Online automatic monitoring system and method for carbon dioxide gas concentration in soil

Abstract

The invention relates to the field of gas detection, in particular to an online automatic monitoring system and method for the concentration of carbon dioxide gas in soil. By establishing a CNN convolutional neural network model, inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training to obtain carbon dioxide gas concentration data; whether the carbon dioxide gas concentration data is larger than an early warning threshold value or not is judged, if the carbon dioxide gas concentration data is larger than the early warning threshold value, the real-time carbon dioxide gas data are input into a CNN convolutional neural network model to be recognized, and carbon dioxide is transmitted into the soil through a carbon dioxide release device; monitoring the carbon dioxide gas data in the soil in real time to obtain target carbon dioxide gas concentration data; and when the target carbon dioxide gas concentration data meets the preset standard value, stopping transmitting the carbon dioxide into the soil by using the carbon dioxide release device. And the carbon dioxide gas concentration data in the soil can be monitored in real time.

Description

Technical Field

[0001] The invention relates to the field of gas detection, and in particular to an online automatic monitoring system and method for carbon dioxide gas concentration in soil. Background Art

[0002] Carbon dioxide is an important raw material for plant photosynthesis, through which carbon dioxide, water and light energy can be converted into organic matter and oxygen. With the increase of carbon dioxide, the photosynthetic efficiency and nutrient utilization rate of plants will also increase. Therefore, the concentration of carbon dioxide in the soil is usually related to the production of plants. However, since the concentration of carbon dioxide in the soil is usually detected by sensors, the sensor usually detects the carbon dioxide concentration of local soil. The concentration of a single sensor cannot indicate the total carbon dioxide content of the soil, and the carbon dioxide concentration in the soil will be affected by factors such as temperature and light. Therefore, how to detect the concentration of carbon dioxide in the soil and automatically adjust the concentration of carbon dioxide in the soil is a technical problem that needs to be solved at this stage. Summary of the invention

[0003] The purpose of the present invention is to solve the above problems and to design an online automatic monitoring system and method for carbon dioxide gas concentration in soil.

[0004] To achieve the above object, the technical solution of the present invention is that, further, in the above-mentioned online automatic monitoring system for carbon dioxide gas concentration in soil, the online automatic monitoring system comprises the following steps:

[0005] A gas data acquisition module, used to acquire historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor, and perform data preprocessing on the historical carbon dioxide gas data to obtain training carbon dioxide gas data;

[0006] A first gas data recognition module is used to establish a CNN convolutional neural network model, input the training carbon dioxide gas data into the CNN convolutional neural network model for training, and obtain carbon dioxide gas concentration data;

[0007] A carbon dioxide neutralization module is used to determine whether the carbon dioxide gas concentration data is greater than the warning threshold. If the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through a carbon dioxide neutralization device, and real-time carbon dioxide gas data in the soil is collected in real time;

[0008] A second gas data recognition module is used to input the real-time carbon dioxide gas data into the CNN convolutional neural network model for recognition to obtain initial carbon dioxide gas concentration data;

[0009] A gas data transmission module, used to determine whether the initial carbon dioxide gas concentration data meets the preset standard value, and if the initial carbon dioxide gas concentration data meets the preset soil standard value, transmit the initial carbon dioxide gas concentration data to the display terminal;

[0010] A carbon dioxide supplement module, used to transmit carbon dioxide to the soil through a carbon dioxide release device if the initial carbon dioxide gas concentration data is less than a preset standard value;

[0011] The gas data monitoring module is used to monitor the carbon dioxide gas data in the soil in real time to obtain the target carbon dioxide gas concentration data; when the target carbon dioxide gas concentration data meets the preset standard value, the carbon dioxide release device is stopped from transmitting carbon dioxide to the soil.

[0012] Furthermore, in the above-mentioned online automatic monitoring system, the gas data acquisition module includes the following submodules:

[0013] The sensor submodule is used to obtain historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor and perform data preprocessing on the historical carbon dioxide gas data; the carbon dioxide gas sensor at least includes a solid electrolytic CO 2 Sensors, optical fiber CO 2 Sensor, Capacitive CO 2 sensor;

[0014] The sensor setting submodule is used to determine that the carbon dioxide gas sensor is inserted into the soil by 10 cm and the arrangement density of the carbon dioxide gas sensor is 1 / 2m 2 ;

[0015] A data determination submodule, used to determine that the historical carbon dioxide gas data is electrical signal data and digital signal data of a carbon dioxide gas sensor; the historical carbon dioxide gas data includes at least electrical signal data of more than 500 carbon dioxide gas sensors;

[0016] A data denoising submodule, for performing denoising processing on the historical carbon dioxide gas data using a wavelet threshold denoising method to obtain denoised historical carbon dioxide gas data;

[0017] A submodule is obtained, which is used to randomly extract 80% of the historical carbon dioxide gas data to obtain training carbon dioxide gas data.

