Sewage analysis processing method and system based on big data

Abstract

The invention discloses a sewage analysis and treatment method and system based on big data, and relates to the technical field of sewage reuse, the system collects component data of agricultural sewage, soil and crops in real time through a sensor group and an instrument, generates a component content data set, and stores the component content data set in a distributed storage library. By calculating the tolerance index nsx of the crops, the tolerance of the crops is comprehensively evaluated, so that a basis is provided for sewage reuse. After the sewage is recycled, crop physiological analysis is executed, a crop physiological state feedback index scl is calculated, and a crop return water growth state index hsz is calculated in combination with a crop tolerance index nsx, so that the growth health condition of crops is evaluated. If the crops grow healthily, sewage is recycled continuously; otherwise, measures are taken in time for optimization processing through system control. According to the system, the recycling process of agricultural sewage is optimized through a big data technology and intelligent analysis, the growth health of crops is ensured, and the utilization efficiency of water resources is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage reuse, and specifically to a method and system for sewage analysis and treatment based on big data. Background Art

[0002] With the continuous growth of the global population and the increasing demand for agricultural production, the shortage of water resources has become increasingly serious. Especially in arid and semi-arid regions, the tension of agricultural water use is even more severe. At the same time, agricultural pollution is increasing day by day, and the pollution of agricultural sewage discharge to water resources and soil environment has also become a hot topic of global concern. Facing this situation, how to effectively manage water resources and realize the recycling of sewage has become one of the key challenges for sustainable agricultural development. In this context, the innovation and application of sewage treatment and reuse technologies are not only related to the sustainability of agricultural production, but also related to the protection of the ecological environment and the rational utilization of water resources.

[0003] Although current sewage reuse technologies have been applied in some areas, their implementation effects are not satisfactory. Traditional sewage reuse mostly relies on a single water quality standard and reuse threshold, without fully considering the physiological state of crops and the types and concentration changes of specific pollutants in sewage, resulting in uncontrollable impacts of reclaimed water on crops and even possible adverse effects. For example, in some cases, even though the pollutant concentration of sewage meets the reuse standard, due to the influence of pollutants on the physiological state of crops, it may still lead to poor crop growth. In addition, the existing analysis systems have relatively simple evaluations of sewage treatment and reuse, lacking comprehensive data support and precise monitoring means, and not fully considering the dynamic changes of sewage and the adaptability of crops to water quality changes. Therefore, a more accurate and comprehensive sewage reuse evaluation system is needed to dynamically evaluate the impact of reclaimed water on crops by combining the tolerance analysis and physiological state of crops. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a method and system for sewage analysis and treatment based on big data, which solves the problems in the above background art.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A sewage analysis and treatment system based on big data, including a sewage monitoring module, a tolerance analysis module, a crop physiological analysis module, and a comprehensive status evaluation module;

[0006] The sewage monitoring module is used to collect the component data of sewage, soil, and crops in real time according to the sensor group and instruments installed in agricultural sewage and crop soil, construct a sewage analysis system for pretreatment, obtain a component content data group, and then store it in a distributed repository;

[0007] The tolerance analysis module is used to calculate based on the attribute data group. After obtaining the crop adaptability index swx and the sewage stratification dynamic pollution index lwb, it comprehensively calculates to obtain the crop tolerance index nsx for sewage reuse evaluation;

[0008] The crop physiological analysis module is used to calculate based on the crop physiological data group after sewage reuse to obtain the crop physiological state feedback index scl;

[0009] The comprehensive state evaluation module is used to calculate based on the crop tolerance index nsx and the crop physiological state feedback index scl to obtain the crop return water growth state index hsz for crop growth health evaluation.

