Method and system for real-time monitoring and analysis of environmental data for a planted field

Abstract

The application discloses a kind of environment data real-time monitoring and analysis method and system for planting field, it is related to agricultural planting technical field, it aims at solving the technical problems that existing technology cannot monitor environmental data implicit change, it is difficult to comprehensively analyze multi-source data, problem diagnosis and processing are not accurate, including the following steps: S1: the planting environment data of planting field is monitored in real time, and the water quality data, soil physicochemical data, soil microbial data, crop image data corresponding to different positions are obtained;S2: the above four kinds of data are arranged according to time sequence respectively, and water quality data change curve, soil physicochemical data change curve, soil microbial data change curve, crop image data change curve are generated;S3: the above four kinds of data change curve are scored according to corresponding parameter respectively, the present application can accurately judge the deterioration condition and position of environment by real-time acquisition of multi-source planting field environment data, solve the monitoring problem of prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of agricultural planting technology, more particularly, to an environment data real-time monitoring and analysis method and system for planting fields. BACKGROUND

[0002] With the continuous improvement of science and technology, people have a greater impact on the ecological environment. Changes in the environment indirectly affect the continuation and development of humans and other organisms. The existing ecological monitoring system is mainly used for ecological environment protection and ecological system investigation. It provides guidance for agricultural production processes by obtaining information about the state of changes in the ecological environment, and timely discovers problems in the ecological system to avoid damage to the ecological environment and promote the harmonious development of humans and the natural environment. It also provides decision-making basis for agricultural production to ensure the stable and sustainable development of agricultural production. With the development of big data technology, big data technology is gradually applied to the planting field environment monitoring system.

[0003] The existing ecological monitoring system in the prior art mainly obtains environmental data directly through sensors in terms of monitoring means. This method can alarm in time when the environmental data is obviously abnormal, but it is difficult to detect potential changes when the environmental data is within the normal range. For example, the slow changes of trace elements in the soil and the subtle adjustments of microbial community structure. These changes do not cause the environmental data to trigger an alarm in the short term, but long-term accumulation can have a negative impact on crop growth and sustainability, and existing simple data judgment methods cannot timely discover these potential problems.

[0004] In terms of data analysis, the existing technology analyzes environmental data in a relatively single way. Most of them only perform simple statistics and comparison of data, lack comprehensive analysis ability of multi-source data, and are difficult to mine the internal relationship and potential rules between data. This makes it impossible for agricultural producers to fully understand the trend of changes in the ecological environment of the planting field, to predict possible problems in advance and to take effective measures.

[0005] In addition, the existing monitoring system also has deficiencies in problem diagnosis and treatment. When the environmental data deteriorates, it is difficult to quickly and accurately determine whether it is caused by soil factors, crop factors or other factors, and it is difficult to develop precise solutions to specific problems, resulting in poor pertinence and effectiveness of problem treatment, affecting the yield and quality of crops and restricting the sustainable development of agriculture. In view of this, we propose an environment data real-time monitoring and analysis method and system for planting fields. SUMMARY

[0006] The present application aims to provide a kind of environment data real-time monitoring and analysis method and system for planting field, to solve the technical problems that prior art cannot monitor implicit change of environmental data, it is difficult to comprehensively analyze multi-source data, problem diagnosis and processing are not accurate.

[0007] To solve the above technical problems, the present application provides the following technical solutions: a kind of environment data real-time monitoring and analysis method for planting field, comprising the following steps:

[0008] S1: real-time monitoring the planting environment data of planting field, obtains the water quality data, soil physicochemical data, soil microbial data, crop image data corresponding to different positions;

[0009] S2: the above four types of data are arranged in time sequence respectively, and water quality data change curve, soil physicochemical data change curve, soil microbial data change curve, crop image data change curve are generated;

[0010] S3: the above four types of data change curve are scored according to corresponding parameters, obtain several scores corresponding to the above four types of data change curve, and then obtain the comprehensive score of the above four types of data, the above four types of comprehensive score are arranged in matrix format according to time sequence, and comprehensive score matrix is obtained;