[0018] Further, in the above-mentioned online automatic monitoring system, the first gas data identification module includes the following units:

[0019] A model building unit, used to build a CNN convolutional neural network model and optimize the CNN convolutional neural network model using a back propagation algorithm;

[0020] A model training unit, used for inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training and keeping the model weights unchanged;

[0021] A back propagation calculation unit, used to calculate the predicted value of the CNN convolutional neural network model using a back propagation algorithm, and calculate the error of the output layer by comparing the predicted value with the expected output;

[0022] The recursive calculation unit is used to utilize the error to propagate layer by layer in reverse order, recursively calculate the local gradient of each neuron of the CNN convolutional neural network model, calculate the change amount of each weight, update the weight of the CNN convolutional neural network model, and obtain the carbon dioxide gas concentration data.

[0023] Furthermore, in the above-mentioned online automatic monitoring system, the carbon dioxide neutralization module includes the following submodules:

[0024] A judgment submodule, used to judge whether the carbon dioxide gas concentration data is greater than a warning threshold, and the warning threshold at least includes that the carbon dioxide gas concentration data is greater than 3%;

[0025] The threshold submodule is used to determine that if the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device. When the carbon dioxide gas concentration data is 3%-5%, the spraying concentration of calcium hydroxide is 6%, and 100 ml is sprayed per square meter;

[0026] The numerical submodule is used to determine that when the carbon dioxide gas concentration data is greater than 5%, the spraying concentration of calcium hydroxide is 8%, and 200 ml is sprayed per square meter;

[0027] A category submodule, used to determine that the carbon dioxide neutralization device at least includes a calcium hydroxide spraying device, a calcium oxide powder spraying device, and a sodium hydroxide spraying device;

[0028] The identification submodule is used to collect real-time carbon dioxide gas data in the soil in real time, input the real-time carbon dioxide gas data into the CNN convolutional neural network model for identification, and obtain initial carbon dioxide gas concentration data.

[0029] Furthermore, in the above-mentioned online automatic monitoring system, the gas data transmission module includes the following submodules:

[0030] A judgment submodule, used to judge whether the initial carbon dioxide gas concentration data meets a preset standard value, and the preset standard value is that the initial carbon dioxide gas concentration data is less than 0.5%;

[0031] A transmission submodule, configured to transmit the initial carbon dioxide gas concentration data to a display terminal if the initial carbon dioxide gas concentration data meets a preset soil standard value;

[0032] The early warning submodule is used to transmit the initial carbon dioxide gas concentration data and the carbon dioxide neutralization device spraying data to the server for early warning if the initial carbon dioxide gas concentration data does not meet the preset standard value of the soil.

[0033] Furthermore, in the above-mentioned online automatic monitoring system, the carbon dioxide supplement module includes the following submodules:

[0034] A gas release unit, used to determine if the initial carbon dioxide gas concentration data is less than a preset standard value, then transmit carbon dioxide to the soil through a carbon dioxide release device;

[0035] A gas numerical unit, used to determine that when the initial carbon dioxide gas concentration data is 0.2%-0.3%, a carbon dioxide gas with a concentration of 3% is released through the carbon dioxide release device, and 300 ml is released per square meter; when the initial carbon dioxide gas concentration data is less than 0.2%, a carbon dioxide gas with a concentration of 5% is released through the carbon dioxide release device, and 400 ml is released per square meter;

[0036] The release arrangement unit is used to determine that the carbon dioxide release device is inserted into the soil by 6 cm, and the arrangement density of the carbon dioxide release device is 1 / 4m 2 .

[0037] Furthermore, in the above-mentioned online automatic monitoring system, the gas data monitoring module includes the following units:

[0038] The gas data acquisition unit is used to monitor the carbon dioxide gas data in the soil in real time, and acquire the carbon dioxide gas data in the soil every 5 minutes through the carbon dioxide sensor to obtain the target carbon dioxide gas concentration data;

[0039] A gas data transmission unit, used for recording the carbon dioxide concentration release data corresponding to the target carbon dioxide gas concentration data, and inputting the target carbon dioxide gas concentration data and the carbon dioxide concentration release data into a database for storage;

[0040] The gas release control unit is used to stop using the carbon dioxide release device to transmit carbon dioxide into the soil when the target carbon dioxide gas concentration data meets the preset standard value.

