Ammonia volatilization online detection device based on arduino board

Abstract

The application discloses an ammonia volatile online detection device based on an Arduino board, which comprises a rain cover, a one-way air cavity, a support, a cleaning chamber, a data processing unit, a detection chamber, a PTC heating element, a stepping motor, a screw rod and a gravity blade I; the rain cover is fixed above the one-way air cavity through a rain cover support, the cleaning chamber is fixed at the top center of the one-way air cavity and communicates with the one-way air cavity, the detection chamber is fixed at the top of the cleaning chamber and below the rain cover, more than three supports are movably arranged outside the lower part of the one-way air cavity, and the bottom of the one-way air cavity is provided with an opening; the device has high automation degree, is easy to carry, can adapt to a field detection environment, can stably remotely detect ammonia concentration, and the detection result is relatively accurate.

Description

Technical Field

[0001] This invention belongs to the field of ammonia volatilization detection technology, specifically relating to an online ammonia volatilization detection device based on an Arduino board. Background Technology

[0002] Ammonia volatilization refers to the evaporation of nitrogen from the soil as gaseous NH3 from the surface of farmland or farmland water, reducing the nitrogen content in the soil and decreasing the utilization efficiency of nitrogen fertilizer applied in agricultural production. Traditional methods for measuring ammonia volatilization mostly rely on acid absorption methods, but these methods are time-consuming, labor-intensive, and have limited accuracy. More importantly, it is difficult to obtain real-time ammonia volatilization rates. In recent years, the use of sensors combined with algorithms has become increasingly well-known. However, single sensors are not only inaccurate, but also prone to malfunctions, causing the device to stop working. Against this backdrop, this design employs an Arduino board and multi-sensor data fusion algorithm technology, improving the device's accuracy while ensuring continuous high-intensity operation in the harsh environment of farmland. Summary of the Invention

[0003] This invention provides an online ammonia volatilization detection device based on an Arduino board, which includes a rain cover, a one-way gas chamber, a support, a cleaning chamber, a data processing unit, a detection chamber, a PTC heating element, a stepper motor, a screw, and a gravity blade I. The rain cover is fixed above the one-way gas chamber by a rain cover support. The cleaning chamber is fixed at the center of the top of the one-way gas chamber and communicates with it. The detection chamber is fixed on top of the cleaning chamber and located below the rain cover. Three or more supports are movably arranged on the lower outer side of the one-way gas chamber. The bottom of the one-way gas chamber is open.

[0004] When the PTC heating element is powered on, it can raise the temperature of the detection chamber to 43°C within 1 minute. At such an ambient temperature, the residual ammonia and other gases in the sensor probe will evaporate, thus achieving the effect of cleaning the sensor probe.

[0005] A stepper motor is fixed at the top center of the one-way air chamber via a stepper motor bracket. The output shaft of the stepper motor is fixed to the screw via a coupling. One or more guide rods are provided inside the one-way air chamber. The grid chassis is fitted onto the screw and guide rods, and its center is threaded with the screw. Two or more gravity blades I are connected to the grid chassis via hinges. The gravity blades I are located above the holes on the grid chassis. The PTC heating element is fixed inside the cleaning chamber via a bracket and located above the stepper motor.

[0006] The detection chamber includes a hollow shell with openings at the top and bottom, and a flow guide plate. The flow guide plate is fixed below the lower opening of the shell by a bracket. Two gravity blades II are movably mounted at the upper opening of the shell via shafts. A sensor bracket is fixed inside the detection chamber, on which three chemical sensors and one semiconductor sensor are installed. The sensors are a CLE-1012-400 chemical sensor, a 7ID-NH3 chemical sensor, an NH3-B1 chemical sensor, and an MQ137 semiconductor sensor. The sensor bracket is cross-shaped, and the flow guide plate is a circular plate.

[0007] The data processing unit includes a housing and an Arduino Mega2560, an Arduino Uno board, and a wireless transmission module installed in the housing. The Arduino Mega2560 is connected to the wireless transmission module through the Arduino Uno board. The Arduino Uno board is connected to the stepper motor and the PTC heating element respectively. The four sensors are connected to the Arduino Mega2560 respectively. The wireless transmission module is connected to a computer or smartphone.

