CN113554850A - 5G network real-time early warning method and system - Google Patents
5G network real-time early warning method and system Download PDFInfo
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Abstract
The invention discloses a 5G network real-time early warning method and a system, wherein the method is applied to a chemical laboratory management system, the system is in communication connection with an intelligent camera, and the method comprises the following steps: acquiring first gas detection information of a first divided area according to first image information of a first intelligent camera and a first chemical laboratory; constructing a first chemical gas identification library; obtaining a first library of matching categories of the first gas detection information; obtaining a first matching code based on the first matching category library; constructing a first real-time early warning signal library; according to the first matching codes, corresponding first matching early warning frequencies are obtained and combined with a preset response period to generate first matching early warning signals; and sending the first matching early warning signal to the chemical room management system for early warning. The method solves the technical problems that the early warning method in the prior art is not rapid enough and the early warning response has certain time delay.
Description
Technical Field
The invention relates to the related field of early warning, in particular to a 5G network real-time early warning method and system.
Background
The chemical laboratory is an important place for specially providing chemical experimental conditions and carrying out scientific exploration. Chemical laboratories are usually equipped with chemical cabinets, in which the usual chemicals are contained. The dangerous degree of chemistry experiment room is high because there are a large amount of chemical hazardous articles in it, consequently, the dangerous accident takes place for the prevention chemistry experiment room, will strengthen the safeguard measure of this aspect to the emergence of dangerous accident is prevented to the mode of early warning.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
the early warning method in the prior art is not rapid enough, and the early warning response has the technical problem of certain time delay.
Disclosure of Invention
The embodiment of the application provides a 5G network real-time early warning method and a system, solves the technical problems that an early warning method in the prior art is not rapid enough and early warning response has certain time delay, and achieves the technical effects of realizing multi-level flexible early warning through characteristics based on a 5G network and further improving real-time performance and intelligence of early warning.
In view of the foregoing problems, the embodiments of the present application provide a method and a system for real-time early warning of a 5G network.
In a first aspect, an embodiment of the present application provides a 5G network real-time warning method, where the method is applied to a chemical laboratory management system, the system is in communication connection with an intelligent camera, and the method includes: acquiring first image information of a first chemical laboratory according to a first intelligent camera; acquiring first gas detection information of a first divided area according to the first image information; constructing a first chemical gas identification library; classifying the gas in the first chemical gas identification library according to the multi-attribute information to obtain a multi-class gas identification library; obtaining a first matching category library by matching the first gas detection information with the multi-category gas identification library; obtaining a first matching code based on the first matching category library, wherein the first matching code is a code corresponding to the first matching category library; constructing a first real-time early warning signal library; obtaining a first matching early warning attribute of the first matching code based on the first real-time early warning signal library; generating a first matching early warning signal according to the first matching early warning attribute; and sending the first matching early warning signal to the chemical room management system for early warning.
On the other hand, this application still provides a real-time early warning system of 5G network, the system includes: the first obtaining unit is used for obtaining first image information of a first chemical laboratory according to a first intelligent camera; a second obtaining unit, configured to obtain first gas detection information of a first partition area according to the first image information; a first building unit for building a first chemical gas identification library; a third obtaining unit, configured to classify the gas in the first chemical gas identification library according to multi-attribute information, so as to obtain a multi-class gas identification library;
a fourth obtaining unit, configured to obtain a first matching category library by matching the first gas detection information with the multi-category gas identification library; a fifth obtaining unit, configured to obtain a first matching code based on the first matching category library, where the first matching code is a code corresponding to the first matching category library; the second construction unit is used for constructing a first real-time early warning signal library; a sixth obtaining unit, configured to obtain a first matching early warning attribute of the first matching code based on the first real-time early warning signal library; the first generating unit is used for generating a first matching early warning signal according to the first matching early warning attribute; and the first sending unit is used for sending the first matching early warning signal to a chemical room management system for early warning.
