Data detection device and method based on object model

Abstract

The invention relates to a data detection device and method based on an object model, and relates to the technical field of Internet of Things, and the device is composed of a product management module, an equipment management module, a communication driving module, a data storage module and a data detection module. A product management module defines an object model to construct a data blueprint and clarify data attributes and specifications, and an equipment management module creates instances and configures communication based on the object model to realize equipment access and communication preparation. Smooth information transmission between equipment and the system is guaranteed through the communication driving module, the data detection module takes an object model as a reference, compares data with specifications through an identifier association list, judges whether the data meets the specifications or not, and correspondingly processes abnormal data according to a preset exception handling mechanism, so that stable and efficient operation of the system is guaranteed. Abnormality in the equipment operation process is found by detecting and standardizing the equipment data according to the physical model, definition of the physical model is perfected, equipment faults or problems are found in time, and correctness of operation of the Internet of Things system is ensured.

Description

Technical Field

[0001] The present application relates to the technical field of Internet of Things, and in particular to a data detection device and method based on a physical model. Background Art

[0002] The Internet of Things (IoT) represents another revolution in the development of computer networks in the information age. It connects any object to the network through information sensing devices and agreed-upon protocols. Objects exchange and communicate information through information media, enabling intelligent identification, positioning, tracking, and monitoring services, and realizing ubiquitous connections between people, machines, and objects. Currently, IoT technology is widely applied in various fields, from smart homes to smart cities, from smart logistics to smart healthcare, from industrial manufacturing to agricultural management. IoT applications have penetrated every aspect of our lives. With the in-depth development of technologies such as artificial intelligence, big data, and 5G, IoT technology will continue to advance and expand.

[0003] The Internet of Things (IoT) requires access to a wide variety of terminal devices. The lack of data connectivity between different manufacturers and industries significantly limits its development. To address this issue, object models have been introduced to abstract objects. The construction of a unified description language for these models shields the differences between underlying devices and standardizes the expression of device capabilities and interaction methods. Object models help describe and manage various devices, sensors, and data in the physical world, enabling unified management, interoperability, and data standardization across IoT devices.

[0004] However, when using object models to describe terminal devices, ensuring that device data matches the defined object models has received little attention. The typical process involves first defining a set of object models based on the device type and then using them for data exchange. However, device anomalies during use are often not addressed. Alternatively, some devices may not be compatible with the object model being used, or the object model may not be updated synchronously after a device upgrade, leading to data anomalies. Summary of the Invention

[0005] The embodiment of the present invention provides a data detection device and method based on a physical model, which detects and standardizes device data according to the physical model to discover anomalies during device operation, improve the definition of the physical model, promptly discover device failures or problems, and ensure the correctness of the operation of the Internet of Things system.

[0006] On the one hand, an embodiment of the present invention provides a data detection device based on a physical model, the method comprising: a product management module, a device management module, a communication driver module, and a data detection module;

[0007] The product management module is connected to the device management module and is used to extract common features of terminal devices of different specifications but the same type, perform abstract descriptions, and then define corresponding object models according to device functions;

[0008] The device management module is connected to the data detection module and is used to create a device instance according to the object model and register, configure and manage the life cycle of the device based on the device instance;

[0009] The communication driver module is connected to the data detection module and is used to establish a connection with the terminal device based on the communication protocol defined by the object model to realize the reception of the reported data and the issuance of the execution instruction;

[0010] The data detection module is used to perform normative detection on the reported data and / or execution instructions according to the physical model to obtain an abnormality detection result, and perform abnormal data processing on the abnormality detection result according to the abnormality processing method defined in the physical model.

[0011] Furthermore, it also includes: a data storage module,

[0012] The data storage module is connected to the product management module, the device management module and the data detection module respectively, and is used to store the object model definition, device instance information, reported data, issued instructions and exception processing logs of the terminal device.

