CN116560946A - Soil pollution data pushing system based on cloud computing - Google Patents
Soil pollution data pushing system based on cloud computing Download PDFInfo
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- CN116560946A CN116560946A CN202310550694.5A CN202310550694A CN116560946A CN 116560946 A CN116560946 A CN 116560946A CN 202310550694 A CN202310550694 A CN 202310550694A CN 116560946 A CN116560946 A CN 116560946A
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- 238000003900 soil pollution Methods 0.000 title claims abstract description 13
- 239000002689 soil Substances 0.000 claims abstract description 150
- 238000012544 monitoring process Methods 0.000 claims abstract description 132
- 238000012545 processing Methods 0.000 claims abstract description 52
- 238000001514 detection method Methods 0.000 claims abstract description 24
- 230000002159 abnormal effect Effects 0.000 claims abstract description 17
- 238000011282 treatment Methods 0.000 claims abstract description 15
- 238000013500 data storage Methods 0.000 claims description 12
- 238000012549 training Methods 0.000 claims description 12
- 229910052757 nitrogen Inorganic materials 0.000 claims description 9
- 238000013473 artificial intelligence Methods 0.000 claims description 7
- 238000012937 correction Methods 0.000 claims description 6
- 238000007726 management method Methods 0.000 claims description 5
- 230000000737 periodic effect Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000004806 packaging method and process Methods 0.000 claims description 2
- 230000000007 visual effect Effects 0.000 abstract description 3
- 238000000034 method Methods 0.000 description 8
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 6
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 3
- ZLMJMSJWJFRBEC-UHFFFAOYSA-N Potassium Chemical compound [K] ZLMJMSJWJFRBEC-UHFFFAOYSA-N 0.000 description 3
- 229910052698 phosphorus Inorganic materials 0.000 description 3
- 239000011574 phosphorus Substances 0.000 description 3
- 229910052700 potassium Inorganic materials 0.000 description 3
- 239000011591 potassium Substances 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 241000282414 Homo sapiens Species 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 229910001385 heavy metal Inorganic materials 0.000 description 2
- 235000013619 trace mineral Nutrition 0.000 description 2
- 239000011573 trace mineral Substances 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013527 convolutional neural network Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000003973 irrigation Methods 0.000 description 1
- 230000002262 irrigation Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3058—Monitoring arrangements for monitoring environmental properties or parameters of the computing system or of the computing system component, e.g. monitoring of power, currents, temperature, humidity, position, vibrations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
- G06F11/324—Display of status information
- G06F11/327—Alarm or error message display
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- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computing Systems (AREA)
- Processing Of Solid Wastes (AREA)
Abstract
The invention discloses a soil pollution data pushing system based on cloud computing, relates to the technical field of data pushing, and solves the technical problem that a soil data pushing result is not visual; acquiring monitoring data of soil through a data acquisition module; the data processing module compares the monitoring data with a monitoring threshold value; when the monitoring data is equal to or greater than the monitoring threshold value, the data processing module sends an alarm signal to the safety alarm module; when the monitoring data is smaller than the monitoring threshold value, the data processing module acquires a soil coefficient according to the monitoring data, and acquires a fluctuation label according to the soil coefficient and the soil detection model; when the soil coefficient is in an abnormal fluctuation state, the data processing module packages the soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data and sends the packaged soil coefficient, the monitoring data and the historical monitoring data to an intelligent terminal of a treatment technician associated with the monitored soil; abnormal fluctuation soil data is found in time, so that the cost of soil treatment is reduced.
Description
Technical Field
The invention belongs to the field of cloud computing, relates to a data pushing technology, and particularly relates to a soil pollution data pushing system based on cloud computing.
Background
Soil is one of the basic elements of the land ecological system, is also one of the material bases on which human beings depend to survive, and the soil environment condition is directly related to ecological safety and human health, and also directly related to the yield, quality and safety of agricultural products.