[0041] To achieve the above object, the technical solution of the present invention is that, further, in the above-mentioned method for online automatic monitoring of carbon dioxide gas concentration in soil, the online automatic monitoring method comprises:

[0042] A data acquisition module, used to acquire historical seedling image data of seedlings in mangroves through an image acquisition device, and perform data preprocessing on the historical seedling image data to obtain growth status data of mangroves to be trained;

[0043] Acquire historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor, perform data preprocessing on the historical carbon dioxide gas data, and obtain training carbon dioxide gas data;

[0044] Establishing a CNN convolutional neural network model, inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training, and obtaining carbon dioxide gas concentration data;

[0045] Determine whether the carbon dioxide gas concentration data is greater than a warning threshold value. If the carbon dioxide gas concentration data is greater than the warning threshold value, spray calcium hydroxide through a carbon dioxide neutralization device and collect real-time carbon dioxide gas data in the soil in real time;

[0046] Inputting the real-time carbon dioxide gas data into the CNN convolutional neural network model for identification to obtain initial carbon dioxide gas concentration data;

[0047] Determine whether the initial carbon dioxide gas concentration data meets the preset standard value, and if the initial carbon dioxide gas concentration data meets the preset soil standard value, transmit the initial carbon dioxide gas concentration data to the display terminal;

[0048] If the initial carbon dioxide gas concentration data is less than a preset standard value, carbon dioxide is transmitted to the soil through a carbon dioxide release device;

[0049] The carbon dioxide gas data in the soil is monitored in real time to obtain the target carbon dioxide gas concentration data; when the target carbon dioxide gas concentration data meets the preset standard value, the carbon dioxide release device is stopped from transmitting carbon dioxide into the soil.

[0050] Furthermore, in the above-mentioned method for online automatic monitoring of carbon dioxide gas concentration in soil, the establishment of a CNN convolutional neural network model, inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training, and obtaining carbon dioxide gas concentration data, includes:

[0051] Establishing a CNN convolutional neural network model, and optimizing the CNN convolutional neural network model using a back propagation algorithm;

[0052] Inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training and keeping the model weights unchanged;

[0053] The predicted value of the CNN convolutional neural network model is calculated using a back propagation algorithm, and the error of the output layer is calculated by comparing the predicted value with the expected output;

[0054] The error is propagated layer by layer in reverse order to recursively calculate the local gradient of each neuron in the CNN convolutional neural network model, calculate the change of each weight, update the weight of the CNN convolutional neural network model, and obtain the carbon dioxide gas concentration data.

[0055] Furthermore, in the above-mentioned method for online automatic monitoring of carbon dioxide gas concentration in soil, the step of judging whether the carbon dioxide gas concentration data is greater than a warning threshold value, and if the carbon dioxide gas concentration data is greater than the warning threshold value, spraying calcium hydroxide through a carbon dioxide neutralization device, and collecting real-time carbon dioxide gas data in the soil in real time, comprises:

[0056] Determine whether the carbon dioxide gas concentration data is greater than a warning threshold, the warning threshold at least including the carbon dioxide gas concentration data being greater than 3%;

[0057] If the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device. When the carbon dioxide gas concentration data is 3%-5%, the spraying concentration of calcium hydroxide is 6%, and 100 ml is sprayed per square meter;

[0058] When the carbon dioxide gas concentration is greater than 5%, the spraying concentration of calcium hydroxide is 8%, 200 ml per square meter;

[0059] The carbon dioxide neutralization device at least includes a calcium hydroxide spraying device, a calcium oxide powder spraying device, and a sodium hydroxide spraying device;

[0060] Real-time carbon dioxide gas data in the soil is collected in real time, and the real-time carbon dioxide gas data is input into the CNN convolutional neural network model for identification to obtain initial carbon dioxide gas concentration data.

[0061] The beneficial effect lies in that, through the gas data acquisition module, the historical carbon dioxide gas data in the soil is acquired through the carbon dioxide gas sensor, and the historical carbon dioxide gas data is preprocessed to obtain the training carbon dioxide gas data; the first gas data recognition module is used to establish a CNN convolutional neural network model, and the training carbon dioxide gas data is input into the CNN convolutional neural network model for training to obtain carbon dioxide gas concentration data; the carbon dioxide neutralization module is used to determine whether the carbon dioxide gas concentration data is greater than the warning threshold, if the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device, and real-time carbon dioxide gas data in the soil is collected in real time; the second gas data recognition module is used to input the real-time carbon dioxide gas concentration data into the CNN convolutional neural network model for training to obtain carbon dioxide gas concentration data. The carbon gas data is input into the CNN convolutional neural network model for identification to obtain the initial carbon dioxide gas concentration data; the gas data transmission module is used to determine whether the initial carbon dioxide gas concentration data meets the preset standard value. If the initial carbon dioxide gas concentration data meets the preset standard value of the soil, the initial carbon dioxide gas concentration data is transmitted to the display terminal; the carbon dioxide supplement module is used to transmit carbon dioxide to the soil through the carbon dioxide release device if the initial carbon dioxide gas concentration data is less than the preset standard value; the gas data monitoring module is used to monitor the carbon dioxide gas data in the soil in real time to obtain the target carbon dioxide gas concentration data; when the target carbon dioxide gas concentration data meets the preset standard value, the carbon dioxide release device is stopped from transmitting carbon dioxide to the soil. The carbon dioxide gas concentration data in the soil of a large area can be monitored in real time, the carbon dioxide concentration in the soil of a large area can be automatically monitored and warned, and the carbon dioxide concentration in the soil of a large area can be effectively adjusted automatically, thereby improving management efficiency and reducing the input of manpower and material resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the following detailed description of the preferred embodiment.The drawings are only for the purpose of illustrating the preferred embodiments and are not to be construed as limiting the invention.