[0013] Furthermore, each data information in the object model includes a unique identifier and the following standard definitions: name, data type, data length, value range or enumeration value, unit, description information and exception handling method.

[0014] Furthermore, the data detection module includes a classification unit, a basic type processing library and a combination type processing library;

[0015] The classification unit is used to classify the data types of reported data and issued instructions into basic types and combined types, wherein the basic types include integer type, floating point type, enumeration type, text type, time type and Boolean type, and the combined types include array type and structure type;

[0016] The basic type processing library is used to perform value range, step multiple, enumeration value matching, text length or time format detection on basic type data;

[0017] The combination type processing library splits the combination type data into basic types and then detects them item by item.

[0018] Furthermore, the communication driver module supports adaptation of multiple communication protocols and dynamically switches the protocol parsing mode according to the object model. The communication protocols include MQTT, Zigbee, CoAP or HTTP.

[0019] Furthermore, the communication driver module is also used to trigger the device management module to perform device re-registration or communication link reconstruction operations when the device connection is abnormal.

[0020] On the other hand, an embodiment of the present invention provides a method for detecting data based on a physical model based on the above-mentioned device for detecting data based on a physical model, the method comprising:

[0021] Define physical models of terminal devices of the same type but with different specifications through the product management module;

[0022] Creating a device instance based on the object model and configuring communication parameters through a device management module;

[0023] Establish a connection with the device through the communication driver module and transmit reported data and execute instructions;

[0024] The data detection module performs a normative detection on the reported data and the execution instruction according to the physical model to obtain an abnormality detection result, and performs abnormal data processing on the abnormality detection result according to the abnormality processing method defined in the physical model.

[0025] Furthermore, the regulatory testing includes:

[0026] Marking the reported data and / or the data information of the instruction to be issued with an identifier according to the physical model in the data storage module;

[0027] Based on the identifier, a preset data specification is queried to detect whether the data content of the communication data meets the preset data specification, and an abnormality detection result is obtained.

[0028] Furthermore, after marking the reported data and / or the data information of the instruction to be issued with an identifier according to the physical model in the data storage module, the method further includes:

[0029] Using the identifier of the reported data and / or the instruction to be issued as a keyword, the corresponding content value is stored as a numerical content in a first association list;

[0030] Obtain the detailed specification definition corresponding to the object model of the reported data and / or the instruction to be issued, and store the detailed specification definition as the value content into a second association list using the identifier as a keyword.

[0031] Furthermore, the querying of a preset data specification based on the identifier, detecting whether the data content of the communication data complies with the specification, and obtaining an abnormality detection result includes:

[0032] Traversing the first association list according to the identifier to obtain the corresponding content value, and querying the corresponding detailed specification definition according to the identifier from the second association list;

[0033] Based on the content value and its corresponding detailed specification definition, a preset data specification is queried to detect whether the data content of the communication data meets the preset data specification, and an abnormality detection result is obtained.

[0034] This invention utilizes a product management module to standardize the definition of physical models and precisely create and configure device instances. Combined with communication drivers and data detection modules, this approach ensures strict control of data compliance and effectively guarantees data accuracy. Timely and efficient exception handling ensures stable system operation and reduces the risk of failure. The invention's unified physical model specification significantly reduces device management complexity and improves management efficiency. The entire solution boasts excellent compatibility and scalability, enabling easy and convenient integration of new devices, effectively promoting the stable development and continuous upgrade of the system.

[0035] In order to solve the compatibility problem between the object model and the Internet of Things equipment, the described data detection device and method can timely discover abnormal situations that occur during the operation of the equipment or after upgrading and transformation, and find problems that the data does not match the object model definition specifications. It helps the system to identify abnormal data in time and assist in problem solving through its exception handling method, thereby improving the system's utilization efficiency and enhancing the system's adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 The figure shows a structural schematic diagram of a data detection device based on a physical model according to an embodiment of the present application.

[0038] Figure 2 The figure shows a schematic flow chart of data classification detection performed by the data detection module according to an embodiment of the present application.