In a third aspect, the present invention provides a 5G network real-time warning system, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
because the intelligent camera is adopted to collect the image in the first chemical chamber, the collected influence information is frozen and analyzed, and then detecting the divided areas by a gas detector to obtain first gas detection information, and then the matching of the corresponding codes is completed according to a first matching category library corresponding to the first gas detection information obtained by tree-like hierarchical division of chemical gas in advance, further, the early warning frequency represented by the digital sequence in the corresponding codes and the early warning response time attribute and the like are combined to generate matched early warning signals, and then the generated first matching early warning signals are sent to a chemical room management system for early warning, so that the technical effects of realizing multi-level flexible early warning through the characteristics based on a 5G network and further improving the real-time performance and intelligence of the early warning are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flowchart of a 5G network real-time warning method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a 5G network real-time warning system according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a first constructing unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a fifth obtaining unit 16, a second constructing unit 17, a sixth obtaining unit 18, a first generating unit 19, a first transmitting unit 20, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 305.
Detailed Description
The embodiment of the application provides a 5G network real-time early warning method and a system, solves the technical problems that an early warning method in the prior art is not rapid enough and early warning response has certain time delay, and achieves the technical effects of realizing multi-level flexible early warning through characteristics based on a 5G network and further improving real-time performance and intelligence of early warning. Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
Summary of the application
The chemical laboratory is an important place for specially providing chemical experimental conditions and carrying out scientific exploration. Chemical laboratories are usually equipped with chemical cabinets, in which the usual chemicals are contained. The dangerous degree of chemistry experiment room is high because there are a large amount of chemical hazardous articles in it, consequently, the dangerous accident takes place for the prevention chemistry experiment room, will strengthen the safeguard measure of this aspect to the emergence of dangerous accident is prevented to the mode of early warning. However, the early warning method in the prior art is not rapid enough, and the early warning response has a certain time delay.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides a 5G network real-time early warning method, which is applied to a chemical laboratory management system, wherein the system is in communication connection with an intelligent camera, and the method comprises the following steps: acquiring first image information of a first chemical laboratory according to a first intelligent camera; acquiring first gas detection information of a first divided area according to the first image information; constructing a first chemical gas identification library; classifying the gas in the first chemical gas identification library according to the multi-attribute information to obtain a multi-class gas identification library; obtaining a first matching category library by matching the first gas detection information with the multi-category gas identification library; obtaining a first matching code based on the first matching category library, wherein the first matching code is a code corresponding to the first matching category library; constructing a first real-time early warning signal library; obtaining a first matching early warning attribute of the first matching code based on the first real-time early warning signal library; generating a first matching early warning signal according to the first matching early warning attribute; and sending the first matching early warning signal to the chemical room management system for early warning.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides a 5G network real-time warning method, where the method is applied to a chemical laboratory management system, the system is in communication connection with an intelligent camera, and the method includes:
step S100: acquiring first image information of a first chemical laboratory according to a first intelligent camera;
particularly, first intelligent camera is the camera of intelligent collection image, can carry out multi-angle and diversified intelligent change, for example when having taken place in a certain region some chemical reaction and having under the condition of dynamic change, first intelligent camera can intelligent change direction and angle, and then reach the influence information that corresponds with clear collection. The first chemical laboratory is a chemical laboratory applied to the 5G network real-time early warning system or an indoor chemical supply storage system in a chemical plant, and the first image information is image information such as indoor medicine storage areas acquired by indoor corresponding image acquisition according to the first intelligent camera.
Step S200: acquiring first gas detection information of a first divided area according to the first image information;
specifically, the first divided area is one of the medicine storage areas obtained by performing area analysis according to the collected first image information, wherein the first divided area needs to be classified or stored at intervals to form a corresponding certain area, such as a chemical storage cabinet, a chemical reagent, a semi-finished product of an operation console, and the like, because there are many chemical stored articles, the first gas detection information is gas information obtained by performing gas detection according to a gas detector existing in the first divided area, and specific detection information such as gas concentration, gas composition, gas attribute and the like, so that the first gas detection information is further subjected to detailed analysis, and a basis of data analysis is provided for later early warning.
Step S300: constructing a first chemical gas identification library;
step S400: classifying the gas in the first chemical gas identification library according to the multi-attribute information to obtain a multi-class gas identification library;
specifically, the first chemical gas identification library is constructed based on a chemical gas identification library which is correspondingly generated by identifying the information of the types of chemicals and the like in the first chemical laboratory, further, the multi-attribute information is generated by classifying and storing all the information based on all the attribute information in the chemical gas, such as whether the chemical gas identification library has various attribute information of danger, dangerous degree, corrosiveness, inflammability, toxicity and the like, further, the multi-class gas identification library is formed, further, the chemical gas in multiple classes is generated by classifying and storing and identifying the attributes of the first chemical gas identification library, the detected gas can be identified specifically, the system response speed is improved, and based on the characteristics of high transmission speed and high response speed in a 5G network, the delayed response time of the system can be reduced on the basis of data processing, thereby improving the technical effect of early warning timeliness.
