Quick access method for sensor in edge server

Abstract

The invention discloses a method for quickly accessing a sensor in an edge server. The method comprises the following steps of: acquiring a sensor ID (Identity) of the sensor; analyzing the sensor ID, and associating the sensor ID with the matched sensor parameter type model; adding the matched sensor parameter type model into a sensor data processing model of the edge server; a standardized sensor access mechanism is constructed through a sensor data processing model, and a sensor is accessed to an edge server; when the sensor is accessed, the edge server carries out self-calibration and intelligent identification on the sensor; and the edge server performs data analysis on the received sensor data based on the sensor data processing model. According to the method, the sensor ID is associated with the matched sensor parameter type model, a standardized sensor access mechanism is constructed, and the sensor access efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of sensor access technology, and in particular to a method for quickly accessing sensors in an edge server. Background Art

[0002] With the rapid growth of the number of IoT devices and sensor types, the demand for access to various new sensors and devices is increasing, and the traditional manual configuration method cannot meet the rapidly changing needs. Therefore, future edge servers need to have the ability to quickly access multiple sensor devices and automatically analyze multiple sensor data. It must be able to flexibly access different types of sensors, and be able to quickly deploy and dynamically add in various application scenarios to ensure automatic identification of sensor types and automatic analysis of sensor data.

[0003] Especially in scenarios such as industry, environmental monitoring, and smart cities, the diversity and rapid changes of equipment require edge servers to be able to adapt and integrate new sensors. Regardless of whether they are sensors of different models, different brands, or different functions, they can all be seamlessly connected to the system and quickly start data collection and processing.

[0004] This trend means that edge servers must not only provide basic sensor access functions, but also provide more efficient integration solutions through dynamic data model generation and intelligent automation addition. They can automatically identify sensor device types, parameter types, parameter quantities, parameter units, and data formats, significantly reducing deployment costs and system complexity. Summary of the invention

[0005] In view of the above problems, the purpose of the present invention is to provide a method for rapid access of sensors in an edge server, so that the edge server can provide a highly flexible, low-cost and efficient solution when dealing with the rapidly growing types of sensors and diversified application scenarios of the Internet of Things.

[0006] From sensor identification, parameter extraction to model storage, the entire process is fully automated, avoiding the complex manual operations under traditional methods.

[0007] Through standardized data models, unified management and efficient access of multiple types of sensors are ensured.

[0008] The system can dynamically adjust and expand the model based on newly added sensors, supporting long-term evolution and adaptation.

[0009] The design of data model storage and multi-module sharing ensures efficient coordination of sensor access and use.

[0010] The power-off preservation mechanism of the data model ensures the data integrity of the system in the event of an unexpected power outage, enhances the reliability of the system, and is suitable for industrial and mission-critical scenarios.

[0011] It supports multi-module sharing of data models (local algorithms, local Web services, cloud analysis, etc.), improves the system's integration and overall performance, and adapts to the needs of the distributed architecture of the Internet of Things.

[0012] A first aspect of the present invention provides a method for quickly accessing a sensor in an edge server, comprising:

[0013] Get the sensor ID of the sensor;

[0014] By analyzing the sensor ID, the sensor ID is associated with a matching sensor parameter type model;

[0015] adding the matched sensor parameter type model to the sensor data processing model of the edge server;

[0016] By using the sensor data processing model, a standardized sensor access mechanism is constructed to connect the sensor to the edge server;

[0017] When a sensor is connected, the edge server performs self-calibration and intelligent identification on the sensor;

[0018] The edge server performs data analysis on the received sensor data based on the sensor data processing model.

[0019] In this solution, the sensor ID is analyzed to associate the sensor ID with a matching sensor parameter type model, including:

[0020] Determining a sensor parameter type of the sensor by analyzing the sensor ID;

[0021] Searching a sensor parameter type model in a local database of the edge server according to the sensor parameter type to determine a sensor parameter type model that matches the sensor parameter type;

[0022] The sensor parameter type is mapped to a matching sensor parameter type model.

[0023] This plan also includes:

[0024] When the sensor corresponding to the sensor ID includes multiple parameter types, determining a sensor parameter type model matching each sensor parameter type respectively;

[0025] Each sensor parameter type is mapped to a matching sensor data processing model.