[0039] Figure 3 It is a flow chart of a data detection method provided by a data monitoring device based on a physical model according to an embodiment of the present invention.

[0040] Figure 4 This is an index structure diagram of the association table involved in the embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0042] The terms "first," "second," "third," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0043] Below, the exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application, and it should be understood that the present application is not limited to the exemplary embodiments described herein.

[0044] Application Overview

[0045] The Internet of Things requires access to a variety of terminal devices. The lack of data connectivity between different manufacturers and industries will greatly limit the development of the Internet of Things. To solve this problem, people have introduced object models to abstract objects. The construction of a unified description language for the model shields the differences between underlying devices and standardizes the device capability expression and interaction methods.

[0046] Object models help describe and manage various devices, sensors, and data in the physical world, enabling unified management, interoperability, and data standardization of IoT devices. However, when using object models to describe terminal devices, ensuring that device data matches the defined object models has received little attention. The typical process involves defining an object model based on the device type and then using that object model for data exchange. However, device anomalies during use are often not addressed. Alternatively, some devices may not be compatible with the object model being used, or the object model may not be updated synchronously after device upgrades, leading to data anomalies.

[0047] In response to the deficiencies of the prior art, the present invention provides a data detection device and method based on a physical model, which uses a unified physical model as a standard to standardize data interaction and processing. The product management module defines the physical model to construct a data blueprint, clarifying data attributes and specifications. The device management module creates an instance based on the physical model and configures communication to achieve device access and communication preparation. The communication driver module ensures smooth information transmission between the device and the system. The data detection module uses the physical model as a reference, compares the data with the specification through the identifier association list, determines whether the data is compliant, and processes the abnormal data accordingly according to the preset exception handling mechanism to ensure stable and efficient operation of the system. The device data is detected and standardized based on the physical model to discover anomalies in the device operation process, improve the definition of the physical model, and promptly discover device failures or problems to ensure the correctness of the operation of the Internet of Things system.

[0048] After introducing the basic principles of the present application, various non-limiting embodiments of the present application will be described in detail with reference to the accompanying drawings.

[0049] Exemplary Methods

[0050] Figure 1 The figure shows a structural schematic diagram of a data detection device based on a physical model according to an embodiment of the present application.

[0051] like Figure 1 As shown, the data detection device 100 based on the object model according to the embodiment of the present application includes: a product management module 102, a device management module 103, a communication driving module 105 and a data detection module 104.

[0052] The product management module 102 is connected to the device management module 103 and is used to extract common features of terminal devices of different specifications but the same type, perform abstract descriptions, and then define corresponding object models based on the device functions;

[0053] The device management module 103 is connected to the data detection module 104 and is used to create device instances according to the object model and register, configure and manage the life cycle of the device based on the device instance;

[0054] The communication driver module 105 is connected to the data detection module 104 and is used to establish a connection with the terminal device based on the communication protocol defined by the object model to realize the reception of reported data and the issuance of execution instructions;

[0055] The data detection module 104 is used to perform a normative detection on the reported data and / or execution instructions according to the physical model, obtain an abnormality detection result, and perform abnormal data processing on the abnormality detection result according to the abnormality processing method defined in the physical model.

[0056] Among them, the product management module 102 is connected to the device management module 103 to provide object model support, the device management module 103 is connected to the communication driver module 105 to realize device communication control, and the communication driver module 105 is connected to the data detection module 104 to transmit the parsed data.

