A method and system for detecting farmland ammonia volatilization loss based on the Internet of Things

Abstract

The invention discloses a method and system for detecting farmland ammonia volatilization loss based on the Internet of Things, belonging to the technical field of farmland ammonia volatilization monitoring. The method comprises: determining the boundary of a target field, using a sensor to collect data, and sending the collected data to a cloud for centralized management; simulating and measuring the reaction rate of ammonia at different temperatures and humidity, and constructing a farmland ammonia parameterization model for calculating the reaction rate constant k; extracting environmental factors from sensor data according to the collected data, integrating the sensor data, and obtaining ammonia concentrations at different positions and at different times; extracting ammonia concentration data at different heights, and generating concentration profile data, obtaining dynamic changes in ammonia concentrations at vertical heights, and calculating an instantaneous ammonia volatilization flux formula; constructing a three-dimensional concentration distribution model for describing the distribution of ammonia concentrations at various positions in the field that varies with height, and calculating the total ammonia volatilization amount of the farmland according to the three-dimensional concentration distribution model.

Description

Technical Field

[0001] The present invention relates to the technical field of farmland ammonia volatilization monitoring, and in particular to a farmland ammonia volatilization loss detection method and system based on the Internet of Things. Background Art

[0002] Ammonia volatilization from farmland is one of the main ways of nitrogen fertilizer loss in agricultural production and an important source of ammonia in the atmosphere. At present, the detection methods of ammonia volatilization loss from farmland mainly include micrometeorological method and chamber method. The micrometeorological method calculates surface ammonia volatilization by measuring the turbulence conditions of the near-ground layer and the ammonia concentration in the air, which can truly reflect the actual situation of ammonia volatilization in farmland, but it requires a large and flat test area, and the instruments and equipment are expensive, which limits its application. The chamber method is simple in principle, low in cost, and easy to use. It is the most commonly used method for measuring ammonia volatilization in farmland, but it has obvious defects.

[0003] The traditional box method usually only considers diffusion and convection processes, ignoring the chemical reactions between ammonia and the environment, such as the reaction between moisture and acidic gases. At the same time, this method ignores the influence of environmental factors such as temperature and humidity on the reaction rate, and the test results are not accurate enough. In addition, the box method cannot accurately describe the distribution of ammonia volatilization losses at different heights and locations, and the spatial resolution is low.

[0004] Therefore, there is an urgent need for a new method for detecting ammonia volatilization losses in farmland, which can comprehensively consider processes such as diffusion, convection and chemical reaction, dynamically adjust the influence of environmental factors, improve spatial resolution, and verify through experimental data, so as to achieve accurate detection of ammonia volatilization losses in farmland. Summary of the invention

[0005] One of the purposes of the present invention is to provide a method for detecting farmland ammonia volatilization loss based on the Internet of Things, and to solve the shortcomings of the prior art that the distribution of ammonia volatilization loss at different heights and locations cannot be accurately described and the spatial resolution is low.

[0006] The present invention is implemented by the following technical scheme. A method for detecting farmland ammonia volatilization loss based on the Internet of Things includes: S100, determining the boundary size of the target field, and recording the longitude and latitude and altitude, then dividing the target field into multiple square plots, arranging an ammonia concentration sensor at the center of each plot according to the vertical height, and installing a soil sensor cluster in each plot to measure soil information for evaluating the influence of soil conditions on ammonia volatilization, installing a meteorological station in the target field to obtain environmental parameters affecting ammonia volatilization, and sending the data collected by the ammonia concentration sensor, the soil sensor and the meteorological station to the cloud for centralized management through the Internet of Things platform; S200, simulating and measuring the reaction rate of ammonia at different temperatures and humidities, and constructing a farmland ammonia parameterization model for calculating the reaction rate constant k; S300, processing the data collected by the sensor, obtaining the ammonia concentration sensor cluster and the soil sensor cluster to monitor the ammonia concentration and soil conditions of their respective positions in real time, and obtaining the environmental parameters obtained by the meteorological station in real time, and extracting environmental factors from the sensor data, and synthesizing the sensor data to obtain the ammonia concentration C (x, y, z, t), where x and y are specific plane positions in the target field, z is height, and t is time; S400, extracting ammonia concentration data at different heights and generating concentration profile data to obtain the dynamic change of ammonia concentration at vertical heights, and calculating the instantaneous ammonia volatilization flux formula according to the ammonia concentration C(x, y, z, t) and the farmland ammonia reaction rate constant,

