Production environment supervision method and system, terminal and storage medium

Abstract

The invention relates to the technical field of data processing, and particularly provides a production environment supervision method and system, a terminal and a storage medium, and the method comprises the steps: distributing a message queue for a monitoring device, and pushing the monitoring data of the monitoring device to the message queue; setting a theme for the monitoring device, binding a topic of the message queue for the theme, creating a data model under the theme, and associating the monitoring data to the data model; generating a theme table corresponding to the theme, and storing the monitoring data in the data model to the theme table; screening out abnormal monitoring data and generating an alarm task based on the monitoring data in the theme table and a corresponding GMP standard threshold value; and calling a target processing system to execute a processing program for the alarm task based on the task type of the alarm task and a preset corresponding relationship between the task type and the processing system. The method can ensure that the production process meets the GMP standard.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and specifically relates to a production environment supervision method, system, terminal and storage medium. Background Art

[0002] GMP is the international general name for "Good Manufacturing Practice for Pharmaceuticals". This practice is the basic principle for pharmaceutical production and quality management, and is applicable to the entire process of pharmaceutical preparation production and key processes in raw material production that affect the quality of finished products. GMP requires companies to establish a comprehensive quality management system that covers all factors that affect product quality, including production, control, product release, storage, and shipment. The focus is on reducing the risks of contamination, cross-contamination, confusion, and errors in the production process, and ensuring the continuous and stable production of drugs that meet the intended use and registration requirements. In the GMP standard, there are certain requirements for the production environment, but these requirements may vary depending on the specific regulations of different countries and regions and the types of products produced (such as drugs, food, cosmetics, etc.). Generally, the GMP standard requires that the production environment be maintained in a controlled state to ensure the quality and safety of the product.

[0003] Although the existing production environment control system can realize the automatic detection of environmental parameters, when there is a lot of environmental data to be detected, the independent control systems cannot coordinate the control, and there are problems such as data omission and non-traceability. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a production environment supervision method, system, terminal and storage medium to solve the above-mentioned technical problems.

[0005] In a first aspect, the present invention provides a production environment supervision method, comprising: Allocating a message queue for the monitoring device, and pushing the monitoring data of the monitoring device to the message queue; Setting a topic for the monitoring device, binding the topic of the message queue to the topic, creating a data model under the topic, and associating the monitoring data with the data model; Generate a topic table corresponding to the topic, and store the monitoring data in the data model into the topic table; Based on the monitoring data in the subject table and the corresponding GMP standard thresholds, filter out abnormal monitoring data and generate alarm tasks; Based on the task type of the alarm task and the preset correspondence between the task type and the processing system, the target processing system is called to execute a processing program for the alarm task.

[0006] In an optional implementation, allocating a message queue to a monitoring device and pushing monitoring data of the monitoring device to the message queue includes: Identify new monitoring devices through the Internet of Things; The data content that defines the MQTT message queue topic includes: monitoring type, monitoring value and monitoring location.

[0007] In an optional implementation, the data model includes: The fields in the data table to be generated; The Chinese meaning of the identification data item, wherein the identification data item includes temperature and humidity; The field type specified when constructing the table field, the field type matches the raw data of the monitoring device; a default value to use when a data item in the original data is empty; The fields in the original data are associated with the associated paths in the data model, where the associated paths use json paths.

[0008] In an optional implementation, generating a topic table corresponding to the topic, and storing the monitoring data in the data model into the topic table, includes: Data analysis and data extraction are performed on the data model under the same theme, and the extracted data is saved in the theme table.

[0009] In an optional implementation, based on the task type of the alarm task and the preset correspondence between the task type and the processing system, calling the target processing system to execute a processing program for the alarm task includes: Extracting a task type and an alarm location from the alarm task, wherein the task type includes temperature exceeding a threshold, humidity exceeding a threshold, and an emergency accident type; Acquire a processing system of a target type according to the task type and the corresponding relationship, wherein the types of the processing system include a temperature control system, a humidity control system, and a system for emergency production stop; A target processing system is screened out from processing systems of the target type according to the alarm position, and a control instruction for the target processing system is generated based on the abnormal monitoring data.