Step S500: obtaining a first matching category library by matching the first gas detection information with the multi-category gas identification library;
specifically, the first matching category library performs multiple judgments according to the attribute information of the first gas detection information, and corresponding matching categories obtained from corresponding levels in the multi-category gas identification library, for example, when the concentration in the gas detector reaches a certain standard, indicating that leakage has occurred at the time when the concentration of the gas is high, further performs multiple attribute judgments on the leaked gas, and then generates a corresponding matching category library.
Step S600: obtaining a first matching code based on the first matching category library, wherein the first matching code is a code corresponding to the first matching category library;
specifically, the first matching code is code information generated after correspondence is performed on the basis of the first matching category library, wherein the first matching code is a set code of 3 sequence numbers, each sequence number represents a matching library of a certain category, for example, a leaked chemical gas is judged to have a toxic attribute, the first dangerous gas library is matched on the basis of danger, the first toxic gas library is matched on the basis of toxicity, and the gas library cannot be interfered by personnel interference, wherein each matched gas library corresponds to a specific code, and the first matching code is generated on the basis of a gas attribute, so that real-time analysis and monitoring on the basis of accurate gas attribute are achieved, the gas is classified, coded and stored, corresponding representative code information is generated, and real-time information, and real-time information for later early warning are provided, Effective basic conditions.
Step S700: constructing a first real-time early warning signal library;
specifically, the construction of the first real-time early warning signal library is based on the setting of the early warning signal corresponding to the codes of the corresponding numbers in all the corresponding category identification libraries, and further, the first real-time early warning signal library comprises the matching settings of the early warning mode, the early warning frequency, the early warning period, the early warning response tone, the early warning color and the like, so that the corresponding information in the first real-time early warning signal library is set based on all the coding information. For example, for the toxic hazardous gas in the above example, the frequency and decibel of the warning may be set based on the gas hazard, and some warning response mode may be set based on the toxicity, such as one of long horn, intermittent horn, and regular horn; the construction is specifically carried out on the basis that the pre-warning color can be preset to be red and the like on the basis of unsuitable personnel processing.
Step S800: obtaining a first matching early warning attribute of the first matching code based on the first real-time early warning signal library;
step S900: generating a first matching early warning signal according to the first matching early warning attribute;
specifically, the first matching code obtained by analyzing the first gas detection information corresponds to a number sequence, on the basis of constructing the first real-time early warning signal library, acquiring early warning attribute information corresponding to the first matching code, namely, the response color, the response frequency, the early warning mode and other information, wherein, as each sequence number in the first matching code corresponds to certain early warning attribute information, the first match alert signal may be generated for transmission in response to the first match alert attribute, wherein, on the basis of 5G, the large data quantitative transmission and low time delay can be realized, the data information corresponding to the first matching early warning attribute can be transmitted and responded in time, therefore, the technical effect of improving the early warning real-time performance on the basis of improving the intellectualization and the individuation is achieved.
Step S1000: and sending the first matching early warning signal to the chemical room management system for early warning.
Particularly, because the chemical room management system is the total control system that carries out the integrated management to the chemical room, wherein, not only can accurately grasp the chemical gas attribute information who reveals at present after receiving first matching early warning signal, simultaneously chemical room management system also can be according to first matching early warning signal control the linkage of external equipment such as exhaust facility, solenoid valve, exhaust fan, alarm bell, early warning signal lamp among the first chemical experiment to reached and realized the nimble early warning of multilayer level through the characteristic based on 5G network, and then promoted real-time, intelligent technological effect of early warning.