[0007] ,

[0008] Among them, F (x, y, t) is the instantaneous ammonia volatilization flux, which means the volatilization rate of ammonia per unit area at the position (x, y) at time t, and the dimension is g / (m²·s); x, y are the horizontal coordinates in the field plane; z is the vertical coordinate (height), which is integrated from the ground to the height h; D is the diffusion coefficient, with the dimension of m² / s, which is used to describe the diffusion characteristics of ammonia in the air; v w is the vertical wind speed, used to describe the transport of ammonia in the vertical wind direction; k is the reaction rate constant, used to describe the rate at which ammonia is consumed in the air; S500, construct a three-dimensional concentration distribution model for describing the distribution of ammonia concentration at various locations in the field as it changes with height, the three-dimensional concentration distribution model is expressed as,

[0009] , where C0(x, y, z) is the baseline value of the concentration and is the initial concentration; the total ammonia volatilization of the farmland is calculated according to the three-dimensional concentration distribution model.

[0010] Furthermore, the vertical arrangement of ammonia concentration sensors includes placing the highest level sensor 2.5 m above the ground and then arranging the sensors towards the ground at intervals of 0.5 m. The sensors arranged vertically at the same center form a gradient detection ammonia concentration sensor cluster.

[0011] Further, the farmland ammonia parameterization model is obtained through the following steps: S210, selecting a temperature range of 10-40°C and a humidity range of 20%-90%RH; S220, combining different temperature ranges and humidity ranges, testing the combinations of different temperature ranges and humidity ranges, and measuring the ammonia reaction rate under different temperature and humidity conditions; S230, after obtaining data of the reaction rate constant k under multiple groups of temperatures and humidities, considering the influence of temperature and humidity on the reaction rate constant k, determining the humidity influence function f (RH), , where α is the slope obtained by fitting the data using a linear regression method; S240, fitting the humidity influence function f (RH) and the reaction rate constant k to obtain the farmland ammonia reaction rate model, , where k0 is a constant determined by fitting experimental data; Ea is the activation energy; R is the gas constant; T is the temperature; and e is a natural constant.

[0012] Furthermore, environmental factors are obtained through a weather station and a soil sensor cluster installed in the target field. The environmental factors are combined with the data from the ammonia concentration sensor to comprehensively evaluate the dynamic changes of the ammonia concentration C(x, y, z, t) and its influencing factors.

[0013] Further, the instantaneous ammonia volatilization flux formula is obtained according to the following steps: S410, using the mass transfer equation, the change of ammonia concentration in the farmland with time and space, respectively considering the diffusion, convection and reaction of ammonia concentration, wherein the substance diffuses from the high concentration area to the low concentration area to form a concentration gradient, using In the mass transfer equation representing the diffusion of ammonia concentration, the vertical wind speed v w The material transport caused by convection is The convection of ammonia concentration, the chemical reaction or other consumption process of ammonia is represented by the product of ammonia concentration C(x, y, z, t) and the farmland ammonia reaction rate constant k, kC, and the mass transfer equation is obtained.

[0014] , where C(x, y, z, t) is the ammonia concentration, which varies with time t and spatial position (x, y, z); is the Laplace operator; D is the diffusion coefficient; v wis the vertical wind speed, k is the farmland ammonia reaction rate constant; S420, instantaneous volatilization flux F(x, y, t) is used to characterize the volatilization of ammonia in the vertical direction, which is the integral from the ground to a certain height h. The total amount is determined by the mass transfer term and is obtained by accumulating the mass transfer rate in the range of [0, h].

[0015] Furthermore, the total ammonia volatilization is calculated by the following steps:

[0016] S510, through the concentration distribution model

[0017] , taking the derivative of the instantaneous ammonia volatilization flux formula, we get the following derivative:

[0018] The following derivatives are obtained:

[0019] ,

[0020] ,

[0021] S520, Substituting the obtained derivative into the instantaneous flux formula, we can obtain:

[0022] ,

[0023] Simplifying the above formula, we can get the derivatives of each term,

[0024] ,

[0025] S530, further simplify the formula to obtain:

[0026] ,

[0027] S540, calculate the spatial integral over the entire field area according to the simplified formula to obtain the total ammonia volatilization per unit time L(t),

[0028] ,

[0029] S550, calculate the total ammonia volatilization per unit time L(t), and then perform time integration on L(t).

[0030] ,

[0031] Finally, the total ammonia volatilization of farmland ammonia within the total time T is obtained: total .