[0010] In a second aspect, the present invention provides a production environment monitoring system, comprising: A data push module, used to allocate a message queue to a monitoring device and push the monitoring data of the monitoring device to the message queue; A data association module, used to set a topic for the monitoring device, bind the topic to the title of the message queue, create a data model under the topic, and associate the monitoring data with the data model; A data storage module, used to generate a topic table corresponding to the topic, and store the monitoring data in the data model into the topic table; The abnormal screening module is used to screen abnormal monitoring data and generate alarm tasks based on the monitoring data in the subject table and the corresponding GMP standard threshold; The exception handling module is used to call the target processing system to execute the processing program for the alarm task based on the task type of the alarm task and the preset corresponding relationship between the task type and the processing system.

[0011] In an optional implementation, the data push module includes: A device identification unit, used to identify newly added monitoring devices through the Internet of Things; The queue setting unit is used to define the data content of the MQTT message queue topic, including: monitoring type, monitoring value and monitoring location.

[0012] In an optional implementation, the data model includes: The fields in the data table to be generated; The Chinese meaning of the identification data item, wherein the identification data item includes temperature and humidity; The field type specified when constructing the table field, the field type matches the raw data of the monitoring device; a default value to use when a data item in the original data is empty; The fields in the original data are associated with the associated paths in the data model, where the associated paths use json paths.

[0013] In a third aspect, a terminal is provided, including: processor, memory, wherein: The memory is used to store computer programs. The processor is used to call and run the computer program from the memory, so that the terminal executes the above-mentioned terminal method.

[0014] According to a fourth aspect, a computer storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the computer executes the methods described in the above aspects.

[0015] The beneficial effects of the present invention are that the production environment supervision method, system, terminal and storage medium provided by the present invention include the following advantages: Improved compliance: This approach ensures that the manufacturing process complies with GMP standards, helps pass audits and inspections by regulatory agencies, and reduces compliance risks; Real-time monitoring and early warning: The system can monitor various indicators of the production environment in real time, such as temperature, humidity, cleanliness, etc. Once the indicators deviate from the specified range, an early warning will be issued immediately so that timely measures can be taken; Reduce human errors: Automated data collection and analysis reduces reliance on manual operations, thereby reducing errors caused by human factors; Improve efficiency and productivity: Automated monitoring and early warning systems can improve production efficiency, reduce production interruptions caused by environmental problems, and improve overall productivity; Data integrity and traceability: The system records all relevant monitoring data to ensure data integrity and traceability, facilitating post-analysis and auditing; Cost savings: Although the initial investment may be high, in the long run, the automated monitoring and early warning system can reduce product losses caused by environmental out-of-control and save costs; Enhanced quality control: The system helps to more tightly control the production environment, thereby improving product quality and consistency; Improved decision making: Providing accurate environmental monitoring data helps management and engineers better understand the production process and make more informed decisions.

[0016] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.

[0019] Figure 2 It is a hierarchical diagram of the device-subject-data model of the method according to an embodiment of the present invention.

[0020] Figure 3 is a schematic block diagram of a system according to an embodiment of the present invention.

[0021] Figure 4 A schematic diagram of the structure of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0024] The production environment monitoring method provided in the embodiment of the present invention is executed by a computer device, and accordingly, the production environment monitoring system runs in the computer device.

[0025] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. Figure 1 The execution subject may be a production environment supervision system. According to different requirements, the order of the steps in the flowchart may be changed, and some may be omitted.

[0026] like Figure 1 As shown, the method includes: Step 110, allocating a message queue for the monitoring device, and pushing the monitoring data of the monitoring device to the message queue; Step 120, setting a topic for the monitoring device, binding the topic of the message queue to the topic, creating a data model under the topic, and associating the monitoring data with the data model; Step 130, generating a topic table corresponding to the topic, and storing the monitoring data in the data model into the topic table; Step 140, based on the monitoring data in the subject table and the corresponding GMP standard threshold, filter out abnormal monitoring data and generate an alarm task; Step 150 , based on the task type of the alarm task and the preset correspondence between the task type and the processing system, call the target processing system to execute the processing program for the alarm task.

[0027] To facilitate understanding of the present invention, the production environment supervision method provided by the present invention is further described below based on the principle of the production environment supervision method of the present invention and in combination with the process of supervising the production environment in the embodiment.

[0028] Specifically, the production environment supervision methods include: S1. Allocate a message queue for a monitoring device, and push monitoring data of the monitoring device to the message queue.