[0008] The wireless transmission module is model ESP8266. The Arduino Mega2560 is responsible for collecting and processing the data (Rs, time) obtained from the sensor. The Arduino Uno board is responsible for receiving commands from the host computer, controlling the movement of the stepper motor, and transmitting data.

[0009] This device can also be equipped with a display screen on the data processing unit, which is connected to the Arduino Mega2560 to display ammonia concentration and time. It can also be equipped with a speed control button on the data processing unit, which is connected to the stepper motor through the Arduino Uno board to adjust the speed of the stepper motor.

[0010] The Arduino Mega2560 also includes a calculation module for converting the collected sensor resistance data into ammonia concentration over a certain time period, specifically:

[0011] (1) First, use this device to detect ammonia gas of known concentration and obtain the resistance value R of the sensor under ammonia gas conditions. s Calculate R s The ratio of / R0, where R0 is the resistance of the sensor under air conditions, and R is the resistance of the sensor under air conditions. s Using the R0 ratio as the ordinate and ammonia concentration as the abscissa, a standard curve was plotted, yielding the regression equation C = a·X- for each sensor. c +b, X=R s / R0;

[0012] Formula V RL / R L =(V C -VRL ) / R s Substituting these values ​​into the above regression equation yields the ammonia concentrations C and V. RL The relation, where R L For the output resistance, V C V is the loop voltage of the sensor. RL The output voltage of the sensor;

[0013] (2) Place this device in the test environment where ammonia gas evaporates using a bracket. The Arduino Mega2560 collects the R signals from four sensors. s Substitute the values ​​into the ammonia concentrations C and V from step (1). RL In the formula, the ammonia concentration detected by the four sensors in a certain time period is calculated; then, the ammonia concentration C in the detection area in a certain time period is obtained by weighted fusion of the ammonia concentration detected by the four sensors through an adaptive weighted fusion algorithm.

[0014] When using the above-mentioned device, it is placed on the ground to be tested using a support. A rain cover is used to prevent rainwater from entering the device in agricultural environments and affecting the accuracy of ammonia detection. A computer or smartphone sends a signal to the Arduino Uno board in the data processing unit via a wireless transmission module, activating the stepper motor. The stepper motor rotates in reverse, initiating negative pressure air intake. The stepper motor drives the grid base to move downwards along the guide rod and screw. Gravity blade I on the grid base opens under negative pressure, while gravity blade II closes under its own weight and the negative pressure within the one-way air chamber. The one-way air chamber draws in the gas to be tested due to the negative pressure. The external gas to be tested passes through the grid base and enters the one-way air chamber, completing the air intake process. The stepper motor then rotates in the forward direction, driving the grid base upwards. The gas to be tested passes through the clean chamber and enters the detection chamber. The resistance value R of the sensors under ammonia conditions is obtained through three chemical sensors and one semiconductor sensor. s The Arduino Mega2560 collects data detected by the sensor and obtains the ammonia concentration through the calculation module. At the same time, as the gas moves upward on the grid chassis, it pushes open the gravity blade II, and the gas is discharged. Gravity blade I closes under its own weight and the gas pressure in the cavity until the grid chassis moves upward to its limit stroke, completing the detection and exhaust process.

[0015] Compared with the prior art, the beneficial effects of the present invention are:

[0016] 1. A sensor array consisting of four different types of sensors can be used to detect ammonia volatilization, which can quickly, effectively and accurately obtain the ammonia concentration in the farmland environment, and help to carry out scientific farming.

[0017] 2. By using an improved adaptive weighted fusion algorithm, data fusion is achieved through weighting factors assigned to each sensor. This not only prevents the failure of a single sensor from causing malfunction during operation, but also allows for more accurate data acquisition and analysis compared to traditional detection methods.

[0018] 3. The one-way gas chamber controlled by the stepper motor can scientifically collect and release ammonia, and detect the PTC heating element in the gas chamber to clean the probe by heating and evaporating ammonia.