Further, after generating a first matching early warning signal according to the first matching early warning attribute, step S900 in this embodiment of the present application further includes:
step S910: obtaining multi-gas detection information of a plurality of divided areas;
step S920: acquiring multiple matching early warning signals corresponding to the multiple gas detection information;
step S930: inputting the multi-gas detection information and the multi-matching early warning signals into an early warning signal detection model to obtain a first precision coefficient;
step S940: judging whether the first precision coefficient is in a preset precision coefficient threshold value or not;
step S950: and if the first precision coefficient is in the preset precision coefficient threshold value, obtaining a first sending instruction.
Specifically, the multi-gas detection information and the multi-matching early warning signal are data information which is simulated for multiple times when the model performs precision inspection, the early warning signal detection model is a detection model for detecting the precision of the early warning signal, a large amount of data based on the multi-gas detection information and the multi-matching early warning signal is used as a support and then input into the early warning signal detection model for data analysis, so that the first precision coefficient is obtained, and when the model precision reaches a certain target precision, a model precision inspection result is sent based on the first sending instruction. In detail, the early warning signal detection model is a model established based on a neural network model. The neural network is an operation model formed by interconnection of a large number of neurons, when output information reaches a preset accuracy rate/reaches a convergence state, the supervision learning process is finished, the technical effects of further determining the model accuracy through the early warning signal detection model and improving the system early warning response analysis accuracy rate are achieved.
Further, the embodiment of the present application further includes:
step S941: if the first precision coefficient is not in the preset precision coefficient threshold value, obtaining a first self-checking instruction;
step S942: obtaining a first error coefficient of the early warning signal detection model according to the first self-checking instruction;
step S943: judging whether the first error coefficient is in a preset error coefficient threshold value or not;
step S944: if the first error coefficient is not in the preset error coefficient threshold value, obtaining a first gas classification threshold value and a first early warning attribute threshold value;
step S945: determining a first error correlation of the first gas classification threshold and a first early warning attribute threshold;
step S946: and obtaining a first adjusting instruction according to the first error correlation.
Specifically, if the first precision coefficient does not reach the target coefficient threshold value, it indicates that a certain error exists in the acquisition of the current early warning signal, and further, the error coefficient needs to be further determined by performing self-inspection on the whole process of acquiring the early warning signal, and because a certain change of the external environment, such as the rise of the humidity or the temperature of the external environment and the air, will form a certain objective influence on the generation of the early warning signal corresponding to the gas detection, further, the error needs to be further refined and analyzed, wherein when the first error coefficient exceeds the preset threshold value range, it indicates that a certain controllable factor exists in the current error, so that the judgment threshold value of the gas classification and the judgment threshold value of the early warning attribute are further adjusted in a related manner, i.e., an accurate division manner, and the finally formed matching code has accuracy and validity.
Further, if the first precision coefficient is not within the preset precision coefficient threshold, after the first self-check instruction is obtained, step S941 in this embodiment of the present application further includes:
step S9411: acquiring first false alarm error information in a first preset self-checking period according to a first data acquisition instruction;
step S9412: acquiring first false alarm missing information in the first preset self-detection period according to a second data acquisition instruction;
step S9413: counting the first false alarm error information and the first false alarm error information according to a first quantity counting instruction to obtain a first false alarm error rate and a first false alarm error rate;
step S9414: and inputting the first false alarm error rate and the first false alarm error rate into an early warning self-checking model, and obtaining the first error coefficient according to the early warning self-checking model.
Specifically, the detection of the error coefficient in the previous embodiment needs to collect data information in a certain preset self-check period for further statistical analysis, where the first data collection instruction is used to collect first false alarm error information, the first false alarm error information is a false alarm performed on gas that has not leaked in the detected gas, the second data collection instruction is used to collect first false alarm error information, the first false alarm error information is obtained by omitting gas that has leaked in the detected gas and not accurately performing alarm corresponding information, and further, the error rate therein is calculated according to the first number statistical instruction, so as to complete the obtaining of the first error coefficient. The information in a certain preset period is collected in real time, and then statistical analysis is completed, so that the reliability and high precision of obtaining real-time early warning signals are improved, and the technical effect of real-time early warning is improved.
Further, the embodiment of the present application further includes:
step S1110: obtaining a first level tree classification rule according to the first gas attribute;
step S1120: classifying the gas in the first chemical gas identification library according to the first hierarchical tree classification rule to obtain a first sequence number;
step S1130: obtaining a second sequence number according to a second level tree-shaped classification rule generated by a second gas attribute;
step S1140: obtaining a third sequence number according to a third level tree-shaped classification rule generated by a third gas attribute;
step S1150: and generating the first matching code according to the first sequence number, the second sequence number and the third sequence number.