[0063] Figure 1 This is a schematic diagram of a first embodiment of an online automatic monitoring system for carbon dioxide gas concentration in soil according to an embodiment of the present invention;

[0064] Figure 2 This is a schematic diagram of a second embodiment of an online automatic monitoring system for carbon dioxide gas concentration in soil according to an embodiment of the present invention;

[0065] Figure 3 This is a schematic diagram of a third embodiment of an online automatic monitoring system for carbon dioxide gas concentration in soil according to an embodiment of the present invention;

[0066] Figure 4 Schematic diagram of a first embodiment of an online automatic monitoring method for carbon dioxide gas concentration in soil according to an embodiment of the present invention. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0068] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a", "an" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0069] The present invention will be described in detail below in conjunction with the accompanying drawings. Figure 1 As shown, an online automatic monitoring system for carbon dioxide gas concentration in soil, the online automatic monitoring system includes the following modules:

[0070] The gas data acquisition module is used to acquire historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor, perform data preprocessing on the historical carbon dioxide gas data, and obtain training carbon dioxide gas data; specifically, the present embodiment also includes a sensor submodule, which is used to acquire historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor, and perform data preprocessing on the historical carbon dioxide gas data; the carbon dioxide gas sensor at least includes a solid electrolytic CO 2 Sensors, optical fiber CO 2 Sensor, Capacitive CO 2 Sensor; sensor setting submodule, used to determine that the carbon dioxide gas sensor is inserted into the soil 10cm, and the arrangement density of the carbon dioxide gas sensor is 1 / 2m 2 ; A data determination submodule is used to determine that the historical carbon dioxide gas data is the electrical signal data and digital signal data of the carbon dioxide gas sensor; the historical carbon dioxide gas data includes at least the electrical signal data of more than 500 carbon dioxide gas sensors; a data denoising submodule is used to perform denoising on the historical carbon dioxide gas data using a wavelet threshold denoising method to obtain denoised historical carbon dioxide gas data; an obtaining submodule is used to randomly extract 80% of the historical carbon dioxide gas data to obtain training carbon dioxide gas data.

[0071] The first gas data recognition module is used to establish a CNN convolutional neural network model, input the training carbon dioxide gas data into the CNN convolutional neural network model for training, and obtain carbon dioxide gas concentration data;

[0072] Specifically, the present embodiment also includes a model building unit, which is used to build a CNN convolutional neural network model and optimize the CNN convolutional neural network model using a back propagation algorithm; a model training unit, which is used to input the training carbon dioxide gas data into the CNN convolutional neural network model for training and keep the model weights unchanged; a back propagation calculation unit, which is used to calculate the predicted value of the CNN convolutional neural network model using a back propagation algorithm, and calculate the error of the output layer by comparing the predicted value with the expected output; a recursive calculation unit, which is used to use the error to propagate layer by layer in reverse, recursively calculate the local gradient of each neuron of the CNN convolutional neural network model, and calculate the change in each weight, update the weight of the CNN convolutional neural network model, and obtain carbon dioxide gas concentration data.

[0073] The carbon dioxide neutralization module is used to determine whether the carbon dioxide gas concentration data is greater than the warning threshold. If the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device and real-time carbon dioxide gas data in the soil is collected in real time;

[0074] Specifically, the present embodiment also includes a judgment submodule, which is used to judge whether the carbon dioxide gas concentration data is greater than the warning threshold, and the warning threshold at least includes that the carbon dioxide gas concentration data is greater than 3%; a threshold submodule, which is used to determine that if the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device, and when the carbon dioxide gas concentration data is 3%-5%, the spraying concentration of calcium hydroxide is 6%, and 100 ml is sprayed per square meter; a numerical submodule, which is used to determine that when the carbon dioxide gas concentration data is greater than 5%, the spraying concentration of calcium hydroxide is 8%, and 200 ml is sprayed per square meter; a category submodule, which is used to determine that the carbon dioxide neutralization device at least includes a calcium hydroxide spraying device, a calcium oxide powder spraying device, and a sodium hydroxide spraying device; an identification submodule, which is used to collect real-time carbon dioxide gas data in the soil in real time, and input the real-time carbon dioxide gas data into the CNN convolutional neural network model for identification to obtain initial carbon dioxide gas concentration data.

