Agricultural environment intelligent monitoring device, system and method

Abstract

The invention belongs to the technical field of environment intelligent monitoring, and particularly relates to an agricultural environment intelligent monitoring device, system and method, and the system comprises a monitoring influence level determination module which is used for determining an agricultural environment monitoring influence level; the first initial level determination module is used for judging whether the state of the agricultural meteorological environment is qualified or not and determining a first initial level of agricultural environment monitoring; the second initial grade determination module is used for judging whether the agricultural soil environment state is qualified or not and determining a second initial grade of agricultural environment monitoring; the third initial grade determination module is used for judging whether the agricultural insect pest state is qualified or not and determining a third initial grade of agricultural environment monitoring; and the agricultural environment monitoring level determination module is used for obtaining the agricultural environment monitoring level and judging whether a danger early warning prompt needs to be sent to the agricultural environment. According to the invention, a more accurate intelligent monitoring result of an agricultural environment can be obtained, crop growth conditions are optimized, and the yield and quality of crops are enhanced.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent environmental monitoring, and in particular relates to an intelligent agricultural environmental monitoring device, system and method. Background Art

[0002] Agricultural environmental testing is essential to ensure food security, improve crop yields and quality, and promote sustainable agricultural development. Agricultural environmental testing can monitor and evaluate various environmental factors that affect crop growth in real time, such as soil conditions, climate parameters, and pests and diseases, so that timely measures can be taken to optimize growth conditions and prevent and reduce damage caused by environmental changes.

[0003] There are many monitoring technologies applied to agricultural environments. However, these technologies still have some shortcomings. For example, they rely on manual observation and recording, which is not only inefficient but also susceptible to human errors, resulting in inaccurate data. In addition, traditional monitoring systems often lack real-time and dynamic analysis capabilities, making it difficult to cope with rapidly changing environmental conditions, and data integration from different sources is difficult, making it impossible to form comprehensive analysis results. This limits the in-depth understanding and timely response to the agricultural environment, affecting the efficiency of agricultural production and the healthy growth of crops. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an agricultural environment intelligent monitoring device, system and method, which help to obtain more accurate intelligent monitoring results of the agricultural environment, optimize crop growth conditions, and enhance crop yield and quality.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: An agricultural environment intelligent monitoring system comprises a monitoring impact level determination module, a first initial level determination module, a second initial level determination module, a third initial level determination module and an agricultural environment monitoring level determination module, wherein: Monitoring impact level determination module, used to analyze agricultural agronomic conditions and determine the agricultural environmental monitoring impact level; The first initial level determination module is used to analyze the agricultural meteorological environment, determine whether the agricultural meteorological environment state is qualified and determine the first initial level of agricultural environment monitoring; The second initial level determination module is used to analyze the agricultural soil environment, determine whether the agricultural soil environment state is qualified and determine the second initial level of agricultural environment monitoring; The third initial level determination module is used to analyze the agricultural pest status, determine whether the agricultural pest status is qualified and determine the third initial level of agricultural environment monitoring; The agricultural environment monitoring level determination module is used to accumulate the first initial level of agricultural environment monitoring, the second initial level of agricultural environment monitoring, the third initial level of agricultural environment monitoring and the agricultural environment monitoring impact level to obtain the agricultural environment monitoring level, and determine whether it is necessary to issue a danger warning prompt for the agricultural environment. If a danger warning prompt needs to be issued, then after the danger warning prompt is issued, the agricultural environment adjustment plan is obtained.

[0006] Preferably, the process of analyzing agricultural agronomic conditions and determining the agricultural environmental monitoring impact level is: Obtain agricultural agronomic conditions data, including monitoring the frequency of fertilization in agricultural areas, monitoring the frequency of irrigation in agricultural areas, and monitoring the average single irrigation volume in agricultural areas; Based on the acquired agricultural agronomic conditions data, the agricultural agronomic conditions characteristic factors are obtained through comprehensive analysis. The agricultural agronomic conditions characteristic factors are used as the analysis basis for determining the impact level of agricultural environmental monitoring. The agricultural agronomic condition characteristic factor is stored as a designated label, and the designated label is compared with each set label stored in the database to obtain the set label corresponding to the designated label, and the agricultural environment monitoring impact level corresponding to the set label stored in the database is obtained.

[0007] Preferably, the calculation method of the agricultural agronomic condition characteristic factor is: ; In the formula, is the characteristic factor of agricultural agronomic conditions, sfp is the fertilization frequency of the monitored agricultural area, ggp is the irrigation frequency of the monitored agricultural area, ggl is the average single irrigation amount of the monitored agricultural area, , , are the compensation factors of the set sfp, ggp, and ggl respectively, and e is a natural constant.

[0008] Preferably, the process of judging whether the agricultural meteorological environment state is qualified and determining the first initial level of agricultural environment monitoring is: Obtain agricultural meteorological environment data, including monitoring the light intensity deviation rate, temperature deviation rate, and precipitation deviation rate in agricultural areas; Based on the acquired agricultural meteorological environmental data, a comprehensive analysis is performed to obtain characteristic signals of the agricultural meteorological environmental status, which are used as the analysis basis for judging whether the agricultural meteorological environmental status is qualified and determining the first initial level of agricultural environmental monitoring; comparing the agricultural meteorological environment state characteristic signal with the agricultural meteorological environment state characteristic threshold value stored in the database; If the agricultural meteorological environment state characteristic signal is not lower than the agricultural meteorological environment state characteristic threshold, the agricultural meteorological environment state corresponding to the agricultural meteorological environment state characteristic signal is qualified, and the first initial level of agricultural environment monitoring is zero; If the agricultural meteorological environment state characteristic signal is lower than the agricultural meteorological environment state characteristic threshold, the agricultural meteorological environment state corresponding to the agricultural meteorological environment state characteristic signal is unqualified, and the first initial level of agricultural environment monitoring is level one.

[0009] Preferably, the process of judging whether the agricultural soil environmental status is qualified and determining the second initial level of agricultural environmental monitoring is: Obtain agricultural soil environmental data, including monitoring the soil pH deviation rate in agricultural areas, monitoring the soil moisture deviation rate in agricultural areas, and monitoring the soil heavy metal content in agricultural areas; Based on the acquired agricultural soil environmental data, a comprehensive analysis is conducted to obtain characteristic signals of the agricultural soil environmental status, which are used as the analysis basis for judging whether the agricultural soil environmental status is qualified and determining the second initial level of agricultural environmental monitoring; comparing the agricultural soil environmental state characteristic signal with the agricultural soil environmental state characteristic threshold value stored in the database; If the agricultural soil environment state characteristic signal is not lower than the agricultural soil environment state characteristic threshold, the agricultural soil environment state corresponding to the agricultural soil environment state characteristic signal is qualified, and the second initial level of agricultural environment monitoring is zero; If the agricultural soil environmental state characteristic signal is lower than the agricultural soil environmental state characteristic threshold, the agricultural soil environmental state corresponding to the agricultural soil environmental state characteristic signal is unqualified, and the second initial level of agricultural environmental monitoring is level one.