Specifically, the first gas attribute is attribute information for judging whether the first gas attribute is dangerous gas, and a corresponding digital series is generated according to two judging results and corresponds to the first-level tree-shaped classification rule; the second gas attribute is to judge whether the second gas has flammability, toxicity and corrosivity, and a corresponding digital sequence corresponding to the second-level tree classification rule is generated according to three judged results; the third gas attribute is that whether two results suitable for people to come in and go out are generated to generate corresponding digital sequences corresponding to the third-level tree-shaped classification rule, and then the first matching codes are generated to achieve the purposes of carrying out code presetting based on attributes, further completing the coding of the attributes of corresponding gases and carrying out corresponding early warning attribute setting, so that the mode of carrying out corresponding division of gases by tree-shaped levels and then completing the coding is achieved, the multi-level flexible early warning is achieved, and the technical effects of improving the real-time performance and intelligence of the early warning are further improved.
Further, the embodiment of the present application further includes:
step S110: analyzing the first image information according to the first intelligent camera to obtain a first identification instruction;
step S120: acquiring a first dynamic identification area and a first static identification area according to the first identification instruction;
step S130: generating first real-time early warning image information according to the first dynamic identification area and the first static identification area;
step S140: and storing the first real-time early warning image information into a first image calling library.
Specifically, the first identification instruction is used for acquiring images of some dangerous situations of chemical gas leakage or chemical gas collision reaction and identifying areas, wherein the area identification is to perform area storage in a mode of combining a dynamic area and a static area so as to generate the first real-time early warning image information, and further, the images can be stored and called from the first image calling library through calling instructions when the corresponding images need to be called through the chemical gas classified connection intelligent camera, so that relevant workers can take measures in time based on the influence information stored in real time.
Further, the step S930 of the embodiment of the present application further includes that the multiple gas detection information and the multiple matching early warning signals are input to an early warning accuracy detection model to obtain a first accuracy coefficient:
step S931: inputting the multi-gas detection information and the multi-matching early warning signals into an early warning precision detection model, wherein the early warning precision detection model is obtained by training multiple groups of training data, and each group of the multiple groups of training data comprises: the multi-gas detection information and the multi-matching early warning signal and identification information identifying a first output result;
step S932: and obtaining a first output result in the early warning precision detection model, wherein the first output result is a first precision coefficient.
Specifically, the first accuracy coefficient is input into each group of training data as supervision data, supervision learning is performed on the multi-gas detection information and the multi-matching early warning signal, the early warning accuracy detection model is trained for a prototype building model according to a neural network model, further, the training process is substantially the supervision learning process, each group of supervision data comprises the multi-gas detection information, the multi-matching early warning signal and identification information for identifying a first output result, the early warning accuracy detection model is continuously corrected and adjusted by itself until the obtained output result is consistent with the identification information, the group of data supervision learning is ended, and the next group of data supervision learning is performed. And when the output information of the early warning precision detection model reaches the preset accuracy rate/reaches the convergence state, ending the supervised learning process. Through the mode of continuously training a plurality of groups of data, the first precision coefficient with accurate output is achieved, and the technical effect of improving the data processing level is achieved.
To sum up, the 5G network real-time early warning method and system provided by the embodiment of the present application have the following technical effects:
1. the method comprises the steps of collecting images in a first chemical chamber through an intelligent camera, freezing and analyzing collected influence information, detecting divided areas by a gas detector to obtain first gas detection information, matching corresponding codes according to a first matching class library corresponding to the first gas detection information obtained by tree-level division of chemical gas in advance, combining early warning frequency represented by digital sequences in the corresponding codes with early warning response time attributes to generate matched early warning signals, and sending the generated first matching early warning signals to a chemical chamber management system for early warning, so that multi-level flexible early warning is realized through characteristics based on a 5G network, and real-time performance of early warning is improved, Intelligent technical effect.
2. Because the mode that the encoding of the attribute of the corresponding gas is completed and the corresponding early warning attribute is set by setting the hierarchical tree classification rule and the encoding is completed after the corresponding division of the gas is performed by the tree hierarchy is adopted, the technical effect of realizing the multi-level flexible early warning and further improving the individuation and the accuracy of the early warning is achieved.