[0011] S4: according to comprehensive score matrix and data standard deviation, judge whether the data monitored in current time period appears deterioration, and determine the deterioration position according to data change curve;

[0012] S5: judge whether the environmental data in current time period appears deterioration, if deterioration appears, judge whether the current soil factor and crop factor appear deterioration, and alarm;

[0013] In step S4, the formula for judging whether the data monitored in current time period appears deterioration is:

[0014] ;

[0015] In the formula, It is the pollution or change severity of planting field in this time change, It is the variance of environmental data comprehensive score in current time period, It is the variance of environmental data comprehensive score in the last time change, It is the variance of environmental data comprehensive score in the last two time changes, 、 It is a calculation parameter, It is data standard deviation.

[0016] The application can effectively solve the problems of unable to monitor hidden environmental changes and incomplete data analysis in the prior art by acquiring multi-aspect data of water quality, soil physicochemical properties, soil microorganisms and crop images in real time, generating corresponding data change curves for comprehensive scoring and analysis, utilizing comprehensive scoring matrix and data standard deviation to accurately judge whether the environmental data is deteriorating and the deterioration position, comprehensively evaluating the influence of environmental changes on crop growth and sustainable ability, providing scientific and comprehensive decision basis for agricultural production, enabling producers to discover potential problems in time and take preventive measures.

[0017] Preferably, the planting environment data of the planting field is monitored in real time in the step S1 to obtain corresponding water quality, soil physicochemical, soil microbial and crop image data at different positions, and specifically includes the following steps:

[0018] S101: Real-time monitoring of water quality data by a sensor, if the water quality data monitoring fails, then after waiting, the step S101 is re-executed, if the water quality data monitoring succeeds, then the step S102 is entered;

[0019] S102: Real-time detection of soil physicochemical data and soil microbial data by a soil monitor, if the soil physicochemical data or soil microbial data monitoring fails, then the step S101 is returned, if the soil physicochemical data and soil microbial data monitoring succeeds, then the step S103 is entered;

[0020] S103: Real-time detection of crop image data by a real-time image recognition module, if the crop image data monitoring fails, then the step S101 is returned, if the crop image data monitoring succeeds, then the step S104 is entered;

[0021] S104: Storing the four types of data monitored in real time into a local database.

[0022] Preferably, the step S3 specifically includes the following steps:

[0023] S301: Obtaining the maximum value and minimum value of the horizontal axis data of the water quality data change curve, and calculating the width of the water quality data change curve, multiplying the width with the score value corresponding to the pre-stored width to obtain the scores of several segments of the water quality data change curve, and further obtaining the water quality data change curve scores of several segments;

[0024] S302: Obtaining the soil physicochemical data change curve score, soil microbial data change curve score and crop image data change curve score by using the same algorithm;

[0025] S303: According to the overall distribution of the data change of the four types of data, the four types of data change curve scores are respectively corrected, and further the comprehensive scores of the four types of data are obtained;

[0026] S304: The water quality data comprehensive score, the soil physicochemical data comprehensive score, the soil microbial data comprehensive score and the crop image data comprehensive score are arranged in matrix format according to time sequence to obtain a comprehensive score matrix.

[0027] Preferably, the water quality data change curve score obtained in the step S301 is obtained by the following method: the width of the water quality data change curve is , the pre-stored width corresponding score value is , and the score of a certain section of the water quality data change curve is .

[0028] Preferably, the soil physicochemical data change curve score obtained in the step S302 is obtained by the following method: the width is , the pre-stored width corresponding score value is , and the score of a certain section of the soil physicochemical data change curve is

[0029] .

[0030] Preferably, the step S303 is modified respectively to the water quality data, the soil physicochemical data, the soil microbial data and the crop image data data change curve score, and then the water quality data comprehensive score, the soil physicochemical data comprehensive score, the soil microbial data comprehensive score and the crop image data comprehensive score are obtained by the following method:

[0031] The correction coefficient of the water quality data comprehensive score is , the correction coefficient of the soil physicochemical data comprehensive score is , the correction coefficient of the soil microbial data comprehensive score is , and the correction coefficient of the crop image data comprehensive score is , and then:

[0032] The water quality data comprehensive score is

[0033] .