[0010] Preferably, the sewage monitoring module includes a data monitoring unit, a data processing unit, and a data storage unit;

[0011] The data monitoring unit is used to collect the composition data of sewage, soil, and crops in real time based on the sensor group and instruments installed in agricultural sewage and crop soil;

[0012] The sensor group includes a leaf reflectance spectrum sensor, a leaf water sensor, a temperature sensor, a soil humidity sensor, and a pH sensor;

[0013] The instruments include a gas analyzer, a multi-parameter water quality detector, a permeameter, and a stomatal conductance meter.

[0014] Preferably, the data processing unit is used to construct a sewage analysis system, establish a communication connection between the sensor group and the instruments and the sewage analysis system through wireless communication, and transmit the obtained composition data to the sewage analysis system in real time for data cleaning, denoising, data correction, data time synchronization, and dimensionless processing to obtain a composition content data group;

[0015] The composition content data group includes an attribute data group and a crop physiological data group;

[0016] The attribute data group includes a pollutant content data group and a soil composition data group

[0017] The pollutant content data group includes the pollutant concentration cf and the environmental residual pollutant concentration wl;

[0018] The soil composition data group includes the soil permeability ct and the soil pH;

[0019] The crop physiological data group includes the stomatal conductance gs, the chlorophyll content cc, the relative leaf water content rc, the leaf temperature tl, and the soil humidity sm;

[0020] The data storage unit is used to construct a distributed storage repository according to the sewage analysis system, and store the component content data group in the distributed storage repository in real time.

[0021] Preferably, the tolerance analysis module includes a preliminary analysis unit and a crop tolerance analysis unit;

[0022] The preliminary analysis unit is used to calculate the crop adaptability index swx and the sewage stratification dynamic pollution index lwb according to the pollutant content data group and the soil composition data group respectively, and the specific acquisition formula is as follows;

[0023]

[0024] Where N represents the total number of pollutant types, cf i represents the concentration of the i-th pollutant in sewage, T i represents the optimal absorption concentration of crops for the i-th pollutant under standard conditions, wl i represents the environmental residual concentration of the i-th pollutant, α represents the pollutant hazard adjustment factor, and ∈ represents the minimum constant to prevent the denominator from being zero;

[0025]

[0026] In the formula, cf i，0 represents the initial concentration of the i-th pollutant in the sewage, t represents the current monitoring time, t0 represents the initial time of sewage discharge, β represents the pollutant degradation rate factor, e represents the exponential function, λ represents the pollutant degradation attenuation factor, a1 represents the regulating factor of pollutant degradation affected by the environment, and a2 represents the regulating factor of the influence of soil pH on pollutant degradation.

[0027] Preferably, the crop tolerance analysis unit includes a tolerance calculation unit and a wastewater reuse assessment unit;

[0028] The tolerance calculation unit is used to perform summary calculation based on the obtained crop adaptability index swx and the sewage stratification dynamic pollution index lwb to obtain the crop tolerance index nsx;

[0029] The crop tolerance index nsx is obtained by the following formula:

[0030] nsx=b1*sWx+b2*lwb;

[0031] Wherein, b1 and b2 represent the weight factors of the crop adaptability index swx and the sewage stratification dynamic pollution index lwb respectively, and 0<b1<1, 0<b2<1, and the specific values are set by the user.

[0032] Preferably, the reclaimed water evaluation unit is used to extract the historical component content data group from the distributed repository, and calculate the mean value of the historical crop tolerance index nsx by the statistical method. And set a preset first reclaimed water threshold A and a second reclaimed water threshold B, specifically: Then conduct reclaimed water evaluation with the obtained crop tolerance index nsx;

[0033] When the crop tolerance index nsx < the first reclaimed water threshold A, reclaimed water is prohibited;

[0034] When the first reclaimed water threshold A ≤ the crop tolerance index nsx ≤ the second reclaimed water threshold B, the sewage needs to be treated before reuse, and at this time, crop physiological analysis is performed;

[0035] When the crop tolerance index nsx > the second reclaimed water threshold B, the sewage can be directly reused, and at this time, crop physiological analysis is performed.