[0075] The second gas data recognition module is used to input the real-time carbon dioxide gas data into the CNN convolutional neural network model for recognition to obtain initial carbon dioxide gas concentration data;

[0076] A gas data transmission module, used to determine whether the initial carbon dioxide gas concentration data meets the preset standard value. If the initial carbon dioxide gas concentration data meets the preset soil standard value, the initial carbon dioxide gas concentration data is transmitted to the display terminal;

[0077] Specifically, the present embodiment also includes a judgment submodule, which is used to judge whether the initial carbon dioxide gas concentration data meets the preset standard value, and the preset standard value is that the initial carbon dioxide gas concentration data is less than 0.5%; a transmission submodule, which is used to transmit the initial carbon dioxide gas concentration data to the display terminal if the initial carbon dioxide gas concentration data meets the soil preset standard value; an early warning submodule, which is used to transmit the initial carbon dioxide gas concentration data and the carbon dioxide neutralization device spraying data to the server for early warning if the initial carbon dioxide gas concentration data does not meet the soil preset standard value.

[0078] A carbon dioxide supplement module is used to transmit carbon dioxide to the soil through a carbon dioxide release device if the initial carbon dioxide gas concentration data is less than a preset standard value;

[0079] Specifically, the present embodiment also includes a gas release unit, which is used to determine that if the initial carbon dioxide gas concentration data is less than a preset standard value, carbon dioxide is transmitted to the soil through the carbon dioxide release device; a gas value unit, which is used to determine that when the initial carbon dioxide gas concentration data is 0.2%-0.3%, carbon dioxide gas with a concentration of 3% is released through the carbon dioxide release device, and 300 ml per square meter is released; when the initial carbon dioxide gas concentration data is less than 0.2%, carbon dioxide gas with a concentration of 5% is released through the carbon dioxide release device, and 400 ml per square meter is released; a release arrangement unit, which is used to determine that the carbon dioxide release device is inserted into the soil by 6 cm, and the arrangement density of the carbon dioxide release device is 1 / 4m 2 .

[0080] The gas data monitoring module is used to monitor the carbon dioxide gas data in the soil in real time to obtain the target carbon dioxide gas concentration data; when the target carbon dioxide gas concentration data meets the preset standard value, the carbon dioxide release device is stopped from transmitting carbon dioxide to the soil.

[0081] Specifically, the present embodiment also includes a gas data acquisition unit, which is used to monitor the carbon dioxide gas data in the soil in real time, and obtain the carbon dioxide gas data in the soil every 5 minutes through the carbon dioxide sensor to obtain the target carbon dioxide gas concentration data; a gas data transmission unit, which is used to record the carbon dioxide concentration release data corresponding to the target carbon dioxide gas concentration data, and input the target carbon dioxide gas concentration data and the carbon dioxide concentration release data into a database for storage; a gas release control unit, which is used to stop using the carbon dioxide release device to transmit carbon dioxide to the soil when the target carbon dioxide gas concentration data meets the preset standard value.

[0082] The beneficial effect lies in that, through the gas data acquisition module, the historical carbon dioxide gas data in the soil is acquired through the carbon dioxide gas sensor, and the historical carbon dioxide gas data is preprocessed to obtain the training carbon dioxide gas data; the first gas data recognition module is used to establish a CNN convolutional neural network model, and the training carbon dioxide gas data is input into the CNN convolutional neural network model for training to obtain carbon dioxide gas concentration data; the carbon dioxide neutralization module is used to determine whether the carbon dioxide gas concentration data is greater than the warning threshold. If the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device, and real-time carbon dioxide gas data in the soil is collected in real time; the second gas data recognition module is used to input the real-time carbon dioxide gas concentration data into the CNN convolutional neural network model for training to obtain carbon dioxide gas concentration data. The volume data is input into the CNN convolutional neural network model for identification to obtain the initial carbon dioxide gas concentration data; the gas data transmission module is used to determine whether the initial carbon dioxide gas concentration data meets the preset standard value. If the initial carbon dioxide gas concentration data meets the preset standard value of the soil, the initial carbon dioxide gas concentration data is transmitted to the display terminal; the carbon dioxide supplement module is used to transmit carbon dioxide to the soil through the carbon dioxide release device if the initial carbon dioxide gas concentration data is less than the preset standard value; the gas data monitoring module is used to monitor the carbon dioxide gas data in the soil in real time to obtain the target carbon dioxide gas concentration data; when the target carbon dioxide gas concentration data meets the preset standard value, the carbon dioxide release device is stopped from transmitting carbon dioxide to the soil. The carbon dioxide gas concentration data in the soil of a large area can be monitored in real time, the carbon dioxide concentration in the soil of a large area can be automatically monitored and warned, and the carbon dioxide concentration in the soil of a large area can be effectively adjusted automatically, improving management efficiency and reducing the investment of manpower and material resources.