[0034] The soil physicochemical data comprehensive score is

[0035] .

[0036] The soil microbial data comprehensive score is

[0037] .

[0038] The crop image data comprehensive score is

[0039] .

[0040] Preferably, if the environment data of the current time period does not deteriorate, the comprehensive score of the environment data of the current time period is obtained according to the following formula:

[0041] ;

[0042] In the formula, is the comprehensive score of the environment data of the current time period, is the weight of the curve score corresponding to the i-th curve, is the number of curves, the weight of the i-th curve is 1, is the expected value of the curve score corresponding to the i-th curve.

[0043] Preferably, the step S5 specifically comprises the following steps:

[0044] S501: If the environment data of the current time period deteriorates, it is determined whether the current soil factor deteriorates, if not, it is further determined whether the current crop factor deteriorates, if not, the step S503 is entered; if yes, the step S504 is entered;

[0045] S502: If the current soil factor deteriorates, the minimum value of the soil physicochemical data change curve score at the current position is found according to the deterioration position to alarm;

[0046] S503: If the current crop factor deteriorates, the minimum value of the crop image data change curve score at the current position is found according to the deterioration position to alarm;

[0047] S504: If the current soil factor and the crop factor deteriorate at the same time, the comprehensive score matrix is blocked according to the position, the feature change is compared, and it is determined whether the soil factor or the crop factor changes more seriously according to the comparison result, and then the main reason for the deterioration is determined.

[0048] A kind of environment data real-time monitoring and analysis system for planting field, comprising:

[0049] Data monitoring module, for real-time monitoring the planting environment data of planting field, obtains the water quality data, soil physicochemical data, soil microbial data, crop image data corresponding at different positions, and stores data into local database;

[0050] Data analysis module, for extracting four types of data in local database, and the above four types of data are arranged according to time sequence, and water quality data change curve, soil physicochemical data change curve, soil microbial data change curve, crop image data change curve are generated;

[0051] ​​a curve scoring module, configured to score the four types of data change curves according to corresponding parameters respectively, to obtain a plurality of scores corresponding to the four types of data change curves, and to further obtain comprehensive scores of the four types of data, and to arrange the four types of comprehensive scores in a matrix format according to time sequence to obtain a comprehensive score matrix;

[0052] an alarm module, configured to determine whether the monitoring parameters in the current time period deteriorate according to the comprehensive score matrix and the data standard deviation, to determine whether the current soil factors or crop factors deteriorate if the environmental data in the current time period deteriorate, and to perform an alarm.

[0053] Preferably, the data monitoring module comprises a water quality data monitoring unit for collecting water quality data, a soil data monitoring unit for collecting soil physicochemical data and soil microbial data, and a crop image data monitoring unit for collecting crop image data.

[0054] The soil physicochemical data comprises apparent soil conductivity, soil salinity and effective cation concentration of leaf surface nutrient solution.

[0055] The water quality data comprises dissolved oxygen concentration, conductivity, pH value and oxidation-reduction potential.

[0056] The soil microbial data comprises total number of soil microorganisms, number of ammonia-oxidizing bacteria, number of nitrite-oxidizing bacteria, number of nitrate-reducing bacteria and number of pseudomonas.

[0057] The crop image data comprises color feature parameters, definition feature parameters, texture feature parameters and morphological feature parameters.

[0058] Compared with the prior art, the present application has the following advantages:

[0059] 1. The present application can effectively solve the problems of inability to monitor hidden environmental changes and incomplete data analysis in the prior art by real-time acquisition of various data of water quality, soil physicochemical properties, soil microorganisms and crop images, generation of corresponding data change curves for comprehensive scoring and analysis, accurate determination of whether the environmental data deteriorate and the deterioration position by using the comprehensive score matrix and the data standard deviation, and comprehensive evaluation of the influence of environmental changes on crop growth and sustainable ability, thereby providing a scientific and comprehensive decision basis for agricultural production, enabling producers to discover potential problems in time and take preventive measures.

