CN114323136A - Production environment monitoring method and system based on Internet of things - Google Patents
Production environment monitoring method and system based on Internet of things Download PDFInfo
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Abstract
The embodiment of the application discloses a production environment monitoring method and system based on the Internet of things. The production environment monitoring method based on the Internet of things comprises the following steps: determining original on-line production environment monitoring data and original detection data of at least one Internet of things production project in the original on-line production environment monitoring data; determining detection strength data of each Internet of things production item in at least one Internet of things production item in the original online production environment monitoring data according to the production environment quality index data and the original detection data of the at least one Internet of things production item; and according to the detection strength data of at least one Internet of things production project, updating the production environment quality of the original online production environment monitoring data to generate target production environment monitoring data.
Description
Technical Field
The application relates to the technical field of Internet of things and environmental monitoring, in particular to a production environment monitoring method and system based on the Internet of things.
Background
Nowadays, with the continuous development of the internet of things, the application field based on the internet of things is more and more extensive, however, in the actual process of responding to, how to accurately and effectively monitor the production environment is a technical problem that needs to be improved at present.
Disclosure of Invention
In order to solve the technical problems in the related art, the application provides a production environment monitoring method and system based on the Internet of things.
The application provides a production environment monitoring method based on the Internet of things, which comprises the following steps: determining original on-line production environment monitoring data and detection type production environment monitoring data corresponding to the original on-line production environment monitoring data; the detection type production environment monitoring data covers original detection data of at least one Internet of things production project in the original on-line production environment monitoring data; recording the production environment monitoring data on the original line and the detection type production environment monitoring data; determining a production environment concern label and production environment quality information through an environment monitoring model or through production interaction; optimizing an original detection evaluation value corresponding to original detection data of the at least one Internet of things production item through the production environment attention label to obtain an optimized detection evaluation value of each Internet of things production item in the at least one Internet of things production item; determining detection strength data of each Internet of things production project according to the production environment quality information and the optimized detection evaluation value of each Internet of things production project in the at least one Internet of things production project; and updating the production environment quality of the original on-line production environment monitoring data through the detection strength data of the at least one Internet of things production project to generate target production environment monitoring data.
Optionally, the optimizing, by the production environment attention tag, an original detection evaluation value corresponding to original detection data of the at least one internet of things production item to obtain an optimized detection evaluation value of each internet of things production item in the at least one internet of things production item includes: setting the optimized detection evaluation value of a first internet of things production item in the at least one internet of things production item as the comparison content of the original detection evaluation value of the first internet of things production item and the detection evaluation value of the focus type production node corresponding to the production environment attention label, and setting the optimized detection evaluation value of a second internet of things production item in the at least one internet of things production item as an empty set, wherein the original detection evaluation value of the first internet of things production item is larger than the detection evaluation value of the focus type production node, and the original detection evaluation value of the second internet of things production item is smaller than the detection evaluation value of the focus type production node.
Optionally, the optimizing, by the production environment attention tag, an original detection evaluation value corresponding to original detection data of the at least one internet of things production item to obtain an optimized detection evaluation value of each internet of things production item in the at least one internet of things production item includes: and setting the optimized detection evaluation value of each Internet of things production item as an evaluation value of a comparison result between the original detection evaluation value of the Internet of things production item and the detection evaluation value of the focused production node corresponding to the production environment attention label.
Optionally, the detection strength data includes a part of the production project; through the detection dynamics data of at least one thing networking production project, to production environment monitoring data carries out production environment quality update on the original online, generates target production environment monitoring data, includes: and taking part of the production items of the at least one Internet of things production item as network parameters of a set algorithm, and updating the production environment quality of the at least one Internet of things production item of the original on-line production environment monitoring data through a set mechanism to generate target production environment monitoring data.
The embodiment of the application also provides an Internet of things production environment monitoring system, which comprises a memory, a processor and a network module; wherein the memory, the processor, and the network module are electrically connected directly or indirectly; the processor reads the computer program from the memory and runs the computer program to realize the method.
The technical scheme provided by the embodiment of the application can have the following beneficial effects.