[0019] 4. Through cloud services and wireless communication functions, the device can be controlled by smartphones or computers to monitor the daily changes in ammonia volatilization in real time and accurately control the daily ammonia concentration in the greenhouse. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the device structure of the present invention;

[0021] Figure 2 This is a schematic diagram of the structure of the device of the present invention;

[0022] Figure 3 This is a schematic diagram of the internal structure of a unidirectional air cavity;

[0023] Figure 4 A schematic diagram of the indoor structure for inspection;

[0024] Figure 5 This is a schematic diagram of part of the structure of the device of the present invention;

[0025] Figure 6 The standard curve for sensor NH3-B1;

[0026] Figure 7 The standard curve for sensor 7ID-NH3;

[0027] Figure 8 The standard curve for sensor CLE-1012-400;

[0028] Figure 9 The standard curve for the MQ137 sensor;

[0029] In the diagram: 1-Rain cover; 2-Rain cover bracket; 3-One-way air chamber; 4-Bracket; 5-Clean chamber; 6-Data processing unit; 7-Detection chamber; 8-Gravity blade II; 9-Drain plate; 10-Sensor bracket; 11-PTC heating element; 12-Stepper motor bracket; 13-Stepper motor; 14-Screw; 15-Gravity blade I; 16-Grid chassis; 17-Sensor; 18-Guide rod. Detailed Implementation

[0030] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. However, the scope of protection of the present invention is not limited to the contents described. Unless otherwise specified, the methods in the embodiments are conventional methods.

[0031] Example 1: As Figure 1-5 As shown, the ammonia volatilization precision online detection device based on an Arduino board in this embodiment includes a rain cover 1, a one-way gas chamber 3, a bracket 4, a cleaning chamber 5, a data processing unit 6, a detection chamber 7, a PTC heating element 11, a stepper motor 13, a screw 14, and a gravity blade I 15. The rain cover 1 is fixed above the one-way gas chamber 3 by a rain cover bracket 2. The one-way gas chamber 3 is a cylindrical structure with an open bottom. The cleaning chamber 5 is welded and fixed to the center opening at the top of the one-way gas chamber 3 and communicates with it. The cylindrical detection chamber 7 is fixed on top of the cleaning chamber 5 and located below the rain cover 1. Three brackets 4 are movably arranged on the lower outer side of the one-way gas chamber 3. The upper end of the bracket 4 is inserted into three perforated support seats fixed on the lower outer side of the one-way gas chamber 3 by a pin and cooperates with each other. It can be folded up for storage and can be supported on the ground when rotated downwards. A stepper motor 13 is fixed at the top center of the one-way gas chamber 3 by a stepper motor bracket 12. The output shaft of the stepper motor 13 is fixed to the screw 14 by a coupling. The unidirectional air chamber 3 is equipped with three guide rods 18. A circular grid base 16 is fitted onto the screw 14 and guide rods 18, with its center threaded into the screw. Three gravity blades I 15 are connected to the grid base 16 via hinges. The three gravity blades I 15 are located above the holes on the grid base 16 and completely cover the grid base. The PTC heating element 11 is fixed in the cavity of the cleaning chamber 5 by a bracket and is located above the stepper motor 13. The detection chamber 7 includes a hollow shell with upper and lower openings and a drainage plate 9. The drainage plate 9 is a circular plate and is fixed below the lower opening of the shell by a bracket. Two semi-circular gravity blades II 8 are movably set at the upper opening of the shell via a shaft. A cross-shaped sensor bracket 10 is welded and fixed in the detection chamber 7, on which three chemical sensors (CLE-1012-400 chemical sensor, 7ID-NH3 chemical sensor, NH3-B1 chemical sensor) and one semiconductor sensor (MQ137 semiconductor sensor) are installed.

[0032] The data processing unit includes a housing and an Arduino Mega2560, an Arduino Uno board, and a wireless transmission module housed within the housing. The Arduino Mega2560 is connected to the wireless transmission module (ESP8266) via the Arduino Uno board. The Arduino Uno board is connected to a stepper motor and a PTC heating element, respectively. Four sensors 17 are connected to the Arduino Mega2560, and the wireless transmission module is connected to a computer. The Arduino Mega2560 includes a calculation module used to convert the collected sensor resistance data into ammonia concentration over a certain time period.

