obtaining first matching information of the first identification fixed asset information of the first fixed asset and the second identification fixed asset information, and calibrating the second identification fixed asset information of the second fixed asset according to the first matching information. The fixed asset information is collected through the mobile terminal and the fixed terminal, relatively accurate information is obtained by using the mobility performance of the mobile terminal so as to calibrate the information in a larger range obtained by the fixed terminal, and the fixed asset checking efficiency is improved while the fixed asset checking accuracy is ensured.

Description

Technical Field

[0001] The present application relates at least to the field of data technology, and in particular to a method, device and medium for inventorying fixed assets. Background Art

[0002] The current methods for fixed asset inventory include manual handheld mobile devices to read fixed asset information and fixed asset identification methods using fixed cameras. Mobile devices read fixed asset information more accurately, but the identification process is labor-intensive. Fixed asset identification methods such as fixed cameras provide rough and inaccurate information. Summary of the Invention

[0003] In response to the above-mentioned shortcomings, the present application provides a fixed asset inventory method, device and medium to solve the following technical problem: how to efficiently and accurately identify fixed asset information.

[0004] In a first aspect, the present application provides a method for inventorying fixed assets, the method comprising:

[0005] Acquire first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of the first fixed asset and the second fixed asset within a second range collected by a fixed terminal;

[0006] First matching information of first identification fixed asset information and second identification fixed asset information of the first fixed asset is obtained, and second identification fixed asset information of the second fixed asset is calibrated according to the first matching information.

[0007] Furthermore, obtaining first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of a first fixed asset and a second fixed asset within a second range collected by a fixed terminal, specifically includes:

[0008] Obtain a Building Information Model (BIM) of the building where the fixed asset is located, discretize the BIM into three-dimensional grid units, and obtain the grid coordinates of each three-dimensional grid unit;

[0009] Acquire first distinguishing identification information and first positioning information of a first fixed asset within a first three-dimensional grid unit collected by a mobile augmented reality (AR) terminal, wherein the distinguishing identification information includes an identifier and / or attribute for distinguishing the fixed asset, and the first positioning information corresponds to a first grid coordinate of the first three-dimensional grid unit;

[0010] Second distinguishing identification information and second positioning information of the first fixed asset and the second fixed asset within a second range collected by the fixed terminal are obtained, wherein the second range includes and is larger than the first three-dimensional grid unit, and the second positioning information includes the distance between the second fixed asset and the first fixed asset.

[0011] Furthermore, obtaining first matching information of first identification fixed asset information of the first fixed asset and second identification fixed asset information, and calibrating second identification fixed asset information of the second fixed asset according to the first matching information specifically includes:

[0012] Matching the same first distinguishing identification information and the second distinguishing identification information to obtain second positioning information of the first fixed asset;

[0013] Obtain a second grid coordinate corresponding to the second fixed asset according to the first grid coordinate and the distance between the second fixed asset and the first fixed asset.

[0014] Further, wherein:

[0015] The distinguishing identification information includes radio frequency identification (RFID) information and visual tag identification information, the positioning information includes ultra-wideband (UWB) positioning information, the RFID information includes the identification and attribute information of the fixed assets, the attribute information includes the equipment model, responsible person, depreciation or scrapping information, the visual tag identification information includes the identification of the fixed assets, and the second positioning information includes the distance between the visual tag of the second fixed asset and the first fixed asset.

[0016] Furthermore, the method further comprises:

[0017] Obtaining an identification mapping, the identification mapping including a mapping between the first distinguishing identification information and the first three-dimensional grid unit and a mapping between the second distinguishing identification information of the second fixed asset and the second three-dimensional grid unit corresponding to the second grid coordinates;

[0018] Obtain record mapping, which includes mapping of the latest recorded fixed asset information in the asset database to the three-dimensional grid cells of the BIM;

[0019] Compare the differences between the identification mapping and the recorded mapping of the same 3D grid cells, and analyze the root causes of the differences based on the historical fixed asset information in the asset database.

[0020] Furthermore, obtaining the record mapping includes:

[0021] A unique code is bound to each three-dimensional grid unit, and each three-dimensional grid unit has the same size;

[0022] Obtain the latest recorded fixed asset information in the asset database, where the recorded fixed asset information includes the recorded location coordinates, recorded asset identifier, and recorded asset attribute information of the fixed asset;

[0023] A record mapping relationship between fixed assets and three-dimensional grid units is established based on the latest recorded location coordinates, and the recorded asset identification and recorded asset attribute information are mapped in the three-dimensional grid unit corresponding to the BIM.

[0024] Furthermore, the method further comprises:

[0025] Obtain all fixed assets to be counted and their corresponding fixed terminals;

[0026] For each fixed terminal, at least one first three-dimensional grid unit having at least one fixed asset is selected;

[0027] generating an optimal movement path for the mobile AR terminal within the building where the fixed asset is located based on positions of the plurality of first three-dimensional grid cells in the BIM;

[0028] The mobile AR terminal moves within the building where the fixed asset is located according to the optimal moving path to collect first distinguishing identification information and first positioning information of the first fixed asset within the first three-dimensional grid unit.