3. Because the mode of inputting the first false alarm error rate and the first false alarm error rate into the early warning self-checking model for self-checking, and acquiring in real time to complete statistical analysis is adopted, the reliability and high precision of obtaining the real-time early warning signal are improved, and the technical effect of real-time early warning is improved.
Example two
Based on the same inventive concept as the 5G network real-time early warning method in the foregoing embodiment, the present invention further provides a 5G network real-time early warning system, as shown in fig. 2, the system includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first image information of a first chemical laboratory according to a first intelligent camera;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain first gas detection information of a first partition area according to the first image information;
a first building unit 13, the first building unit 13 being configured to build a first chemical gas identification library;
a third obtaining unit 14, where the third obtaining unit 14 is configured to classify the gas in the first chemical gas identification library according to multiple attribute information to obtain a multi-class gas identification library;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain a first matching category library by matching the first gas detection information with the multi-category gas identification library;
a fifth obtaining unit 16, where the fifth obtaining unit 16 is configured to obtain a first matching code based on the first matching category library, where the first matching code is a code corresponding to the first matching category library;
the second construction unit 17, the second construction unit 17 is configured to construct a first real-time early warning signal library;
a sixth obtaining unit 18, where the sixth obtaining unit 18 is configured to obtain a first matching early warning attribute of the first matching code based on the first real-time early warning signal library;
a first generating unit 19, where the first generating unit 19 is configured to generate a first matching early warning signal according to the first matching early warning attribute;
a first sending unit 20, where the first sending unit 20 is configured to send the first matching early warning signal to a chemical room management system for early warning.
Further, the system further comprises:
a seventh obtaining unit for obtaining multi-gas detection information of a multi-divided area;
an eighth obtaining unit, configured to obtain multiple matching early warning signals corresponding to the multiple gas detection information;
a ninth obtaining unit, configured to input the multiple gas detection information and the multiple matching early warning signals into an early warning signal detection model, and obtain a first accuracy coefficient;
the first judgment unit is used for judging whether the first precision coefficient is in a preset precision coefficient threshold value or not;
a tenth obtaining unit, configured to obtain a first sending instruction if the first precision coefficient is within the preset precision coefficient threshold.
Further, the system further comprises:
an eleventh obtaining unit, configured to obtain a first self-checking instruction if the first precision coefficient is not within the preset precision coefficient threshold;
a twelfth obtaining unit, configured to obtain a first error coefficient of the early warning signal detection model according to the first self-checking instruction;
a second judging unit, configured to judge whether the first error coefficient is within a preset error coefficient threshold;
a thirteenth obtaining unit, configured to obtain a first gas classification threshold and a first warning attribute threshold if the first error coefficient is not within a preset error coefficient threshold;
a third determining unit, configured to determine a first error correlation between the first gas classification threshold and the first warning attribute threshold;
a fourteenth obtaining unit, configured to obtain a first adjustment instruction according to the first error correlation.
Further, the system further comprises:
a fifteenth obtaining unit, configured to obtain, according to the first data acquisition instruction, first false alarm error information in a first preset self-check period;
the second generating unit is used for acquiring first false alarm missing information in the first preset self-detection period according to a second data acquisition instruction;
a sixteenth obtaining unit, configured to count the first false alarm error information and the first false alarm error missing information according to a first number counting instruction, and obtain a first false alarm error rate and a first false alarm missing error rate;
a seventeenth obtaining unit, configured to input the first false alarm error rate and the first false alarm error rate into an early warning self-checking model, and obtain the first error coefficient according to the early warning self-checking model.
Further, the system further comprises:
an eighteenth obtaining unit, configured to obtain the first hierarchical tree classification rule according to the first gas attribute.
A nineteenth obtaining unit, configured to classify the gas in the first chemical gas identification library according to the first hierarchical tree classification rule, so as to obtain a first sequence number;
a twentieth obtaining unit, configured to obtain a second sequence number according to a second hierarchical tree-like classification rule generated by a second gas attribute;
a twenty-first obtaining unit, configured to obtain a third sequence number according to a third level tree classification rule generated by a third gas attribute;
a twenty-second obtaining unit, configured to rank the second merged color information according to the first filtering rule, to obtain second ranked color information;
a second generating unit, configured to generate the first matching code according to the first sequence number, the second sequence number, and the third sequence number.