[0010] Preferably, the process of judging whether the agricultural pest status is qualified and determining the third initial level of agricultural environmental monitoring is: Obtain agricultural pest status data, including monitoring the proportion of crop pest areas in agricultural areas and monitoring insect population density in agricultural areas; Based on the acquired agricultural pest status data, a comprehensive analysis is performed to obtain characteristic signals of the agricultural pest status, which are used as the analysis basis for judging whether the agricultural pest status is qualified and determining the third initial level of agricultural environmental monitoring; comparing the agricultural pest state characteristic signal with the agricultural pest state characteristic threshold stored in the database; If the agricultural pest state characteristic signal is not lower than the agricultural pest state characteristic threshold, the agricultural pest state corresponding to the agricultural pest state characteristic signal is qualified, and the third initial level of agricultural environment monitoring is zero; If the agricultural pest state characteristic signal is lower than the agricultural pest state characteristic threshold, the agricultural pest state corresponding to the agricultural pest state characteristic signal is unqualified, and the third initial level of agricultural environment monitoring is level one.

[0011] Preferably, the calculation method of the characteristic signal of the agricultural pest state is: ; In the formula, is the characteristic signal of agricultural pest status, hs is the proportion of crop pest area in the monitored agricultural area, cm is the insect population density in the monitored agricultural area, , is the compensation factor of the set hs and cm, and e is a natural constant.

[0012] Preferably, the agricultural environment monitoring level is determined, and it is judged whether it is necessary to issue a danger warning prompt for the agricultural environment. If a danger warning prompt needs to be issued, the process of obtaining the agricultural environment adjustment plan after the danger warning prompt is issued is: The agricultural environment monitoring level is obtained by accumulating the first initial level of agricultural environment monitoring, the second initial level of agricultural environment monitoring, the third initial level of agricultural environment monitoring and the impact level of agricultural environment monitoring; comparing the agricultural environment monitoring level with the agricultural environment monitoring threshold level stored in the database; If the agricultural environment monitoring level is not lower than the agricultural environment monitoring threshold level, the agricultural environment corresponding to the agricultural environment monitoring level is safe and there is no need to issue a danger warning prompt; If the agricultural environment monitoring level is lower than the agricultural environment monitoring threshold level, the agricultural environment corresponding to the agricultural environment monitoring level is unsafe and a danger warning prompt needs to be issued: After issuing a danger warning prompt, obtaining the light intensity of the monitored agricultural area, and comparing the light intensity of the monitored agricultural area with the light intensity threshold stored in the database; If the light intensity in the monitored agricultural area is not lower than the light intensity threshold, there is no need to turn on the supplementary light; If the light intensity of the monitored agricultural area is lower than the light intensity threshold, a supplementary lighting scheme needs to be determined, and the light intensity of the monitored agricultural area is compared with the supplementary lighting schemes corresponding to the light intensity of each monitored agricultural area stored in the database to obtain the supplementary lighting scheme corresponding to the light intensity of the monitored agricultural area, and the light intensity of the monitored agricultural area is adjusted based on the determined supplementary lighting scheme; At the same time, the agricultural meteorological environment status characteristic signal, the agricultural soil environment status characteristic signal and the agricultural pest status characteristic signal are stored as designated tags, and the designated tags are compared with the set tags stored in the database to obtain the set tag corresponding to the designated tag, and obtain the second agricultural environment adjustment plan corresponding to the set tag stored in the database.

[0013] An agricultural environment intelligent monitoring method, based on the above-mentioned agricultural environment intelligent monitoring system, comprises the following steps: Determine the agricultural environment monitoring level, which is obtained by accumulating the first initial agricultural environment monitoring level, the second initial agricultural environment monitoring level, the third initial agricultural environment monitoring level and the agricultural environment monitoring impact level, wherein the first initial agricultural environment monitoring level is determined based on the analysis of the agricultural meteorological environment, the second initial agricultural environment monitoring level is determined based on the analysis of the agricultural soil environment, the third initial agricultural environment monitoring level is determined based on the analysis of the agricultural pest status, and the agricultural environment monitoring impact level is determined based on the analysis of agricultural agronomic conditions; Determine whether an alarm is needed based on the agricultural environment monitoring level: If no alarm is needed, continue to obtain the agricultural environment monitoring level and determine again whether an alarm is needed; If an alarm is required, the current agricultural environment data is obtained, which includes the environment brightness, environment humidity and environment alcohol content; Acquire the agricultural environment parameter data stored in the database, the agricultural environment parameter data including the environment parameter brightness, environment parameter humidity and environment parameter alcohol content; If the absolute value of the difference between the ambient brightness and the ambient reference brightness is greater than the brightness deviation threshold stored in the database, the ambient brightness is adjusted based on the LED module; If the absolute value of the ambient humidity and the ambient reference humidity is greater than the humidity deviation threshold stored in the database, the ambient humidity is adjusted based on the humidity adjustment device; If the difference between the environmental alcohol content and the environmental reference alcohol content is greater than the alcohol concentration deviation threshold stored in the database, the environmental alcohol is purified based on the alcohol treatment device and an abnormal alcohol concentration warning is sent.

[0014] An agricultural environment intelligent monitoring device, used to implement the above-mentioned agricultural environment intelligent monitoring system, includes a data acquisition module, an LED module, a humidity adjustment device, an alcohol treatment device, a control processing module, an agricultural environment monitoring level acquisition module and an early warning processing module: The data acquisition module is used to obtain agricultural agronomic conditions data, agricultural meteorological environment data, agricultural soil environment data and agricultural pest status data; The agricultural environmental monitoring level is used to determine the agricultural environmental monitoring level based on agricultural agronomic conditions data, agricultural meteorological environment data, agricultural soil environment data and agricultural pest status data; The early warning processing module is used to determine whether an early warning is needed based on the agricultural environment monitoring level, and send the early warning information to the control processing module when an early warning is needed; The control processing module is used to control and process the LED module, the humidity adjustment device, and the alcohol treatment device when receiving the warning information; The LED module is used to adjust the ambient brightness under the control of the control processing module; The humidity adjustment device is used to adjust the ambient humidity under the control of the control processing module; The alcohol treatment device is used to purify environmental alcohol under the control of the control processing module.