According to the embodiment, aiming at the on-line production environment monitoring data acquired in advance, the detection strength data can be determined for at least one internet of things production project in the on-line production environment monitoring data according to the production environment quality indexes determined for multiple times and the detection data corresponding to the on-line production environment monitoring data, then the production environment quality of the internet of things production project in the on-line production environment monitoring data is updated according to the determined detection strength data, and the target production environment monitoring data is generated, so that the target production environment monitoring data with higher quality can be obtained by adjusting the on-line production environment monitoring data.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart of a production environment monitoring method based on the internet of things according to an embodiment of the present application.
Fig. 2 is a schematic diagram of a hardware structure of an internet of things production environment monitoring system provided in an embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
Referring to fig. 1, an embodiment of the present application provides a schematic flow chart of a production environment monitoring method based on the internet of things, and the method may specifically include the following technical solutions recorded in steps 100 to 300.
Step 100, determining production environment monitoring data on an original line and detection type production environment monitoring data corresponding to the production environment monitoring data on the original line; the detection type production environment monitoring data covers original detection data of at least one Internet of things production project in the original on-line production environment monitoring data; and recording the production environment monitoring data on the original line and the detection type production environment monitoring data.
200, determining a production environment attention label and production environment quality information through an environment monitoring model or production interaction; and optimizing the original detection evaluation value corresponding to the original detection data of the at least one Internet of things production project through the production environment attention label to obtain the optimized detection evaluation value of each Internet of things production project in the at least one Internet of things production project.
For some exemplary embodiments, the optimizing the original detection evaluation value corresponding to the original detection data of the at least one internet of things production item through the production environment attention tag recorded in step 200 to obtain an optimized detection evaluation value of each internet of things production item in the at least one internet of things production item may specifically be described in the following two embodiments.
The first embodiment: setting the optimized detection evaluation value of a first internet of things production item in the at least one internet of things production item as the comparison content of the original detection evaluation value of the first internet of things production item and the detection evaluation value of the focus type production node corresponding to the production environment attention label, and setting the optimized detection evaluation value of a second internet of things production item in the at least one internet of things production item as an empty set, wherein the original detection evaluation value of the first internet of things production item is larger than the detection evaluation value of the focus type production node, and the original detection evaluation value of the second internet of things production item is smaller than the detection evaluation value of the focus type production node.
The second embodiment: and setting the optimized detection evaluation value of each Internet of things production item as an evaluation value of a comparison result between the original detection evaluation value of the Internet of things production item and the detection evaluation value of the focused production node corresponding to the production environment attention label.
For some exemplary embodiments, the recorded detection force data includes a part of the production project; through the detection dynamics data of at least one thing networking production project, right production environment quality is updated to the production environment monitoring data on the original line, generates target production environment monitoring data, specifically can include: and taking part of the production items of the at least one Internet of things production item as network parameters of a set algorithm, and updating the production environment quality of the at least one Internet of things production item of the original on-line production environment monitoring data through a set mechanism to generate target production environment monitoring data.
Step 300, determining detection strength data of each Internet of things production project according to the production environment quality information and the optimized detection evaluation value of each Internet of things production project in the at least one Internet of things production project; and updating the production environment quality of the original on-line production environment monitoring data through the detection strength data of the at least one Internet of things production project to generate target production environment monitoring data.
In summary, for the on-line production environment monitoring data acquired in advance, detection strength data can be determined for at least one internet of things production item in the on-line production environment monitoring data according to the production environment quality indexes determined for multiple times and detection data corresponding to the on-line production environment monitoring data, and then the production environment quality of the internet of things production item in the on-line production environment monitoring data is updated according to the determined detection strength data to generate target production environment monitoring data, so that target production environment monitoring data with high quality can be obtained by adjusting the on-line production environment monitoring data.
On the basis, please refer to fig. 2 in combination, the present application further provides a schematic diagram of a hardware structure of an internet of things production environment monitoring system 200, which specifically includes a memory 210, a processor 220, a network module 230, and a production environment monitoring device. The memory 210, the processor 220, and the network module 230 are electrically connected directly or indirectly to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 210 stores a production environment monitoring device including at least one software function module which can be stored in the memory 210 in the form of software or firmware (firmware), and the processor 220 executes the software program and the module stored in the memory 210.
The Memory 210 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 210 is used for storing a program, and the processor 220 executes the program after receiving an execution instruction.