[0036] Preferably, the crop physiological analysis module is used to perform crop physiological analysis after reclaimed water reuse;

[0037] The crop physiological analysis is used to perform summary calculation based on the obtained crop physiological data group to obtain the crop physiological state feedback index scl, which is used to analyze the physiological conditions of crops in real time after reclaimed water reuse;

[0038] The crop physiological state feedback index scl is obtained through the following formula;

[0039]

[0040] In the formula, gs thr 、tl thr and sm thr respectively represent the standard reference values of stomatal conductance gs, leaf temperature tl and soil moisture sm under normal growth conditions, cc max and rc max respectively represent the peak values of chlorophyll content cc and leaf relative water content rc of crops in the optimal growth state, e represents the exponential function, and c represents the temperature influence factor.

[0041] Preferably, the comprehensive state evaluation module includes a growth state analysis unit and a growth state evaluation unit;

[0042] The growth state analysis unit is used to perform summary calculation based on the obtained crop tolerance index nsx and crop physiological state feedback index scl to obtain the crop reclaimed water growth state index hsz, and analyze the mutual influence between sewage quality and crop physiological state;

[0043] The crop backwater growth state index hsz is obtained through the following formula;

[0044] hsz = nsx * (1 - e β*sel )

[0045] In the formula, e represents the exponential function, and β represents the control coefficient of the sensitivity of the crop physiological state feedback index scl.

[0046] Preferably, the growth state evaluation unit is used to preset the crop physiological state threshold Z according to the crop growth industry standard, and perform crop growth health evaluation with the obtained crop backwater growth state index hsz. The specific evaluation scheme is as follows;

[0047] When the crop backwater growth state index hsz ≤ the crop physiological state threshold Z, it indicates that the crop is damaged. At this time, crop damage information is generated, and the crop damage information is transmitted to relevant personnel, notifying to close the recycled sewage outlet. After the sewage is treated, iterative analysis is performed through the tolerance analysis module;

[0048] When the crop backwater growth state index hsz > the crop physiological state threshold Z, the crop grows healthily, and the sewage is continuously recycled and monitored.

[0049] A sewage analysis and treatment method based on big data includes the following steps:

[0050] S1. According to the sensor group and instruments installed in agricultural sewage and crop soil, the component data of sewage, soil and crops are collected in real time, and a sewage analysis system is constructed for pretreatment to obtain the component content data group, and then it is stored in the distributed repository;

[0051] S2. Calculate according to the attribute data group. After obtaining the crop adaptability index swx and the sewage stratified dynamic pollution index lwb, comprehensively calculate to obtain the crop tolerance index nsx for sewage reuse evaluation;

[0052] S3. After sewage reuse, calculate according to the crop physiological data group to obtain the crop physiological state feedback index scl;

[0053] S4. Calculate according to the crop tolerance index nsx and the crop physiological state feedback index scl to obtain the crop backwater growth state index hsz for crop growth health evaluation.

[0054] The present invention provides a sewage analysis and treatment method and system based on big data. It has the following beneficial effects:

[0055] (1) The sewage monitoring module of this system realizes the real-time collection of the components of sewage, soil, and crops through the sensor groups and instruments arranged in agricultural sewage and crop soil, and monitors the growth environment and water quality of crops in real time. The obtained component data is processed through cleaning, denoising, calibration, and dimensionless processing, and finally forms an attribute data group and a crop physiological data group. These data will be stored in a distributed repository to provide data support for subsequent analysis and evaluation.

[0056] (2) The tolerance analysis module of this system conducts a detailed assessment of the adaptability of crops. It calculates the crop adaptability index swx and the sewage stratified dynamic pollution index lwb using the pollutant content data group and the soil component data group respectively. These indexes help to evaluate the impact of different pollutants and the possibility of sewage reuse. By comprehensively using these data, the crop tolerance index nsx is obtained, which can effectively judge whether the sewage at a certain pollution level is suitable for reuse. When the crop tolerance index nsx is lower than the first sewage reuse threshold A, the system will judge that the sewage is not suitable for reuse; when it is between the first sewage reuse threshold A and the second sewage reuse threshold B, the sewage can be reused after treatment; if the crop tolerance index nsx is higher than the second sewage reuse threshold B, the sewage can be directly reused.