[0026] This plan also includes:

[0027] When the sensor is successfully matched with the edge server, the sensor data processing model is stored in the SPIFS file system;

[0028] The local Web server, the data algorithm module and the MQTT cloud server access and use the sensor data processing model of the sensor through the SPIFS file system.

[0029] In this solution, when the sensor is connected, the edge server performs self-calibration and intelligent identification on the sensor, including:

[0030] When a sensor is connected, the edge server performs sensor self-calibration on the sensor and evaluates and adjusts the sensor performance in real time;

[0031] The edge server identifies the parameter type and data format of the sensor, and configures the data collection method and data collection frequency for the sensor.

[0032] This plan also includes:

[0033] When a new sensor is connected to the edge server, if the local database of the edge server does not have a sensor parameter type model that matches the sensor ID of the new sensor, the corresponding sensor data processing model is expanded according to the parameter characteristics of the new sensor;

[0034] The expanded sensor data processing model is added to the local database of the edge server.

[0035] In this solution, the edge server performs data parsing on the received sensor data based on the sensor data processing model, including:

[0036] When the edge server receives the sensor data, it determines the sensor ID of the sensor data;

[0037] Selecting a corresponding sensor data processing model according to the sensor ID of the sensor data to parse the sensor data to obtain real-time parsed data;

[0038] Storing the real-time parsed data in a local database;

[0039] According to the scenario field matching, the specified local algorithm is input for local algorithm data, displayed on the web page icon, and received by the MQTT cloud server.

[0040] This plan also includes:

[0041] Encoding according to the sensor parameter type of the sensor to determine the sensor ID, wherein the sensor ID is composed of a combination code P and a serial number S;

[0042] determining a physical parameter of the sensor according to a sensor parameter type of the sensor;

[0043] Assign a unique 16-bit code to each single physical parameter and combination of multiple physical parameters, and determine the combination code P of different sensor types;

[0044] Corresponding serial numbers S are set for different sensors of the same sensor type in turn.

[0045] This plan also includes:

[0046] The formula for obtaining the sensor ID code is:

[0047]

[0048] The formula for extracting the combined code is:

[0049] P= ( ID>>16 ) &0xFFFF ；

[0050] The formula for extracting the serial number is:

[0051] S＝ID&0xFFFF ;

[0052] Among them, ID is the sensor ID, P is the combination code, S is the serial number, and 0xFFFF is the complement code.

[0053] The present invention discloses a method for quickly accessing a sensor in an edge server, the method comprising: obtaining a sensor ID of a sensor; associating the sensor ID with a matching sensor parameter type model by analyzing the sensor ID; adding the matching sensor parameter type model to a sensor data processing model of the edge server; building a standardized sensor access mechanism through the sensor data processing model to connect the sensor to the edge server; when the sensor is connected, the edge server performs self-calibration and intelligent identification on the sensor; the edge server performs data analysis on the received sensor data based on the sensor data processing model. The present invention associates the sensor ID with a matching sensor parameter type model to build a standardized sensor access mechanism, thereby improving the efficiency of sensor access. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A flow chart of a method for quickly accessing a sensor in an edge server provided by the present invention is shown;

[0055] Figure 2 A flow chart showing a method for associating a sensor ID with a sensor parameter type model provided by the present invention is shown;

[0056] Figure 3 The flowchart of the method for self-calibration and intelligent identification of a sensor provided by the present invention is shown. DETAILED DESCRIPTION

[0057] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0058] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0059] Figure 1 A flow chart of a method for quickly accessing sensors in an edge server provided by the present invention is shown.

[0060] like Figure 1 As shown, the present invention discloses a method for quickly accessing a sensor in an edge server, comprising:

[0061] S102, obtaining a sensor ID of a sensor;

[0062] S104, by analyzing the sensor ID, associating the sensor ID with a matching sensor parameter type model;

[0063] S106, adding the matching sensor parameter type model to the sensor data processing model of the edge server;

[0064] S108, building a standardized sensor access mechanism through a sensor data processing model to connect the sensor to the edge server;

[0065] S110, when the sensor is connected, the edge server performs self-calibration and intelligent identification on the sensor;

[0066] S112, the edge server performs data analysis on the received sensor data based on the sensor data processing model.