Along with the continuous development of intelligent agriculture, soil moisture content monitoring has become an indispensable part, and remote monitoring and data collection of an intelligent soil system have certain guiding significance for grasping soil effectiveness, reflecting soil improvement effect, implementing water-saving irrigation, knowing the influence of climate change on soil moisture content and the like. The intelligent soil system monitors the temperature, humidity, pH value, nitrogen, phosphorus, potassium content and other factors of the soil in real time by utilizing the relevant soil sensors, has a multi-platform data pushing function, can be connected with an independent platform, and can also view field device data and monitoring videos on a mobile phone. However, in the prior art, after the monitoring data of the soil is pushed to the receiving personnel, the receiving personnel still need to analyze and process the data, so that the pushing result is not visual.
Therefore, a soil pollution data pushing system based on cloud computing is provided.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides a soil pollution data pushing system based on cloud computing, which solves the problem that in the prior art, after monitoring data of soil is pushed to a receiving person, the receiving person still needs to analyze and process the data, so that a pushing result is not visual.
To achieve the above objective, according to an embodiment of the first aspect of the present invention, a soil pollution data pushing system based on cloud computing is provided, which includes a data acquisition module, a data processing module, a data storage module, and a safety alarm module;
the data acquisition module is used for acquiring monitoring data of soil; the monitoring data are sent to the data processing module, and the monitoring data are sent to the data storage module for storage;
the data processing module is used for receiving the monitoring data and marking the monitoring data as Jn; wherein N is the number of the acquisition period, the value of N is 1,2,3 and … … N, and N is the total number of the acquisition period;
the data processing module sets a monitoring threshold value and compares the monitoring data with the monitoring threshold value;
when the monitoring data is equal to or greater than the monitoring threshold value, the data processing module sends an alarm signal to the safety alarm module;
after receiving the alarm signal, the safety alarm module sends the monitoring data to an intelligent terminal of a management technician associated with the monitored soil;
when the monitoring data is smaller than the monitoring threshold value, the data processing module acquires a soil coefficient according to the monitoring data and sends the soil coefficient to the data storage module for storage;
the data processing module acquires soil coefficients according to the monitoring data, and comprises the following steps:
the soil coefficient is marked as Xn,
the calculation formula of the soil coefficient is as follows:
wherein, alpha is a correction coefficient of the monitoring data, and alpha is a real number larger than 0; j (J) Label (C) Standard data for monitoring data, and J Label (C) A real number greater than 0;
wherein alpha is i Is J in Is used for the correction coefficient of (a); it should be further noted that i is monitoringThe type of data;
acquiring a fluctuation label according to the soil coefficient and the soil detection model; wherein, the soil detection model is established based on an artificial intelligence model;
and identifying the fluctuation label, when the soil coefficient is in an abnormal fluctuation state, acquiring the historical soil coefficient and the historical monitoring data from the data storage module by the data processing module, packaging the soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data and sending the packaged soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data to an intelligent terminal of a treatment technician associated with the monitored soil.
Preferably, the data acquisition module acquires the monitoring data in a periodic acquisition mode;
the acquisition period of the monitoring data is marked as T, wherein the unit of T is a day, and T is a positive integer greater than 0.
Preferably, the value of the fluctuation label is 0 or 1, when the fluctuation label is 0, the corresponding soil coefficient is in a normal fluctuation state, and when the fluctuation label is 1, the corresponding soil coefficient is in an abnormal fluctuation state.
Preferably, the method for acquiring the fluctuation label according to the soil coefficient and the soil detection model comprises the following steps:
acquiring a soil detection model from a data processing module;
taking the collection period of the soil coefficients as a reference period, extracting P soil coefficients before the reference period from the soil coefficients, and integrating to generate original data; wherein P is a positive integer greater than or equal to 5;
and inputting the original data into the soil detection model to obtain a corresponding fluctuation label.