[0057] Specifically, the product management module 102 is responsible for abstracting the common features of products of the same type but of different specifications from different manufacturers to form a model, which is defined using a physical model. The model typically includes three dimensions: attributes, services, and events, which describe what the product is, what it can do, and what information it can provide to the outside world. It also provides functions such as adding, deleting, modifying, and querying products to control and manage the products. The device management module 103 establishes and configures devices based on the physical model in the product management module 102, provides functions such as adding, deleting, modifying, and querying devices, and performs lifecycle management functions such as control and management of the devices. The data detection module 104 provides data detection functions for data interaction with devices, detects whether there are any anomalies in the data reported by the device, and detects whether the data sent by the device conforms to the physical model definition. The communication driver module 105 is responsible for maintaining a communication link with the device entity according to the physical model communication protocol and performing data interaction, including receiving data reported by the device and issuing execution instructions to the connected device.

[0058] Optionally, each data information in the object model includes a unique identifier and the following standard definitions: name, data type, data length, value range or enumeration value, unit, description information and exception handling method.

[0059] The data detection device based on the physical model provided in this embodiment further includes: a data storage module 106,

[0060] The data storage module 106 is connected to the product management module 102, the device management module 103 and the data detection module 104 respectively, and is used to store the object model definition, device instance information, reported data, issued instructions and exception handling logs of terminal devices.

[0061] Specifically, the data storage module is used to store data such as product model definitions, device instance information, device operation data, and exception handling logs, and is also used to establish an association relationship between products and devices. Among them, the data detection module 104 is connected to the data storage module to store detection results and exception logs.

[0062] Optionally, the data detection module 104 in the object model-based data detection device in the embodiment of the present invention includes a classification unit, a basic type processing library and a combination type processing library.

[0063] The classification unit is used to classify the data types of reported data and issued instructions into basic types and combined types, wherein the basic types include integer type, floating point type, enumeration type, text type, time type and Boolean type, and the combined types include array type and structure type;

[0064] The basic type processing library is used to perform value range, step multiple, enumeration value matching, text length or time format detection on basic type data;

[0065] Figure 2 The data detection module 104 provides a flow chart of data classification detection according to an embodiment of the present invention. The data detection module 104 pre-classifies data into two categories, including basic data types and combined data types, according to different data types in the object model.

[0066] Basic data types include integer type, floating-point type, enumeration type, text type, time type, and Boolean type. Composite data types include array type and structure type.

[0067] Integer and floating-point types can be grouped together due to their similar detection methods. They both require determining the range and step size of the data content value. Enumeration and Boolean types both require determining whether the data content value conforms to the enumeration value and can also be grouped together. Boolean types are a special type of enumeration. Time types require determining whether the data content conforms to the time format requirements. Text types require determining whether the text length meets the specification requirements. Composite data types need to be broken down into their basic data types for testing. Array types are broken down into individual array elements, and structure types are broken down into individual structures.

[0068] The combination type processing library splits the combination type data into basic types and then detects them item by item.

[0069] Optionally, the communication driver module 105 in the object model-based data detection device in the embodiment of the present invention supports adaptation of multiple communication protocols and dynamically switches protocol parsing modes according to the object model.

[0070] Among them, the communication protocol may include MQTT, CoAP or HTTP.

[0071] Optionally, the communication driver module 105 is further configured to trigger the device management module 103 to perform device re-registration or communication link reconstruction operations when the device connection is abnormal.

[0072] An embodiment of the present invention further provides a method for detecting data based on a physical model based on the above-mentioned device for detecting data based on a physical model, the method comprising:

[0073] The product management module 102 defines object models of terminal devices of the same type but with different specifications;

[0074] Creating a device instance based on the object model and configuring communication parameters through the device management module 103;

[0075] Establishing a connection with the device through the communication driver module 105 and transmitting reported data and execution instructions;

[0076] The data detection module 104 performs a normative detection on the reported data and the execution instruction according to the physical model to obtain an abnormality detection result, and performs abnormal data processing on the abnormality detection result according to the abnormality processing method defined in the physical model.