[0067] According to an embodiment of the present invention, each sensor is uniquely identified by a sensor ID (including a type code and a serial number), and its corresponding data processing model, i.e., a sensor parameter type model, is generated according to the identification. The sensor parameter type model is obtained by training the historical detection data of various sensors stored in the edge server, and each sensor parameter type model is used to perform data analysis on the corresponding sensor data. The sensor data processing model of the edge server is a collection of data processing models of the edge server for the connected sensors. When the sensor is connected, no manual configuration is required. Through automatic identification and automatic matching, the sensor ID is associated with the matching sensor parameter type model, and the associated sensor parameter type model is added to the sensor data processing model of the edge server. Through the association of the sensor ID and the sensor parameter type model, a standardized sensor access mechanism is constructed to connect the sensor to the edge server, thereby avoiding the disadvantages of relying on manual configuration in the traditional way and realizing automatic access and configuration.

[0068] Among them, the data fields in the sensor data processing model include: sensor name, scene name, location information, online status, sensor ID, number of parameters, and the following fields of each parameter: parameter type, parameter name, parameter unit, data interval, high threshold, low threshold, high threshold enable, low threshold enable and numerical variable, etc.

[0069] The edge server can dynamically create an adaptive data access model and parsing framework, and realize automatic configuration and optimization of different sensors through intelligent algorithms or data learning mechanisms, thereby improving the flexibility and adaptability of the system, avoiding delays and errors caused by human intervention in traditional access methods, and realizing standardization and automation of sensor access. When a new sensor is connected, the data accuracy and parameter configuration of the sensor are automatically adjusted through self-calibration and intelligent recognition mechanisms to ensure accurate data collection and processing. Automatic matching and configuration of sensors are achieved through the system's preset intelligent algorithm, and the functional attributes of the sensor, such as the sensor's working range, data type (analog / digital), acquisition cycle and other parameters, are determined through the sensor ID code (including device type and serial number), and the parameter configuration is automatically optimized according to the needs of the scene after access. The system will automatically identify and match with the preset model, further enhancing the collaboration between devices and sensors.

[0070] In addition, in the IoT environment, sensors from different manufacturers may use different data formats or protocols. By associating the sensor ID with the matching sensor parameter type model, sensors with the same sensor ID use a unified sensor parameter type model. The edge server can ensure that all sensor data is in a unified format, reducing the difficulty of cross-manufacturer sensor access and ensuring system interoperability. It can not only simplify data parsing, but also easily adapt to different types of sensors through the data format conversion mechanism, supporting a wider range of device access.

[0071] After receiving the sensor data, the edge server selects a matching sensor parameter type model according to the sensor ID of the received sensor data for real-time data analysis, and stores the obtained real-time analysis data in the local database for subsequent data retrieval and analysis.

[0072] Figure 2 A flow chart showing a method for associating a sensor ID with a sensor parameter type model provided by the present invention is shown;

[0073] like Figure 2 As shown, according to an embodiment of the present invention, by analyzing the sensor ID, the sensor ID is associated with a matching sensor parameter type model, including:

[0074] S202, determining the sensor parameter type of the sensor by analyzing the sensor ID;

[0075] S204, searching the sensor parameter type model in the local database of the edge server according to the sensor parameter type to determine the sensor parameter type model that matches the sensor parameter type;

[0076] S206: Map the sensor parameter type to a matching sensor parameter type model.

[0077] It should be noted that the sensor parameter type of the sensor includes common sensor parameters such as temperature, humidity, and pressure. The sensor parameter ID of the sensor parameter type of the sensor is compared with the ID of the sensor parameter type model in the local database to find the sensor parameter type model with the same ID and determine it as the sensor parameter type model that matches the sensor parameter type.

[0078] Automatic identification and matching of sensor parameter types are achieved through sensor IDs, and sensor parameter types (such as temperature, humidity, pressure, etc.) are automatically mapped to matching sensor parameter type models without human intervention. Building a standardized sensor access mechanism based on the sensor parameter type model can improve the efficiency of sensor access and avoid configuration errors or delays caused by human intervention. It is particularly suitable for the rapid deployment and dynamic adjustment of large-scale, multi-type sensor networks.