[0029] Identify newly added monitoring devices through the Internet of Things; define the data content of the MQTT message queue topic including: monitoring type, monitoring value and monitoring location. MQTT (Message Queue Telemetry Transport) is a client-server based message publish / subscribe transmission protocol. The MQTT protocol is lightweight, simple, open and easy to implement, which makes it very widely applicable. In many cases, including restricted environments such as machine-to-machine (M2M) communication and the Internet of Things (IoT). It has been widely used in sensors communicating via satellite links, medical devices that occasionally dial up, smart homes, and some miniaturized devices.

[0030] Specifically, the monitoring device includes a temperature sensor, a humidity sensor, a gas detection sensor, a camera, etc. When identifying a newly added monitoring device, the device code of the identified monitoring device is compared with the device code in the list of identified devices. If the device code does not exist in the list of identified devices, the monitoring device is determined to be a newly added monitoring device. If the device code exists in the list of identified devices, the monitoring device is determined to be an identified monitoring device, and there is no need to allocate a message queue for it.

[0031] S2. Setting a topic for the monitoring device, binding the topic to the title of the message queue, creating a data model under the topic, and associating the monitoring data to the data model.

[0032] After creating the device, you need to create a topic in the system device according to its queue. This topic mainly covers the following information: 1. The message queue topic or queue name to subscribe to.

[0033] 2. The name of the data table where the device data needs to be stored.

[0034] After establishing the topic for receiving data, you need to establish a data model based on the message queue data format.

[0035] The data model includes: fields in the data table to be generated; the Chinese meaning of the identification data items, the identification data items include temperature and humidity; the field type specified when constructing the table field, the field type matches the original data of the monitoring device; the default value used when the data item in the original data is empty; the field in the original data is associated with the association path in the data model, and the association path uses a json path.

[0036] After identifying a new monitoring device, you only need to understand the fields in the queue message. You can connect to the new monitoring device by creating a device, creating a topic-bound queue, and building a data model based on the message fields.

[0037] like Figure 2 As shown, a soil temperature sensor at a base is connected. The sensor transmits data using MQTT, topic: / get, message body: {"records":{ "temperature":22, "moisture":23}} Based on this information, you can create a device in the system, the device name is "soil temperature sensor", create a topic under the device, and bind the topic to its MQTT topic. Then create temperature and humidity data models in this topic. The data model needs to use the "association path" mentioned above to establish an association relationship with the fields in the original data. For example, the association path for temperature is records.temperature, and the association path for humidity is records.moisture. No matter how many nested levels of JSON are, the data items of the original data can be mapped through the association path.

[0038] S3. Generate a topic table corresponding to the topic, and store the monitoring data in the data model into the topic table.

[0039] After the device, topic, and data model are created, the corresponding data table, namely the topic table, will be generated based on the relevant information.

[0040] When the original data of the device flows into the system through the message queue, the system first finds the related topic in the system according to the queue name / topic, and then parses and extracts the data according to the data model configured in the topic. Finally, the data is stored in the topic table of the relevant device.

[0041] S4. Based on the monitoring data in the subject table and the corresponding GMP standard threshold, filter out abnormal monitoring data and generate an alarm task.

[0042] After the equipment is installed and connected to the system, it is necessary to set the allowable range for the data model of various sensor devices according to the department and workshop environment specifications. Depending on the requirements, the threshold can be configured by level.

[0043] For example, a temperature sensor in a department can be set to threshold 1, with an optimum temperature of 5-10 degrees Celsius. Threshold 2, above 10 degrees Celsius and below 15 degrees Celsius. Threshold 3, above 15 degrees Celsius, etc. Each type of threshold can be configured with different alarm information templates according to the severity. It is used to issue alarms to users after exceeding the threshold range.

[0044] For example, behavior cameras can be set to prohibit various behaviors, such as smoking. Threshold limits can be set for human behavior based on the scenario.

[0045] S5. Based on the task type of the alarm task and the preset correspondence between the task type and the processing system, call the target processing system to execute a processing program for the alarm task.

[0046] A task type and an alarm position are extracted from the alarm task, wherein the task type includes temperature exceeding a threshold, humidity exceeding a threshold, and emergency accident type; a processing system of a target type is acquired according to the task type and the corresponding relationship, wherein the types of the processing systems include temperature control systems, humidity control systems, and systems for emergency production stop; a target processing system is screened out from the processing systems of the target type according to the alarm position, and a control instruction for the target processing system is generated based on the abnormal monitoring data.