Preferably, the soil detection model is built based on an artificial intelligence model, comprising the following steps:
standard training data are acquired from a data processing module;
training the artificial intelligent model through standard training data, and marking the trained artificial intelligent model as a soil detection model;
the standard training data comprises a plurality of groups of input data and corresponding fluctuation labels, and the content attributes of the input data and the original data are consistent.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the data acquisition module is used for acquiring the monitoring data of the soil; and sending the monitoring data to a data processing module; the data processing module receives the monitoring data; setting a monitoring threshold value, and comparing the monitoring data with the monitoring threshold value; when the monitoring data is equal to or greater than the monitoring threshold value, the data processing module sends an alarm signal to the safety alarm module; after receiving the alarm signal, the safety alarm module immediately sends the monitoring data to an intelligent terminal of a treatment technician associated with the monitored soil; alarming can be carried out timely according to some or more abnormal monitoring data;
when the monitoring data is smaller than the monitoring threshold value, the data processing module acquires a soil coefficient according to the monitoring data, and acquires a fluctuation label according to the soil coefficient and the soil detection model; the fluctuation label is identified, and when the soil coefficient is in an abnormal fluctuation state, the data processing module packages and transmits the soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data to an intelligent terminal of a management technician associated with the monitored soil; when the soil coefficient is in a normal fluctuation state, other treatments are not carried out; the fluctuation condition of the soil can be obtained according to the monitoring data of the soil, and the abnormal fluctuation soil data can be found in time, so that the cost of soil treatment is reduced.
Drawings
FIG. 1 is a schematic diagram of the present invention;
fig. 2 is a flow chart of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
1-2, a soil pollution data pushing system based on cloud computing comprises a data acquisition module, a data processing module, a data storage module and a safety alarm module; the modules perform information interaction based on digital signals;
the data acquisition module is used for acquiring monitoring data of soil; wherein the monitoring data comprise nitrogen, phosphorus, potassium, organic matters, moisture, salinity, PH, species trace elements, heavy metals and the like;
the monitoring data are sent to the data processing module, and the monitoring data are sent to the data storage module for storage;
specifically, the data acquisition module acquires the monitoring data in a periodic acquisition mode;
it should be further noted that the acquisition period of the data acquisition module is set by a professional; the acquisition period is marked as T, wherein T is in days and T is a positive integer greater than 0.
The data processing module is used for receiving the monitoring data and processing the monitoring data;
the data processing module processes the monitoring data and comprises the following steps:
the data processing module receives the monitoring data and marks the monitoring data as Jn; wherein N is the number of the acquisition period, the value of N is 1,2,3 and … … N, and N is the total number of the acquisition period;
the data processing module receives the monitoring data;
the data processing module sets a monitoring threshold value and marks the monitoring threshold value as JMax;
the data processing module compares the monitoring data with the monitoring threshold;
when the monitoring data is equal to or greater than the monitoring threshold value, the data processing module sends an alarm signal to the safety alarm module;
the safety alarm module immediately sends the monitoring data to an intelligent terminal of a management technician associated with the monitored soil after receiving the alarm signal;
the system can alarm in time according to some or more abnormal monitoring data;
when the monitoring data is smaller than the monitoring threshold value, the data processing module acquires a soil coefficient according to the monitoring data, and acquires a fluctuation label according to the soil coefficient and a soil detection model; wherein, the soil detection model is established based on an artificial intelligence model;
when the soil coefficient is in an abnormal fluctuation state, the data processing module acquires the historical soil coefficient and the historical monitoring data from the data storage module, packages the soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data and sends the packaged soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data to an intelligent terminal of a treatment technician associated with the monitored soil;
when the soil coefficient is in a normal fluctuation state, other treatments are not performed;
the system acquires the fluctuation condition of the soil according to the monitoring data of the soil, and timely discovers the abnormally fluctuating soil data, so that the cost of soil treatment is reduced.
