A method and system for dynamically configuring physical model attributes

Abstract

The present invention discloses a method and system for dynamically configuring physical model attributes, including: receiving configuration information based on a zigbee driver, generating a physical model according to the configuration information, and reporting it to a link driver; after reading a device list and supported physical model attribute information based on the link driver, uploading it to a server; arranging the device list and supported physical model attribute information based on the server, obtaining a device supported attribute list, and dynamically displaying the device list and the device supported attribute list on the server. Various devices can be added dynamically, and the corresponding attribute list can be modified dynamically, thereby improving the accuracy of the dynamic configuration of physical model attributes, and performing accurate data display to improve user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of physical model configuration, and in particular to a physical model attribute dynamic configuration method and system. Background Art

[0002] Currently, IoT control can be achieved based on servers, but in this process, various devices cannot be added dynamically and the corresponding attribute lists cannot be modified dynamically, resulting in inaccurate data display and affecting the user's viewing experience. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems in the above-mentioned technology to a certain extent. To this end, the first purpose of the present invention is to propose a method for dynamically configuring the attributes of a physical model, which can dynamically add various devices and dynamically modify the corresponding attribute list, improve the accuracy of the dynamic configuration of the attributes of the physical model, and perform accurate data display to improve the user experience.

[0004] The second objective of the present invention is to provide a system for dynamically configuring attributes of object models.

[0005] To achieve the above object, a first embodiment of the present invention provides a method for dynamically configuring attributes of a physical model, comprising:

[0006] Receive configuration information based on the ZigBee driver, generate an object model based on the configuration information, and report it to the link driver;

[0007] After reading the device list and supported object model attribute information based on the link driver, upload it to the server;

[0008] Based on the server collating the device list and the supported object model attribute information, a list of attributes supported by the device is obtained, and the server dynamically displays the device list and the list of attributes supported by the device.

[0009] According to some embodiments of the present invention, generating a model according to configuration information includes:

[0010] The zigbee driver obtains the object nodes of the generated object model, calculates the operation feedback characteristic values ​​of the current object nodes, balances the configuration information according to the operation feedback characteristic values, and obtains the balanced configuration information;

[0011] Generate first construction information based on the balancing configuration information and the object node ID;

[0012] Determine the association relationship between each object node and the node weight of each object node as the second construction information;

[0013] A model is generated according to the first construction information and the second construction information.

[0014] According to some embodiments of the present invention, calculating the operation feedback characteristic value of the current object node includes:

[0015] Obtain the attribute information of each object node, and perform numerical processing to obtain the corresponding attribute value; sort the attribute values ​​of each object node from small to large to obtain the sorting result;

[0016] According to the sorting result, determine the previous object node of the current object node as the reference object node;

[0017] Obtaining the operation relationship between the reference object node and the current object node, and calculating the operation feedback characteristic value of the current object node;

[0018] T b = ( 1 − λ ) + λ × T a × [ 0 . 2 × w ( a , b ) + 0 . 3 × P ( a , b ) + 0 . 5 × N ]

[0019] in, The current object node The operation feedback characteristic value of is the running attenuation parameter between the reference object node and the current object node; Reference Node The operation feedback characteristic value of is the operation activity parameter between the reference object node a and the current object node b; is the average distance of all running paths between the reference object node a and the current object node b; It is the serial number of the current object node b in the sorting result.

[0020] According to some embodiments of the present invention, after the device list and supported object model attribute information are read based on the link driver, they are uploaded to the server, including:

[0021] Based on the link driver, it traverses all devices connected to the system and the supported object model attribute information;

[0022] Format the read data to obtain sorted data;

[0023] Upload the sorted data to the server based on the HTTP protocol.

[0024] According to some embodiments of the present invention, the link-driven interface includes reading a list, reading attribute information of a single object model, storing data objects, and storing a deep synchronization identifier.

[0025] According to some embodiments of the present invention, the further comprising:

[0026] Extract the category information to which the device belongs;

[0027] Based on the mapping relationship between the category information and the function information, the function information corresponding to the device is determined and uploaded to the server for dynamic display.