[0047] Specifically, in various production scenarios, the Internet of Things can be used to set linkage effects for equipment to save labor costs.

[0048] The temperature sensor is linked to the temperature control system to ensure that the temperature of the production environment is kept within the specified range. The humidity sensor is linked to the humidity control system to control the humidity of the production environment.

[0049] When the temperature, humidity or other key parameters of the production environment exceed the preset range, the sensor triggers the alarm system to notify the operator to take action.

[0050] The alarm system can also be linked with the automatic control system to automatically adjust environmental parameters.

[0051] Sensors and data management systems: The data collected by sensors are processed and analyzed through the data management system, and compared with production plans and quality standards to ensure the linkage between the safety system and the production system: in emergency situations such as fire, chemical leakage, etc., valves are automatically closed and power is cut off to ensure the safety of personnel and the environment is not polluted.

[0052] Linkage between production equipment and waste treatment system: Waste generated during the production process needs to be classified and treated through the waste treatment system to ensure compliance with environmental regulations.

[0053] In practical applications, the specific data processing flow includes: 1. Each scene workshop collects data regularly and uploads it to the platform; 2. The platform records various production data in real time and monitors various data; 3. If the sensor data exceeds the threshold range, an alarm can be issued to relevant staff according to the alarm message template configuration; 4. If the scene is set with device linkage effect, when the relevant equipment and personnel behavior are detected, instructions are issued to other devices for linkage response; 5. The platform regularly summarizes data, makes trend analysis, and reports on equipment and personnel that show signs of violations.

[0054] In some embodiments, the production environment monitoring system may include multiple functional modules composed of computer program segments. The computer programs of each program segment in the production environment monitoring system may be stored in a memory of a computer device and executed by at least one processor to perform (see Figure 1 Description) Function of production environment supervision.

[0055] In this embodiment, the production environment monitoring system can be divided into multiple functional modules according to the functions it performs, such as Figure 3 As shown. The functional modules of the system 300 may include: a data push module 310, a data association module 320, a data storage module 330, an exception screening module 340 and an exception handling module 350. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0056] A data push module, used to allocate a message queue to a monitoring device and push the monitoring data of the monitoring device to the message queue; A data association module, used to set a topic for the monitoring device, bind the topic to the title of the message queue, create a data model under the topic, and associate the monitoring data with the data model; A data storage module, used to generate a topic table corresponding to the topic, and store the monitoring data in the data model into the topic table; The abnormal screening module is used to screen abnormal monitoring data and generate alarm tasks based on the monitoring data in the subject table and the corresponding GMP standard threshold; The exception handling module is used to call the target processing system to execute the processing program for the alarm task based on the task type of the alarm task and the preset corresponding relationship between the task type and the processing system.

[0057] Optionally, as an embodiment of the present invention, the data push module includes: A device identification unit, used to identify newly added monitoring devices through the Internet of Things; The queue setting unit is used to define the data content of the MQTT message queue topic, including: monitoring type, monitoring value and monitoring location.

[0058] Optionally, as an embodiment of the present invention, the data model includes: The fields in the data table to be generated; The Chinese meaning of the identification data item, wherein the identification data item includes temperature and humidity; The field type specified when constructing the table field, the field type matches the raw data of the monitoring device; a default value to use when a data item in the original data is empty; The fields in the original data are associated with the associated paths in the data model, where the associated paths use json paths.

[0059] Figure 4 The present invention provides a schematic diagram of the structure of a terminal 400 provided in an embodiment of the present invention. The terminal 400 can be used to execute the production environment monitoring method provided in an embodiment of the present invention.

[0060] The terminal 400 may include: a processor 410, a memory 420 and a communication unit 430. These components communicate via one or more buses. Those skilled in the art will appreciate that the server structure shown in the figure does not limit the present invention, and it may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0061] The memory 420 can be used to store the execution instructions of the processor 410, and the memory 420 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. When the execution instructions in the memory 420 are executed by the processor 410, the terminal 400 can perform some or all of the steps in the following method embodiments.

[0062] The processor 410 is the control center of the storage terminal, and uses various interfaces and lines to connect various parts of the entire electronic terminal. It runs or executes software programs and / or modules stored in the memory 420, and calls data stored in the memory to perform various functions of the electronic terminal and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 410 can include only a central processing unit (CPU). In the embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0063] The communication unit 430 is used to establish a communication channel so that the storage terminal can communicate with other terminals, receive user data sent by other terminals or send user data to other terminals.