[0060] 2、The application further optimizes the problem diagnosis mechanism on the basis of realizing monitoring of implicit environmental changes and accurate judgment of environmental data deterioration, when environmental data deteriorates, the system can quickly judge whether the problem is caused by soil factors or crop factors, and according to the minimum value of the score of the corresponding data change curve at the deterioration position, an alarm is given, which enables the agricultural producer to quickly locate the problem source, compared with the traditional way, the problem diagnosis time is greatly shortened, valuable time is gained for timely remedial measures, the damage of environmental deterioration to crops is effectively reduced, and the healthy growth and yield stability of crops are further ensured.

[0061] 3、For the complex situation that soil factors and crop factors deteriorate at the same time, the application can accurately judge which change of soil factors or crop factors is more serious by position blocking and feature change comparison of the comprehensive score matrix, so as to determine the main cause of deterioration, based on this, the agricultural producer can develop more accurate and effective solutions, and the precision of the solution significantly improves the pertinence and effectiveness of problem processing, fundamentally reduces the adverse effects of environmental deterioration on crops, and ensures the long-term output of planting fields and the sustainable development of agriculture. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 is a method flowchart of the application;

[0063] Figure 2 is a system structure schematic diagram of the application. DETAILED DESCRIPTION

[0064] As Figure 1 shown, the application relates to a kind of for planting field's environmental data real-time monitoring and analysis method, comprising the following steps:

[0065] S1: the planting environment data of planting field is monitored in real time, and the water quality data, soil physicochemical data, soil microbial data, crop image data corresponding to different positions are obtained;

[0066] In the embodiment of the application, the soil physicochemical data specifically includes apparent soil conductivity, soil salinity, leaf surface nutrient solution effective cation concentration;

[0067] The water quality data specifically includes dissolved oxygen concentration, conductivity, pH value, oxidation-reduction potential;

[0068] The soil microbial data specifically includes total number of soil microorganisms, number of ammonia-oxidizing bacteria, number of nitrite-oxidizing bacteria, number of nitrate-reducing bacteria and number of pseudomonas;

[0069] The crop image data specifically includes color feature parameters, definition feature parameters, texture feature parameters and morphological feature parameters;

[0070] In the embodiment of the present application, the planting environment data of the planting field is monitored in real time in step S1 to obtain corresponding water quality data, soil physical and chemical data, soil microbial data and crop image data at different positions, specifically including the following steps:

[0071] S101: Real-time monitoring of water quality data by a sensor, if the water quality data monitoring fails, then after waiting, re-executing step S101, if the water quality data monitoring succeeds, then entering step S102;

[0072] S102: Real-time detection of soil physical and chemical data and soil microbial data by a soil monitor, if the soil physical and chemical data or soil microbial data monitoring fails, then returning to step S101, if the soil physical and chemical data and soil microbial data monitoring succeeds, then entering step S103;

[0073] S103: Real-time detection of crop image data by a real-time image recognition module, if the crop image data monitoring fails, then returning to step S101, if the crop image data monitoring succeeds, then entering step S104;

[0074] S104: Storing the real-time monitored water quality data, soil physical and chemical data, soil microbial data and crop image data into a local database;

[0075] S2: Arranging the water quality data, soil physical and chemical data, soil microbial data and crop image data in time sequence respectively, and generating a water quality data change curve, a soil physical and chemical data change curve, a soil microbial data change curve and a crop image data change curve;

[0076] S3: Scoring the water quality data change curve, the soil physical and chemical data change curve, the soil microbial data change curve and the crop image data change curve according to corresponding parameters to obtain a plurality of water quality data change curve scores, soil physical and chemical data change curve scores, soil microbial data change curve scores and crop image data change curve scores, and further obtaining water quality data comprehensive scores, soil physical and chemical data comprehensive scores, soil microbial data comprehensive scores and crop image data comprehensive scores, arranging the above four types of comprehensive scores in matrix format according to time sequence to obtain a comprehensive score matrix;

[0077] In the embodiment of the present application, step S3 specifically includes the following steps:

[0078] S301: Obtaining the maximum and minimum values of the horizontal axis data of the water quality data change curve, and calculating the width of the water quality data change curve, multiplying the width with the score value corresponding to the pre-stored width to obtain a plurality of water quality data change curve scores, and further obtaining a plurality of water quality data change curve scores;