[0015] The present invention has the following beneficial effects: The present invention can comprehensively evaluate the health status of the agricultural environment by independently analyzing the three aspects of meteorology, soil and pests, which helps to identify potential problems in advance. Clear monitoring levels and impact assessments provide a scientific basis for agricultural management, and accurate decisions can be made based on specific environmental conditions. Effective monitoring and management of various aspects of the agricultural environment can help optimize crop growth conditions and increase crop yield and quality. Analyzing agricultural agronomic conditions can help measure the impact of agricultural agronomic conditions on the agricultural environment and obtain more accurate intelligent monitoring results for the agricultural environment. Through data collection, analysis and real-time feedback, agricultural management can be promoted in a data-driven direction and the scientific nature of agricultural management can be improved.

[0016] The present invention determines the impact level of agricultural environmental monitoring by analyzing agricultural agronomic conditions. By analyzing agronomic conditions, the impact of agricultural agronomic conditions on agricultural environmental monitoring can be measured, providing a basis for targeted management, and helping to make more accurate judgments on agricultural environmental monitoring. By monitoring agronomic conditions and analyzing the impact level, potential risks such as drought, insect pests and diseases can be identified more accurately in advance, so as to formulate countermeasures. If the monitoring results show that certain indicators exceed the safe range, an early warning can be issued in time to reduce losses. Agricultural management can rely more on data analysis results, make more scientific and rational management decisions, and reduce the blindness of previous reliance on experience judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of system module connection of the present invention; Figure 2 It is a schematic diagram of the method steps of the present invention; Figure 3 A flowchart of the steps for judging whether the agricultural meteorological environment status is qualified and determining the first initial level of agricultural environmental monitoring; Figure 4 It is a schematic diagram of the connection of the device modules of the present invention. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings.

[0019] Example 1: Figure 1 As shown, an agricultural environment intelligent monitoring system includes: a monitoring impact level determination module, which is used to analyze agricultural agronomic conditions and determine the agricultural environment monitoring impact level.

[0020] The specific analysis process is as follows: obtaining agricultural agronomic conditions data, including monitoring the frequency of fertilization in agricultural areas, monitoring the frequency of irrigation in agricultural areas, and monitoring the average single irrigation volume in agricultural areas; based on the obtained agricultural agronomic conditions data, comprehensive analysis is performed to obtain agricultural agronomic conditions characteristic factors, and the agricultural agronomic conditions characteristic factors are used as the analysis basis for determining the agricultural environmental monitoring impact level; the agricultural agronomic conditions characteristic factors are stored as designated tags, and the designated tags are compared with the various settings stored in the database to obtain the setting tags corresponding to the designated tags, and the agricultural environmental monitoring impact level corresponding to the setting tags stored in the database is obtained.

[0021] Fertilization frequency is usually expressed as the number of times fertilizer is applied per week, month, or per growing season. Irrigation frequency can be calculated on a weekly, monthly, or per growing cycle basis. The average single irrigation volume is usually expressed in millimeters (mm) or cubic meters.

[0022] Fertilization frequency and irrigation method directly affect the nutrient supply and water conditions of the soil, which in turn affects the growth, health and final yield of crops. Reasonable fertilization and irrigation can increase the organic matter content in the soil and improve the soil's water holding capacity and buffering capacity. Different fertilization and irrigation management will also change the habitat of pests and the survival of their natural enemies, affecting the ecological balance. By monitoring agronomic condition data such as fertilization frequency, irrigation frequency and single irrigation volume, the characteristic factors of crop growth can be accurately extracted to enhance the understanding of the crop growth environment. Dynamic characteristic factor analysis can continuously optimize management measures to adapt to changing environmental conditions and ensure that crops grow in the best state. By comparing the characteristic factors of agricultural agronomic conditions with the set labels stored in the database, the current agricultural environmental monitoring impact level can be quickly and accurately determined. Automatic comparison and identification can greatly improve monitoring efficiency, reduce manual intervention, and reduce the possibility of human error. Through the association between characteristic factors and environmental monitoring impact levels, it is possible to clearly understand which agronomic conditions have a significant impact on environmental monitoring. Through impact level analysis, potential environmental risk factors in crop growth can be effectively identified, and timely measures can be taken to reduce losses.

[0023] The calculation method of the characteristic factors of agricultural agronomic conditions is: ; In the formula, is the characteristic factor of agricultural agronomic conditions, sfp is the fertilization frequency of the monitored agricultural area, ggp is the irrigation frequency of the monitored agricultural area, ggl is the average single irrigation amount of the monitored agricultural area, , , are the compensation factors of the set sfp, ggp, and ggl respectively, and e is a natural constant.

[0024] In this embodiment, each formula is normalized as needed during calculation, and each compensation factor is obtained from a mapping set of compensation factors established based on historical data.

[0025] By accurately monitoring fertilization and irrigation, we can optimize the use of resources and improve crop yield and quality. Accurate monitoring and management can help reduce unnecessary resource waste and promote the development of sustainable agriculture. Reasonable fertilization and irrigation management can improve the nutrient structure and water retention capacity of the soil, promote the accumulation of organic matter, and improve the overall health of the soil. By monitoring the frequency of fertilization, we can reduce water pollution caused by improper fertilization and reduce the environmental risks caused by fertilizer loss. Monitoring the frequency of fertilization can also help adjust climate adaptability.

[0026] The first initial level determination module is used to analyze the agricultural meteorological environment, determine whether the agricultural meteorological environment status is qualified and determine the first initial level of agricultural environment monitoring.

[0027] like Figure 3 As shown, the specific analysis process is: obtaining agricultural meteorological environmental data, including monitoring the light intensity deviation rate of agricultural areas, monitoring the temperature deviation rate of agricultural areas, and monitoring the precipitation deviation rate of agricultural areas; based on the obtained agricultural meteorological environmental data, a comprehensive analysis is performed to obtain the characteristic signal of the agricultural meteorological environmental state, and the characteristic signal of the agricultural meteorological environmental state is used as the analysis basis for judging whether the agricultural meteorological environmental state is qualified and determining the first initial level of agricultural environmental monitoring; The agricultural meteorological environment state characteristic signal is compared with the agricultural meteorological environment state characteristic threshold stored in the database; if the agricultural meteorological environment state characteristic signal is not lower than the agricultural meteorological environment state characteristic threshold, the agricultural meteorological environment state corresponding to the agricultural meteorological environment state characteristic signal is qualified, and the first initial level of agricultural environment monitoring is zero; if the agricultural meteorological environment state characteristic signal is lower than the agricultural meteorological environment state characteristic threshold, the agricultural meteorological environment state corresponding to the agricultural meteorological environment state characteristic signal is unqualified, and the first initial level of agricultural environment monitoring is one.