In this embodiment, the value of the fluctuation label is 0 or 1, when the fluctuation label is 0, the corresponding soil coefficient is in a normal fluctuation state, and when the fluctuation label is 1, the corresponding soil coefficient is in an abnormal fluctuation state; in other preferred schemes, the fluctuation label can be distinguished by other marks, for example, the value of the fluctuation label is A or B, when the fluctuation label is A, the corresponding soil coefficient is in a normal fluctuation state, and when the fluctuation label is B, the corresponding soil coefficient is in an abnormal fluctuation state.
In this embodiment, the data processing module obtains a soil coefficient according to the monitoring data, and includes the following steps:
the soil coefficient is marked as Xn,
the calculation formula of the soil coefficient is as follows:
wherein, alpha is a correction coefficient of the monitoring data, and alpha is a real number larger than 0; j (J) Label (C) Standard data for monitoring data, and J Label (C) A real number greater than 0;
wherein alpha is i Is J in Is used for the correction coefficient of (a); it should be further noted that i is the type of the monitoring data; the monitoring data comprises nitrogen, phosphorus, potassium, organic matters, moisture, salt, PH, trace elements, heavy metals and the like, and are respectively marked as J 1n 、J 2n 、J 3n 、J 4n 、J 5n 、J 6n J 7n Etc.
In this embodiment, the method for obtaining the fluctuation label according to the soil coefficient and the soil detection model includes the following steps:
acquiring a soil detection model from a data processing module;
taking the collection period of the soil coefficients as a reference period, extracting P soil coefficients before the reference period from the soil coefficients, and integrating to generate original data;
and inputting the original data into the soil detection model to obtain a corresponding fluctuation label.
In this embodiment, P is an integer greater than or equal to 5, and verification proves that accurate fluctuation labels can be obtained only when the soil coefficients are at least 5.
In an alternative embodiment, the soil detection model is built based on an artificial intelligence model, comprising the steps of:
standard training data are acquired from a data processing module;
and training the artificial intelligent model through standard training data, and marking the trained artificial intelligent model as a soil detection model.
In this embodiment, the standard training data includes several groups of input data and corresponding fluctuation labels, and the content attributes of the input data and the original data are consistent; it will be appreciated that both the input data and the raw data include a selected number N of soil coefficients, with the exception that the soil coefficients are of different magnitudes.
In this embodiment, the artificial intelligence model includes a model with strong nonlinear fitting capability such as a deep convolutional neural network model or an RBF neural network model.
In this embodiment, the data storage module is configured to store the monitoring data and the soil coefficient.
In this embodiment, the data acquisition module is in communication and/or electrical connection with the data processing module;
the data processing module is in communication and/or electrical connection with the safety alarm module.
According to the system, the fluctuation condition of the soil is obtained according to the monitoring data of the soil, and the abnormal fluctuation soil data is found in time, so that the cost of soil treatment is reduced;
the obtained soil data is analyzed and processed, the abnormal condition of the soil is found in time, the abnormal data is pushed to a treatment technician, and the treatment technician can more intuitively know the soil condition according to the monitoring data and the soil coefficient after the analysis and processing.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The working principle of the invention is as follows:
the data acquisition module acquires monitoring data of soil in a periodic acquisition mode; and sending the monitoring data to a data processing module;
the data processing module receives the monitoring data; setting a monitoring threshold value, and comparing the monitoring data with the monitoring threshold value;
when the monitoring data is equal to or greater than the monitoring threshold value, the data processing module sends an alarm signal to the safety alarm module; after receiving the alarm signal, the safety alarm module immediately sends the monitoring data to an intelligent terminal of a treatment technician associated with the monitored soil;
when the monitoring data is smaller than the monitoring threshold value, the data processing module acquires a soil coefficient according to the monitoring data, and acquires a fluctuation label according to the soil coefficient and the soil detection model;
the fluctuation label is identified, and when the soil coefficient is in an abnormal fluctuation state, the data processing module packages and transmits the soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data to an intelligent terminal of a management technician associated with the monitored soil;