[0033] The above-mentioned device is used as follows:

[0034] 1. Upon first use, use this device to detect ammonia gas with a concentration of 3.5-100 ppm and obtain the resistance values ​​R of the four sensors under ammonia gas conditions. s Simultaneously, the resistance values ​​R0 of the four sensors were measured under air conditions, and R was calculated. s The ratio of / R0, with R s Plot a standard curve with the R0 ratio as the ordinate and ammonia concentration as the abscissa (see [reference]). Figure 6-9 The regression equation for the four sensors was obtained as C = 21.5717X - 0.8565 +0.2176(NH3-B1); C=26.0141X- 6811 +0.1024(7ID-NH3);C=27.6252X- 0.6205 +0.1476(CLE-1012-400); C=25.6581X- 0.71274 +0.2764(MQ137); where X = R s / R0;

[0035] Formula V RL / R L =(V C -V RL ) / R s Substituting these values ​​into the above regression equation yields the concentrations C and V. RL The following relation is given, where R L For the output resistor (R of CLE-1012-400) L (4Ω, MQ137 is 29Ω, NH3-B1 is 10Ω, 7ID-NH3 is 1Ω), V C The loop voltage of the sensors (V of the four sensors) C (5V), V RL The output voltage of the sensor;

[0036] C1

[0037] C2

[0038] C3

[0039] C4

[0040] 2. The above-mentioned device is placed on the ground of the farmland to be tested using the support 4. The rain cover 1 is used to prevent rainwater from entering the device and affecting the accuracy of ammonia detection. The computer sends a signal to the Arduino Uno board in the data processing unit 6 via the wireless transmission module to turn on the stepper motor 13. The stepper motor rotates in reverse to perform negative pressure air intake. The stepper motor drives the grid base 16 to move downward along the guide rod 18 and the screw 14. The gravity blade I 15 on the grid base opens under the negative pressure, and the gravity blade II 8 closes under its own weight and the negative pressure in the one-way air chamber. The one-way air chamber 3 is drawn in the gas to be tested due to the negative pressure. The gas to be tested passes through the grid base and enters the one-way air chamber, completing the air intake process. The stepper motor rotates in the forward direction, driving the grid base to move upward. The gas to be tested passes through the clean chamber 5 and enters the detection chamber 7. The resistance values ​​R of the four sensors under ammonia conditions are obtained through three chemical sensors and one semiconductor sensor. s The Arduino Mega2560 collects the sensor's resistance value Rs data and calculates the ammonia concentration C and V in the module. RL The ammonia concentration is obtained from the formula. At the same time, as the gas moves upward on the grid chassis, it pushes open the gravity blade II, and the gas is discharged. Gravity blade I closes under its own weight and the gas pressure in the cavity until the grid chassis moves upward to its limit stroke, completing the detection and exhaust process. The distance the grid chassis moves upward (0.9 min) or downward (0.9 min) along the screw is 189 mm, and the stepper motor rotates 13.5 revolutions.

[0041] This process obtains ammonia concentrations detected by four sensors. Then, an adaptive fusion algorithm assigns weighting factors to each sensor to allocate the acquired values. The fusion process is as follows: first, the initial measurement values ​​of each sensor are obtained; then, the variance of these measurement data is calculated; finally, the optimal weight is obtained adaptively using the total mean square error of the initial values. Multiplying the optimal weight by the initial value yields the best fused value. After processing by the adaptive weighting algorithm, the data from each sensor is weighted and fused into a single ammonia concentration. The weight calculation steps are as follows: first, the measurement variances of the ammonia sensors are weighted separately... Let ci be the ammonia concentration measured by ammonia sensor i; let wi be the optimal weight value of sensor i; and let the final data fusion value be... Based on the adaptive weighting algorithm, we have: where σ is the total mean square error and is a multivariate quadratic function of the weighting factor wi.

[0042]

[0043]

[0044]

[0045] To make the total mean square error σ 2 To minimize, we need to consider f(w1, w2, ..., w) n Therefore, according to the extremum theorem for multivariable functions, we can obtain:

[0046]

[0047]

[0048] By wi Substituting into equations (1) and (3), we can solve for the optimal measured weights w1, w2, w3, and w4 of each sensor; finally, we can obtain the ammonia concentration detected in this test using formula (2).

[0049] 3. After the test is completed, turn on the PTC heating element 11 in the cleaning chamber. When the PTC heating element is powered on, it can raise the temperature of the test chamber to 43°C within 1 minute. At this ambient temperature, the residual ammonia and other gases in the sensor probe will evaporate, thus achieving the effect of cleaning the sensor probe.