[0032] On the other hand, the present invention provides a computer system, the device comprising: a processor; a memory storing a computer program, and when the computer program is executed by the processor, the above-mentioned method for detecting farmland ammonia volatilization loss based on the Internet of Things is implemented.

[0033] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0034] 1. The present invention monitors environmental factors such as ammonia concentration, temperature, and humidity in real time, incorporates them into the reaction rate calculation model, and dynamically adjusts the reaction rate constant, thereby solving the defects of the prior art that the influence of environmental factors is ignored and the model results are not accurate enough. By combining the data of the meteorological station and the information monitored by the soil sensor, the influence of environmental factors and soil conditions on ammonia volatilization can be comprehensively evaluated, thereby providing an accurate ammonia loss assessment.

[0035] 2. In the ammonia volatilization calculation formula, in addition to considering the diffusion and convection processes, the present invention also introduces the influence of the chemical reaction between ammonia and the environment, thereby overcoming the problem that the prior art ignores the reaction process and the detection results are not accurate enough. By establishing a three-dimensional model and calculating the ammonia volatilization distribution based on the x, y, and z three-dimensional space, the spatial resolution of the detection is improved, and the defect that the prior art cannot accurately describe the distribution of ammonia volatilization losses at different heights and positions is solved.

[0036] 3. By deploying ammonia concentration sensors at different positions and heights, the present invention can obtain precise ammonia concentration data, capture the changes in ammonia concentration on the vertical profile, and ensure comprehensive monitoring of ammonia volatilization. At the same time, the low-power wide area network in the Internet of Things technology is used for data transmission, which can achieve efficient data collection and upload, and ensure the real-time and long-term stable operation of the monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0038] Figure 1 A method flow chart provided for exemplary embodiment 1 of the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0040] Embodiment 1,

[0041] Traditional methods for detecting farmland ammonia volatilization do not comprehensively consider processes such as diffusion, convection and chemical reactions, as well as the impact of dynamically adjusting environmental factors. In order to address the shortcomings of the above-mentioned prior art, a method for detecting farmland ammonia volatilization losses based on the Internet of Things is disclosed in this embodiment. Figure 1 The flowchart of this embodiment is disclosed. It can be seen from the figure that this method includes the following steps:

[0042] Step 1: In this embodiment, a 10-acre farmland is selected as the target field. First, the boundary size of the target field is determined, and the longitude and latitude and altitude are recorded. Then the target field is divided into multiple plots at a distance of 5m×5m (the distance can also be set at 1m×1m, or other lengths), and 5 ammonia concentration sensors are arranged in the center of each plot, where the sensors are 2.5m from the ground according to the highest layer of sensors in the height direction, and then arranged to the ground at intervals of 0.5m, forming a cluster of gradient detection ammonia concentration sensors, which detects the ammonia concentration in the air and the ammonia concentration at different heights in real time. At the same time, a soil sensor cluster is installed in each plot to measure the temperature, humidity, pH value and ammonia source of the soil, and to evaluate the impact of soil conditions on ammonia volatilization. A meteorological station is installed in the target field. The meteorological station is equipped with meteorological sensors such as temperature, humidity, wind speed, and wind direction to obtain environmental parameters that affect ammonia volatilization.

[0043] The data collected by ammonia concentration sensors, soil sensors and weather stations are sent to the cloud for centralized management through the IoT platform. The data collected by the sensors can be uploaded every hour or every half hour to ensure the real-time and stability of the monitoring system. Specifically, the IoT platform can be a low-power wide area network such as LoRa and NB-IoT.

[0044] Step 2: Simulate and measure the reaction rate of ammonia at different temperatures and humidity in the laboratory and establish a parameterized model of ammonia in farmland.

[0045] Specifically, first determine the temperature range to be 10~40℃ and the humidity range to be 20%~90%RH.

[0046] Then experiment with different temperature and humidity conditions. For example, you can choose the following combinations:

[0047] Temperature: 10℃, 20℃, 30℃, 40℃; humidity: 20%RH, 50%RH, 70%RH, 90%RH. Under each set of temperature and humidity conditions, measure the change of ammonia concentration over time and record the ammonia concentration C(t).

[0048] Calculate the reaction rate constant k for each set of conditions. Use linear regression or nonlinear regression to fit the change in concentration over time and calculate the reaction rate constant.