[0079] In the embodiment of the present application, the scores of the water quality data change curves obtained in step S301 are obtained by the following method: assuming that the width of the water quality data change curve is , the pre-stored width corresponding score value is , then the score of the water quality data change curve is ;

[0080] S302: the scores of the soil physicochemical data change curve, the soil microbial data change curve and the crop image data change curve are obtained by using the same algorithm;

[0081] In the embodiment of the present application, the score of the soil physicochemical data change curve obtained in step S302 is obtained by the following method: assuming that the width is , the pre-stored width corresponding score value is , then the score of the soil physicochemical data change curve is

[0082] ;

[0083] S303: according to the overall distribution of the corresponding data changes of the water quality data, the soil physicochemical data, the soil microbial data and the crop image data, the scores of the above four types of data change curves are respectively corrected, and then the comprehensive score of the water quality data, the comprehensive score of the soil physicochemical data, the comprehensive score of the soil microbial data and the comprehensive score of the crop image data are obtained;

[0084] In the embodiment of the present application, the scores of the water quality data, the soil physicochemical data, the soil microbial data and the crop image data are respectively corrected in step S303, and then the comprehensive score of the water quality data, the comprehensive score of the soil physicochemical data, the comprehensive score of the soil microbial data and the comprehensive score of the crop image data are obtained by the following method:

[0085] assuming that the correction coefficient of the comprehensive score of the water quality data is , the correction coefficient of the comprehensive score of the soil physicochemical data is , the correction coefficient of the comprehensive score of the soil microbial data is , and the correction coefficient of the comprehensive score of the crop image data is , then:

[0086] The comprehensive score of the water quality data is

[0087] ;

[0088] The comprehensive score of the soil physicochemical data is

[0089] ;

[0090] The comprehensive score of the soil microbial data is

[0091] ;

[0092] Crop image data comprehensive score:

[0093] ;

[0094] S304: The water quality data comprehensive score, the soil physicochemical data comprehensive score, the soil microbial data comprehensive score and the crop image data comprehensive score are arranged in a matrix format according to the time sequence to obtain a comprehensive score matrix;

[0095] S4: According to the comprehensive score matrix and the data standard deviation, it is judged whether the data monitored in the current time period appears deterioration, and the deterioration position is determined according to the data change curve;

[0096] In the embodiment of the present application, the formula for judging whether the data monitored in the current time period appears deterioration in the step S4 is:

[0097] ;

[0098] In the formula, is the pollution or change severity of the planting field in the current time period, is the variance of the environmental data comprehensive score in the current time period, is the variance of the environmental data comprehensive score in the last time period, is the variance of the environmental data comprehensive score in the last two time periods, 、 is a calculation parameter, is the data standard deviation;

[0099] In the embodiment of the present application, if the environmental data in the current time period does not appear deterioration, the environmental data comprehensive score in the current time period is obtained according to the following formula:

[0100] ;

[0101] In the formula, is the environmental data comprehensive score in the current time period, is the weight of the curve score corresponding to the first curve, is the number of curves, the weight sum of is 1, is the expected value of the curve score corresponding to the first curve;

[0102] ​​The present application can effectively solve the problems of being unable to monitor implicit environmental changes and incomplete data analysis in the prior art by acquiring multi-aspect data of water quality, soil physicochemical properties, soil microorganisms and crop images in real time, and generating corresponding data change curves for comprehensive scoring and analysis, using comprehensive scoring matrix and data standard deviation, whether the environmental data is deteriorated and the deterioration position can be accurately judged, the influence of environmental changes on crop growth and sustainable ability is comprehensively evaluated, scientific and comprehensive decision basis is provided for agricultural production, and the producer can timely find potential problems and take preventive measures.

[0103] S5: judging whether the environmental data in the current time period appears deterioration, if the deterioration appears, judging whether the soil factor and the crop factor in the current time period appear deterioration, and alarming.