[0029] Furthermore, the method specifically includes, by the edge gateway:

[0030] An ant colony algorithm is set to obtain an optimal movement path, a mobile AR terminal is connected to transmit the optimal movement path and a recorded mapping of the first three-dimensional grid unit to the mobile AR terminal, and first distinguishing identification information and first positioning information sent by the mobile AR terminal are received, a fixed terminal is connected to receive second distinguishing identification information and second positioning information sent by the fixed terminal, and recognition mapping is implemented;

[0031] Connect to the asset database to obtain recorded fixed asset information, connect to the BIM model library to obtain the BIM model of the building where the fixed assets are located, discretize the BIM model and map the latest recorded fixed asset information to obtain three-dimensional grid units and record mappings, set up an inference model to obtain the differences and root causes of the differences between the identification mapping and the record mapping, and import the obtained differences and root causes of the differences into the asset database for recording.

[0032] In a second aspect, the present application provides a fixed asset inventory device, the device comprising:

[0033] an information collection unit, configured to obtain first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of the first fixed asset and the second fixed asset within a second range collected by a fixed terminal;

[0034] The information calibration unit is connected to the information acquisition unit and is used to obtain first matching information of the first fixed asset identification information and the second fixed asset identification information of the first fixed asset, and calibrate the second fixed asset identification information of the second fixed asset according to the first matching information.

[0035] In a third aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the fixed asset inventory method as described above is implemented.

[0036] The present application provides a fixed asset inventory method, device and medium, which respectively collect fixed asset information through a mobile terminal and a fixed terminal, utilize the mobility of the mobile terminal to obtain relatively accurate information, and calibrate the information within a larger range obtained by the fixed terminal, thereby ensuring the accuracy of the fixed asset inventory while improving the efficiency of the fixed asset inventory. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart of a fixed asset inventory method according to an embodiment of the present application;

[0038] Figure 2 This is a structural diagram of a fixed asset inventory device according to an embodiment of the present application;

[0039] Figure 3 This is an architectural diagram of a fixed asset inventory system according to an embodiment of the present application;

[0040] Figure 4 is a flow chart of another fixed asset inventory method according to an embodiment of the present application;

[0041] Figure 5 This is an architectural diagram of a terminal device according to an embodiment of the present application;

[0042] Figure 6 This is a flow chart of a method for on-site dynamic inspection of fixed assets according to an embodiment of the present application;

[0043] Figure 7 This is a flow chart of a method for multi-asset inventory across computer rooms according to an embodiment of the present application;

[0044] Figure 8 This is a flow chart of a method for asset inventory based on tag number positioning according to an embodiment of the present application;

[0045] Figure 9 This is a flowchart of a specific asset retrieval and inventory method according to an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the technical solution of the present application, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0047] It should be understood that the specific embodiments and drawings described herein are only used to explain the present application, rather than to limit the present application.

[0048] It can be understood that, in the absence of conflict, the various embodiments and features in the embodiments of the present application can be combined with each other.

[0049] It will be understood that, for the sake of ease of description, the drawings of this application only show the parts related to this application, while the parts not related to this application are not shown in the drawings.

[0050] It can be understood that each module and unit involved in the embodiments of the present application may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple modules and units may be integrated into one physical structure.

[0051] It is understood that, in the absence of conflict, the functions and steps marked in the flowcharts and block diagrams of the present application may occur in an order different from that marked in the drawings.

[0052] It is understood that the flowcharts and block diagrams of the present application illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present application. Each box in the flowchart or block diagram may represent a module, unit, program segment, or code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based device that implements the specified functions, or by a combination of hardware and computer instructions.

[0053] It can be understood that the modules and units involved in the embodiments of the present application can be implemented by software or hardware, for example, the modules and units can be located in a processor.

[0054] Example 1:

[0055] like Figure 1 As shown, the present application provides a fixed asset inventory method, the method comprising:

[0056] S1. Acquire first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of the first fixed asset and the second fixed asset within a second range collected by a fixed terminal;

[0057] S2. Obtain first matching information of first identification fixed asset information and second identification fixed asset information of the first fixed asset, and calibrate second identification fixed asset information of the second fixed asset according to the first matching information.

[0058] In this embodiment, the method collects fixed asset information through mobile terminals and fixed terminals respectively, and uses the mobility of mobile terminals to obtain relatively accurate information to calibrate the information obtained by fixed terminals in a wider range, thereby ensuring the accuracy of fixed asset inventory and improving the efficiency of fixed asset inventory. Figure 1 The method shown is applied to Figure 2 The device shown.

[0059] More specifically, this embodiment provides a method for inventorying fixed assets. Inventory of fixed assets is the core work of verifying the consistency between physical assets and records in the management system. Its functions include: verification of consistency between accounts and actual assets: ensuring that the physical existence, location, and status of the equipment are consistent with the management system; full life cycle management: providing data support for procurement, depreciation, and scrapping decisions; risk control: timely detection of abnormal assets that are lost, misplaced, or have inconsistent information. The method achieves the following three goals: through centimeter-level mapping of BIM (Building Information Modeling) models and asset databases, precise positioning in three-dimensional space is achieved; root cause analysis of differences based on inference large models provides decision support; dynamic path planning algorithms optimize inspection efficiency and reduce ineffective movement.