[0049] Then, after obtaining experimental data of the reaction rate constant k under multiple sets of temperature and humidity, the influence of temperature and humidity on the reaction rate constant k is considered to determine the humidity influence function f (RH). Since the influence of humidity on the rate constant is in linear form, , where α is the slope obtained by fitting the data using linear regression.

[0050] The humidity influence function f (RH) and the reaction rate constant k were fitted to the Arrhenius equation, and the farmland ammonia reaction rate model was obtained.

[0051] ,

[0052] Wherein, k0 is a constant determined by fitting experimental data; Ea is the activation energy; R is the gas constant; T is the temperature; and e is a natural constant.

[0053] Step 3: Process the data collected by the sensors to obtain the ammonia concentration sensor cluster and the soil sensor cluster to monitor the ammonia concentration and soil conditions at their respective locations in real time. At the same time, obtain the environmental parameters of the weather station in real time.

[0054] These sensor data are combined to obtain the ammonia concentration C(x, y, z, t) at different locations (x, y, z) and different times (t), where x and y are specific plane locations in the target field, z represents height, and t represents time. Environmental factors can also be extracted from the sensor data.

[0055] Specifically, environmental factors mainly refer to those environmental parameters that can affect ammonia volatilization and ammonia concentration. These environmental factors include meteorological factors and soil factors.

[0056] Among them, meteorological factors include temperature. Air temperature will affect the volatilization rate of ammonia. The higher the temperature, the greater the ammonia volatilization rate may be.

[0057] Humidity. Air humidity will also affect the volatilization process of ammonia. The volatilization rate may decrease when the humidity is high.

[0058] Wind speed. Wind speed affects the diffusion and transport of ammonia. Higher wind speeds can accelerate the diffusion of ammonia.

[0059] Wind direction determines the path of ammonia in the air.

[0060] Soil factors include soil temperature, which affects the generation and volatilization of ammonia in the soil.

[0061] Soil moisture. Soil moisture will affect the release and diffusion of ammonia. Being too dry or too wet may affect the volatilization of ammonia.

[0062] Soil pH. The acidity and alkalinity of the soil will affect the formation and stability of ammonia. Changes in pH may change the volatilization rate of ammonia.

[0063] The sources of ammonia in the soil, the concentration of ammonia in the soil and the amount of ammonia available for volatilization.

[0064] These environmental factors are monitored and recorded in real time by a weather station and soil sensor cluster installed in the target field. These data, combined with the data from the ammonia concentration sensor, can comprehensively evaluate the dynamic changes of ammonia concentration C(x, y, z, t) and its influencing factors.

[0065] Step 4: Extract ammonia concentration data at different heights from the sensor data, and collect concentration data at different heights z1~z5 according to the ammonia concentration sensor to form concentration profile data.

[0066] According to the concentration profile data, the dynamic change data of ammonia concentration at vertical height are obtained. According to the ammonia concentration C(x, y, z, t) and the farmland ammonia reaction rate constant, the dynamic change mass transfer equation of ammonia concentration is obtained:

[0067] , where C(x, y, z, t) is the ammonia concentration, which varies with time t and spatial position (x, y, z); is the Laplace operator; D is the diffusion coefficient; v w is the vertical wind speed, and k is the ammonia reaction rate constant of the farmland.

[0068] According to the mass transfer equation of the dynamic change of ammonia concentration, we can calculate the instantaneous ammonia volatilization flux, which specifically includes the following contents:

[0069] The mass transfer equation describes the variation of ammonia concentration in farmland with time and space, taking into account three key factors: diffusion, convection and reaction. Used to represent diffusion, the spread of a substance from an area of ​​high concentration to an area of ​​low concentration according to a concentration gradient. , which is represented by the vertical wind speed v w The transport of substances caused by the chemical reaction or other consumption process of ammonia is represented by kC.

[0070] In order to describe the volatilization of ammonia in the vertical direction, we define the instantaneous volatilization flux F(x, y, t) as the integral form from the ground to a certain height h, and the total amount is determined by the mass transfer term. The actual volatilization flux is calculated by accumulating the mass transfer rate in the range [0, h]. By integration, the flux density caused by each mass transfer process is accumulated to obtain the overall volatilization flux. The instantaneous ammonia volatilization flux formula is derived by combining the concentration profile data obtained by the sensor at different heights with the mass transfer equation:

[0071] ,

[0072] Where F(x,y,t) is the instantaneous ammonia volatilization flux, which means the volatilization rate of ammonia per unit area at position (x,y) at time t, and the dimension is mass / (area·time) g / (m²·s). x, y are the horizontal coordinates in the field plane; z is the vertical coordinate (height), which is integrated from the ground to height h. D is the diffusion coefficient, with the unit of area / time (m² / s), which is used to describe the diffusion characteristics of ammonia in the air; v w is the vertical wind speed, which is used to describe the transport of ammonia in the vertical wind direction; k is the reaction rate constant, which is used to describe the rate at which ammonia is consumed in the air.