[0028] The light intensity deviation rate refers to the difference between the actual measured light intensity and a certain standard or ideal light intensity. Light intensity directly affects the photosynthesis, nitrogen utilization and growth and development of crops. The calculation of the deviation rate helps to understand whether the light conditions meet the growth requirements of crops. The temperature deviation rate refers to the difference between the actual measured temperature and a certain standard or ideal temperature. Temperature is a key factor in crop growth and development. The deviation rate can help farmers identify whether they need to adjust breeding time, pollination period and growth cycle, etc. The precipitation deviation rate refers to the difference between actual precipitation and a certain standard or expected precipitation. Understanding the difference between the actual and expected precipitation can help farmers optimize irrigation plans to ensure that crops get enough water and avoid drought or waterlogging. The deviation rate refers to the ratio of the absolute value of the difference between the actual value and the reference value to the reference value.

[0029] By monitoring the light intensity deviation rate, temperature deviation rate, and precipitation deviation rate, the state of the agricultural environment can be evaluated in real time, which helps to respond to environmental changes in a timely manner. Accurately evaluating environmental conditions can help farmers avoid waste of inputs caused by environmental changes, thereby reducing the risks of agricultural production. Timely identification of unqualified agricultural meteorological environmental conditions can take measures in advance to reduce losses, especially before extreme weather occurs. A suitable meteorological environment is conducive to maintaining soil moisture and nutrients, and analyzing data can help avoid soil degradation caused by an unsuitable environment.

[0030] The calculation method of the characteristic signal of agricultural meteorological environment state is: ; In the formula, is the characteristic signal of agricultural meteorological environment status, gzp is the deviation rate of light intensity in monitored agricultural area, wdp is the deviation rate of temperature in monitored agricultural area, jsl is the deviation rate of precipitation in monitored agricultural area, , , They are the compensation factors of gzp, wdp and jsl respectively.

[0031] By monitoring these deviation rates, abnormal weather conditions, such as excessively high or low light, temperature, or precipitation, can be quickly identified to reduce potential losses. Monitoring and analyzing meteorological data can better adapt to climate change, thereby improving the risk resistance of agricultural production. Monitoring the deviation rate of precipitation can help measure irrigation plans, reduce water waste, and ensure that crops get enough water during the dry season. The occurrence of certain pests and diseases is closely related to temperature and humidity. Monitoring the characteristic signals of environmental status can provide early warning information for pest and disease control.

[0032] The second initial level determination module is used to analyze the agricultural soil environment, determine whether the agricultural soil environment status is qualified and determine the second initial level of agricultural environment monitoring.

[0033] The specific analysis process is as follows: obtaining agricultural soil environmental data, including monitoring the deviation rate of soil pH value in agricultural areas, monitoring the deviation rate of soil moisture in agricultural areas, and monitoring the content of heavy metals in soil in agricultural areas; based on the obtained agricultural soil environmental data, comprehensive analysis is performed to obtain characteristic signals of agricultural soil environmental status, which are used as the analysis basis for judging whether the agricultural soil environmental status is qualified and determining the second initial level of agricultural environmental monitoring; The agricultural soil environment state characteristic signal is compared with the agricultural soil environment state characteristic threshold stored in the database; if the agricultural soil environment state characteristic signal is not lower than the agricultural soil environment state characteristic threshold, the agricultural soil environment state corresponding to the agricultural soil environment state characteristic signal is qualified, and the second initial level of agricultural environment monitoring is zero; if the agricultural soil environment state characteristic signal is lower than the agricultural soil environment state characteristic threshold, the agricultural soil environment state corresponding to the agricultural soil environment state characteristic signal is unqualified, and the second initial level of agricultural environment monitoring is one.

[0034] The soil pH deviation rate refers to the difference between the actual measured soil pH and the standard or ideal pH. The pH value affects the availability of nutrients in the soil. Monitoring the soil pH deviation rate can help determine whether there is an acid-base imbalance in the soil. The soil moisture deviation rate refers to the difference between the actual measured soil moisture and a certain standard or ideal moisture. Soil moisture is crucial to the water supply of crops. Appropriate moisture can ensure the healthy growth of crops and prevent drought and over-humidity. The soil heavy metal content refers to the concentration of various heavy metals (such as lead, cadmium, arsenic, copper, zinc, etc.) in the soil, usually measured in milligrams per kilogram of soil (mg / kg) or ppm (parts per million). The presence of heavy metals can have a negative impact on crop growth and human health. Monitoring the soil heavy metal content can help identify potential pollution risks.

[0035] By monitoring the deviation rate of soil pH, moisture and heavy metal content, the chemical and physical conditions of the soil can be understood in a timely manner. A soil environment that meets the standards helps maintain the biological activity and nutrient cycle of the soil, ensuring the growth and high yield of crops. Monitoring the heavy metal content in the soil can ensure the safety of agricultural products, and a soil environment that meets the standards can avoid the contamination of crops by heavy metals, thereby improving the quality of agricultural products. Healthy soil can maintain the balance of the ecosystem, support the survival of soil microorganisms and other beneficial organisms, and promote biodiversity. Once the soil environment status is detected to be unqualified, corrective measures can be taken in a timely manner to reduce the risk of crop diseases and pests caused by soil problems and reduce economic losses.

[0036] The calculation method of the characteristic signal of agricultural soil environmental status is: ; In the formula, is the characteristic signal of agricultural soil environmental status, php is the deviation rate of soil pH value in agricultural areas, sdp is the deviation rate of soil moisture in agricultural areas, zjs is the content of heavy metals in agricultural areas, , , These are the compensation factors for php, sdp, and zjs respectively.

[0037] By monitoring the pH and moisture of the soil, fertilization and irrigation strategies can be better adjusted to ensure that soil conditions are suitable for crop growth, which helps to improve crop yield and quality. Regular monitoring of soil heavy metal content can help identify pollution sources and take appropriate measures to improve soil quality, maintain the ecological environment, and protect crops from heavy metal pollution. Understanding the changes in soil moisture and pH can improve the adaptability of crops to adverse growing conditions and enhance stress resistance. Soil pH directly affects the availability of nutrients, and monitoring its deviation rate can reduce the risk of environmental pollution. A healthy soil environment can inhibit the occurrence of certain pests and diseases. Monitoring the soil environment can also assist in identifying soil conditions related to pests and diseases and help take preventive measures.