[0060] In one embodiment, S1, acquiring first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of the first fixed asset and the second fixed asset within a second range collected by a fixed terminal, specifically includes:

[0061] Obtain a Building Information Model (BIM) of the building where the fixed asset is located, discretize the BIM into three-dimensional grid units, and obtain the grid coordinates of each three-dimensional grid unit;

[0062] Acquire first distinguishing identification information and first positioning information of a first fixed asset within a first three-dimensional grid unit collected by a mobile augmented reality (AR) terminal, wherein the distinguishing identification information includes an identifier and / or attribute for distinguishing the fixed asset, and the first positioning information corresponds to a first grid coordinate of the first three-dimensional grid unit;

[0063] Second distinguishing identification information and second positioning information of the first fixed asset and the second fixed asset within a second range collected by the fixed terminal are obtained, wherein the second range includes and is larger than the first three-dimensional grid unit, and the second positioning information includes the distance between the second fixed asset and the first fixed asset.

[0064] In this embodiment, a technology for intelligent inventory of fixed assets in data centers and communication rooms that integrates building information modeling (BIM), augmented reality (AR) and reasoning big models is provided, which includes methods, systems, hardware devices and computer-readable storage media. The system architecture Figure 3 As shown, the information collected by the mobile terminal and the fixed terminal includes information for distinguishing fixed assets and information indicating the location of fixed assets, so as to obtain the different locations of different fixed assets in the building.

[0065] In one embodiment, S2, obtaining first matching information between first identifying fixed asset information of a first fixed asset and second identifying fixed asset information, and calibrating second identifying fixed asset information of a second fixed asset according to the first matching information, specifically includes:

[0066] Matching the same first distinguishing identification information and the second distinguishing identification information to obtain second positioning information of the first fixed asset;

[0067] Obtain a second grid coordinate corresponding to the second fixed asset according to the first grid coordinate and the distance between the second fixed asset and the first fixed asset.

[0068] In this embodiment, the method can at least achieve positioning calibration, including calibrating the positioning information of assets within a larger range collected by the fixed terminal by comparing the accurate asset positioning information collected by the mobile AR terminal.

[0069] In one embodiment, wherein:

[0070] The distinguishing identification information includes radio frequency identification (RFID) information and visual tag identification information, the positioning information includes ultra-wideband (UWB) positioning information, the RFID information includes the identification and attribute information of the fixed assets, the attribute information includes the equipment model, responsible person, depreciation or scrapping information, the visual tag identification information includes the identification of the fixed assets, and the second positioning information includes the distance between the visual tag of the second fixed asset and the first fixed asset.

[0071] In this embodiment, the current mainstream asset inventory technologies include: manual inventory: relying on paper lists for item-by-item verification, which is inefficient and has a high error rate (>5%); barcode / RFID (Radio Frequency Identification) scanning technology: using a handheld device to scan the tag, record the asset ID (identity) and link it to a database. This is suitable for simple environments where the tag is visible, but it cannot locate the spatial position of the device and cannot determine whether the device is in the correct location; image recognition technology: using a camera to identify the device appearance and combine it with OCR (Optical Character Recognition) technology to extract tag information. This is suitable for open environments with sufficient light, but the recognition rate for obscured devices is low. In view of this, this embodiment combines optical recognition and RFID recognition, and connects the optical recognition result with the positioning recognition result and the RFID recognition result.

[0072] In one embodiment, the method further comprises:

[0073] Obtaining an identification mapping, the identification mapping including a mapping between the first distinguishing identification information and the first three-dimensional grid unit and a mapping between the second distinguishing identification information of the second fixed asset and the second three-dimensional grid unit corresponding to the second grid coordinates;

[0074] Obtain record mapping, which includes mapping of the latest recorded fixed asset information in the asset database to the three-dimensional grid cells of the BIM;

[0075] Compare the differences between the identification mapping and the recorded mapping of the same 3D grid cells, and analyze the root causes of the differences based on the historical fixed asset information in the asset database.

[0076] In this embodiment, by Figure 3 As shown in the figure, the mapping relationship between recorded asset data and BIM models is obtained from the asset database and the BIM model database. By comparing the recognition results obtained based on the AR terminal, the asset information that is inconsistent with the record and the actual can be obtained, and the cause of the data inconsistency can be determined by analyzing historical data.

[0077] In one embodiment, obtaining a record mapping specifically includes:

[0078] A unique code is bound to each three-dimensional grid unit, and each three-dimensional grid unit has the same size;

[0079] Obtain the latest recorded fixed asset information in the asset database, where the recorded fixed asset information includes the recorded location coordinates, recorded asset identifier, and recorded asset attribute information of the fixed asset;

[0080] A record mapping relationship between fixed assets and three-dimensional grid units is established based on the latest recorded location coordinates, and the recorded asset identification and recorded asset attribute information are mapped in the three-dimensional grid unit corresponding to the BIM.

[0081] In this embodiment, if Figure 4 As shown, a specific inventory method process for on-site dynamic inspection using mobile AR equipment is as follows:

[0082] Step A1: 3D spatial modeling and data mapping

[0083] A11. BIM model processing:

[0084] The computer room BIM model is discretized into grid units of 0.5m×0.5m×0.5m. Each unit is bound to a unique code (such as GX05-Y12-Z03). The code of each grid unit corresponds to the coordinate range of the physical space (for example, 0.5m×0.5m×0.5m), which is used to clarify the spatial ownership of assets.

[0085] A bidirectional mapping table is established between the asset database and the BIM grid. The bidirectional mapping table binds the asset information in the asset database (including full information such as asset ID, model, responsible person, depreciation cost, etc.) with the discretized grid units in the BIM model (such as GX05-Y12-Z03), thereby achieving centimeter-level location recording of assets in the computer room.