[0057] (3) The crop physiological analysis module and the comprehensive status evaluation module of this system monitor and evaluate the growth status of crops, further improving the accuracy of the system. After reusing the sewage, the crop physiological analysis is carried out. According to the obtained crop physiological data group, the crop physiological status feedback index scl is calculated by summarization. The system can real-time feedback the physiological status of crops and make adjustments when necessary. The comprehensive status evaluation module combines the crop tolerance index nsx and the physiological feedback index scl to calculate the crop return water growth status index hsz, and further analyzes the impact of sewage reuse on crop growth. If the growth of crops is affected, the system will automatically generate crop damage information and take corresponding measures, close the sewage reuse port and treat the sewage. Overall, this system effectively guarantees the safety of sewage reuse and the health of crop growth through the integration of big data analysis and real-time monitoring, and at the same time provides a scientific basis and decision-making support for the sustainable development of agriculture. Description of the Drawings

[0058] Figure 1 It is a schematic flow chart of a sewage analysis and treatment system based on big data according to the present invention;

[0059] Figure 2 It is a schematic diagram of the steps of a sewage analysis and treatment method based on big data according to the present invention;

[0060] Figure 3This is the operating principle diagram of a sewage analysis and treatment system based on big data according to the present invention;

[0061] Figure 4 This is the structural schematic diagram of a sewage analysis and treatment system based on big data according to the present invention. Specific embodiments

[0062] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0063] Embodiment 1

[0064] Please refer to Figure 1 and Figure 4 The present invention provides a sewage analysis and treatment system based on big data. To achieve the above objectives, the present invention is realized through the following technical solutions: including a sewage monitoring module, a tolerance analysis module, a crop physiological analysis module, and a comprehensive status evaluation module;

[0065] The sewage monitoring module is used to collect the component data of sewage, soil, and crops in real time based on the sensor group and instruments installed in agricultural sewage and crop soil, and construct a sewage analysis system for preprocessing to obtain a component content data group, and then store it in a distributed repository;

[0066] The tolerance analysis module is used to calculate based on the attribute data group. After obtaining the crop adaptability index swx and the sewage stratification dynamic pollution index lwb, the crop tolerance index nsx is comprehensively calculated for sewage reuse evaluation;

[0067] The crop physiological analysis module is used to calculate based on the crop physiological data group after sewage reuse to obtain the crop physiological state feedback index scl;

[0068] The comprehensive status evaluation module is used to calculate based on the crop tolerance index nsx and the crop physiological state feedback index scl to obtain the crop backwater growth state index hsz for crop growth health evaluation.

[0069] In this embodiment, the sewage monitoring module relies on a high-precision sensor group and instruments to collect the composition data of agricultural sewage, soil, and crops in real time. Compared with the traditional single data collection method, through the collaborative work of multiple sensors, this system can not only obtain more comprehensive data, but also perform data cleaning, denoising, and calibration, greatly improving the reliability of the data. This provides accurate basic data for subsequent analysis and avoids the influence of manual measurement errors. In the tolerance analysis module, the system comprehensively analyzes the pollutants in the sewage and the soil components, uses the attribute data group to summarize and calculate to obtain the crop adaptability index swx and the sewage stratified dynamic pollution index lwb, and comprehensively calculates to obtain the crop tolerance index nsx, and then evaluates the suitability of sewage reuse by comparing with the preset first sewage reuse threshold A and the second sewage reuse threshold B. Compared with traditional technologies, this system can more scientifically judge the reuse risk of sewage through accurate calculations and dynamic monitoring, and avoid the possible impact on crop health caused by inappropriate sewage reuse. In addition, the system can analyze the suitability of sewage reuse based on historical data and make timely adjustments to ensure agricultural safety during the sewage reuse process. The crop physiological analysis module and the comprehensive status evaluation module further enhance the accuracy and dynamic response ability of the system. After sewage reuse, the crop physiological state feedback index scl accurately reflects the growth state of the crop by analyzing the physiological data of the crop in real time. The comprehensive status evaluation module combines the tolerance index nsx and the physiological state feedback index scl to calculate the crop backwater growth state index hsz, providing a more targeted growth health assessment. Compared with traditional agricultural monitoring methods, this system can monitor the health status of crops in real time during the dynamic reuse process and adjust the sewage reuse strategy in a timely manner. Through the improvement of these technical means, the system significantly improves the safety and operability of sewage reuse, optimizes agricultural production efficiency, and promotes the development of sustainable agriculture.