[0028] According to some embodiments of the present invention, before reporting the object model to the link driver, the method further includes:

[0029] Collecting status data of each object node in the object model; the status data includes current location information, working current and working voltage;

[0030] Calculate characteristic data of the object node according to the state data of the object node; wherein the characteristic data includes: average value, change value, difference value from key points, difference value from average points, and credibility of the state data;

[0031] Determine whether the physical model is abnormal based on the characteristic data of each physical node, mark the abnormal physical model, perform correction processing, obtain the corrected physical model and report it to the link driver.

[0032] According to some embodiments of the present invention, before receiving configuration information based on the ZigBee driver, the method further includes:

[0033] Start and initialize the zigbee driver;

[0034] Create a startup monitoring thread for the zigbee driver, monitor the startup status of the zigbee driver in real time to determine whether to perform the reset operation of the zigbee driver according to the stable running time and startup times of the zigbee driver.

[0035] To achieve the above object, a second embodiment of the present invention provides a system for dynamically configuring physical model attributes, including:

[0036] The generation module is used to receive configuration information based on the ZigBee driver, generate an object model based on the configuration information, and report it to the link driver;

[0037] The reading module is used to read the device list and supported object model attribute information based on the link driver and upload them to the server;

[0038] The display module is used to sort out the device list and the supported object model attribute information based on the server, obtain the attribute list supported by the device, and the server dynamically displays the device list and the attribute list supported by the device.

[0039] The present invention proposes a method and system for dynamically configuring the attributes of a physical model, which can dynamically add various devices and dynamically modify the corresponding attribute list, thereby improving the accuracy of the dynamic configuration of the attributes of the physical model, and performing accurate data display to improve the user experience.

[0040] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0041] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0043] Figure 1 is a flow chart of a method for dynamically configuring attributes of a physical model according to an embodiment of the present invention;

[0044] Figure 2 is a flow chart of generating a model according to configuration information according to one embodiment of the present invention;

[0045] Figure 3 It is a block diagram of a system for dynamically configuring attributes of a physical model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0047] like Figure 1 As shown, the first embodiment of the present invention proposes a method for dynamically configuring attributes of a physical model, including steps S1-S3:

[0048] S1. Receive configuration information based on the ZigBee driver, generate an object model based on the configuration information, and report it to the link driver;

[0049] S2, after reading the device list and supported object model attribute information based on the link driver, upload it to the server;

[0050] S3. Based on the server, the device list and the supported object model attribute information are sorted out to obtain the attribute list supported by the device. The server dynamically displays the device list and the attribute list supported by the device.

[0051] Working principle of the above technical solution: In this embodiment, in the Internet of Things (IoT) system, Zigbee technology is used to receive configuration information, and based on these configuration information, object models (also called device models or object models) are generated, and then these models are reported to the Link driver, which is a higher-level communication or management protocol / system), Zigbee network settings and device connection: Establishing a Zigbee network: Establishing a Zigbee network based on the Zigbee coordinator. Device joining the network: Adding devices that need to be configured (such as sensors, actuators, etc.) to the network through the Zigbee protocol. Receive configuration information: Send configuration information: Send configuration information from the central control system or configuration server to the device through the Zigbee network. These configuration information include the device's ID, type, parameter settings, etc. Device reception: The Zigbee module on the device receives these configuration information and stores them in the device's non-volatile memory. Parse the configuration information and generate an object model: Parse the configuration: The software (or firmware) on the device parses the received configuration information and understands the meaning of each configuration item.

[0052] Generate object model: Dynamically generate or update the object model of the device according to the configuration information. The object model is a structured data representation that describes the device's properties (such as temperature, humidity), services (such as reading data, controlling devices) and events (such as state change notifications). Report to Link driver: Data encapsulation: Encapsulate the generated object model data into a format suitable for Link driver to receive. Including JSON, XML or other custom formats. Reporting mechanism: Direct reporting: If the Link driver directly supports Zigbee, the device can report data directly through the Zigbee network. Indirect reporting: If the Link driver does not support Zigbee, it is necessary to convert Zigbee data into a format supported by the Link driver (such as MQTT, CoAP, etc.) through a gateway or other intermediate device, and then report it. Communication protocol: According to the requirements of the Link driver, select a suitable communication protocol for data transmission. Verify reported data: Verify whether the received object model data is correct on the Link driver side. If there is a problem, perform necessary debugging, including checking Zigbee communication, configuration information parsing, object model generation and reporting process, etc. Based on the Zigbee driver, the configuration information is received and the generated model is reported to the Link driver to achieve flexible configuration and efficient management of IoT devices.