[0086] A12. Dynamic update mechanism:

[0087] When the location or information of a device changes (including device relocation, model updates, changes in responsible personnel, depreciation status adjustments, and equipment retirement), the edge gateway synchronizes the BIM model with the asset database in real time. When device information or location changes, the edge gateway immediately updates the bidirectional mapping table and synchronizes it with the asset database and BIM model. The edge gateway is a local server deployed inside or near the computer room to ensure low-latency communication. It uses an industrial-grade edge computing gateway (such as the Huawei Atlas500 or Advantech ARK-3500) and supports BIM model slice preloading and multi-terminal collaboration.

[0088] Step A2: Multimodal data collection and comparison

[0089] A21, RFID group reading and visual recognition:

[0090] RFID cluster readers scan RFID tags on devices within an 8-meter radius (capturing 200 tags per second); the vision module recognizes the visual tag data. Using an Impinj R720 reader / writer, which supports ultra-high-frequency (UHF) RFID, installed high on the ceiling or wall of the equipment room, it covers an 8-meter radius. Unlike RFID modules in AR, it provides wide-area coverage, while mobile AR terminals fill in blind spots. Both provide real-time data synchronization via an edge gateway. A wide-angle camera (such as the Sony IMX586 sensor) combined with a deep learning model (such as YOLOv5) identifies devices behind the cabinet using image stitching and occlusion segmentation algorithms. The vision module, integrated into the terminal, works in conjunction with the RFID cluster reader, covering static RFID blind spots as the terminal moves.

[0091] A22, Real-time difference detection:

[0092] The system automatically compares the scan data with the asset platform records and marks the following types of differences: position offset (>0.5m), information mismatch (model / responsible person conflict), and asset loss (not detected). The UWB (Ultra Wide Band) positioning unit (such as the Decawave DW1000 chip) is embedded in the AR terminal to provide centimeter-level positioning accuracy. The system determines whether the offset exceeds 0.5m by comparing the actual coordinates of the device (UWB positioning) with the BIM mapping coordinates. The system automatically matches the device model and responsible person fields of RFID / visual recognition with the asset database records, and marks conflicts as "information mismatch". If the device is not identified by the RFID / visual module within the expected grid and is not synchronized to other areas, it is judged as "asset loss".

[0093] Step A3: Gap analysis and report generation

[0094] A31. Root cause analysis of the large inference model:

[0095] Input difference data and historical records, and use the Graph Attention Network (GAT) to extract the correlation features between devices. Output the probability distribution of the root cause of the difference (such as "human error: 65%"). The types of correlation features are: physical proximity: the spatial position relationship of the equipment in the BIM model (such as adjacent grid cells); functional dependency: the power, network or data link dependency between devices (such as the server relying on UPS power supply); historical operation association: inventory records of multiple devices in the same time period. Extraction method: Construct a device relationship graph with devices as nodes and edges representing association relationships (such as dependency, proximity, and operation association). Use GAT to automatically learn the feature representation of nodes (equipment) and capture implicit associations.

[0096] How GAT works: Input layer: Initial feature vector for each node (such as device type, status, and location coordinates). Attention coefficient calculation: Attention weights are calculated for each pair of adjacent nodes. Feature aggregation: Weighted aggregation of neighboring node features generates a new representation for the current node. Multi-layer stacking: Captures correlation patterns at different levels through multi-head attention. Training process: Uses historical data to supervise training using a cross-entropy loss function to maximize the predicted probability of the correct root cause category. Feature fusion: Concatenates the device feature vector output by GAT with the global context (such as environmental data). Fully connected layer: Maps the fused features to the root cause category space through a fully connected network. Softmax normalization: Converts the output to a probability distribution. The model learns the characteristic patterns of different root causes from the training data. GAT dynamically focuses on key correlated features to enhance its ability to distinguish root causes. A discrepancy root cause refers to the underlying cause of the discrepancy between asset data and records. For example, if devices A and B are power dependent, and device B has a recent maintenance record, the system may infer that the discrepancy root cause is "a failure in device B affected device A" (with a 65% probability).

[0097] A32. Generate asset inventory report:

[0098] Including text reports (list of difference equipment, root cause conclusions, treatment suggestions, etc.), 3D reports (highlighting difference equipment in the BIM model, marking offset direction and conflict fields), etc.

[0099] A33, Difference comparison table:

[0100] Summarize the standard value and actual value. The standard value refers to the preset information recorded in the asset database (such as location coordinates, model, and responsible person), and the actual value refers to the field data collected in real time through the RFID / vision module.

[0101] In one embodiment, the method further comprises:

[0102] Obtain all fixed assets to be counted and their corresponding fixed terminals;

[0103] For each fixed terminal, at least one first three-dimensional grid unit having at least one fixed asset is selected;

[0104] generating an optimal movement path for the mobile AR terminal within the building where the fixed asset is located based on positions of the plurality of first three-dimensional grid cells in the BIM;

[0105] The mobile AR terminal moves within the building where the fixed asset is located according to the optimal moving path to collect first distinguishing identification information and first positioning information of the first fixed asset within the first three-dimensional grid unit.