[0070] Embodiment 2

[0071] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 and Figure 3 , specifically: The sewage monitoring module includes a data monitoring unit, a data processing unit, and a data storage unit;

[0072] The data monitoring unit is used to collect the composition data of sewage, soil, and crops in real time according to the sensor group and instruments installed in agricultural sewage and crop soil;

[0073] The sensor group includes a leaf reflectance spectrum sensor, a leaf water sensor, a temperature sensor, a soil humidity sensor, and a pH sensor;

[0074] The instruments include a gas analyzer, a multi-parameter water quality detector, a permeameter, and a stomatal conductance meter;

[0075] The leaf reflectance spectrum sensor is used to collect the chlorophyll content cc of crops;

[0076] The leaf moisture sensor is used to collect the relative water content rc of crop leaves;

[0077] The temperature sensor is used to collect the leaf temperature tl of crops;

[0078] The soil moisture sensor is used to collect the soil moisture sm;

[0079] The pH sensor is used to collect the pH value of the soil;

[0080] The gas analyzer is used to analyze volatile organic compounds and obtain the concentration wl of environmental residual pollutants;

[0081] The multi-parameter water quality detector is used to monitor the pollutant concentration cf in water in real time;

[0082] The permeameter is used to measure the soil permeability ct;

[0083] The stomatal conductance meter is used to collect the stomatal conductance gs of crops.

[0084] The data processing unit is used to construct a sewage analysis system, and establish a communication connection between the sensor group and the instrument and the sewage analysis system through wireless communication, and transmit the acquired component data to the sewage analysis system in real time for data cleaning, denoising, data correction, data time synchronization and dimensionless processing to obtain a component content data group;

[0085] The component content data group includes an attribute data group and a crop physiological data group;

[0086] The attribute data group includes a pollutant content data group and a soil component data group

[0087] The pollutant content data group includes the pollutant concentration cf and the environmental residual pollutant concentration wl;

[0088] The soil component data group includes the soil permeability ct and the soil pH;

[0089] The crop physiological data group includes the stomatal conductance gs, the chlorophyll content cc, the relative water content rc of the leaves, the leaf temperature tl and the soil moisture sm;

[0090] The data storage unit is used to construct a distributed repository based on the sewage analysis system and store the component content data group in the distributed repository in real time.

[0091] In this embodiment, the system relies on a variety of high-precision sensors to comprehensively monitor various parameters of crops and their growth environment, and can fully capture the dynamic changes of sewage and soil environment. These sensors transmit data to the sewage analysis system in real time through wireless communication to ensure the timeliness and accuracy of the data. Through the data processing unit, the system not only cleans, denoises and corrects the data, but also synchronously processes and dimensionlessly processes these data to ensure their applicability in different environments, thereby generating accurate component content data sets to facilitate subsequent analysis and decision-making. In addition, all monitoring data are stored in a distributed repository, which can effectively manage and trace historical data, and improve the long-term stability and scalability of the system. The implementation of this comprehensive solution makes agricultural sewage reuse more scientific and accurate, which can effectively ensure the healthy growth of crops and optimize the utilization efficiency of water resources.