[0083] In this embodiment, please refer to Figure 2 In a second embodiment of an online automatic monitoring system for carbon dioxide gas concentration in soil according to an embodiment of the present invention, the first gas data identification module includes the following units:

[0084] A model building unit, used to build a CNN convolutional neural network model and optimize the CNN convolutional neural network model using a back propagation algorithm;

[0085] A model training unit, used for inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training and keeping the model weights unchanged;

[0086] A back propagation calculation unit is used to calculate the predicted value of the CNN convolutional neural network model using a back propagation algorithm, and to calculate the error of the output layer by comparing the predicted value with the expected output;

[0087] The recursive calculation unit is used to utilize the error to propagate layer by layer in reverse order, recursively calculate the local gradient of each neuron of the CNN convolutional neural network model, calculate the change of each weight, update the weight of the CNN convolutional neural network model, and obtain the carbon dioxide gas concentration data.

[0088] In this embodiment, please refer to Figure 3 In a third embodiment of an online automatic monitoring system for carbon dioxide gas concentration in soil according to an embodiment of the present invention, the carbon dioxide neutralization module includes the following submodules:

[0089] A judgment submodule, used to judge whether the carbon dioxide gas concentration data is greater than a warning threshold, and the warning threshold at least includes the carbon dioxide gas concentration data being greater than 3%;

[0090] The threshold submodule is used to determine that if the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device. When the carbon dioxide gas concentration data is 3%-5%, the spraying concentration of calcium hydroxide is 6%, and 100 ml is sprayed per square meter;

[0091] The numerical submodule is used to determine that when the carbon dioxide gas concentration data is greater than 5%, the spraying concentration of calcium hydroxide is 8%, and 200 ml is sprayed per square meter;

[0092] A category submodule, used to determine that the carbon dioxide neutralization device at least includes a calcium hydroxide spraying device, a calcium oxide powder spraying device, and a sodium hydroxide spraying device;

[0093] The identification submodule is used to collect real-time carbon dioxide gas data in the soil, input the real-time carbon dioxide gas data into the CNN convolutional neural network model for identification, and obtain initial carbon dioxide gas concentration data.

[0094] The above describes an online automatic monitoring system for carbon dioxide gas concentration in soil provided by an embodiment of the present invention. The following describes an online automatic monitoring method for carbon dioxide gas concentration in soil provided by an embodiment of the present invention. Figure 4, an embodiment of the online automatic monitoring method in the embodiment of the present invention includes:

[0095] Acquire historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor, perform data preprocessing on the historical carbon dioxide gas data, and obtain training carbon dioxide gas data;

[0096] A CNN convolutional neural network model is established, and the training carbon dioxide gas data is input into the CNN convolutional neural network model for training to obtain carbon dioxide gas concentration data;

[0097] Determine whether the carbon dioxide gas concentration data is greater than the warning threshold. If the carbon dioxide gas concentration data is greater than the warning threshold, spray calcium hydroxide through the carbon dioxide neutralization device and collect real-time carbon dioxide gas data in the soil in real time;

[0098] The real-time carbon dioxide gas data is input into the CNN convolutional neural network model for identification to obtain the initial carbon dioxide gas concentration data;

[0099] Determine whether the initial carbon dioxide gas concentration data meets the preset standard value. If the initial carbon dioxide gas concentration data meets the preset soil standard value, transmit the initial carbon dioxide gas concentration data to the display terminal;

[0100] If the initial carbon dioxide gas concentration data is less than the preset standard value, carbon dioxide is transmitted to the soil through the carbon dioxide release device;

[0101] The carbon dioxide gas data in the soil is monitored in real time to obtain the target carbon dioxide gas concentration data; when the target carbon dioxide gas concentration data meets the preset standard value, the carbon dioxide release device is stopped from transmitting carbon dioxide into the soil.

[0102] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An online automatic monitoring system for carbon dioxide gas concentration in soil, characterized in that: The online automatic monitoring system includes the following modules: A gas data acquisition module, used to acquire historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor, and perform data preprocessing on the historical carbon dioxide gas data to obtain training carbon dioxide gas data; A first gas data recognition module is used to establish a CNN convolutional neural network model, input the training carbon dioxide gas data into the CNN convolutional neural network model for training, and obtain carbon dioxide gas concentration data; A carbon dioxide neutralization module is used to determine whether the carbon dioxide gas concentration data is greater than the warning threshold. If the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through a carbon dioxide neutralization device, and real-time carbon dioxide gas data in the soil is collected in real time; A second gas data recognition module is used to input the real-time carbon dioxide gas data into the CNN convolutional neural network model for recognition to obtain initial carbon dioxide gas concentration data; A gas data transmission module, used to determine whether the initial carbon dioxide gas concentration data meets the preset standard value, and if the initial carbon dioxide gas concentration data meets the preset soil standard value, transmit the initial carbon dioxide gas concentration data to the display terminal; A carbon dioxide supplement module, used for transmitting carbon dioxide into the soil through a carbon dioxide release device if the initial carbon dioxide gas concentration data is less than a preset standard value; The gas data monitoring module is used to monitor the carbon dioxide gas data in the soil in real time to obtain the target carbon dioxide gas concentration data; when the target carbon dioxide gas concentration data meets the preset standard value, the carbon dioxide release device is stopped from transmitting carbon dioxide to the soil.