[0104] In the embodiment of the present application, the step S5 specifically comprises the following steps:

[0105] S501: if the environmental data in the current time period appears deterioration, judging whether the soil factor in the current time period appears deterioration, if not, further judging whether the crop factor in the current time period appears deterioration, if yes, entering step S503; if yes, entering step S504;

[0106] S502: if the soil factor in the current time period appears deterioration, according to the deterioration position, searching for the minimum value of the soil physicochemical data change curve score of the current position to alarm;

[0107] S503: if the crop factor in the current time period appears deterioration, according to the deterioration position, searching for the minimum value of the crop image data change curve score of the current position to alarm;

[0108] On the basis of monitoring implicit environmental changes and accurately judging environmental data deterioration, the present application further optimizes the problem diagnosis mechanism. When the environmental data appears deterioration, the system can quickly judge whether the problem is caused by the soil factor or the crop factor, and according to the deterioration position, searching for the minimum value of the corresponding data change curve score to alarm. This enables the agricultural producer to quickly locate the problem source, compared with the traditional way, greatly shortens the problem diagnosis time, gains valuable time for timely taking remedial measures, effectively reduces the damage of environmental deterioration to crops, and further guarantees the healthy growth and yield stability of crops.

[0109] S504: if the soil factor and the crop factor in the current time period appear deterioration at the same time, the comprehensive scoring matrix is divided according to the position, the feature change is compared, according to the feature change comparison result, judging whether the soil factor or the crop factor changes more seriously, and further determining the main reason for deterioration.

[0110] For the complex situation of soil factors and crop factors deteriorating at the same time, the application can accurately determine which change of soil factors or crop factors is more serious by position blocking and feature change comparison of the comprehensive score matrix, so as to determine the main cause of deterioration. Based on this, agricultural producers can develop more accurate and effective solutions, such as targeted soil improvement measures for soil factor deterioration, including reasonable fertilization, adjustment of soil pH, etc.; for crop factor deterioration, precise pest control or optimization of crop cultivation management measures can be carried out in time. This precise strategy significantly improves the pertinence and effectiveness of problem processing, fundamentally reduces the adverse effects of environmental deterioration on crops, and ensures the long-term output of planting fields and the sustainable development of agriculture.

[0111] As shown in Figure 2 An environment data real-time monitoring and analysis system for a planting field, comprising a data monitoring module, a data analysis module, a curve scoring module and an alarm module;

[0112] The data monitoring module is used to monitor the planting environment data of the planting field in real time, obtain corresponding water quality data, soil physicochemical data, soil microbial data and crop image data at different positions, and store the data in a local database.

[0113] The data analysis module is used to extract water quality data, soil physicochemical data, soil microbial data and crop image data from the local database, arrange the water quality data, soil physicochemical data, soil microbial data and crop image data in time sequence, and generate water quality data change curve, soil physicochemical data change curve, soil microbial data change curve and crop image data change curve.

[0114] The curve scoring module is used to score the water quality data change curve, soil physicochemical data change curve, soil microbial data change curve and crop image data change curve according to the corresponding parameters, respectively, to obtain several water quality data change curve scores, soil physicochemical data change curve scores, soil microbial data change curve scores and crop image data change curve scores, and then obtain water quality data comprehensive score, soil physicochemical data comprehensive score, soil microbial data comprehensive score and crop image data comprehensive score. The above four types of comprehensive scores are arranged in matrix format according to time sequence to obtain a comprehensive score matrix.

[0115] The alarm module is used to determine whether the monitoring parameters of the current time period have deteriorated according to the comprehensive score matrix and data standard deviation, and to determine whether the current soil factors or crop factors have deteriorated if the environmental data of the current time period has deteriorated, and to alarm.

[0116] As another embodiment of the present application, the data monitoring module comprises a water quality data monitoring unit, a soil data monitoring unit and a crop image data monitoring unit.

[0117] The embodiments of the present application are disclosed as preferred embodiments, but are not limited thereto, and those skilled in the art can easily understand the spirit of the present application according to the above embodiments, and make different inferences and changes, as long as they do not deviate from the spirit of the present application, and are within the protection scope of the present application.