[0053] In this embodiment, the device list and object model attribute information are read: Device discovery and enumeration: Traverse or query the devices connected to the system through the Link driver to obtain the device list. Attribute information reading: For each device in the list, read the object model attribute information supported by it through the Link driver or the corresponding device interface. These attribute information include device type, unique identifier, supported attributes (such as temperature, humidity, switch status, etc.), and attribute data type and unit, etc. Data sorting and formatting: Data structuring: The read device list and object model attribute information are sorted into structured data, such as JSON or XML format. This helps data transmission, parsing and storage. Data verification: Before uploading, verify the data to ensure the integrity and correctness of the data. Upload to the server: Select the upload method: Select the appropriate upload method according to the server requirements and the current network environment. Upload methods include HTTP POST request, MQTT message publishing, WebSocket connection, etc. Build a request or message: According to the selected upload method, build a request or message containing the device list and object model attribute information. Send data: Send the constructed request or message to the specified endpoint or topic of the server. Verification and response processing: Receive response: Wait for the server's response and receive the result returned by the server. Verify result: Check the response result to confirm whether the data is successfully uploaded. If the upload fails, perform corresponding processing according to the error information, such as retrying the upload or recording the error log. The device list and supported object model attribute information read by the Link driver can be efficiently uploaded to the server to provide data support for subsequent IoT applications.

[0054] In this embodiment, the server first needs to receive the device list and object model attribute information sent from the Internet of Things system (such as uploaded by Link driver). This is achieved through HTTP requests, MQTT messages or other suitable communication protocols. Data storage: The received data needs to be stored on the server for subsequent query and display. These data can be stored in relational databases (such as MySQL, PostgreSQL), or NoSQL databases (such as MongoDB) can be used to better process JSON format data. Data processing: Parsing data: Parse the received data (such as JSON format) into a data structure that the server program can understand. Organizing information: Traverse the parsed data to extract the device list and the object model attribute information supported by each device. Organize this information into the format required by the server, such as key-value pairs, lists or more complex object structures. Data indexing and query optimization: Indexing: In order to improve query efficiency, the device list and attribute information in the database are indexed. Especially for frequently queried fields (such as device ID, attribute name), indexing can greatly reduce query time. Query optimization: Optimize query statements according to actual needs to ensure that results can be returned quickly when querying large amounts of data. Dynamic display: Front-end design: Design a user-friendly front-end interface to display the device list and attribute information. This can be a web page, mobile application or desktop application. Data binding: Use front-end technologies (such as HTML, CSS, JavaScript) to communicate with the back-end (server) to dynamically bind the data on the server to the front-end interface. This is achieved through AJAX requests, WebSocket connections, or data binding mechanisms provided by frameworks (such as React, Vue, Angular). Update interface: When the back-end data changes (such as new devices added, device attributes updated), the front-end interface can be updated in real time or near real time to reflect these changes, listen to data changes and update the DOM. The server can organize the device list and supported object model attribute information, and dynamically display this information to the front-end user. This will provide users with an intuitive, real-time, and secure device management interface.

[0055] The beneficial effects of the above technical solution are: various devices can be added dynamically, and the corresponding attribute lists can be modified dynamically, thereby improving the accuracy of dynamic configuration of object model attributes, and performing accurate data display to improve user experience.

[0056] like Figure 2 As shown, according to some embodiments of the present invention, generating a model according to configuration information includes steps S11-S14:

[0057] S11, the zigbee driver obtains the object node of the generated object model, calculates the operation feedback characteristic value of the current object node, balances the configuration information according to the operation feedback characteristic value, and obtains the balanced configuration information;

[0058] S12, generating first construction information based on the balancing configuration information and the object node ID;

[0059] S13, determining the association relationship between each object node and the node weight of each object node as the second construction information;

[0060] S14. Generate a model according to the first construction information and the second construction information.