[0050] In this embodiment, a closed field experiment was conducted from February 27, 2022 to March 7, 2022 at the Panax notoginseng field (101°45′E, 24°40′N) of the College of Agriculture and Food Science, Kunming University of Science and Technology. The experiment was conducted during the dry season in Kunming. The average indoor temperature was 16.2℃ and the average humidity was 16.3%. One day before the experiment, ordinary urea (CH4N2O containing 46% N) was applied. The ammonia concentration was measured daily using both this device and the aerated sponge boric acid absorption method. The test started at 7:00 AM on the first day and ended at 7:00 AM on the second day. The device collected data every 15 minutes, 4 times per hour, for a total of 96 sets of data per day. The total ammonia concentration detected by the device that day was summed up.

[0051] The aeration-type sponge phosphoric acid absorption method uses a 200mm diameter acrylic cylinder with ventilation at both ends. Two layers of sponges impregnated with glycerol phosphate solution are placed on top, and the bottom layer is pressed into the soil. This method detects ammonia volatilization and requires the two layers of sponges to be retrieved the following morning for re-arranging new absorption sponges. The ammonia content in the retrieved sponges represents the total ammonia volatilization in the area covered by the aeration-type sponge phosphoric acid absorption method from the start to the end of the experiment. The ammonia concentration absorbed by the aeration-type sponge phosphoric acid absorption method on that day is calculated using the obtained ammonia volatilization amount and the indoor volume. The results are as follows:

[0052] Detection time ppm value detected by ventilation method Device detection value ppm relative error 2022 / 2 / 27 9.168 9.384 2.30％ 2022 / 2 / 28 14.784 15.432 4.20％ 2022 / 3 / 1 23.448 24.528 4.40％ 2022 / 3 / 2 31.152 32.496 4.14％ 2022 / 3 / 3 38.232 40.008 4.44％ 2022 / 3 / 4 44.616 46.608 4.27％ 2022 / 3 / 5 47.544 50.520 5.89％ 2022 / 3 / 6 49.344 52.968 6.84％ 2022 / 3 / 7 50.448 54.432 7.32％

[0053] In this embodiment, the detection accuracy of the device of the present invention was tested using NH3 standard gas at concentrations of 3 ppm, 15 ppm, 20 ppm, 50 ppm, and 100 ppm, respectively; the results are shown in the table below (ppm):

[0054]

[0055] The table shows that the maximum error of this device is 2.23%, indicating that this device has good accuracy in ammonia detection.

[0056] This embodiment tests the stability of the device of the present invention: the ammonia gas with a concentration of 15 ppm was used to run the test 8 times. The results show that the standard deviation of the ammonia volatilization detection device system value does not change significantly, the range is 0.245 ppm, and the overall deviation is 0.435 ppm. The device of the present invention has good stability.

[0057]

[0058] In the experiment, the device of this invention sensed changes in ammonia concentration within the range of 2.4 to 4.5 seconds, exhibiting extremely high response speed. The ammonia concentration detected by this device was consistently higher than that detected by the aeration-type acid absorption method, with a relative error range of 2.30% to 7.32%. Considering that a small amount of ammonia may remain on the sponge in the aeration-type acid absorption method, thus lowering the actual detection result, the above results indicate that the device of this invention can adapt to the field testing environment, stably and remotely detect ammonia concentration in farmland, and provide relatively accurate detection results.

[0059] Example 2: The device structure in this example is the same as in Example 1, except that a display screen is set on the data processing unit. The display screen is connected to the Arduino Mega2560 and is used to display the ammonia concentration and time, which can be used for real-time observation on site.

[0060] Based on the ammonia concentration, the ammonia volatilization rate s = ρW / tA is calculated, where ρ is the ammonia concentration, W is the air intake volume, t is the time, and A is the detection area (i.e., the bottom surface area of ​​the one-way gas chamber).

[0061] Because the aeration-type acid absorption method for detecting ammonia volatilization takes a long time and cannot achieve real-time detection, it can only obtain the concentration of volatilized ammonia within a certain time period. In contrast, the device of this invention can not only obtain the total ammonia concentration within a certain time period, but also the ammonia concentration at different time points within that time period, thereby obtaining the ammonia volatilization status of Panax notoginseng fields in real time. The device of this invention can adapt to the detection environment of Panax notoginseng fields, can stably detect ammonia volatilization concentration remotely, and the detection results are more accurate.