[0079] According to an embodiment of the present invention, it also includes:

[0080] When the sensor corresponding to the sensor ID contains multiple parameter types, a sensor parameter type model matching each sensor parameter type is determined respectively;

[0081] Each sensor parameter type is mapped to a matching sensor data processing model.

[0082] It should be noted that the dynamic adaptation and management of multiple sensor parameters avoids the complexity of parameter configuration and improves the flexibility and scalability of the system. The multiple parameter types contained in the sensor ID are distinguished according to the sensor ID, and the matching sensor parameter type model is determined for each parameter type of sensor parameter ID in turn, and these parameter types are mapped to the matching sensor parameter type model respectively, for example, the temperature parameter and humidity parameter of the temperature and humidity sensor are mapped to the temperature parameter type model and the humidity parameter type model respectively.

[0083] According to an embodiment of the present invention, it also includes:

[0084] When the sensor is successfully matched with the edge server, the sensor data processing model is stored in the SPIFS file system;

[0085] The local web server, data algorithm module and MQTT cloud server access and use the sensor data processing model of the sensor through the SPIFS file system.

[0086] It should be noted that the generated sensor data model is stored in the SPIFS file system to ensure that the data is still available after power failure. The model can be accessed and used by the local web server, data algorithm model and MQTT cloud server at the same time. The data management process is unified to ensure the persistence and cross-module accessibility of model data, and improve the reliability and sharing efficiency of data.

[0087] Figure 3 The flowchart of the method for self-calibration and intelligent identification of a sensor provided by the present invention is shown.

[0088] like Figure 3 As shown, according to an embodiment of the present invention, when a sensor is connected, the edge server performs self-calibration and intelligent identification on the sensor, including:

[0089] S302, when the sensor is connected, the edge server performs sensor self-calibration on the sensor and evaluates and adjusts the sensor performance in real time;

[0090] S304, the edge server identifies the parameter type and data format of the sensor, and configures the data collection method and data collection frequency for the sensor.

[0091] It should be noted that when the sensor is connected to the edge server, the edge server automatically performs sensor self-calibration, that is, through real-time evaluation and adjustment of sensor performance, it automatically corrects possible deviations. For example, temperature sensors, humidity sensors, etc. may drift or have errors in different working environments. The system can dynamically adjust the output value of the sensor through the built-in self-calibration mechanism to ensure the accuracy of the sensor data.

[0092] In addition to calibration, the edge server can also intelligently identify the sensor parameter type and data format, such as temperature, humidity, pressure and other common sensor parameters, and automatically configure its data collection method and frequency. Through self-calibration and intelligent identification functions, manual intervention can be greatly reduced and the stability and accuracy of the system can be improved.

[0093] According to an embodiment of the present invention, it also includes:

[0094] When a new sensor is connected to the edge server, if the local database of the edge server does not have a sensor parameter type model that matches the sensor ID of the new sensor, the corresponding sensor data processing model is expanded according to the parameter characteristics of the new sensor;

[0095] The expanded sensor data processing model is added to the local database of the edge server.

[0096] It should be noted that the edge server supports the dynamic addition of new sensors. When a new sensor is connected to the edge server, its corresponding sensor parameter type model can be automatically expanded according to the parameter characteristics of the new sensor, so that the edge server can continue to evolve as the sensor types become richer. It has extremely high adaptability and can flexibly respond to diverse scenarios and needs, supporting the long-term expansion and iteration of the IoT system.

[0097] According to an embodiment of the present invention, the edge server performs data parsing on the received sensor data based on the sensor data processing model, including:

[0098] When the edge server receives the sensor data, it determines the sensor ID of the sensor data;

[0099] According to the sensor ID of the sensor data, a corresponding sensor data processing model is selected to parse the sensor data to obtain real-time parsed data;

[0100] Store real-time parsed data in a local database;

[0101] According to the scenario field matching, the specified local algorithm is input for local algorithm data, displayed on the web page icon, and received by the MQTT cloud server.