[0073] Step 5: Since the concentration of ammonia in farmland generally decays exponentially with height z, the decay rate is determined by the reaction rate constant k and the vertical wind speed v w Therefore, a three-dimensional model can be established to describe the distribution of ammonia concentration at various locations in the field as it changes with height. The three-dimensional concentration distribution model is expressed as:

[0074] , where C0(x, y, z) is the baseline concentration, usually the initial concentration measured on the ground or at a specific height.

[0075] After establishing the three-dimensional concentration distribution model, the total ammonia volatilization is further calculated, that is, the cumulative loss is calculated. The total ammonia volatilization is finally obtained by calculating the ammonia volatilization from the surface to the height h per unit time within a specific time range.

[0076] In step 4, we obtained the formula for the instantaneous ammonia volatilization flux, which represents the instantaneous volatilization flux within the vertical height [0, h]. For a certain time t, the ammonia volatilization amount F(x, y, t) from the surface to the height h per unit time is calculated by the following steps:

[0077] First, the concentration distribution model , to calculate the derivative, we can get,

[0078] ,

[0079] ,

[0080] Substituting into the instantaneous flux formula, we get:

[0081] ,

[0082] After simplification, the derivatives of each term are:

[0083] ,

[0084] Further simplifying the formula, we get

[0085] ,

[0086] According to the simplified formula, the spatial integral is further calculated over the entire field area to obtain the total ammonia volatilization per unit time L(t).

[0087] ,Right now:

[0088] ,

[0089] The total ammonia volatilization per unit time L(t) is calculated according to the above formula, and then L(t) is integrated over time.

[0090] ,

[0091] The cumulative volatilization loss of ammonia in the farmland within the total time T is obtained as L total (Total ammonia volatilization).

[0092] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting farmland ammonia volatilization loss based on the Internet of Things, characterized in that: The steps include: S100, determine the boundary of the target field, and record the longitude, latitude and altitude, then divide the target field into multiple square plots, arrange ammonia concentration sensors at the center of each square plot according to the vertical height, and install a soil sensor cluster in each square plot to measure soil information for evaluating the impact of soil conditions on ammonia volatilization, and install a meteorological station in the target field to obtain environmental parameters that affect ammonia volatilization. The data collected from ammonia concentration sensors, soil sensors and weather stations are sent to the cloud for centralized management through the IoT platform; S200, simulate and measure the reaction rate of ammonia at different temperatures and humidity, and build a parameterized model of farmland ammonia to calculate the reaction rate constant k; S300, processing the data collected by the sensor, obtaining the ammonia concentration sensor cluster and the soil sensor cluster, monitoring the ammonia concentration and soil conditions at their respective locations in real time, obtaining the environmental parameters obtained by the weather station in real time, and extracting the environmental factors from the sensor data, integrating the sensor data, and obtaining the ammonia concentration C(x, y, z, t) at different locations and different times, where x and y are specific plane positions in the target field, z is the height, and t is the time; S400, extracting ammonia concentration data at different heights and generating concentration profile data, obtaining the dynamic change of ammonia concentration at vertical heights, and calculating the instantaneous ammonia volatilization flux formula based on the ammonia concentration C (x, y, z, t) and the farmland ammonia reaction rate constant. ， Among them, F (x, y, t) is the instantaneous ammonia volatilization flux, which means the volatilization rate of ammonia per unit area at the position (x, y) at time t, and the dimension is g / (m²·s); x, y are the horizontal coordinates in the field plane; z is the vertical coordinate, which is integrated from the ground to the height h; D is the diffusion coefficient, with the dimension of m² / s, which is used to describe the diffusion characteristics of ammonia in the air; v w is the vertical wind speed, which is used to describe the transport of ammonia in the vertical wind direction; k is the reaction rate constant, which is used to describe the rate at which ammonia is consumed in the air; S500, constructing a three-dimensional concentration distribution model for describing the distribution of ammonia concentration at various locations in the field as it changes with height, wherein the three-dimensional concentration distribution model is expressed as: ， Among them, C0(x, y, z) is the baseline value of concentration, indicating the initial concentration; The total ammonia volatilization of the farmland is calculated based on the three-dimensional concentration distribution model and the instantaneous ammonia volatilization flux formula; The expression of the farmland ammonia parameterization model is: ， Wherein, k0 is a constant determined by fitting experimental data; Ea is activation energy; R is gas constant; T is temperature; e is natural constant; The total ammonia volatilization amount is calculated by the following formula: ， Among them, L total is the total ammonia volatilization, L(t) is the total ammonia volatilization per unit time, and T is the total time range; The total ammonia volatilization per unit time is calculated by the following formula: 。 2. The method for detecting farmland ammonia volatilization loss based on the Internet of Things according to claim 1, characterized in that: The vertical arrangement of the ammonia concentration sensors includes placing the highest layer of sensors 2.5 m above the ground and then arranging them towards the ground at intervals of 0.5 m. The sensors arranged vertically at the same center form a gradient detection ammonia concentration sensor cluster.