[0061] Working principle of the above technical solution: In this embodiment, object node identification: Zigbee driver first needs to be able to identify and connect to each object node (i.e., IoT device) in the network. These object nodes are the basis for the object model. Object model generation: Generate the corresponding object model based on the device type, attributes, services and other information of the object node. The object model is an abstract representation of the device in the IoT system. Calculate the operation feedback characteristic value: Data collection: Collect real-time operation data from the object node through the Zigbee protocol, such as sensor readings, device status, etc. Characteristic value calculation: Calculate the operation feedback characteristic value of the object node based on the collected data. These characteristic values ​​include device performance indicators (such as response time, efficiency), health status (such as wear and tear, fault warning) or user behavior patterns (such as frequency of use, preference settings), etc. Characteristic value analysis: Analyze the calculated characteristic values ​​to understand the current operation status and potential problems of the object node. Configuration information acquisition: Obtain the configuration information of the current object node from the server or local storage. These configuration information may include device parameter settings, working mode, communication protocol, etc. Balance strategy formulation: Formulate a configuration information balance strategy based on the operation feedback characteristic value of the object node. The balancing strategy aims to optimize the operating efficiency of the equipment, extend the life of the equipment, and improve the user experience. Configuration information adjustment: According to the balancing strategy, the configuration information of the object node is dynamically adjusted. This includes modifying parameter settings, switching working modes, adjusting communication protocols, etc. Balancing configuration information application and verification: Configuration information distribution: The adjusted balancing configuration information is distributed to the object node through the Zigbee protocol. Configuration takes effect: The object node receives and applies the new configuration information and adjusts its operating status. Effect verification: The effect of the balancing configuration information is verified by continuously monitoring the operating data of the object node. If the effect is not ideal, it may be necessary to readjust the balancing strategy and distribute the configuration information again. Feedback loop: Feedback the verification results to the balancing strategy formulation process to form a closed-loop feedback mechanism. Strategy optimization: Based on the verification results and new operating data, the balancing strategy is continuously optimized to improve the accuracy and effectiveness of the configuration. The Zigbee driver can realize real-time monitoring, data analysis and configuration optimization of the object node, thereby improving the overall performance and user experience of the IoT system.

[0062] In this embodiment, the purpose of generating the first construction information is to combine the balancing configuration information of each object node with its unique identifier (ID) to form a basic data set containing configuration details and identity identification. The balancing configuration information of each object node is associated with its corresponding ID. ID is the unique identifier of the object node in the network, which is used to distinguish different devices. The associated balancing configuration information and the object node ID are integrated into a structured data set, which is the first construction information. It contains the basic data required to build the object model. The purpose of determining the second construction information is to identify the interactions and dependencies between the object nodes in the Internet of Things system and evaluate the importance of each object node in the system (i.e., node weight). Analyze the association relationship: Determine the association relationship between them by analyzing the communication records, data flows, control logic and other information between the object nodes. These relationships include parent-child relationships, parallel relationships, dependency relationships, etc. Evaluate node weight: Evaluate the weight of each object node based on factors such as the function, performance, and reliability of the object node in the system. Nodes with high weights usually have a greater impact on the system, so they need to be given more attention in the object model. Generate the second construction information: Integrate the analyzed association relationship and the evaluated node weight into a new data set, which is the second construction information. It provides the information of network structure and node importance required for building the object model. The first construction information and the second construction information are combined to build a complete object model. Information fusion: The first construction information and the second construction information are fused. This includes combining the balancing configuration information and the object node ID with the association relationship between the object nodes and the node weight to form a comprehensive data set. Model construction: Based on the fused data set, use appropriate modeling methods (such as object-oriented methods, graph theory methods, etc.) to build the object model. The object model should be able to accurately reflect the attributes, behaviors, association relationships of the object nodes, and their role and importance in the system. Verification and adjustment: Verify the constructed object model to ensure that it can accurately describe the actual situation of the Internet of Things system. If any problems or deficiencies are found, corresponding adjustments and optimizations need to be made. A complete and accurate object model can be generated based on the balancing configuration information and the association relationship between the object nodes and the node weight.