[0038] The third initial level determination module is used to analyze the agricultural pest status, determine whether the agricultural pest status is qualified and determine the third initial level of agricultural environmental monitoring.

[0039] The specific analysis process is as follows: obtaining agricultural pest status data, including monitoring the proportion of crop pest area in agricultural areas and monitoring the insect population density in agricultural areas; based on the obtained agricultural pest status data, comprehensive analysis is performed to obtain agricultural pest status characteristic signals, which are used as the analysis basis for judging whether the agricultural pest status is qualified and determining the third initial level of agricultural environmental monitoring; The agricultural pest state characteristic signal is compared with the agricultural pest state characteristic threshold stored in the database; if the agricultural pest state characteristic signal is not lower than the agricultural pest state characteristic threshold, the agricultural pest state corresponding to the agricultural pest state characteristic signal is qualified, and the third initial level of agricultural environmental monitoring is zero; if the agricultural pest state characteristic signal is lower than the agricultural pest state characteristic threshold, the agricultural pest state corresponding to the agricultural pest state characteristic signal is unqualified, and the third initial level of agricultural environmental monitoring is one.

[0040] The proportion of crop pest area refers to the ratio of the crop area infested by pests to the total crop area in a specific agricultural area. It can directly reflect the severity of pests and help judge the impact of pests on crops. Pest density refers to the number of pests per unit area (usually per square meter or per hectare) in a specific area. Pest density is used to assess the number level of pests. The level of pest density directly affects the health of crops, and a higher pest density usually means a greater risk of pests.

[0041] Monitoring the proportion of crop pest area and insect population density can quickly identify the affected crop area, which helps to take timely measures to reduce the spread of pests. Real-time monitoring and management of pests can effectively reduce crop losses caused by pests, thereby increasing the total yield and market quality of crops. By setting pest status characteristic thresholds, pest risks can be identified in a timely manner to prevent large-scale outbreaks of pests. Based on the analysis of pest status characteristic signals, more scientific and effective decisions can be made to optimize resource allocation.

[0042] The calculation method of the characteristic signal of agricultural pest status is: ; In the formula, is the characteristic signal of agricultural pest status, hs is the proportion of crop pest area in the monitored agricultural area, cm is the insect population density in the monitored agricultural area, , is the compensation factor of the set hs and cm.

[0043] By regularly monitoring the pest area and insect population density, the risk of pest outbreaks can be identified early, and prevention and control measures can be taken in time to reduce the impact of pests on crops. After obtaining detailed pest data, more accurate pest management strategies can be implemented. Reducing the damage caused by pests can effectively improve the yield and quality of crops. Monitoring the insect population density can help predict the life cycle and outbreak pattern of pests, reasonably arrange the frequency of prevention and control, help break the cycle of pests and diseases, and reduce the long-term threat of pests. The collection and analysis of pest monitoring data provides strong decision-making support, which can adjust management measures based on real-time information and carry out production scientifically and rationally.

[0044] The agricultural environment monitoring level determination module is used to accumulate the first initial level of agricultural environment monitoring, the second initial level of agricultural environment monitoring, the third initial level of agricultural environment monitoring and the agricultural environment monitoring impact level to obtain the agricultural environment monitoring level, and determine whether it is necessary to issue a danger warning prompt for the agricultural environment. If a danger warning prompt needs to be issued, then after the danger warning prompt is issued, the agricultural environment adjustment plan is obtained.

[0045] The specific analysis process is as follows: the first initial agricultural environmental monitoring level, the second initial agricultural environmental monitoring level, the third initial agricultural environmental monitoring level and the agricultural environmental monitoring impact level are accumulated to obtain the agricultural environmental monitoring level; the agricultural environmental monitoring level is compared with the agricultural environmental monitoring threshold level stored in the database; if the agricultural environmental monitoring level is not lower than the agricultural environmental monitoring threshold level, the agricultural environment corresponding to the agricultural environmental monitoring level is safe and no danger warning prompt needs to be issued; if the agricultural environmental monitoring level is lower than the agricultural environmental monitoring threshold level, the agricultural environment corresponding to the agricultural environmental monitoring level is unsafe and a danger warning prompt needs to be issued: after issuing the danger warning prompt, the light intensity of the monitored agricultural area is obtained, and the light intensity of the monitored agricultural area is compared with the light intensity threshold stored in the database; If the light intensity of the monitored agricultural area is not lower than the light intensity threshold, there is no need to turn on the supplementary lighting; if the light intensity of the monitored agricultural area is lower than the light intensity threshold, it is necessary to determine the supplementary lighting scheme, and compare the light intensity of the monitored agricultural area with the supplementary lighting schemes corresponding to the light intensities of each monitored agricultural area stored in the database to obtain the supplementary lighting scheme corresponding to the light intensity of the monitored agricultural area, and adjust the light intensity of the monitored agricultural area based on the determined supplementary lighting scheme; at the same time, the characteristic signal of the agricultural meteorological environment state, the characteristic signal of the agricultural soil environment state and the characteristic signal of the agricultural pest state are stored as designated tags, and the designated tag is compared with each set tag stored in the database to obtain the set tag corresponding to the designated tag, and obtain the second agricultural environment adjustment scheme corresponding to the set tag stored in the database.

[0046] Through the monitoring and early warning mechanism, potential agricultural environmental problems can be discovered in time, damage to crops and soil can be reduced, and agricultural safety can be ensured. The monitoring and early warning system provides an objective data basis to help make more scientific decisions and optimize resource allocation and management strategies. Through accurate monitoring and early warning, resource use can be optimized. Through the evaluation of environmental monitoring levels, sustainable agricultural practices are encouraged to reduce environmental pollution and resource waste, and achieve long-term development of agriculture. Timely early warning helps protect the surrounding ecological environment, maintain biodiversity, and reduce the negative impact of agricultural production on the environment. If the monitoring shows that the environmental safety level is unqualified, it will help to form an effective emergency plan, take remedial measures quickly, and reduce the harm to agricultural production.

[0047] By comparing the light intensity in the monitored agricultural area with the threshold, it is possible to accurately determine whether supplementary lighting is needed. This avoids unnecessary supplementary lighting operations and saves energy and resources. For some flower crops that require high light intensity, when the light intensity is lower than the threshold required for their growth, timely opening of supplementary lighting can ensure their normal photosynthesis and flower bud differentiation, and no supplementary lighting is performed when the light is sufficient to prevent excessive light from having adverse effects on the quality of flowers. By comparing the actual light intensity monitored with the corresponding supplementary lighting scheme in the database, accurate customization of supplementary lighting can be achieved. The characteristic signals of the agricultural meteorological environment state, the characteristic signals of the agricultural soil environment state, and the characteristic signals of the agricultural pest state are stored as designated tags and compared to obtain the second agricultural environment adjustment scheme, which can achieve multi-factor comprehensive adjustment. When the light intensity is insufficient and the soil moisture is high at the same time, the second agricultural environment adjustment scheme will adjust the irrigation strategy while supplementing the light to prevent the breeding of pests and diseases caused by insufficient light and inappropriate humidity. Comprehensive adjustment can fully consider the mutual influence between environmental factors and avoid the negative effects of single factor adjustment.