Further, the system further comprises:
a twenty-third obtaining unit, configured to analyze the first image information according to the first intelligent camera, and obtain a first identification instruction;
a twenty-fourth obtaining unit, configured to obtain, according to the first identification instruction, a first dynamic identification region and a first static identification region;
a third generating unit, configured to generate first real-time early warning image information according to the first dynamic identification area and the first static identification area;
the first storage unit is used for storing the first real-time early warning image information into a first image calling library.
Further, the system further comprises:
a first input unit, configured to input the multiple gas detection information and the multiple matching early warning signals into an early warning accuracy detection model, where the early warning accuracy detection model is obtained through training of multiple sets of training data, and each set of the multiple sets of training data includes: the multi-gas detection information and the multi-matching early warning signal and identification information identifying a first output result;
a twenty-fifth obtaining unit, configured to obtain a first output result in the early warning precision detection model, where the first output result is a first precision coefficient.
Various changes and specific examples of the 5G network real-time warning method in the first embodiment of fig. 1 are also applicable to the 5G network real-time warning system in the present embodiment, and through the foregoing detailed description of the 5G network real-time warning method, a person skilled in the art can clearly know the implementation method of the 5G network real-time warning system in the present embodiment, so for the sake of brevity of the description, detailed descriptions are not repeated here.
Exemplary electronic device
The electronic device of the embodiment of the present application is described below with reference to fig. 3.
Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the 5G network real-time early warning method in the foregoing embodiment, the present invention further provides a 5G network real-time early warning system, in which a computer program is stored, and when the computer program is executed by a processor, the steps of any one of the foregoing 5G network real-time early warning methods are implemented.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
The embodiment of the invention provides a 5G network real-time early warning method, which is applied to a chemical laboratory management system, wherein the system is in communication connection with an intelligent camera, and the method comprises the following steps: acquiring first image information of a first chemical laboratory according to a first intelligent camera; acquiring first gas detection information of a first divided area according to the first image information; constructing a first chemical gas identification library; classifying the gas in the first chemical gas identification library according to the multi-attribute information to obtain a multi-class gas identification library; obtaining a first matching category library by matching the first gas detection information with the multi-category gas identification library; obtaining a first matching code based on the first matching category library, wherein the first matching code is a code corresponding to the first matching category library; constructing a first real-time early warning signal library; obtaining a first matching early warning attribute of the first matching code based on the first real-time early warning signal library; generating a first matching early warning signal according to the first matching early warning attribute; and sending the first matching early warning signal to the chemical room management system for early warning. The technical problems that the early warning method in the prior art is not rapid enough and the early warning response has certain time delay are solved, and the technical effects of realizing multi-level flexible early warning through the characteristics based on the 5G network and further improving the real-time performance and intelligence of the early warning are achieved.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, 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 a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. A5G network real-time early warning method is applied to a chemical laboratory management system, the system is in communication connection with an intelligent camera, and the method comprises the following steps:
acquiring first image information of a first chemical laboratory according to a first intelligent camera;
acquiring first gas detection information of a first divided area according to the first image information;
constructing a first chemical gas identification library;
classifying the gas in the first chemical gas identification library according to the multi-attribute information to obtain a multi-class gas identification library;
obtaining a first matching category library by matching the first gas detection information with the multi-category gas identification library;
obtaining a first matching code based on the first matching category library, wherein the first matching code is a code corresponding to the first matching category library;
constructing a first real-time early warning signal library;
obtaining a first matching early warning attribute of the first matching code based on the first real-time early warning signal library;
generating a first matching early warning signal according to the first matching early warning attribute;
and sending the first matching early warning signal to the chemical room management system for early warning.
2. The method of claim 1, after generating a first match pre-warning signal according to the first match pre-warning attribute, the method further comprising:
obtaining multi-gas detection information of a plurality of divided areas;
acquiring multiple matching early warning signals corresponding to the multiple gas detection information;
inputting the multi-gas detection information and the multi-matching early warning signals into an early warning signal detection model to obtain a first precision coefficient;
judging whether the first precision coefficient is in a preset precision coefficient threshold value or not;
and if the first precision coefficient is in the preset precision coefficient threshold value, obtaining a first sending instruction.