[0063] According to some embodiments of the present invention, calculating the operation feedback characteristic value of the current object node includes:

[0064] Obtain the attribute information of each object node, and perform numerical processing to obtain the corresponding attribute value; sort the attribute values ​​of each object node from small to large to obtain the sorting result;

[0065] According to the sorting result, determine the previous object node of the current object node as the reference object node;

[0066] Obtaining the operation relationship between the reference object node and the current object node, and calculating the operation feedback characteristic value of the current object node;

[0067] T b = ( 1 − λ ) + λ × T a × [ 0 . 2 × w ( a , b ) + 0 . 3 × P ( a , b ) + 0 . 5 × N ]

[0068] in, The current object node The operation feedback characteristic value of is the running attenuation parameter between the reference object node and the current object node; Reference Node The operation feedback characteristic value of is the operation activity parameter between the reference object node a and the current object node b; is the average distance of all running paths between the reference object node a and the current object node b; It is the serial number of the current object node b in the sorting result.

[0069] The working principle and beneficial effects of the above technical solution: For each object node, obtain its attribute information, digitize the attribute information, and obtain the corresponding attribute value. Attribute value sorting: Sort the attribute values ​​of all object nodes from small to large. Record the sorting results, that is, the position (serial number) of each object node in the sorted list. Determine the reference object node: For the object node b currently considered, find its previous object node a in the sorting result as the reference object node. If object node b is the first object node in the sorting result, special processing may be required (for example, a default value can be selected). Calculate the operation feedback characteristic value: Obtain the operation relationship between the reference object node a and the current object node b, including the operation attenuation parameter and operation activity parameter between them. Operation attenuation parameter, this parameter is determined based on factors such as the physical distance between the two object nodes, communication quality, and time delay. Calculate the operation activity parameter β, which reflects the frequency and importance of the interaction between the two object nodes. According to the reference object node, the operation feedback characteristic value of the current object node is accurately calculated to facilitate the improvement of the accuracy of data balancing.

[0070] According to some embodiments of the present invention, after the device list and supported object model attribute information are read based on the link driver, they are uploaded to the server, including:

[0071] Based on the link driver, it traverses all devices connected to the system and the supported object model attribute information;

[0072] Format the read data to obtain sorted data;

[0073] Upload the sorted data to the server based on the HTTP protocol.

[0074] Working principle and beneficial effects of the above technical solution: Initialize the Link driver to ensure that it can communicate correctly with the devices in the system. Including loading the necessary drivers, configuring communication parameters (such as baud rate, IP address, etc.), and establishing a connection with the device. Use the functions or APIs provided by the Link driver to traverse all devices connected to the system. Involves sending query commands or requests to the network / bus and receiving responses from each device. Read object model attribute information: For each device, send a specific request to obtain the object model attribute information it supports. This information includes the device's unique identifier, type, manufacturer, model, firmware version, and a specific attribute list (such as temperature, humidity, switch status, etc.). Format the read object model attribute information for subsequent processing and transmission. Including converting data into JSON, XML or other formats suitable for network transmission. When collating data, the integrity and consistency of the data should be ensured, and may include adding additional information such as timestamps and device status. Use the collated data to build an HTTP request. This includes setting the request URL (pointing to a specific endpoint of the server), HTTP method (such as POST), request header (such as Content-Type), and request body (containing the collated data). Send HTTP request to the server, and send the constructed HTTP request to the server through HTTP client library (such as curl, HttpClient, etc.). Realize accurate information of uploading device list and supported object model attribute information based on link driver.

[0075] According to some embodiments of the present invention, the link-driven interface includes reading a list, reading attribute information of a single object model, storing data objects, and storing a deep synchronization identifier.

[0076] The working principle and beneficial effects of the above technical solution are as follows: it is convenient to read the list and the attribute information of a single object model, and it is also convenient to store the corresponding data and determine the corresponding storage identification data.

[0077] According to some embodiments of the present invention, the further comprising:

[0078] Extract the category information to which the device belongs;

[0079] Based on the mapping relationship between the category information and the function information, the function information corresponding to the device is determined and uploaded to the server for dynamic display.

[0080] The working principle and beneficial effects of the above technical solution are: accurately determining the corresponding functional information and displaying it.

[0081] According to some embodiments of the present invention, before reporting the object model to the link driver, the method further includes:

[0082] Collecting status data of each object node in the object model; the status data includes current location information, working current and working voltage;

[0083] Calculate characteristic data of the object node according to the state data of the object node; wherein the characteristic data includes: average value, change value, difference value from key points, difference value from average points, and credibility of the state data;

[0084] Determine whether the physical model is abnormal based on the characteristic data of each physical node, mark the abnormal physical model, perform correction processing, obtain the corrected physical model and report it to the link driver.