3. The method for detecting farmland ammonia volatilization loss based on the Internet of Things according to claim 1, characterized in that: The farmland ammonia parameterization model is obtained by the following steps: S210, select the temperature range of 10~40℃ and the humidity range of 20%~90%RH; S220, combining different temperature ranges and humidity ranges, testing the combination of different temperature ranges and humidity ranges, and measuring the ammonia reaction rate under different temperature and humidity conditions; S230, after obtaining multiple sets of data on the reaction rate constant k under temperature and humidity, considering the influence of temperature and humidity on the reaction rate constant k, determine the humidity influence function f (RH), ， Among them, α is the slope obtained by fitting the data using the linear regression method; S240. Fit the humidity influence function f (RH) and the reaction rate constant k to obtain the farmland ammonia reaction rate model.

4. The method for detecting farmland ammonia volatilization loss based on the Internet of Things according to claim 1, characterized in that: The environmental factors are obtained through a meteorological station and a soil sensor cluster installed in the target field. The environmental factors are combined with the data of the ammonia concentration sensor to comprehensively evaluate the dynamic changes of the ammonia concentration C(x, y, z, t) and its influencing factors.

5. The method for detecting farmland ammonia volatilization loss based on the Internet of Things according to claim 1, characterized in that: The instantaneous ammonia volatilization flux formula is obtained according to the following steps: S410, use the mass transfer equation to calculate the variation of ammonia concentration in farmland with time and space, considering the diffusion, convection and reaction of ammonia concentration respectively. Among them, the substance diffuses from the high concentration area to the low concentration area to form a concentration gradient. The mass transfer equation represents the diffusion of ammonia concentration, Vertical wind speed v w The material transport caused by convection is represents the convection of ammonia concentration, The chemical reaction or other consumption process of ammonia is represented by the product of ammonia concentration C(x, y, z, t) and the farmland ammonia reaction rate constant k, kC, and the mass transfer equation is obtained. ， Where C(x, y, z, t) is the ammonia concentration, which varies with time t and spatial position (x, y, z); is the Laplace operator; D is the diffusion coefficient; v w is the vertical wind speed, k is the farmland ammonia reaction rate constant; S420, instantaneous volatilization flux F(x, y, t) is used to characterize the volatilization of ammonia in the vertical direction. It is the integral from the ground to a certain height h. The total amount is determined by the mass transfer term and is obtained by accumulating the mass transfer rate in the range [0, h].

6. The method for detecting farmland ammonia volatilization loss based on the Internet of Things according to claim 1, characterized in that: The total ammonia volatilization amount is calculated by the following steps: S510, through the concentration distribution model , taking the derivative of the instantaneous ammonia volatilization flux formula, we get the following derivative: ， ， S520, Substituting the obtained derivative into the instantaneous flux formula, we can obtain: ； Simplifying the above formula, we can get the derivatives of each term, ， S530, further simplify the formula to obtain: ， S540, calculating the spatial integral over the entire field area according to the simplified formula to obtain the total ammonia volatilization per unit time L(t); S550, calculate the total ammonia volatilization amount per unit time L(t), then integrate L(t) over time to obtain the total ammonia volatilization amount.

7. A computer device, characterized in that: The device comprises: processor; A memory stores a computer program, and when the computer program is executed by a processor, the method for detecting farmland ammonia volatilization loss based on the Internet of Things as described in any one of claims 1 to 6 is implemented.

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