2. The online automatic monitoring system for carbon dioxide gas concentration in soil according to claim 1, characterized in that: The gas data acquisition module includes the following submodules: The sensor submodule is used to obtain historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor and perform data preprocessing on the historical carbon dioxide gas data; the carbon dioxide gas sensor at least includes a solid electrolytic CO2 sensor, an optical fiber CO2 sensor, and a capacitive CO2 sensor; The sensor setting submodule is used to determine that the carbon dioxide gas sensor is inserted into the soil by 10 cm and the arrangement density of the carbon dioxide gas sensor is 1 / 2m 2 ; A data determination submodule, used to determine that the historical carbon dioxide gas data is electrical signal data and digital signal data of a carbon dioxide gas sensor; the historical carbon dioxide gas data includes at least electrical signal data of more than 500 carbon dioxide gas sensors; A data denoising submodule, used for performing denoising processing on the historical carbon dioxide gas data using a wavelet threshold denoising method to obtain denoised historical carbon dioxide gas data; A submodule is obtained, which is used to randomly extract 80% of the historical carbon dioxide gas data to obtain training carbon dioxide gas data.

3. The online automatic monitoring system for carbon dioxide gas concentration in soil according to claim 1, characterized in that: The first gas data identification module includes the following units: A model building unit, used to build a CNN convolutional neural network model and optimize the CNN convolutional neural network model using a back propagation algorithm; A model training unit, used for inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training and keeping the model weights unchanged; A back propagation calculation unit, used to calculate the predicted value of the CNN convolutional neural network model using a back propagation algorithm, and calculate the error of the output layer by comparing the predicted value with the expected output; The recursive calculation unit is used to utilize the error to propagate layer by layer in reverse order, recursively calculate the local gradient of each neuron of the CNN convolutional neural network model, calculate the change amount of each weight, update the weight of the CNN convolutional neural network model, and obtain the carbon dioxide gas concentration data.

4. The online automatic monitoring system for carbon dioxide gas concentration in soil according to claim 1, characterized in that: The carbon dioxide neutralization module includes the following submodules: A judgment submodule, used to judge whether the carbon dioxide gas concentration data is greater than a warning threshold, and the warning threshold at least includes that the carbon dioxide gas concentration data is greater than 3%; The threshold submodule is used to determine that if the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device. When the carbon dioxide gas concentration data is 3%-5%, the spraying concentration of calcium hydroxide is 6%, and 100 ml is sprayed per square meter; The numerical submodule is used to determine that when the carbon dioxide gas concentration data is greater than 5%, the spraying concentration of calcium hydroxide is 8%, and 200 ml is sprayed per square meter; A category submodule, used to determine that the carbon dioxide neutralization device at least includes a calcium hydroxide spraying device, a calcium oxide powder spraying device, and a sodium hydroxide spraying device; The identification submodule is used to collect real-time carbon dioxide gas data in the soil in real time, input the real-time carbon dioxide gas data into the CNN convolutional neural network model for identification, and obtain initial carbon dioxide gas concentration data.

5. The online automatic monitoring system for carbon dioxide gas concentration in soil according to claim 1, characterized in that: The gas data transmission module includes the following submodules: A judgment submodule, used to judge whether the initial carbon dioxide gas concentration data meets a preset standard value, and the preset standard value is that the initial carbon dioxide gas concentration data is less than 0.5%; A transmission submodule, configured to transmit the initial carbon dioxide gas concentration data to a display terminal if the initial carbon dioxide gas concentration data meets a preset soil standard value; The early warning submodule is used to transmit the initial carbon dioxide gas concentration data and the carbon dioxide neutralization device spraying data to the server for early warning if the initial carbon dioxide gas concentration data does not meet the preset standard value of the soil.

6. The online automatic monitoring system for carbon dioxide gas concentration in soil according to claim 1, characterized in that: The carbon dioxide supplement module includes the following submodules: A gas release unit, used to determine if the initial carbon dioxide gas concentration data is less than a preset standard value, then transmit carbon dioxide to the soil through a carbon dioxide release device; A gas value unit, used to determine that when the initial carbon dioxide gas concentration data is 0.2%-0.3%, a carbon dioxide gas with a concentration of 3% is released through the carbon dioxide release device, and 300 ml is released per square meter; when the initial carbon dioxide gas concentration data is less than 0.2%, a carbon dioxide gas with a concentration of 5% is released through the carbon dioxide release device, and 400 ml is released per square meter; The release arrangement unit is used to determine that the carbon dioxide release device is inserted into the soil by 6 cm, and the arrangement density of the carbon dioxide release device is 1 / 4m 2 .