[0048] A specific example is used to illustrate this embodiment: monitoring agricultural area fertilization frequency (SFP): 3 times / month, monitoring agricultural area irrigation frequency (GGP): 2 times / week, monitoring agricultural area average single irrigation volume (GGL): 50 mm, SFP compensation factor: 0.5, GGP compensation factor: 0.6, GGL compensation factor: 0.4, the agricultural agronomic condition characteristic factor is calculated to be 20.407, the agricultural agronomic condition characteristic factor is stored as a designated label, the designated label is compared with each setting stored in the database, and the setting label corresponding to the designated label is obtained, and the agricultural environment monitoring impact level corresponding to the setting label stored in the database is obtained as level 2.

[0049] Deviation rate of light intensity in monitored agricultural areas (GZP): 10%, deviation rate of temperature in monitored agricultural areas (WDP): 5%, deviation rate of precipitation in monitored agricultural areas (JSL): 15%, compensation factor of GZP: 0.3, compensation factor of WDP: 0.4, compensation factor of JSL: 0.2, the calculated characteristic signal of agricultural meteorological environment state is 0.680, and the characteristic threshold of agricultural meteorological environment state stored in the database is 0.7. Since the calculated characteristic signal of agricultural meteorological environment state (0.680) is lower than the threshold value of 0.7, the agricultural meteorological environment state is unqualified, and the first initial level of agricultural environment monitoring is level one.

[0050] Deviation rate of soil pH value in monitored agricultural areas (PHP): 8%, deviation rate of soil moisture in monitored agricultural areas (SDP): 12%, content of heavy metals in monitored agricultural soil areas (ZJS): 20 mg / kg, compensation factor of PHP: 0.2, compensation factor of SDP: 0.3, compensation factor of ZJS: 0.1, the calculated characteristic signal of agricultural soil environment status is 1.406, and the characteristic threshold of agricultural soil environment status stored in the database is 1.5. Since the calculated characteristic signal of agricultural soil environment status (1.406) is lower than the threshold value of 1.5, the agricultural soil environment status is unqualified, and the second initial level of agricultural environment monitoring is level one.

[0051] The proportion of crop pest area in monitored agricultural areas (hs): 15%, the insect population density in monitored agricultural areas (cm): 10 / m2, the compensation factor of hs: 0.4, the compensation factor of cm: 0.3, the calculated characteristic signal of the agricultural pest state is 0.557, and the characteristic threshold of the agricultural pest state stored in the database is 0.6. Since the calculated characteristic signal of the agricultural pest state (0.557) is lower than the threshold of 0.6, the agricultural pest state is unqualified, and the third initial level of agricultural environment monitoring is level one.

[0052] The first initial level (level 1) of agricultural environment monitoring, the second initial level (level 1) of agricultural environment monitoring, the third initial level (level 1) of agricultural environment monitoring and the impact level (level 2) of agricultural environment monitoring are accumulated, and the agricultural environment monitoring level is level 5. The threshold level of agricultural environment monitoring stored in the database is level 2. Since the calculated agricultural environment monitoring level (level 5) is greater than the threshold level 2, the agricultural environment is unsafe and a danger warning prompt needs to be issued. The light intensity of the monitored agricultural area is 8000 lux, and the light intensity threshold stored in the database is 10000 lux. The light intensity of the monitored agricultural area is lower than the light intensity threshold, so it is necessary to determine the supplementary lighting scheme. The light intensity of the monitored agricultural area is compared with the supplementary lighting schemes corresponding to the light intensity of each monitored agricultural area stored in the database. The supplementary lighting scheme corresponding to the light intensity of the monitored agricultural area is obtained. When the light intensity is between 7001 and 9000 lux, the supplementary lighting scheme is to use LED plant growth lights, turn on the LED plant growth lights to 70%, and supplement light for four hours. At the same time, the second agricultural environmental adjustment plan was obtained. Due to the general meteorological environment, the irrigation frequency was appropriately increased by 10% to cope with changes in water evaporation. The soil environment was moderate, and soil conditioners (500 kg of organic fertilizer per hectare) were applied to improve soil fertility and structure. For moderate insect pests, a combination of biological control and chemical control was adopted. The natural enemies of pests, predatory mites, were released in combination with low-toxic chemical pesticides (avermectin, diluted and sprayed at 1000 times, once every 7 days for 3 consecutive times).

[0053] Embodiment 2: A method for intelligent monitoring of agricultural environment, based on the system in Embodiment 1, such as Figure 2 As shown, the following steps are included: Determine the agricultural environment monitoring level. The agricultural environment monitoring level is obtained by adding the first initial level, the second initial level, the third initial level and the impact level. The first initial level is determined based on the analysis of the agricultural meteorological environment, the second initial level is determined based on the analysis of the agricultural soil environment, the third initial level is determined based on the analysis of the agricultural pest status, and the impact level is determined based on the analysis of the agricultural agronomic conditions. Please refer to the above content for the specific determination method.

[0054] Determine whether an alarm is needed based on the agricultural environment monitoring level: if an alarm is not needed, continue to obtain the agricultural environment monitoring level and judge again whether an alarm is needed; if an alarm is needed, obtain the current agricultural environment data, which includes environmental brightness, environmental humidity and environmental alcohol content, and obtain the agricultural environment parameter data stored in the database, which includes environmental parameter brightness, environmental parameter humidity and environmental parameter alcohol content.

[0055] If the absolute value of the difference between the ambient brightness and the ambient reference brightness is greater than the brightness deviation threshold stored in the database, in this case, if the ambient brightness is less than the ambient reference brightness (that is, when the light intensity in the agricultural area is lower than the light intensity threshold), the LED module will perform fill light and adjust the brightness. If the ambient brightness is greater than the ambient reference brightness difference (that is, when the light intensity in the agricultural area is higher than the light intensity threshold), the LED module will not perform fill light, and for greenhouse agriculture, sunshade operation can be performed.