[0092] Example 3

[0093] This embodiment is explained in Example 2. Please refer to Figure 1 and Figure 3 ,Specifically: the tolerance analysis module includes a preliminary analysis unit and a crop tolerance analysis unit;

[0094] The preliminary analysis unit is used to calculate the crop adaptability index swx and the sewage stratification dynamic pollution index lwb according to the pollutant content data group and the soil composition data group respectively, and the specific acquisition formula is as follows;

[0095]

[0096] Where N represents the total number of pollutant types, cf i represents the concentration of the i-th pollutant in sewage, T i represents the optimal absorption concentration of crops for the i-th pollutant under standard conditions, wl i represents the environmental residual concentration of the i-th pollutant, α represents the pollutant hazard adjustment factor, and ∈ represents the minimum constant to prevent the denominator from being zero;

[0097]

[0098] In the formula, cf i,0 represents the initial concentration of the i-th pollutant in the sewage, t represents the current monitoring time, t0 represents the initial time of sewage discharge, β represents the pollutant degradation rate factor, which is obtained through experiments, e represents the exponential function, λ represents the pollutant degradation attenuation factor, a1 represents the regulating factor of pollutant degradation affected by the environment, and a2 represents the regulating factor of the influence of soil pH on pollutant degradation.

[0099] The crop tolerance analysis unit includes a tolerance calculation unit and a sewage reuse assessment unit;

[0100] The tolerance calculation unit is used to perform summary calculations based on the obtained crop adaptability index swx and the sewage stratification dynamic pollution index lwb to obtain the crop tolerance index nsx;

[0101] The crop tolerance index nsx is obtained through the following formula;

[0102] nsx = bl * sWx + b2 * lwb;

[0103] In the formula, b1 and b2 respectively represent the weight factors of the crop adaptability index swx and the sewage stratification dynamic pollution index lwb, and 0 < b1 < 1, 0 < b2 < 1. The specific values are set by the user.

[0104] The sewage reuse evaluation unit is used to extract the historical component content data group in the distributed repository and calculate the mean value of the historical crop tolerance index nsx by the statistical method And preset the first sewage reuse threshold A and the second sewage reuse threshold B, specifically: Then conduct sewage reuse evaluation with the obtained crop tolerance index nsx;

[0105] When the crop tolerance index nsx < the first sewage reuse threshold A, sewage reuse is prohibited;

[0106] When the first sewage reuse threshold A ≤ the crop tolerance index nsx ≤ the second sewage reuse threshold B, the sewage needs to be treated before reuse, and at this time, crop physiological analysis is performed;

[0107] When the crop tolerance index nsx > the second sewage reuse threshold B, the sewage can be directly reused, and at this time, crop physiological analysis is performed.

[0108] In this embodiment, the tolerance analysis module significantly improves the accuracy and safety of sewage reuse through the close cooperation of the preliminary analysis unit and the crop tolerance analysis unit. The preliminary analysis unit accurately calculates the crop adaptability index swx and the sewage stratification dynamic pollution index 1wb by calculating the pollutant content data group and the soil component data group in detail, providing a scientific basis for crop tolerance evaluation. The crop tolerance index nsx is obtained through comprehensive calculation, and the historical component content data group in the distributed repository is extracted by the sewage reuse evaluation unit, and the mean value of the historical crop tolerance index nsx is calculated by the statistical method Set the first sewage reuse threshold A and the second sewage reuse threshold B to ensure different sewage treatment measures are taken under different pollution levels. The advantage of this module is that it can evaluate the feasibility of sewage reuse in real time based on actual monitoring data and make dynamic adjustments according to the tolerance of crops, avoiding the risks that may be caused by insufficient assessment of pollutant concentrations in traditional reuse methods. Through precise sewage reuse decisions, the system not only improves the safety of agricultural sewage reuse but also ensures the healthy growth of crops, promoting the realization of sustainable agricultural development.