[0077] Optionally, Figure 3 This is a flow chart of a data detection method for a data monitoring device based on a physical model provided by an embodiment of the present invention. Step 301 starts. Step 302 The communication driver module 105 receives a message reported by the device. Step 303 parses the message to obtain data of different dimensions such as attributes, services or events and reports it to the data detection module 104. Step 304 The data detection module 104 obtains the physical model of the corresponding device through the data storage module, and adds corresponding data information identifiers to different data tags according to the physical model definition. Step 305 The data detection module 104 queries the detailed definition of the corresponding data information through different identifiers. Step 306 determines whether its data content value meets the requirements of the physical model specification definition. If so, proceed to step 307, otherwise proceed to step 308. Step 307 If the data detection meets the requirements, it is reported normally and stored in the data storage module. Step 308 If the data detection does not meet the physical model specification definition, obtain the exception handling method corresponding to the data information. Step 309 determines the exception handling method. If no action is taken, step 310 is executed. If the data is set to a null or default value, step 311 is executed. If an alarm or prompt is issued, step 312 is executed. After the exception handling is completed, step 313 records the data and the exception handling method in the data storage module. Step 314 ends the process.

[0078] Optionally, the normative detection in the data detection device based on the physical model in the embodiment of the present invention includes:

[0079] Marking the reported data and / or the data information of the instruction to be issued with an identifier according to the physical model in the data storage module;

[0080] Based on the identifier, a preset data specification is queried to detect whether the data content of the communication data meets the preset data specification, and an abnormality detection result is obtained.

[0081] Optionally, in the physical model-based data detection device in the embodiment of the present invention, after marking the reported data and / or the data information of the instruction to be issued with an identifier according to the physical model in the data storage module, the method includes:

[0082] Using the identifier of the reported data and / or the instruction to be issued as a keyword, the corresponding content value is stored as a numerical content in a first association list;

[0083] Obtain the detailed specification definition corresponding to the object model of the reported data and / or the instruction to be issued, and store the detailed specification definition as the value content into a second association list using the identifier as a keyword.

[0084] Furthermore, the querying of a preset data specification based on the identifier to detect whether the data content of the communication data complies with the specification and obtaining an abnormality detection result includes:

[0085] Traversing the first association list according to the identifier to obtain the corresponding content value, and querying the corresponding detailed specification definition according to the identifier from the second association list;

[0086] Based on the content value and its corresponding detailed specification definition, a preset data specification is queried to detect whether the data content of the communication data meets the preset data specification, and an abnormality detection result is obtained.

[0087] Specifically, Figure 4 This is an index structure diagram of the association table involved in the embodiment of the present invention. The device data contains various data information. According to the object model definition specification, the data information is marked, and the data information unique identifier is used as the keyword. The content value of the data information is stored as a numerical value in the association table, which is the first association list 401 in the figure. The object model corresponding to the device is found to extract the detailed specification definition of the data information. The data information unique identifier is used as the keyword, and the detailed specification definition is stored as the numerical content in the association table, which is the second association list 402 in the figure. Through the two association lists, the data information content value and its corresponding detailed specification definition can be found, and then data detection can be performed.

[0088] The present invention will be further described below with reference to a specific embodiment.

[0089] In a smart home environment, there are numerous smart lighting devices of the same type but with varying specifications. First, an object model is constructed for these smart lighting devices using the product management module 102. This object model includes a light brightness attribute (e.g., an integer with a specified value range of 0-100, representing the degree of brightness from off to full brightness, with a unit of none), a light color attribute (e.g., a string with a value of multiple preset colors, such as red, green, and blue), and a device operating mode attribute (an enumerated type with values ​​such as normal mode, energy-saving mode, and night mode).

[0090] Then, the device management module 103 creates a specific smart lighting device instance according to the object model and configures communication parameters, such as setting the device ID, selecting the communication protocol (such as Zigbee protocol), and specifying the device's address in the network.

[0091] The communication driver module 105 is then used to establish a connection between the device and the server, enabling data exchange. The smart lighting device will periodically report its operating status information, such as light brightness, color, and current operating mode, to the server. The server can also send control commands to the device, such as adjusting light brightness, switching colors, or changing operating modes.