[0102] It should be noted that when the sensor is connected to the edge server, the sensor parameter type model that matches the sensor has been saved in the sensor data processing model of the edge server. When the edge server receives the sensor data, it will automatically parse the real-time data according to the sensor ID of the sensor data and the sensor parameter type model in the sensor data processing model to obtain real-time parsed data. The parsed real-time parsed data is used for historical data storage in the local database, and the local algorithm is specified according to the scene field matching. The local algorithm data is input, displayed on the web page icon, and received by the MQTT cloud server. This mechanism automatically identifies and matches the preset saved model, further enhancing the collaboration between devices and sensors.

[0103] The sensor data processing model works in collaboration with multiple modules (such as local Web, algorithm modules, cloud services, etc.), realizing the core data support function of edge computing. It opens up the path between local computing, remote management and cloud analysis of data, and enhances the integration capability of edge servers in the IoT system.

[0104] According to an embodiment of the present invention, it also includes:

[0105] The sensor ID is determined by encoding according to the sensor parameter type of the sensor, and the sensor ID is composed of a combination code P and a serial number S;

[0106] determining a physical parameter of the sensor according to a sensor parameter type of the sensor;

[0107] Assign a unique 16-bit code to each single physical parameter and combination of multiple physical parameters, and determine the combination code P of different sensor types;

[0108] Corresponding serial numbers S are set for different sensors of the same sensor type in turn.

[0109] It should be noted that the sensor ID is 4 bytes (32 bits) in total. The physical parameters include temperature, humidity, pressure, and light. The combination code P of different sensor types is determined according to the parameter combination coding rules. The parameter combination code P is the high 16-bit code. Its definition goal is to uniquely identify a single physical parameter or a combination of multiple physical parameters to ensure the uniformity and interoperability of sensor access.

[0110] For example, for single physical parameters, a unique code is assigned to each single physical parameter:

[0111] Temperature sensor: P = 0x0001;

[0112] Humidity sensor: P = 0x0002;

[0113] Pressure sensor: P = 0x0003;

[0114] Light sensor: P = 0x0004.

[0115] For multiple physical parameter combinations, a unique code is assigned to each physical parameter combination:

[0116] Temperature and humidity sensor: P = 0x0101;

[0117] Temperature, humidity and pressure sensor: P = 0x0102;

[0118] Temperature, humidity and light sensor: P = 0x0103.

[0119] When adding a new physical parameter or physical parameter combination, you only need to assign a new value from the existing coding range without changing the existing coding rules or structure. For example, the sensor ID of the temperature and humidity sensor is 0x010200A1, and its parameter combination code is 0x0102 (indicating a temperature and humidity sensor), and the serial number is 0x00A1.

[0120] According to an embodiment of the present invention, it also includes:

[0121] The formula for obtaining the sensor ID code is:

[0122]

[0123] The formula for extracting the combined code is:

[0124] P= ( ID>>16 ) &0xFFFF ；

[0125] The formula for extracting the serial number is:

[0126] S＝ID&0xFFFF ;

[0127] Among them, ID is the sensor ID, P is the combination code, S is the serial number, and 0xFFFF is the complement code.

[0128] It should be noted that the sensor ID code consists of a combination code P and a serial number S, where the combination code P is the upper 16 bits, indicating the parameter combination code, which is used to uniquely identify the sensor type. The serial number S is the lower 16 bits, indicating the serial number, which is used to distinguish different devices of the same type of sensor.

[0129] In the process of extracting the combined code, the high 16 bits are extracted by right shifting 16 bits to obtain the parameter combined code P.

[0130] In the process of extracting the serial number, the lower 16 bits are extracted through a bitwise AND operation to obtain the serial number S.

[0131] The information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals (including but not limited to signals transmitted between user terminals and other devices, etc.) involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions. For example, the "sensor ID of the sensor", "sensor parameter type model", etc. involved in this disclosure are all obtained with full authorization.