Claims

1. A method for real-time monitoring and analysis of environmental data for a field, characterized in that, Comprise the following steps: S1: real-time monitoring of planting environment data of planting field, get corresponding water quality data, soil physical and chemical data, soil microbial data, crop image data at different positions; S2: respectively arrange water quality, soil physical and chemical, soil microbial, crop image data according to time sequence, and generate water quality data change curve, soil physical and chemical data change curve, soil microbial data change curve, crop image data change curve; S3: respectively score water quality, soil physical and chemical, soil microbial, crop image data change curve according to corresponding parameters, get several scores of water quality, soil physical and chemical, soil microbial, crop image data change curve, and then get the comprehensive score of water quality, soil physical and chemical, soil microbial, crop image data, arrange the water quality, soil physical and chemical, soil microbial, crop image comprehensive score according to time sequence in matrix format, get comprehensive score matrix, comprising the following steps: S301: get the maximum and minimum of the horizontal axis data of water quality data change curve, and calculate the width of water quality data change curve, multiply the width with the score value corresponding to the pre-stored width to get the score of several segments of water quality data change curve, and then get several water quality data change curve scores; S302: get soil physical and chemical data change curve score, soil microbial data change curve score and crop image data change curve score by using the same algorithm; S303: according to the overall distribution of water quality, soil physical and chemical, soil microbial, crop image data corresponding data change, respectively correct water quality, soil physical and chemical, soil microbial, crop image data change curve score, and then get the comprehensive score of water quality, soil physical and chemical, soil microbial, crop image data; S304: arrange water quality data comprehensive score, soil physical and chemical data comprehensive score, soil microbial data comprehensive score and crop image data comprehensive score according to time sequence in matrix format, get comprehensive score matrix; S4: according to the comprehensive score matrix and data standard deviation, judge whether the data monitored in the current time period is deteriorated, and determine the deterioration position according to the data change curve; S5: judge whether the environmental data in the current time period is deteriorated, if it is deteriorated, judge whether the current soil factor and crop factor are deteriorated, and alarm; The formula for judging whether the data monitored in the current time period is deteriorated in step S4 is: ； wherein is the pollution or severity of change of the planted field within the current time period, is the variance of the environmental data integrated score for the current time period, is the variance of the environmental data integrated score for the previous time period, is the variance of the environmental data integrated score for the previous two time periods, , is the calculation parameter, is the data standard deviation. 2.The method for real-time monitoring and analyzing environmental data for a planted field according to claim 1, wherein, The real-time monitoring of planting environment data of planting field in step S1 gets water quality, soil physical and chemical, soil microbial and crop image data at different positions, comprising the following steps: S101: real-time monitoring of water quality data by sensor, if water quality data monitoring fails, then wait and reexecute step S101, if water quality data monitoring is successful, then enter step S102; S102: real-time detection of soil physical and chemical data and soil microbial data by soil monitor, if soil physical and chemical data or soil microbial data monitoring fails, return to step S101, if soil physical and chemical data and soil microbial data monitoring is successful, then enter step S103; S103: Real-time detection of crop image data is performed by the real-time image recognition module. If the crop image data monitoring fails, the method returns to step S101. If the crop image data monitoring succeeds, the method proceeds to step S104; S104: The real-time monitored water quality, soil physicochemical, soil microbial, and crop image data are stored in the local database. 3.The method for real-time monitoring and analyzing environmental data for a planted field according to claim 1, wherein, The step S301 obtains several water quality data change curve scores by the following method: the width of the water quality data change curve is , the pre-stored width corresponding score value is , and the score of the water quality data change curve is . 4.The method for real-time monitoring and analyzing environmental data for a planted field according to claim 3, wherein, The score of the soil physicochemical data change curve obtained in the step S302 is obtained by the following method: setting the width as , and pre-storing the width corresponding score value as , then the score of the soil physicochemical data change curve of a certain section is 。 5.The method for real-time monitoring and analyzing environmental data for a planted field according to claim 4, wherein, The step S303 is modified for the data change curve scores of the water quality data, soil physicochemical data, soil microbial data, and crop image data, respectively, to obtain a water quality data comprehensive score, a soil physicochemical data comprehensive score, a soil microbial data comprehensive score, and a crop image data comprehensive score. The following methods are used: The correction coefficient of the water quality data comprehensive score is The correction coefficient of the soil physical and chemical data comprehensive score is The correction coefficient of the soil microbial data comprehensive score is The correction coefficient of the crop image data comprehensive score is Then: Water quality data comprehensive score: ； Soil physicochemical data comprehensive score: ； Soil microbial data comprehensive score: ； Crop image data comprehensive score: 。 6.The method for real-time monitoring and analyzing environmental data for a planted field according to claim 1, wherein, If the environmental data of the current time period does not deteriorate, the environmental data comprehensive score of the current time period is obtained according to the following formula: ； In the formula, is an environmental data comprehensive score of a current time period, is a weight of the curve score corresponding to the i-th curve, is a weight of the curve score corresponding to the i-th curve, is the number of curves, the weight of the i-th curve score and the weight of the j-th curve score are 1, is an expected value of the curve score corresponding to the i-th curve, and is an expected value of the curve score corresponding to the i-th curve. 7.The method for real-time monitoring and analyzing environmental data for a field according to claim 1, wherein, The step S5 specifically includes the following steps: S501: If the environmental data of the current time period deteriorates, it is determined whether the current soil factor deteriorates. If not, it is further determined whether the current crop factor deteriorates. If yes, the method proceeds to step S503. If yes, the method proceeds to step S504; S502: If the current soil factor deteriorates, the minimum value of the soil physicochemical data change curve score at the current position is found according to the deterioration position to generate an alarm; S503: If the current crop factor deteriorates, the minimum value of the crop image data change curve score at the current position is found according to the deterioration position to generate an alarm; S504: If the current soil factor and crop factor deteriorate simultaneously, the comprehensive score matrix is divided into blocks according to the position, the feature change is compared, the soil factor or crop factor change is determined to be more serious according to the feature change comparison result, and the main cause of deterioration is determined.