[0092] Conduct compliance checks during data reporting. First, assign identifiers to the reported data and the information to be issued based on the object model stored in the data storage module. The brightness, color, and operating mode information reported by the smart lighting device are assigned identifiers of "brightness value," "color value," and "operating mode," respectively. Commands issued by the server to the device, such as those for adjusting brightness, are assigned the identifier "brightness adjustment command," and those for switching colors are assigned the identifier "color switching command."

[0093] Next, the identifier is used as a keyword to construct an association list. The first association list is constructed by treating the reported data and the specific contents of the command to be issued as numerical values. For example, the list might include "Brightness value: 30," "Color value: Blue," "Operating mode: Normal mode," "Brightness adjustment command: null," and "Color switching command: null." Simultaneously, the corresponding detailed specification definition from the object model is obtained and, using the identifier as a keyword, the specification detailed definition is used as numerical value to form a second association list. Examples include "Brightness value: {data type: integer, value range: 0-100, unitless}," "Color value: {data type: string, value range: a set of preset color names}," "Operating mode: {data type: enumeration, values: Normal mode, Energy saving mode, Night mode}," "Brightness adjustment command: {data type: command, parameter: integer in the range of 0-100}," and "Color switching command: {data type: command, parameter: a value from a set of preset color names}."

[0094] Based on these identifiers, the corresponding content values ​​are searched in the first association list. The detailed specification definitions based on the identifiers are then searched in the second association list, and the detection is performed against the preset data specifications. For example, for a "brightness value: 30," after finding the brightness specification in the second association list, it can be determined that this value is within the specified range and meets the data specification. However, if the reported "brightness value: 120" is found to be outside the range of 0-100 by comparison with the specification, it will be determined to be an anomaly.

[0095] If an anomaly is detected in the data, it will be handled according to the exception handling method predefined in the physical model. Assuming that the physical model specifies recording an exception log for brightness anomalies and notifying the administrator of the situation, the system will log the abnormal brightness data, the ID of the smart lighting device that caused the anomaly, and the time the anomaly was detected. It will also send a notification to the administrator stating that the abnormal brightness data has occurred.

[0096] For example, smart meters are also the same type of terminal devices. They also first build a physical model, including attributes such as voltage, current, and power. Then, they create device instances, configure communication parameters, establish connections to transmit data, and perform a series of operations such as normative testing and exception handling to ensure accurate and stable transmission of meter data.

[0097] The present invention uses the data information identifier in the object model as a keyword, associates the data content value with the detailed data specification definition for analysis and judgment, and distinguishes different types of data through data classification detection methods to perform different data detections. It can timely discover anomalies that occur during the operation of the equipment, maintain the consistency of the equipment entity and the object model, and help the system process abnormal data and solve problems, thereby improving the practicality and reliability of the system and enhancing the adaptability of the system.

[0098] By standardizing the definition of object models, accurately creating and configuring device instances, and combining the communication driver and data detection module 104, strict control of data standardization is achieved, effectively ensuring data accuracy; timely and efficient exception handling ensures stable system operation and reduces the risk of failure; unified object model specifications greatly reduce the complexity of device management and improve management efficiency; the entire solution has good compatibility and scalability, and new equipment can be easily and conveniently connected, which effectively promotes the stable development and continuous upgrading of the system.

[0099] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this application are merely illustrative and not restrictive, and it should not be assumed that these advantages, strengths, and effects are required of each embodiment of this application. In addition, the specific details disclosed above are merely illustrative and facilitating understanding, and are not restrictive. The above details do not limit this application to necessarily being implemented using the above specific details.