[0085] The working principle and beneficial effects of the above technical solution: collect status data from each object node of the object model in real time or regularly. Collection content: current location information, working current and working voltage. Implementation method: obtain data through the built-in sensor or communication interface of the object node, and centrally manage and process the data through the Internet of Things platform or middleware. Calculate the characteristic data of the object node according to the state data of the object node. Average value: calculate the average value of the state data of each object node in a certain time window to reflect its stable state. Change value: analyze the change of state data over time, and calculate the change rate or change amount. Difference value with key points: compare the state data with the preset key threshold or standard value to calculate the difference. Difference value with average point: compare the current state data with the average value of the entire system or the same type of object nodes to evaluate the degree of deviation. Credibility: evaluate the credibility of the state data based on factors such as data quality, collection frequency, historical performance, etc. Determine whether the object model is abnormal based on the characteristic data of each object node. Abnormal judgment logic: combine multiple dimensions of characteristic data (such as whether the average value is abnormally deviated, whether the change value is too large, whether the difference with the key point exceeds the threshold, etc.), and design a comprehensive abnormal judgment logic. Threshold setting: Set reasonable thresholds or ranges for different feature data to determine whether the object node is in an abnormal state. Judgment result: If the feature data of the object node meets the abnormal conditions, the object node is marked as abnormal.

[0086] Mark the abnormal object model and perform correction processing. Mark the abnormal object node in the system for subsequent tracking and processing. Correction processing: Automatic correction: Try to automatically restore the object node to a normal state according to the preset correction strategy (such as restarting the object node, adjusting parameters, etc.). Manual intervention: If the automatic correction fails or requires manual judgment, an alarm message is generated to notify the maintenance personnel to intervene. Record logs: Record the correction process and results in detail for subsequent analysis and optimization. After the correction processing, if the object node returns to normal, update its status data and feature data to form a corrected object model. Report the corrected object model data to the Internet of Things platform or related systems through the link driver for further monitoring and management. Ensure the accuracy of the data and the stability of the system.

[0087] According to some embodiments of the present invention, before receiving configuration information based on the ZigBee driver, the method further includes:

[0088] Start and initialize the zigbee driver;

[0089] Create a startup monitoring thread for the zigbee driver, monitor the startup status of the zigbee driver in real time to determine whether to perform the reset operation of the zigbee driver according to the stable running time and startup times of the zigbee driver.

[0090] The working principle and beneficial effects of the above technical solution are as follows: the zigbee driver is started and initialized, and when it is determined that the stable operation time is less than the preset time threshold and the number of startups is greater than the preset number threshold, the reset operation of the zigbee driver is performed to ensure the accurate operation of the zigbee driver.

[0091] like Figure 3 As shown, the second embodiment of the present invention proposes a system for dynamically configuring physical model attributes, including:

[0092] The generation module is used to receive configuration information based on the ZigBee driver, generate an object model based on the configuration information, and report it to the link driver;

[0093] The reading module is used to read the device list and supported object model attribute information based on the link driver and upload them to the server;

[0094] The display module is used to sort out the device list and the supported object model attribute information based on the server, obtain the attribute list supported by the device, and the server dynamically displays the device list and the attribute list supported by the device.

[0095] The beneficial effects of the above technical solution are: various devices can be added dynamically, and the corresponding attribute lists can be modified dynamically, thereby improving the accuracy of dynamic configuration of object model attributes, and performing accurate data display to improve user experience.