[0106] In this embodiment, if Figure 4 As shown, the specific method process for remote task driven inventory is as follows:

[0107] Step B1: Retrieval information analysis and task issuance

[0108] B11. Enter search criteria: The user enters the asset tag number, device type (such as "UPS (Uninterruptible Power Supply)"), responsible person, and other query criteria through the web or mobile terminal.

[0109] B12. System analysis and target generation: Search the asset database and generate a list of target devices (such as "all UPS devices on the 3rd floor").

[0110] B13. Call BIM services to obtain the three-dimensional coordinates of equipment and related areas (such as power rooms and air-conditioning rooms).

[0111] Step B2: Intelligent Path Planning

[0112] B21. Global path generation: The computer room / area where the target device is located is set as a graph node, and the optimal path is generated based on the topology graph. The algorithm selection is: Ant Colony Algorithm (convergence iteration number ≤ 50) or Dijkstra Algorithm, and the weight setting is: Distance (60%) + Recognition Efficiency (40%). The distance weight (60%) is used to optimize the total movement distance and reduce the operator's walking time. The recognition efficiency weight (40%) is used to prioritize coverage of high-density asset areas (such as cabinet concentration areas) to avoid repeated scanning. For example, if a path has a short total distance but requires a return scan, and another path is slightly longer but can linearly cover the equipment, the system will choose the latter based on the comprehensive weight.

[0113] B22. Path Delivery to Terminals: The AR terminal receives path instructions and displays a green navigation beam to guide the operator. Path generation combines the following data: a topology map, which defines the connections between nodes (such as computer room entrances and equipment areas) and edges; a BIM model, which provides real-world spatial coordinates and a detailed layout of fixed obstacles (such as walls and cabinets); and real-time obstacle data, which captures temporary obstacle information through sensors or manual input. The AR terminal, pre-installed with the BIM model, uses SLAM (Simultaneous Localization and Mapping) technology for real-time positioning. A navigation beam (green guide line) is superimposed on the 3D BIM map displayed by the AR, dynamically indicating the direction of movement.

[0114] Step B3: On-site confirmation and report generation

[0115] B31. Scan by path: The operator moves along the planned path, and the AR terminal automatically triggers RFID / visual recognition.

[0116] B32. Secondary verification of differences: Focus on checking the target device of remote query to ensure information consistency.

[0117] B33. Generate special report: The report focuses on the difference details of the target device and supports comparative analysis with the original query conditions.

[0118] In one embodiment, the method specifically includes, by the edge gateway:

[0119] An ant colony algorithm is set to obtain an optimal movement path, a mobile AR terminal is connected to transmit the optimal movement path and a recorded mapping of the first three-dimensional grid unit to the mobile AR terminal, and first distinguishing identification information and first positioning information sent by the mobile AR terminal are received, a fixed terminal is connected to receive second distinguishing identification information and second positioning information sent by the fixed terminal, and recognition mapping is implemented;

[0120] Connect to the asset database to obtain recorded fixed asset information, connect to the BIM model library to obtain the BIM model of the building where the fixed assets are located, discretize the BIM model and map the latest recorded fixed asset information to obtain three-dimensional grid units and record mappings, set up an inference model to obtain the differences and root causes of the differences between the identification mapping and the record mapping, and import the obtained differences and root causes of the differences into the asset database for recording.

[0121] In this embodiment, the following can be used Figure 3 In the system architecture shown, the edge gateway connects the asset database and BIM model library of the data layer and the AR terminal. The main computing functions are set on the edge gateway. The method can refer to the process of edge gateway acquiring data and computing, or it can include the acquisition process of AR terminal. That is, the device corresponding to the method provided in this embodiment can be an edge gateway, a system including edge gateway, mobile terminal and fixed terminal. In addition, it can also be as follows Figure 5 As shown, the computing function is integrated into the AR terminal, and the corresponding device can be a mobile terminal. Similarly, the computing function can also be integrated into a fixed terminal, and the corresponding device is a fixed terminal.

[0122] The above hardware device can be specifically implemented as follows:

[0123] Lightweight AR terminal: Core modules: Display module: binocular AR lenses (Microsoft HoloLens 2 compatible), supporting the overlay of 3D models with real-world scenes; Perception module: integrated RFID array (Impinj R200 RFID reader / writer compatible), wide-angle camera (Intel RealSense D455 depth camera compatible), and UWB (Ultra Wide Band) positioning unit; Computing module: edge inference chip for real-time data processing. It can perform tasks such as multimodal data fusion, real-time target detection, positioning calibration, dynamic path planning, and root cause reasoning.

[0124] Edge Gateway: Function: Preload computer room BIM model slices (divide the complete computer room BIM model into multiple sub-model blocks according to spatial grid units or functional areas). Each slice corresponds to a discretized three-dimensional grid unit (such as 0.5m×0.5m×0.5m grid GX05-Y12-Z03), and contains the asset information, three-dimensional model data and topological relationships within the grid unit, and supports calling three-dimensional data in offline state. When the computer room network is interrupted or the cloud service is unavailable, the inventory task can still be continued through the preloaded BIM model slices to ensure business continuity. Coordinate the collaborative work of multiple terminals to ensure the synchronization of inventory data across computer rooms. Multiple operators use multiple AR terminals to collaboratively perform tasks, and the edge gateway and central management platform synchronize data and distribute tasks.