The processor 220 may be an integrated circuit chip having data processing capabilities. The Processor 220 may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), and the like. The various methods, steps and logic blocks disclosed in embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The network module 230 is configured to establish a communication connection between the internet of things production environment monitoring system 200 and other communication terminal devices through a network, so as to implement transceiving operation of network signals and data. The network signal may include a wireless signal or a wired signal.
Further, a readable storage medium is provided, on which a program is stored, which when executed by a processor implements the method described above.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
It is well known to those skilled in the art that with the development of electronic information technology such as large scale integrated circuit technology and the trend of software hardware, it has been difficult to clearly divide the software and hardware boundaries of a computer system. As any of the operations may be implemented in software or hardware. Execution of any of the instructions may be performed by hardware, as well as by software. Whether a hardware implementation or a software implementation is employed for a certain machine function depends on non-technical factors such as price, speed, reliability, storage capacity, change period, and the like. Accordingly, it will be apparent to those skilled in the art of electronic information technology that a more direct and clear description of one embodiment is provided by describing the various operations within the embodiment. Knowing the operations to be performed, the skilled person can directly design the desired product based on considerations of said non-technical factors.
The present application may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present application.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present application may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry can execute computer-readable program instructions to implement aspects of the present application by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present application are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, by software, and by a combination of software and hardware are equivalent.
Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the application is defined by the appended claims.
Claims (5)
1. A production environment monitoring method based on the Internet of things is characterized by comprising the following steps:
determining original on-line production environment monitoring data and detection type production environment monitoring data corresponding to the original on-line production environment monitoring data; the detection type production environment monitoring data covers original detection data of at least one Internet of things production project in the original on-line production environment monitoring data; recording the production environment monitoring data on the original line and the detection type production environment monitoring data;
determining a production environment concern label and production environment quality information through an environment monitoring model or through production interaction; optimizing an original detection evaluation value corresponding to original detection data of the at least one Internet of things production item through the production environment attention label to obtain an optimized detection evaluation value of each Internet of things production item in the at least one Internet of things production item;
determining detection strength data of each Internet of things production project according to the production environment quality information and the optimized detection evaluation value of each Internet of things production project in the at least one Internet of things production project; and updating the production environment quality of the original on-line production environment monitoring data through the detection strength data of the at least one Internet of things production project to generate target production environment monitoring data.
2. The method according to claim 1, wherein the optimizing, by the production environment attention tag, an original detection evaluation value corresponding to original detection data of the at least one internet of things production item to obtain an optimized detection evaluation value of each internet of things production item of the at least one internet of things production item comprises:
setting the optimized detection evaluation value of a first internet of things production item in the at least one internet of things production item as the comparison content of the original detection evaluation value of the first internet of things production item and the detection evaluation value of the focus type production node corresponding to the production environment attention label, and setting the optimized detection evaluation value of a second internet of things production item in the at least one internet of things production item as an empty set, wherein the original detection evaluation value of the first internet of things production item is larger than the detection evaluation value of the focus type production node, and the original detection evaluation value of the second internet of things production item is smaller than the detection evaluation value of the focus type production node.
3. The method according to claim 1, wherein the optimizing, by the production environment attention tag, an original detection evaluation value corresponding to original detection data of the at least one internet of things production item to obtain an optimized detection evaluation value of each internet of things production item of the at least one internet of things production item comprises: and setting the optimized detection evaluation value of each Internet of things production item as an evaluation value of a comparison result between the original detection evaluation value of the Internet of things production item and the detection evaluation value of the focused production node corresponding to the production environment attention label.
4. The method of claim 3, wherein the test force data comprises a partial production project; through the detection dynamics data of at least one thing networking production project, to production environment monitoring data carries out production environment quality update on the original online, generates target production environment monitoring data, includes:
and taking part of the production items of the at least one Internet of things production item as network parameters of a set algorithm, and updating the production environment quality of the at least one Internet of things production item of the original on-line production environment monitoring data through a set mechanism to generate target production environment monitoring data.
5. The production environment monitoring system of the Internet of things is characterized by comprising a memory, a processor and a network module; wherein the memory, the processor, and the network module are electrically connected directly or indirectly; the processor implements the method of any one of claims 1-4 by reading the computer program from the memory and running it.
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