[0062] In summary, the above are merely preferred embodiments of the present invention. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. An online ammonia volatilization detection device based on an Arduino board, characterized in that, It includes a rain cover (1), a one-way air chamber (3), a bracket (4), a cleaning chamber (5), a data processing unit (6), a detection chamber (7), a PTC heating element (11), a stepper motor (13), a screw (14), and a gravity blade I (15); the rain cover (1) is fixed above the one-way air chamber (3) by the rain cover bracket (2), the cleaning chamber (5) is fixed at the center of the top of the one-way air chamber (3) and communicates with it, the detection chamber (7) is fixed at the top of the cleaning chamber (5) and located below the rain cover (1), and more than three brackets (4) are movably set on the lower outer side of the one-way air chamber (3), and the bottom of the one-way air chamber (3) is open; A stepper motor (13) is fixed at the top center of the one-way air chamber (3) by a stepper motor bracket (12). The output shaft of the stepper motor (13) is fixed to the screw (14) by a coupling. One or more guide rods (18) are provided in the one-way air chamber (3). The grid chassis (16) is fitted on the screw (14) and the guide rod (18) and its center is threaded with the screw. Two or more gravity blades I (15) are connected on the grid chassis (16) by a hinge. The gravity blades I (15) are located above the holes on the grid chassis (16). The PTC heating element (11) is fixed in the cavity of the cleaning chamber (5) by a bracket and located above the stepper motor (13). The detection chamber (7) includes a hollow shell with upper and lower openings and a flow guide plate (9). The flow guide plate (9) is fixed below the lower opening of the shell by a bracket. Two gravity blades II (8) are movably set at the upper opening of the shell by a shaft. The sensor bracket (10) is fixed inside the detection chamber (7) and has three chemical sensors and one semiconductor sensor installed on it. The stepper motor rotates in the opposite direction, and the gravity blade I (15) on the grid chassis opens under the action of negative pressure, while the gravity blade II (8) closes under the action of its own weight and the negative pressure in the one-way air chamber. As the stepper motor rotates in the forward direction, the gas pushes the gravity blade II upward as it moves up the grid chassis, allowing the gas to escape. Gravity blade I closes due to its own weight and the gas pressure inside the cavity. The data processing unit includes a housing and an Arduino Mega2560, an Arduino Uno board, and a wireless transmission module installed in the housing. The Arduino Mega2560 is connected to the wireless transmission module through the Arduino Uno board. The Arduino Uno board is connected to a stepper motor and a PTC heating element, respectively. Four sensors are connected to the Arduino Mega2560, and the wireless transmission module is connected to a computer or smartphone. The three chemical sensors are CLE-1012-400 chemical sensor, 7ID-NH3 chemical sensor, and NH3-B1 chemical sensor, respectively, and the semiconductor sensor is MQ137 semiconductor sensor.

2. The online ammonia volatilization detection device based on an Arduino board according to claim 1, characterized in that: The sensor bracket is cross-shaped, and the drainage plate is a circular plate.

3. The online ammonia volatilization detection device based on an Arduino board according to claim 1, characterized in that: The data processing unit is equipped with a display screen, which is connected to the Arduino Mega2560.

4. The online ammonia volatilization detection device based on an Arduino board according to claim 1, characterized in that, The Arduino Mega2560 includes a calculation module for converting the acquired sensor resistance data into ammonia concentration, specifically: (1) First, use this device to detect ammonia gas of known concentration and obtain the resistance value of the sensor under ammonia gas conditions. R s ,calculate R s / R 0 The ratio, R 0 The resistance value of the sensor under air conditions is given by... R s / R 0 Plotting the ratio on the ordinate and ammonia concentration on the abscissa, a standard curve is obtained, yielding the regression equation C = a·X for each sensor. -c +b, X= R s / R 0 ; Formula V RL / R L =( V C - V RL ) / R s Substituting into the above regression equation, we obtain the ammonia concentration C and V RL The relation, in which R L For output resistance, V C The loop voltage of the sensor. V RL The output voltage of the sensor; (2) Place the device in the test environment where ammonia gas evaporates using the bracket (4). The Arduino Mega2560 collects data from the four sensors. R s The value is substituted into the ammonia concentration C from step (1) and V RL In the formula, the ammonia concentration detected by the four sensors in a certain time period is calculated; then, the ammonia concentration detected by the four sensors is weighted and fused by the adaptive weighted fusion algorithm to obtain the ammonia concentration in the detection area in a certain time period.

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