[0125] The computer-readable storage medium contains the following data: BIM difference rendering rule library: defines color, dynamic effects and annotation logic; path planning topology map: computer room access path weights and obstacle history records; asset feature library: equipment three-dimensional model (GLB format).

[0126] The method is further described below with reference to some more specific implementation examples and accompanying drawings:

[0127] Implementation Example 1: Figure 6 The figure shows a real-time on-site inventory of fixed assets in the communications room, including the following process: the operator enters the room, the AR terminal loads the BIM model and locates the grid GX00-Y00 (inspection target); the RFID group reader scans the surrounding equipment, and the vision module identifies the obstructed cabinet. The RFID module has two parts, one of which is placed high on the ceiling and wall to provide wide-area coverage. The RFID module is also placed in the AR to fill in the blind spot. The two synchronize data in real time through the edge gateway; the system marks two devices with position offset (offset 0.8m), generates a report, and synchronizes it to the management platform.

[0128] Implementation Example 2: Figure 7As shown, remote query and inventory of assets are carried out to achieve cross-computer room path planning. Scenario: 4 target devices distributed in the oil engine room (A), communication room (B), battery room (C), and air conditioning room (D) need to be remotely queried and inventoried; retrieval and analysis: a list of device tag numbers is input, and the system parses the target locations as the four computer rooms A, B, C, and D; path planning: the four computer room entrances are set as graph nodes, and the optimal path is generated based on the ant colony algorithm: A→D→C→B (the total distance is reduced by 38%). The AR terminal displays the navigation beam and avoids temporary obstacles (such as corridors under maintenance) in real time. Obstacles can be detected by sensors, and operation and maintenance personnel can manually mark temporary obstacle areas through the management platform; on-site execution: the operator scans the target devices in sequence along the path, and the system automatically verifies the consistency of the information; report generation: the output inventory report includes path efficiency analysis (saving 42% time) and equipment difference details, quantifying the efficiency improvement of the technical solution for subsequent cost-benefit analysis, and can also be used to optimize inspection strategies, such as adjusting path weights.

[0129] Implementation Example 3: Figure 8 As shown, remote query locates the fixed assets to be counted based on the tag number. The technical process is as follows: enter the tag number "xxxxxx-xxxxxxxxx", the system resolves the target to be located in the G7 grid of the B2F power room; a navigation path is generated, and the operator scans the equipment upon arrival and finds a position offset of 0.8m; a report notes the offset details and triggers an alarm work order: the operator is responsible for data collection and review, and the offset correction is assigned to a dedicated person after the management platform generates a work order.

[0130] Implementation Example 4: Figure 9 As shown, for specific equipment retrieval, such as a UPS cluster, the technical process is as follows: voice input "show all UPS on the 3rd floor" is used, the system retrieves 12 devices and generates a distribution map; path planning avoids high-density obstacle areas, and the operator completes the scan according to the navigation. It mainly combines on-site dynamic inspections with remote task driving. The operator needs to complete the on-site verification according to the AR navigation to ensure the authenticity and accuracy of the data; and the report statistics the UPS equipment asset inventory.

[0131] This embodiment achieves the following effects: centimeter-level mapping technology of BIM and asset database: through gridded BIM model and dynamic update mechanism, precise alignment of physical space and information space is achieved (error ≤ 0.3m); multimodal fusion recognition strategy: the collaborative mechanism of RFID group reading and visual assistance, the recognition rate in complex environments is increased to 92%; difference analysis driven by large inference model: root cause reasoning model based on graph neural network, with an accuracy rate of > 90%; dynamic path planning algorithm: integrating global topology optimization and local obstacle avoidance, reducing invalid movement by 40%.

[0132] Example 2:

[0133] like Figure 2As shown, the present application provides a fixed asset inventory device, the device comprising:

[0134] An information collection unit 1 is configured to obtain first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of the first fixed asset and the second fixed asset within a second range collected by a fixed terminal;

[0135] The information calibration unit 2 is connected to the information collection unit 1 and is used to obtain first matching information of the first fixed asset identification information and the second fixed asset identification information of the first fixed asset, and calibrate the second fixed asset identification information of the second fixed asset according to the first matching information.

[0136] In this embodiment, a fixed asset inventory device may specifically be an edge gateway, a mobile AR terminal, a fixed terminal, or a system including the three.

[0137] In one embodiment, the information collection unit 1 specifically includes:

[0138] A BIM information acquisition unit is used to obtain the building information model (BIM) of the building where the fixed asset is located, discretize the BIM into three-dimensional grid units, and obtain the grid coordinates of each three-dimensional grid unit;

[0139] a mobile information collection unit, connected to the BIM information collection unit, and configured to obtain first distinguishing identification information and first positioning information of a first fixed asset within a first three-dimensional grid unit collected by the mobile augmented reality (AR) terminal, wherein the distinguishing identification information includes an identifier and / or attribute for distinguishing the fixed asset, and the first positioning information corresponds to a first grid coordinate of the first three-dimensional grid unit;

[0140] The fixed information collection unit is used to obtain second distinguishing identification information and second positioning information of the first fixed asset and the second fixed asset within a second range collected by the fixed terminal, wherein the second range includes and is larger than the first three-dimensional grid unit, and the second positioning information includes the distance between the second fixed asset and the first fixed asset.