when the soil coefficient is in a normal fluctuation state, no other treatment is performed.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (5)
1. The soil pollution data pushing system based on cloud computing is characterized by comprising a data acquisition module, a data processing module, a data storage module and a safety alarm module;
the data acquisition module is used for acquiring monitoring data of soil; the monitoring data are sent to the data processing module, and the monitoring data are sent to the data storage module for storage;
the data processing module is used for receiving the monitoring data and marking the monitoring data as Jn; wherein N is the number of the acquisition period, the value of N is 1,2,3 and … … N, and N is the total number of the acquisition period;
the data processing module sets a monitoring threshold value and compares the monitoring data with the monitoring threshold value;
when the monitoring data is equal to or greater than the monitoring threshold value, the data processing module sends an alarm signal to the safety alarm module;
after receiving the alarm signal, the safety alarm module sends the monitoring data to an intelligent terminal of a management technician associated with the monitored soil;
when the monitoring data is smaller than the monitoring threshold value, the data processing module acquires a soil coefficient according to the monitoring data and sends the soil coefficient to the data storage module for storage;
the data processing module acquires soil coefficients according to the monitoring data, and comprises the following steps:
the soil coefficient is marked as Xn,
the calculation formula of the soil coefficient is as follows:
wherein, alpha is a correction coefficient of the monitoring data, and alpha is a real number larger than 0; j (J) Label (C) Standard data for monitoring data, and J Label (C) A real number greater than 0;
wherein alpha is i Is J in Is used for the correction coefficient of (a); it should be further noted that i is the type of the monitoring data;
acquiring a fluctuation label according to the soil coefficient and the soil detection model; wherein, the soil detection model is established based on an artificial intelligence model;
and identifying the fluctuation label, when the soil coefficient is in an abnormal fluctuation state, acquiring the historical soil coefficient and the historical monitoring data from the data storage module by the data processing module, packaging the soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data and sending the packaged soil coefficient, the monitoring data, the historical soil coefficient and the historical monitoring data to an intelligent terminal of a treatment technician associated with the monitored soil.
2. The cloud computing-based soil pollution data pushing system according to claim 1, wherein the data acquisition module acquires the monitoring data in a periodic acquisition mode;
the acquisition period of the monitoring data is marked as T, wherein the unit of T is a day, and T is a positive integer greater than 0.
3. The cloud computing-based soil pollution data pushing system according to claim 1, wherein the value of the fluctuation label is 0 or 1, when the fluctuation label is 0, the corresponding soil coefficient is in a normal fluctuation state, and when the fluctuation label is 1, the corresponding soil coefficient is in an abnormal fluctuation state.
4. The cloud computing-based soil pollution data pushing system according to claim 1, wherein the acquiring of the fluctuation label according to the soil coefficient and the soil detection model comprises the steps of:
acquiring a soil detection model from a data processing module;
taking the collection period of the soil coefficients as a reference period, extracting P soil coefficients before the reference period from the soil coefficients, and integrating to generate original data; wherein P is a positive integer greater than or equal to 5;
and inputting the original data into the soil detection model to obtain a corresponding fluctuation label.
5. The cloud computing-based soil pollution data pushing system of claim 1, wherein the soil detection model is built based on an artificial intelligence model, comprising the steps of:
standard training data are acquired from a data processing module;
training the artificial intelligent model through standard training data, and marking the trained artificial intelligent model as a soil detection model;
the standard training data comprises a plurality of groups of input data and corresponding fluctuation labels, and the content attributes of the input data and the original data are consistent.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116860563A (en) * | 2023-09-05 | 2023-10-10 | 山东捷瑞数字科技股份有限公司 | Cloud platform-based database server monitoring method and system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116860563A (en) * | 2023-09-05 | 2023-10-10 | 山东捷瑞数字科技股份有限公司 | Cloud platform-based database server monitoring method and system |
| CN116860563B (en) * | 2023-09-05 | 2023-12-15 | 山东捷瑞数字科技股份有限公司 | Cloud platform-based database server monitoring method and system |
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