[0096] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for dynamically configuring physical model attributes, characterized in that: include: Receive configuration information based on the ZigBee driver, generate an object model based on the configuration information, and report it to the link driver; After reading the device list and supported object model attribute information based on the link driver, upload it to the server; Based on the server collating the device list and the supported object model attribute information, a list of attributes supported by the device is obtained, and the server dynamically displays the device list and the list of attributes supported by the device; Generate a model based on the configuration information, including: The zigbee driver obtains the object nodes of the generated object model, calculates the operation feedback characteristic values ​​of the current object nodes, balances the configuration information according to the operation feedback characteristic values, and obtains the balanced configuration information; Generate first construction information based on the balancing configuration information and the object node ID; Determine the association relationship between each object node and the node weight of each object node as the second construction information; generating a model according to the first construction information and the second construction information; Calculate the running feedback characteristic values ​​of the current object node, including: Obtain the attribute information of each object node, and perform numerical processing to obtain the corresponding attribute value; sort the attribute values ​​of each object node from small to large to obtain the sorting result; According to the sorting result, determine the previous object node of the current object node as the reference object node; Obtaining the operation relationship between the reference object node and the current object node, and calculating the operation feedback characteristic value of the current object node; in, The current object node The operation feedback characteristic value of is the running attenuation parameter between the reference object node and the current object node; Reference Node The operation feedback characteristic value of Reference Node With the current object node The running activity parameters between Reference Node With the current object node The average distance of all running paths between them; The current object node The sequence number in the sorted results.

2. The method for dynamically configuring physical model attributes according to claim 1, characterized in that: After reading the device list and supported object model attribute information based on the link driver, upload it to the server, including: Based on the link driver, it traverses all devices connected to the system and the supported object model attribute information; Format the read data to obtain sorted data; Upload the sorted data to the server based on the HTTP protocol.

3. The method for dynamically configuring physical model attributes according to claim 1, characterized in that: The link-driven interface includes reading lists, reading single object model attribute information, storing data objects, and storing deep synchronization identifiers.

4. The method for dynamically configuring physical model attributes according to claim 1, characterized in that: Also includes: Extract the category information to which the device belongs; Based on the mapping relationship between the category information and the function information, the function information corresponding to the device is determined and uploaded to the server for dynamic display.

5. The method for dynamically configuring physical model attributes according to claim 1, characterized in that: Before reporting the object model to the link driver, it also includes: Collecting status data of each object node in the object model; the status data includes current location information, working current and working voltage; Calculate characteristic data of the object node according to the state data of the object node; wherein the characteristic data includes: average value, change value, difference value from key points, difference value from average points, and credibility of the state data; Determine whether the physical model is abnormal based on the characteristic data of each physical node, mark the abnormal physical model, perform correction processing, obtain the corrected physical model and report it to the link driver.

6. The method for dynamically configuring physical model attributes according to claim 1, characterized in that: Before receiving configuration information based on the ZigBee driver, it also includes: Start and initialize the zigbee driver; Create a startup monitoring thread for the zigbee driver, monitor the startup status of the zigbee driver in real time to determine whether to perform the reset operation of the zigbee driver according to the stable running time and startup times of the zigbee driver.

7. A system for dynamically configuring physical model attributes, characterized in that: include: The generation module is used to receive configuration information based on the ZigBee driver, generate an object model based on the configuration information, and report it to the link driver; The reading module is used to read the device list and supported object model attribute information based on the link driver and upload them to the server; A display module is used to sort out the device list and the attribute information of the supported object model based on the server, obtain the attribute list supported by the device, and the server dynamically displays the device list and the attribute list supported by the device; The generation module is used to receive configuration information based on the ZigBee driver, and the method of generating a model according to the configuration information includes: The zigbee driver obtains the object nodes of the generated object model, calculates the operation feedback characteristic values ​​of the current object nodes, balances the configuration information according to the operation feedback characteristic values, and obtains the balanced configuration information; Generate first construction information based on the balancing configuration information and the object node ID; Determine the association relationship between each object node and the node weight of each object node as the second construction information; generating a model according to the first construction information and the second construction information; Calculate the running feedback characteristic values ​​of the current object node, including: Obtain the attribute information of each object node, and perform numerical processing to obtain the corresponding attribute value; sort the attribute values ​​of each object node from small to large to obtain the sorting result; According to the sorting result, determine the previous object node of the current object node as the reference object node; Obtaining the operation relationship between the reference object node and the current object node, and calculating the operation feedback characteristic value of the current object node; in, The current object node The operation feedback characteristic value of is the running attenuation parameter between the reference object node and the current object node; Reference Node The operation feedback characteristic value of Reference Node With the current object node The running activity parameters between Reference Node With the current object node The average distance of all running paths between them; The current object node The sequence number in the sorted results.

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