[0056] If the absolute value of the ambient humidity and the ambient reference humidity is greater than the humidity deviation threshold stored in the database, in this case, if the ambient humidity is lower than the ambient reference humidity, the humidity adjustment device performs a humidification operation; if the ambient humidity is higher than the ambient reference humidity, the humidity adjustment device performs a drying operation.

[0057] If the difference between the ambient alcohol content and the ambient reference alcohol content is greater than the alcohol concentration deviation threshold stored in the database, the alcohol treatment device purifies the ambient alcohol and sends an abnormal alcohol concentration warning.

[0058] Example 3: Figure 4 As shown, an agricultural environment intelligent monitoring device is used to implement the system in Example 1, including a data acquisition module, an LED module, a humidity adjustment device, an alcohol treatment device, a control processing module, an agricultural environment monitoring level acquisition module and an early warning processing module: The data acquisition module is used to obtain agricultural agronomic conditions data, agricultural meteorological environment data, agricultural soil environment data and agricultural pest status data. The acquisition method refers to the above content.

[0059] The agricultural environment monitoring level is used to determine the agricultural environment monitoring level based on agricultural agronomic conditions data, agricultural meteorological environment data, agricultural soil environment data and agricultural pest status data. The method for determining the agricultural environment monitoring level refers to the above content.

[0060] The early warning processing module is used to determine whether an early warning is needed based on the agricultural environment monitoring level, and send the early warning information to the control processing module when an early warning is needed; the control processing module is used to control and process the LED module, the humidity adjustment device, and the alcohol treatment device when receiving the early warning information; the LED module is used to adjust the environmental brightness under the control of the control processing module; the humidity adjustment device is used to adjust the environmental humidity under the control of the control processing module; the alcohol treatment device is used to purify the environmental alcohol under the control of the control processing module.

Claims

1. An intelligent monitoring system for agricultural environment, characterized in that: It includes a monitoring impact level determination module, a first initial level determination module, a second initial level determination module, a third initial level determination module and an agricultural environment monitoring level determination module, wherein: Monitoring impact level determination module, used to analyze agricultural agronomic conditions and determine the agricultural environmental monitoring impact level; The first initial level determination module is used to analyze the agricultural meteorological environment, determine whether the agricultural meteorological environment state is qualified and determine the first initial level of agricultural environment monitoring; The second initial level determination module is used to analyze the agricultural soil environment, determine whether the agricultural soil environment state is qualified and determine the second initial level of agricultural environment monitoring; The third initial level determination module is used to analyze the agricultural pest status, determine whether the agricultural pest status is qualified and determine the third initial level of agricultural environment monitoring; The agricultural environment monitoring level determination module is used to accumulate the first initial level of agricultural environment monitoring, the second initial level of agricultural environment monitoring, the third initial level of agricultural environment monitoring and the agricultural environment monitoring impact level to obtain the agricultural environment monitoring level, and determine whether it is necessary to issue a danger warning prompt for the agricultural environment. If a danger warning prompt needs to be issued, then after the danger warning prompt is issued, the agricultural environment adjustment plan is obtained.

2. The agricultural environment intelligent monitoring system according to claim 1 is characterized in that: The process of analyzing agricultural agronomic conditions and determining the impact level of agricultural environmental monitoring is as follows: Obtain agricultural agronomic conditions data, including monitoring the frequency of fertilization in agricultural areas, monitoring the frequency of irrigation in agricultural areas, and monitoring the average single irrigation volume in agricultural areas; Based on the acquired agricultural agronomic conditions data, the agricultural agronomic conditions characteristic factors are obtained through comprehensive analysis. The agricultural agronomic conditions characteristic factors are used as the analysis basis for determining the impact level of agricultural environmental monitoring. The agricultural agronomic condition characteristic factor is stored as a designated label, and the designated label is compared with each set label stored in the database to obtain the set label corresponding to the designated label, and the agricultural environment monitoring impact level corresponding to the set label stored in the database is obtained.

3. The agricultural environment intelligent monitoring system according to claim 2 is characterized in that: The calculation method of the characteristic factors of agricultural agronomic conditions is: ； In the formula, is the characteristic factor of agricultural agronomic conditions, sfp is the fertilization frequency of the monitored agricultural area, ggp is the irrigation frequency of the monitored agricultural area, ggl is the average single irrigation amount of the monitored agricultural area, , , are the compensation factors of the set sfp, ggp, and ggl respectively, and e is a natural constant.

4. The agricultural environment intelligent monitoring system according to claim 1 is characterized in that: The process of judging whether the agricultural meteorological environment status is qualified and determining the first initial level of agricultural environmental monitoring is as follows: Obtain agricultural meteorological environment data, including monitoring the light intensity deviation rate, temperature deviation rate, and precipitation deviation rate in agricultural areas; Based on the acquired agricultural meteorological environmental data, a comprehensive analysis is performed to obtain characteristic signals of agricultural meteorological environmental status, which are used as the analysis basis for judging whether the agricultural meteorological environmental status is qualified and determining the first initial level of agricultural environmental monitoring; comparing the agricultural meteorological environment state characteristic signal with the agricultural meteorological environment state characteristic threshold value stored in the database; If the agricultural meteorological environment state characteristic signal is not lower than the agricultural meteorological environment state characteristic threshold, the agricultural meteorological environment state corresponding to the agricultural meteorological environment state characteristic signal is qualified, and the first initial level of agricultural environment monitoring is zero; If the agricultural meteorological environment state characteristic signal is lower than the agricultural meteorological environment state characteristic threshold, the agricultural meteorological environment state corresponding to the agricultural meteorological environment state characteristic signal is unqualified, and the first initial level of agricultural environment monitoring is level one.

5. The agricultural environment intelligent monitoring system according to claim 1 is characterized in that: The process of judging whether the agricultural soil environmental status is qualified and determining the second initial level of agricultural environmental monitoring is as follows: Obtain agricultural soil environmental data, including monitoring the soil pH deviation rate in agricultural areas, monitoring the soil moisture deviation rate in agricultural areas, and monitoring the soil heavy metal content in agricultural areas; Based on the acquired agricultural soil environmental data, a comprehensive analysis is conducted to obtain characteristic signals of the agricultural soil environmental status, which are used as the analysis basis for judging whether the agricultural soil environmental status is qualified and determining the second initial level of agricultural environmental monitoring; comparing the agricultural soil environmental state characteristic signal with the agricultural soil environmental state characteristic threshold value stored in the database; If the agricultural soil environment state characteristic signal is not lower than the agricultural soil environment state characteristic threshold, the agricultural soil environment state corresponding to the agricultural soil environment state characteristic signal is qualified, and the second initial level of agricultural environment monitoring is zero; If the agricultural soil environmental state characteristic signal is lower than the agricultural soil environmental state characteristic threshold, the agricultural soil environmental state corresponding to the agricultural soil environmental state characteristic signal is unqualified, and the second initial level of agricultural environmental monitoring is level one.