7. The online automatic monitoring system for carbon dioxide gas concentration in soil according to claim 1, characterized in that: The gas data monitoring module includes the following units: The gas data acquisition unit is used to monitor the carbon dioxide gas data in the soil in real time, and acquire the carbon dioxide gas data in the soil every 5 minutes through the carbon dioxide sensor to obtain the target carbon dioxide gas concentration data; A gas data transmission unit, used for recording the carbon dioxide concentration release data corresponding to the target carbon dioxide gas concentration data, and inputting the target carbon dioxide gas concentration data and the carbon dioxide concentration release data into a database for storage; The gas release control unit is used to stop using the carbon dioxide release device to transmit carbon dioxide into the soil when the target carbon dioxide gas concentration data meets the preset standard value.

8. Implementing the method for online automatic monitoring of carbon dioxide gas concentration in soil as claimed in claim 1, characterized in that: The method for online automatic monitoring of carbon dioxide gas concentration comprises the following steps: Acquire historical carbon dioxide gas data in the soil through a carbon dioxide gas sensor, perform data preprocessing on the historical carbon dioxide gas data, and obtain training carbon dioxide gas data; Establishing a CNN convolutional neural network model, inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training, and obtaining carbon dioxide gas concentration data; Determine whether the carbon dioxide gas concentration data is greater than a warning threshold value. If the carbon dioxide gas concentration data is greater than the warning threshold value, spray calcium hydroxide through a carbon dioxide neutralization device and collect real-time carbon dioxide gas data in the soil in real time; Inputting the real-time carbon dioxide gas data into the CNN convolutional neural network model for identification to obtain initial carbon dioxide gas concentration data; Determine whether the initial carbon dioxide gas concentration data meets the preset standard value, and if the initial carbon dioxide gas concentration data meets the preset soil standard value, transmit the initial carbon dioxide gas concentration data to the display terminal; If the initial carbon dioxide gas concentration data is less than a preset standard value, carbon dioxide is transmitted to the soil through a carbon dioxide release device; The carbon dioxide gas data in the soil is monitored in real time to obtain the target carbon dioxide gas concentration data; when the target carbon dioxide gas concentration data meets the preset standard value, the carbon dioxide release device is stopped from transmitting carbon dioxide to the soil.

9. The method for online automatic monitoring of carbon dioxide gas concentration in soil according to claim 8, characterized in that: The method of establishing a CNN convolutional neural network model and inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training to obtain carbon dioxide gas concentration data includes: Establishing a CNN convolutional neural network model, and optimizing the CNN convolutional neural network model using a back propagation algorithm; Inputting the training carbon dioxide gas data into the CNN convolutional neural network model for training and keeping the model weights unchanged; The predicted value of the CNN convolutional neural network model is calculated using a back propagation algorithm, and the error of the output layer is calculated by comparing the predicted value with the expected output; The error is propagated layer by layer in reverse order to recursively calculate the local gradient of each neuron in the CNN convolutional neural network model, calculate the change of each weight, update the weight of the CNN convolutional neural network model, and obtain the carbon dioxide gas concentration data.

10. The method for online automatic monitoring of carbon dioxide gas concentration in soil according to claim 8, characterized in that: The determining whether the carbon dioxide gas concentration data is greater than a warning threshold, if the carbon dioxide gas concentration data is greater than the warning threshold, spraying calcium hydroxide through a carbon dioxide neutralization device, and collecting real-time carbon dioxide gas data in the soil in real time, includes: Determine whether the carbon dioxide gas concentration data is greater than a warning threshold, the warning threshold at least including the carbon dioxide gas concentration data being greater than 3%; If the carbon dioxide gas concentration data is greater than the warning threshold, calcium hydroxide is sprayed through the carbon dioxide neutralization device. When the carbon dioxide gas concentration data is 3%-5%, the spraying concentration of calcium hydroxide is 6%, and 100 ml is sprayed per square meter; When the carbon dioxide gas concentration is greater than 5%, the spraying concentration of calcium hydroxide is 8%, 200 ml per square meter; The carbon dioxide neutralization device at least includes a calcium hydroxide spraying device, a calcium oxide powder spraying device, and a sodium hydroxide spraying device; Real-time carbon dioxide gas data in the soil is collected in real time, and the real-time carbon dioxide gas data is input into the CNN convolutional neural network model for identification to obtain initial carbon dioxide gas concentration data.

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