[0141] In one embodiment, the information calibration unit 2 specifically includes:

[0142] a matching unit, configured to match the same first distinguishing identification information and the same second distinguishing identification information to obtain second positioning information of the first fixed asset;

[0143] The calibration unit is connected to the matching unit and is used to obtain the second grid coordinates corresponding to the second fixed asset according to the first grid coordinates and the distance between the second fixed asset and the first fixed asset.

[0144] In one embodiment, wherein:

[0145] The distinguishing identification information includes radio frequency identification (RFID) information and visual tag identification information, the positioning information includes ultra-wideband (UWB) positioning information, the RFID information includes the identification and attribute information of the fixed assets, the attribute information includes the equipment model, responsible person, depreciation or scrapping information, the visual tag identification information includes the identification of the fixed assets, and the second positioning information includes the distance between the visual tag of the second fixed asset and the first fixed asset.

[0146] In one embodiment, the device further comprises:

[0147] an identification mapping unit connected to the information calibration unit 2 and configured to obtain an identification mapping, the identification mapping including a mapping between the first distinguishing identification information and the first three-dimensional grid unit and between the second distinguishing identification information of the second fixed asset and the second three-dimensional grid unit corresponding to the second grid coordinate;

[0148] A record mapping unit, used to obtain a record mapping, the record mapping including mapping of the latest recorded fixed asset information in the asset database and the three-dimensional grid unit of the BIM;

[0149] The difference analysis unit is connected to the identification mapping unit and the record mapping unit, and is used to compare the differences between the identification mapping and the record mapping of the same three-dimensional grid unit, and analyze the root causes of the differences based on the historical fixed asset information in the asset database.

[0150] In one embodiment, the record mapping unit specifically includes:

[0151] A grid coding unit, used to bind a unique code to each three-dimensional grid unit, and each three-dimensional grid unit has the same size;

[0152] A record acquisition unit, configured to acquire the latest recorded fixed asset information in the asset database, wherein the recorded fixed asset information includes the recorded location coordinates of the fixed asset, the recorded asset identifier, and the recorded asset attribute information;

[0153] The mapping establishment unit is connected to the grid encoding unit and the record acquisition unit, and is used to establish a record mapping relationship between fixed assets and three-dimensional grid units based on the latest recorded position coordinates, and map the recorded asset identification and recorded asset attribute information into the three-dimensional grid unit corresponding to the BIM.

[0154] In one embodiment, the device further comprises:

[0155] An inventory task acquisition unit is used to acquire all fixed assets to be inventoried and their corresponding fixed terminals;

[0156] a mobile identification point selection unit, connected to the inventory task unit, for selecting at least one first three-dimensional grid unit having at least one fixed asset for each fixed terminal;

[0157] a path optimization unit, connected to the mobile identification point selection unit, for generating an optimal movement path for the mobile AR terminal within the building where the fixed asset is located based on the positions of the plurality of first three-dimensional grid cells in the BIM;

[0158] The mobile collection unit is connected to the path optimization unit and is used for the mobile AR terminal to move within the building where the fixed asset is located according to the optimal moving path to collect first distinguishing identification information and first positioning information of the first fixed asset within the first three-dimensional grid unit.

[0159] In one embodiment, the device is specifically an edge gateway, comprising:

[0160] An acquisition control unit, configured to set an ant colony algorithm to obtain an optimal movement path, connect to a mobile AR terminal to transmit the optimal movement path and a recorded mapping of the first three-dimensional grid unit to the mobile AR terminal, receive first distinguishing identification information and first positioning information sent by the mobile AR terminal, connect to a fixed terminal to receive second distinguishing identification information and second positioning information sent by the fixed terminal, and implement recognition mapping;

[0161] The calibration control unit is used to connect to the asset database to obtain recorded fixed asset information, connect to the BIM model library to obtain the BIM model of the building where the fixed asset is located, discretize the BIM model and map the latest recorded fixed asset information to obtain three-dimensional grid units and record mappings, set up an inference large model to obtain the differences and root causes of the differences between the identification mapping and the record mapping, and import the obtained differences and root causes of the differences into the asset database for recording.

[0162] Example 3:

[0163] Embodiment 3 of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the fixed asset inventory method described in embodiment 1 or the fixed asset inventory device described in embodiment 2 is implemented.

[0164] The computer-readable storage medium includes volatile or non-volatile, removable or non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, computer program elements or other data). Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable read only memory), flash memory or other memory technology, CD-ROM (Compact Disc Read-Only Memory), digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer.

[0165] In addition, the present application may also provide a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the fixed asset inventory method described in Example 1. The computer device may be the fixed asset inventory device described in Example 2.

[0166] The memory is connected to the processor, the memory may be a flash memory, a read-only memory or other memory, and the processor may be a central processing unit or a single-chip microcomputer.

[0167] Embodiments 1-3 of the present application provide a fixed asset inventory method, device, and medium, which respectively collect fixed asset information through a mobile terminal and a fixed terminal, utilize the mobility of the mobile terminal to obtain relatively accurate information, and calibrate the information within a larger range obtained by the fixed terminal, thereby ensuring the accuracy of the fixed asset inventory while improving the efficiency of the fixed asset inventory.

[0168] It is understood that the above embodiments are merely exemplary embodiments for illustrating the principles of the present application, and the present application is not limited thereto. Those skilled in the art may make various modifications and improvements without departing from the spirit and substance of the present application, and such modifications and improvements are also considered to be within the scope of protection of the present application.