6. The agricultural environment intelligent monitoring system according to claim 1, characterized in that: The process of judging whether the agricultural pest status is qualified and determining the third initial level of agricultural environmental monitoring is: Obtain agricultural pest status data, including monitoring the proportion of crop pest areas in agricultural areas and monitoring insect population density in agricultural areas; Based on the acquired agricultural pest status data, a comprehensive analysis is performed to obtain characteristic signals of the agricultural pest status, which are used as the analysis basis for judging whether the agricultural pest status is qualified and determining the third initial level of agricultural environmental monitoring; comparing the agricultural pest state characteristic signal with the agricultural pest state characteristic threshold stored in the database; If the agricultural pest state characteristic signal is not lower than the agricultural pest state characteristic threshold, the agricultural pest state corresponding to the agricultural pest state characteristic signal is qualified, and the third initial level of agricultural environment monitoring is zero; If the agricultural pest state characteristic signal is lower than the agricultural pest state characteristic threshold, the agricultural pest state corresponding to the agricultural pest state characteristic signal is unqualified, and the third initial level of agricultural environment monitoring is level one.

7. The agricultural environment intelligent monitoring system according to claim 6, characterized in that: The calculation method of the characteristic signal of agricultural pest status is: ； In the formula, is the characteristic signal of agricultural pest status, hs is the proportion of crop pest area in the monitored agricultural area, cm is the insect population density in the monitored agricultural area, , is the compensation factor of the set hs and cm, and e is a natural constant.

8. The agricultural environment intelligent monitoring system according to claim 1 is characterized in that: Determine the agricultural environment monitoring level and judge whether it is necessary to issue a danger warning for the agricultural environment. If it is necessary to issue a danger warning, the process of obtaining the agricultural environment adjustment plan after issuing the danger warning is as follows: The agricultural environment monitoring level is obtained by accumulating the first initial level of agricultural environment monitoring, the second initial level of agricultural environment monitoring, the third initial level of agricultural environment monitoring and the impact level of agricultural environment monitoring; comparing the agricultural environment monitoring level with the agricultural environment monitoring threshold level stored in the database; If the agricultural environment monitoring level is not lower than the agricultural environment monitoring threshold level, the agricultural environment corresponding to the agricultural environment monitoring level is safe and there is no need to issue a danger warning prompt; If the agricultural environment monitoring level is lower than the agricultural environment monitoring threshold level, the agricultural environment corresponding to the agricultural environment monitoring level is unsafe and a danger warning prompt needs to be issued: After issuing a danger warning prompt, obtaining the light intensity of the monitored agricultural area, and comparing the light intensity of the monitored agricultural area with the light intensity threshold stored in the database; If the light intensity in the monitored agricultural area is not lower than the light intensity threshold, there is no need to turn on the supplementary light; If the light intensity of the monitored agricultural area is lower than the light intensity threshold, a supplementary lighting scheme needs to be determined, and the light intensity of the monitored agricultural area is compared with the supplementary lighting schemes corresponding to the light intensity of each monitored agricultural area stored in the database to obtain the supplementary lighting scheme corresponding to the light intensity of the monitored agricultural area, and the light intensity of the monitored agricultural area is adjusted based on the determined supplementary lighting scheme; At the same time, the agricultural meteorological environment status characteristic signal, the agricultural soil environment status characteristic signal and the agricultural pest status characteristic signal are stored as designated tags, and the designated tags are compared with the set tags stored in the database to obtain the set tag corresponding to the designated tag, and obtain the second agricultural environment adjustment plan corresponding to the set tag stored in the database.

9. An agricultural environment intelligent monitoring method, based on an agricultural environment intelligent monitoring system according to any one of claims 1 to 8, characterized in that: The following steps are involved: Determine the agricultural environment monitoring level, which is obtained by accumulating the first initial agricultural environment monitoring level, the second initial agricultural environment monitoring level, the third initial agricultural environment monitoring level and the agricultural environment monitoring impact level, wherein the first initial agricultural environment monitoring level is determined based on the analysis of the agricultural meteorological environment, the second initial agricultural environment monitoring level is determined based on the analysis of the agricultural soil environment, the third initial agricultural environment monitoring level is determined based on the analysis of the agricultural pest status, and the agricultural environment monitoring impact level is determined based on the analysis of agricultural agronomic conditions; Determine whether an alarm is needed based on the agricultural environment monitoring level: If no alarm is needed, continue to obtain the agricultural environment monitoring level and determine again whether an alarm is needed; If an alarm is required, the current agricultural environment data is obtained, which includes the environment brightness, environment humidity and environment alcohol content; Acquire the agricultural environment parameter data stored in the database, the agricultural environment parameter data including the environment parameter brightness, environment parameter humidity and environment parameter alcohol content; If the absolute value of the difference between the ambient brightness and the ambient reference brightness is greater than the brightness deviation threshold stored in the database, the ambient brightness is adjusted based on the LED module; If the absolute value of the ambient humidity and the ambient reference humidity is greater than the humidity deviation threshold stored in the database, the ambient humidity is adjusted based on the humidity adjustment device; If the difference between the environmental alcohol content and the environmental reference alcohol content is greater than the alcohol concentration deviation threshold stored in the database, the environmental alcohol is purified based on the alcohol treatment device and an abnormal alcohol concentration warning is sent.

10. An agricultural environment intelligent monitoring device, used to implement an agricultural environment intelligent monitoring system according to any one of claims 1 to 8, characterized in that: It includes data acquisition module, LED module, humidity adjustment device, alcohol processing device, control processing module, agricultural environment monitoring level acquisition module and early warning processing module: The data acquisition module is used to obtain agricultural agronomic conditions data, agricultural meteorological environment data, agricultural soil environment data and agricultural pest status data; The agricultural environmental monitoring level is used to determine the agricultural environmental monitoring level based on agricultural agronomic conditions data, agricultural meteorological environment data, agricultural soil environment data and agricultural pest status data; The early warning processing module is used to determine whether an early warning is needed based on the agricultural environment monitoring level, and send the early warning information to the control processing module when an early warning is needed; The control processing module is used to control and process the LED module, the humidity adjustment device, and the alcohol treatment device when receiving the warning information; The LED module is used to adjust the ambient brightness under the control of the control processing module; The humidity adjustment device is used to adjust the ambient humidity under the control of the control processing module; The alcohol treatment device is used to purify environmental alcohol under the control of the control processing module.

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