[0064] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0065] Therefore, the present invention can ensure that the production process complies with GMP standards, help pass audits and inspections by regulatory agencies, and reduce compliance risks. The technical effects that can be achieved by this embodiment can be found in the description above and will not be repeated here.

[0066] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present invention, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes, including several instructions for enabling a computer terminal (which can be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0067] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

[0068] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, which can be electrical, mechanical or other forms.

[0069] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0070] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0071] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. A production environment supervision method, characterized in that: include: Allocating a message queue for the monitoring device, and pushing the monitoring data of the monitoring device to the message queue; Setting a topic for the monitoring device, binding the topic of the message queue to the topic, creating a data model under the topic, and associating the monitoring data with the data model; Generate a topic table corresponding to the topic, and store the monitoring data in the data model into the topic table; Based on the monitoring data in the subject table and the corresponding GMP standard thresholds, filter out abnormal monitoring data and generate alarm tasks; Based on the task type of the alarm task and the preset correspondence between the task type and the processing system, the target processing system is called to execute a processing program for the alarm task.

2. The method according to claim 1, characterized in that Allocating a message queue to a monitoring device and pushing monitoring data of the monitoring device to the message queue includes: Identify new monitoring devices through the Internet of Things; The data content that defines the MQTT message queue topic includes: monitoring type, monitoring value and monitoring location.

3. The method according to claim 1, characterized in that The data model includes: The fields in the data table to be generated; The Chinese meaning of the identification data item, wherein the identification data item includes temperature and humidity; The field type specified when constructing the table field, the field type matches the raw data of the monitoring device; a default value to use when a data item in the original data is empty; The fields in the original data are associated with the associated paths in the data model, where the associated paths use json paths.

4. The method according to claim 1, characterized in that: Generating a topic table corresponding to the topic, and storing the monitoring data in the data model into the topic table, including: Data analysis and data extraction are performed on the data model under the same theme, and the extracted data is saved in the theme table.

5. The method according to claim 1, characterized in that Based on the task type of the alarm task and the preset correspondence between the task type and the processing system, calling the target processing system to execute a processing program for the alarm task includes: Extracting a task type and an alarm location from the alarm task, wherein the task type includes temperature exceeding a threshold, humidity exceeding a threshold, and an emergency accident type; Acquire a processing system of a target type according to the task type and the corresponding relationship, wherein the types of the processing system include a temperature control system, a humidity control system, and a system for emergency production stop; A target processing system is screened out from processing systems of the target type according to the alarm position, and a control instruction for the target processing system is generated based on the abnormal monitoring data.

6. A production environment monitoring system, characterized in that: include: A data push module, used to allocate a message queue to a monitoring device and push the monitoring data of the monitoring device to the message queue; A data association module, used to set a topic for the monitoring device, bind the topic to the title of the message queue, create a data model under the topic, and associate the monitoring data with the data model; A data storage module, used to generate a topic table corresponding to the topic, and store the monitoring data in the data model into the topic table; The abnormal screening module is used to screen abnormal monitoring data and generate alarm tasks based on the monitoring data in the subject table and the corresponding GMP standard threshold; The exception handling module is used to call the target processing system to execute the processing program for the alarm task based on the task type of the alarm task and the preset corresponding relationship between the task type and the processing system.

7. The system according to claim 6, characterized in that The data push module includes: A device identification unit, used to identify newly added monitoring devices through the Internet of Things; The queue setting unit is used to define the data content of the MQTT message queue topic, including: monitoring type, monitoring value and monitoring location.

8. The system according to claim 6, characterized in that The data model includes: The fields in the data table to be generated; The Chinese meaning of the identification data item, wherein the identification data item includes temperature and humidity; The field type specified when constructing the table field, the field type matches the raw data of the monitoring device; a default value to use when a data item in the original data is empty; The fields in the original data are associated with the associated paths in the data model, where the associated paths use json paths.

9. A terminal, characterized in that: include: A memory device for storing production environment supervision programs; A processor, used to implement the steps of the production environment supervision method as described in any one of claims 1-5 when executing the production environment supervision program.

10. A computer-readable storage medium storing a computer program, characterized in that: The readable storage medium stores a production environment monitoring program, and when the production environment monitoring program is executed by the processor, the steps of the production environment monitoring method according to any one of claims 1 to 5 are implemented.

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