8. A system for real-time monitoring and analyzing environmental data of a field for planting, using the method for real-time monitoring and analyzing environmental data of a field for planting according to any one of claims 1-7, characterized in that, It includes: A data monitoring module for monitoring the planting environment data of a planting field in real time, obtaining water quality data, soil physicochemical data, soil microbial data, and crop image data at different positions, and storing the data in a local database; A data analysis module for extracting four types of data in the local database, arranging the water quality, soil physicochemical, soil microbial, and crop image data in time sequence, and generating water quality data change curves, soil physicochemical data change curves, soil microbial data change curves, and crop image data change curves; A curve scoring module for scoring the water quality, soil physicochemical, soil microbial, and crop image data change curves according to corresponding parameters to obtain scores of the water quality, soil physicochemical, soil microbial, and crop image data change curves, and then obtain comprehensive scores of the water quality, soil physicochemical, soil microbial, and crop image data. The water quality, soil physicochemical, soil microbial, and crop image comprehensive scores are arranged in matrix format according to the time sequence to obtain a comprehensive score matrix. An alarm module is configured to determine whether the monitoring parameter in the current time period is deteriorated according to the comprehensive score matrix and the data standard deviation, and to determine whether the current soil factor or crop factor is deteriorated if the environmental data in the current time period is deteriorated, and to perform alarm. 9.The real-time monitoring and analyzing system for environmental data of a planted field according to claim 8, wherein, The data monitoring module comprises a water quality data monitoring unit for collecting water quality data, a soil data monitoring unit for collecting soil physicochemical data and soil microbial data, and a crop image data monitoring unit for collecting crop image data; The soil physicochemical data comprises apparent soil conductivity, soil salinity and effective cation concentration of leaf nutrient solution; The water quality data comprises dissolved oxygen concentration, conductivity, pH value and oxidation-reduction potential; The soil microbial data comprises total number of soil microorganisms, number of ammonia-oxidizing bacteria, number of nitrite-oxidizing bacteria, number of nitrate-reducing bacteria and number of pseudomonas; The crop image data comprises color feature parameters, definition feature parameters, texture feature parameters and morphological feature parameters.

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