3. The method of claim 2, further comprising:
if the first precision coefficient is not in the preset precision coefficient threshold value, obtaining a first self-checking instruction;
obtaining a first error coefficient of the early warning signal detection model according to the first self-checking instruction;
judging whether the first error coefficient is in a preset error coefficient threshold value or not;
if the first error coefficient is not in the preset error coefficient threshold value, obtaining a first gas classification threshold value and a first early warning attribute threshold value;
determining a first error correlation of the first gas classification threshold and a first early warning attribute threshold;
and obtaining a first adjusting instruction according to the first error correlation.
4. The method of claim 3, wherein after obtaining the first self-test command if the first precision factor is not within the predetermined precision factor threshold, the method further comprises:
acquiring first false alarm error information in a first preset self-checking period according to a first data acquisition instruction;
acquiring first false alarm missing information in the first preset self-detection period according to a second data acquisition instruction;
counting the first false alarm error information and the first false alarm error information according to a first quantity counting instruction to obtain a first false alarm error rate and a first false alarm error rate;
and inputting the first false alarm error rate and the first false alarm error rate into an early warning self-checking model, and obtaining the first error coefficient according to the early warning self-checking model.
5. The method of claim 1, further comprising:
obtaining a first level tree classification rule according to the first gas attribute;
classifying the gas in the first chemical gas identification library according to the first hierarchical tree classification rule to obtain a first sequence number;
obtaining a second sequence number according to a second level tree-shaped classification rule generated by a second gas attribute;
obtaining a third sequence number according to a third level tree-shaped classification rule generated by a third gas attribute;
and generating the first matching code according to the first sequence number, the second sequence number and the third sequence number.
6. The method of claim 1, further comprising:
analyzing the first image information according to the first intelligent camera to obtain a first identification instruction;
acquiring a first dynamic identification area and a first static identification area according to the first identification instruction;
generating first real-time early warning image information according to the first dynamic identification area and the first static identification area;
and storing the first real-time early warning image information into a first image calling library.
7. The method of claim 2, wherein the multiple gas detection information and the multiple matching early warning signals are input to an early warning accuracy detection model to obtain a first accuracy factor, the method further comprising:
inputting the multi-gas detection information and the multi-matching early warning signals into an early warning precision detection model, wherein the early warning precision detection model is obtained by training multiple groups of training data, and each group of the multiple groups of training data comprises: the multi-gas detection information and the multi-matching early warning signal and identification information identifying a first output result;
and obtaining a first output result in the early warning precision detection model, wherein the first output result is a first precision coefficient.
8. A5G network real-time early warning system, wherein the system comprises:
the first obtaining unit is used for obtaining first image information of a first chemical laboratory according to a first intelligent camera;
a second obtaining unit, configured to obtain first gas detection information of a first partition area according to the first image information;
a first building unit for building a first chemical gas identification library;
a third obtaining unit, configured to classify the gas in the first chemical gas identification library according to multi-attribute information, so as to obtain a multi-class gas identification library;
a fourth obtaining unit, configured to obtain a first matching category library by matching the first gas detection information with the multi-category gas identification library;
a fifth obtaining unit, configured to obtain a first matching code based on the first matching category library, where the first matching code is a code corresponding to the first matching category library;
the second construction unit is used for constructing a first real-time early warning signal library;
a sixth obtaining unit, configured to obtain a first matching early warning attribute of the first matching code based on the first real-time early warning signal library;
the first generating unit is used for generating a first matching early warning signal according to the first matching early warning attribute;
and the first sending unit is used for sending the first matching early warning signal to a chemical room management system for early warning.
9. A 5G network real-time warning system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1-7 when executing the program.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117082543A (en) * | 2023-09-11 | 2023-11-17 | 北京市大唐盛兴科技发展有限公司 | Portable wireless signal transmission detection device |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117082543A (en) * | 2023-09-11 | 2023-11-17 | 北京市大唐盛兴科技发展有限公司 | Portable wireless signal transmission detection device |
| CN117082543B (en) * | 2023-09-11 | 2024-04-19 | 北京市大唐盛兴科技发展有限公司 | Portable wireless signal transmission detection device |
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