Claims

1. A method for inventorying fixed assets, characterized in that: The method comprises: Acquire first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of the first fixed asset and the second fixed asset within a second range collected by a fixed terminal; First matching information of first identification fixed asset information and second identification fixed asset information of the first fixed asset is obtained, and second identification fixed asset information of the second fixed asset is calibrated according to the first matching information.

2. The method according to claim 1, characterized in that Acquiring first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of the first fixed asset and the second fixed asset within a second range collected by a fixed terminal, specifically includes: Obtain a Building Information Model (BIM) of the building where the fixed asset is located, discretize the BIM into three-dimensional grid units, and obtain the grid coordinates of each three-dimensional grid unit; Acquire first distinguishing identification information and first positioning information of a first fixed asset within a first three-dimensional grid unit collected by a mobile augmented reality (AR) terminal, wherein the distinguishing identification information includes an identifier and / or attribute for distinguishing the fixed asset, and the first positioning information corresponds to a first grid coordinate of the first three-dimensional grid unit; Second distinguishing identification information and second positioning information of the first fixed asset and the second fixed asset within a second range collected by the fixed terminal are obtained, wherein the second range includes and is larger than the first three-dimensional grid unit, and the second positioning information includes the distance between the second fixed asset and the first fixed asset.

3. The method according to claim 2, characterized in that Obtaining first matching information of first identifying fixed asset information and second identifying fixed asset information of the first fixed asset, and calibrating second identifying fixed asset information of the second fixed asset according to the first matching information, specifically comprising: Matching the same first distinguishing identification information and the second distinguishing identification information to obtain second positioning information of the first fixed asset; Obtain a second grid coordinate corresponding to the second fixed asset according to the first grid coordinate and the distance between the second fixed asset and the first fixed asset.

4. The method according to claim 3, characterized in that in: The distinguishing identification information includes radio frequency identification (RFID) information and visual tag identification information, the positioning information includes ultra-wideband (UWB) positioning information, the RFID information includes the identification and attribute information of the fixed assets, the attribute information includes the equipment model, responsible person, depreciation or scrapping information, the visual tag identification information includes the identification of the fixed assets, and the second positioning information includes the distance between the visual tag of the second fixed asset and the first fixed asset.

5. The method according to claim 3 or 4, characterized in that The method further comprises: Obtaining an identification mapping, the identification mapping including a mapping between the first distinguishing identification information and the first three-dimensional grid unit and a mapping between the second distinguishing identification information of the second fixed asset and the second three-dimensional grid unit corresponding to the second grid coordinates; Obtain record mapping, which includes mapping of the latest recorded fixed asset information in the asset database to the three-dimensional grid cells of the BIM; Compare the differences between the identification mapping and the recorded mapping of the same 3D grid cells, and analyze the root causes of the differences based on the historical fixed asset information in the asset database.

6. The method according to claim 5, characterized in that Get the record mapping, including: A unique code is bound to each three-dimensional grid unit, and each three-dimensional grid unit has the same size; Obtain the latest recorded fixed asset information in the asset database, where the recorded fixed asset information includes the recorded location coordinates, recorded asset identifier, and recorded asset attribute information of the fixed asset; A record mapping relationship between fixed assets and three-dimensional grid units is established based on the latest recorded location coordinates, and the recorded asset identification and recorded asset attribute information are mapped in the three-dimensional grid unit corresponding to the BIM.

7. The method according to claim 6, characterized in that The method further comprises: Obtain all fixed assets to be counted and their corresponding fixed terminals; For each fixed terminal, at least one first three-dimensional grid unit having at least one fixed asset is selected; generating an optimal movement path for the mobile AR terminal within the building where the fixed asset is located based on positions of the plurality of first three-dimensional grid cells in the BIM; The mobile AR terminal moves within the building where the fixed asset is located according to the optimal moving path to collect first distinguishing identification information and first positioning information of the first fixed asset within the first three-dimensional grid unit.

8. The method according to claim 7, characterized in that The method specifically includes, by the edge gateway: An ant colony algorithm is set to obtain an optimal movement path, a mobile AR terminal is connected to transmit the optimal movement path and a recorded mapping of the first three-dimensional grid unit to the mobile AR terminal, and first distinguishing identification information and first positioning information sent by the mobile AR terminal are received, a fixed terminal is connected to receive second distinguishing identification information and second positioning information sent by the fixed terminal, and recognition mapping is implemented; Connect to the asset database to obtain recorded fixed asset information, connect to the BIM model library to obtain the BIM model of the building where the fixed assets are located, discretize the BIM model and map the latest recorded fixed asset information to obtain three-dimensional grid units and record mappings, set up an inference model to obtain the differences and root causes of the differences between the identification mapping and the record mapping, and import the obtained differences and root causes of the differences into the asset database for recording.

9. A fixed asset inventory device, characterized in that: The device comprises: an information collection unit, configured to obtain first identification fixed asset information of a first fixed asset within a first range collected by a mobile terminal, and second identification fixed asset information of the first fixed asset and the second fixed asset within a second range collected by a fixed terminal; The information calibration unit is connected to the information acquisition unit and is used to obtain first matching information of the first fixed asset identification information and the second fixed asset identification information of the first fixed asset, and calibrate the second fixed asset identification information of the second fixed asset according to the first matching information.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the fixed asset inventory method according to any one of claims 1 to 8 is implemented.

Images