[0132] The present invention discloses a method for quickly accessing a sensor in an edge server, the method comprising: obtaining a sensor ID of a sensor; associating the sensor ID with a matching sensor parameter type model by analyzing the sensor ID; adding the matching sensor parameter type model to a sensor data processing model of the edge server; building a standardized sensor access mechanism through the sensor data processing model to connect the sensor to the edge server; when the sensor is connected, the edge server performs self-calibration and intelligent identification on the sensor; the edge server performs data analysis on the received sensor data based on the sensor data processing model. The present invention associates the sensor ID with a matching sensor parameter type model to build a standardized sensor access mechanism, thereby improving the efficiency of sensor access.

[0133] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0134] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0135] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0136] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0137] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A method for quickly accessing a sensor in an edge server, characterized in that: include: Get the sensor ID of the sensor; By analyzing the sensor ID, the sensor ID is associated with a matching sensor parameter type model; adding the matched sensor parameter type model to the sensor data processing model of the edge server; By using the sensor data processing model, a standardized sensor access mechanism is constructed to connect the sensor to the edge server; When a sensor is connected, the edge server performs self-calibration and intelligent identification on the sensor; The edge server performs data analysis on the received sensor data based on the sensor data processing model.

2. The method for rapid sensor access in an edge server according to claim 1, characterized in that: The analyzing the sensor ID and associating the sensor ID with a matching sensor parameter type model includes: Determining a sensor parameter type of the sensor by analyzing the sensor ID; Searching a sensor parameter type model in a local database of the edge server according to the sensor parameter type to determine a sensor parameter type model that matches the sensor parameter type; The sensor parameter type is mapped to a matching sensor parameter type model.

3. The method for rapid sensor access in an edge server according to claim 2, characterized in that: Also includes: When the sensor corresponding to the sensor ID includes multiple parameter types, determining a sensor parameter type model matching each sensor parameter type respectively; Each sensor parameter type is mapped to a matching sensor data processing model.

4. The method for rapid sensor access in an edge server according to claim 1, characterized in that: Also includes: When the sensor is successfully matched with the edge server, the sensor data processing model is stored in the SPIFS file system; The local Web server, the data algorithm module and the MQTT cloud server access and use the sensor data processing model of the sensor through the SPIFS file system.

5. The method for rapid sensor access in an edge server according to claim 1, characterized in that: When the sensor is connected, the edge server performs self-calibration and intelligent identification on the sensor, including: When a sensor is connected, the edge server performs sensor self-calibration on the sensor and evaluates and adjusts the sensor performance in real time; The edge server identifies the parameter type and data format of the sensor, and configures the data collection method and data collection frequency for the sensor.

6. The method for rapid sensor access in an edge server according to claim 1, characterized in that: Also includes: When a new sensor is connected to the edge server, if the local database of the edge server does not have a sensor parameter type model that matches the sensor ID of the new sensor, the corresponding sensor data processing model is expanded according to the parameter characteristics of the new sensor; The expanded sensor data processing model is added to the local database of the edge server.

7. The method for rapid sensor access in an edge server according to claim 1, characterized in that: The edge server performs data parsing on the received sensor data based on the sensor data processing model, including: When the edge server receives the sensor data, it determines the sensor ID of the sensor data; Selecting a corresponding sensor data processing model according to the sensor ID of the sensor data to parse the sensor data to obtain real-time parsed data; Storing the real-time parsed data in a local database; According to the scenario field matching, the specified local algorithm is input for local algorithm data, displayed on the web page icon, and received by the MQTT cloud server.

8. The method for rapid sensor access in an edge server according to claim 1, characterized in that: Also includes: Encoding according to the sensor parameter type of the sensor to determine the sensor ID, wherein the sensor ID is composed of a combination code P and a serial number S; determining a physical parameter of the sensor according to a sensor parameter type of the sensor; Assign a unique 16-bit code to each single physical parameter and combination of multiple physical parameters, and determine the combination code P of different sensor types; Corresponding serial numbers S are set for different sensors of the same sensor type in turn.

9. The method for rapid sensor access in an edge server according to claim 8, characterized in that: Also includes: The formula for obtaining the sensor ID code is: The formula for extracting the combined code is: P= ( ID>>16 ) &0xFFFF ； The formula for extracting the serial number is: S＝ID&0xFFFF ； Among them, ID is the sensor ID, P is the combination code, S is the serial number, and 0xFFFF is the complement code.

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