[0100] The block diagrams of the devices, devices, equipment, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "include," "comprise," "have," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0101] It should also be noted that in the apparatus, device, and method of the present application, each component or each step can be decomposed and / or recombined, and such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0102] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0103] The above description has been provided for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A data detection device based on a physical model, characterized in that: include: Product management module, device management module, communication driver module and data detection module; The product management module is connected to the device management module and is used to extract common features of terminal devices of different specifications but the same type, perform abstract descriptions, and then define corresponding object models according to device functions; The device management module is connected to the data detection module and is used to create a device instance according to the object model and register, configure and manage the life cycle of the device based on the device instance; The communication driver module is connected to the data detection module and is used to establish a connection with the terminal device based on the communication protocol defined by the object model to achieve the reception of the reported data and the issuance of the execution instruction; The data detection module is used to perform a normative detection on the reported data and / or execution instructions according to the physical model to obtain an abnormality detection result, and perform abnormal data processing on the abnormality detection result according to the abnormality processing method defined in the physical model.

2. The data detection device based on the physical model according to claim 1, characterized in that: Also includes: Data storage module, The data storage module is connected to the product management module, the device management module and the data detection module respectively, and is used to store the object model definition, device instance information, reported data, issued instructions and exception processing logs of the terminal device.

3. The data detection device based on physical model according to claim 1, characterized in that: include: Each data information in the object model includes a unique identifier and the following standard definitions: name, data type, data length, value range or enumeration value, unit, description information and exception handling method.

4. The data detection device based on the physical model according to claim 3, characterized in that: The data detection module includes a classification unit, a basic type processing library and a combination type processing library; The classification unit is used to classify the data types of reported data and issued instructions into basic types and combined types, wherein the basic types include integer type, floating point type, enumeration type, text type, time type and Boolean type, and the combined types include array type and structure type; The basic type processing library is used to perform value range, step multiple, enumeration value matching, text length or time format detection on basic type data; The combination type processing library splits the combination type data into basic types and then detects them item by item.

5. The data detection device based on physical model according to claim 1, characterized in that: The communication driver module supports multiple communication protocol adaptations and dynamically switches protocol parsing methods according to the object model. The communication protocols include MQTT, Zigbee, CoAP or HTTP.

6. The data detection device based on physical model according to claim 5, characterized in that: The communication driver module is also used to trigger the device management module to perform device re-registration or communication link reconstruction operations when the device connection is abnormal.

7. A method for detecting data based on a physical model based on the physical model based data detection device according to any one of claims 1 to 6, characterized in that: include: Define physical models of terminal devices of the same type but with different specifications through the product management module; Creating a device instance based on the object model and configuring communication parameters through a device management module; Establish a connection with the device through the communication driver module and transmit reported data and execute instructions; The data detection module performs a normative detection on the reported data and the execution instruction according to the physical model to obtain an abnormality detection result, and performs abnormal data processing on the abnormality detection result according to the abnormality processing method defined in the physical model.

8. The detection method according to claim 7, characterized in that The regulatory testing includes: Marking the reported data and / or the data information of the instruction to be issued with an identifier according to the physical model in the data storage module; Based on the identifier, a preset data specification is queried to detect whether the data content of the communication data meets the preset data specification, and an abnormality detection result is obtained.

9. The detection method according to claim 8, characterized in that After the identifier is added to the reported data and / or the data information of the instruction to be issued according to the physical model in the data storage module, the method includes: Using the identifier of the reported data and / or the instruction to be issued as a keyword, the corresponding content value is stored as a numerical content in a first association list; Obtain the detailed specification definition corresponding to the object model of the reported data and / or the instruction to be issued, and store the detailed specification definition as the value content into a second association list using the identifier as a keyword.

10. The detection method according to claim 9, characterized in that: The querying of a preset data specification based on the identifier, detecting whether the data content of the communication data complies with the specification, and obtaining an abnormality detection result includes: Traversing the first association list according to the identifier to obtain the corresponding content value, and querying the corresponding detailed specification definition according to the identifier from the second association list; Based on the content value and its corresponding detailed specification definition, a preset data specification is queried to detect whether the data content of the communication data meets the preset data specification, and an abnormality detection result is obtained.

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