[0109] Example 4

[0110] This example is an explanatory note based on Example 3. Please refer to Figure 1 and Figure 3 Specifically: The crop physiological analysis module is used to perform crop physiological analysis after sewage reuse;

[0111] The crop physiological analysis is used to perform summary calculations based on the obtained crop physiological data set to obtain the crop physiological state feedback index scl, which is used to analyze the physiological conditions of crops in real time after sewage reuse;

[0112] The crop physiological state feedback index scl is obtained through the following formula;

[0113]

[0114] In the formula, gs thr 、tl thr and sm thr respectively represent the standard reference values of stomatal conductance gs, leaf temperature tl, and soil moisture sm under normal growth conditions. cc max and rc max respectively represent the peak values of chlorophyll content cc and leaf relative water content rc of crops in the optimal growth state. e represents the exponential function, and c represents the temperature influence factor, which is used to control the sensitivity and response intensity of crops to temperature changes and is set according to experiments.

[0115] In this embodiment, the crop physiological analysis module accurately analyzes the growth state of crops after reusing sewage by obtaining the crop physiological data group in real time and using the crop physiological state feedback index scl. The system can evaluate the physiological responses of crops during the dynamic sewage reuse process. In particular, by introducing the temperature influence factor c and adjusting the sensitivity of crops to temperature changes according to experimental data, the adaptability and precise control ability of the system to environmental changes are enhanced. This real-time monitoring and feedback mechanism enables the system to immediately identify the physiological conditions of crops. Whether it is the impact of temperature fluctuations or water changes, it can accurately reflect and make adjustments to ensure that crops can maintain the best growth state when using sewage, significantly improving the sustainability of agricultural production and the health guarantee of crops.

[0116] Embodiment 5

[0117] This embodiment is an explanatory description carried out in Embodiment 4. Please refer to Figure 1 and Figure 3 , specifically: The comprehensive state evaluation module includes a growth state analysis unit and a growth state evaluation unit;

[0118] The growth state analysis unit is used to perform summary calculations based on the obtained crop tolerance index nsx and crop physiological state feedback index scl to obtain the crop backwater growth state index hsz, and analyze the mutual influence between sewage quality and crop physiological state;

[0119] The crop backwater growth state index hsz is obtained through the following formula;

[0120] hsz = nsx * (1 - e β*scl );

[0121] In the formula, e represents the exponential function, and β represents the control coefficient affecting the sensitivity of the crop physiological state feedback index scl, which is obtained through experiments.

[0122] The growth state evaluation unit is used to preset the crop physiological state threshold Z according to the crop growth industry standard and perform crop growth health evaluation with the obtained crop backwater growth state index hsz. The specific evaluation scheme is as follows;

[0123] When the crop backwater growth state index hsz ≤ the crop physiological state threshold Z, it means that the crop is damaged. At this time, crop damage information is generated, and the crop damage information is transmitted to relevant personnel through wireless communication to notify to close the reused sewage outlet. After the sewage is treated, iterative analysis is performed through the tolerance analysis module;

[0124] When the crop backwater growth state index hsz > the crop physiological state threshold Z, the crop grows healthily, and the sewage reuse continues and monitoring is maintained.

[0125] In this embodiment, through the close cooperation of the growth status analysis unit and the growth status evaluation unit, the comprehensive status evaluation module realizes the precise monitoring of the crop growth status and the intelligent regulation of the reclaimed water reuse. By obtaining the crop tolerance index nsx and the physiological status feedback index scl, the crop reclaimed water growth status index hsz is further calculated, and a health assessment is carried out in combination with the industry standards for crop growth. The core advantage of this process lies in its dynamic and real-time response ability. When the crop growth status is affected by pollution, the system can quickly identify and generate damaged information, automatically close the reclaimed water reuse port, ensuring the safety of agricultural production. When the crops grow well, the system can automatically continue to reuse the reclaimed water and maintain monitoring, avoiding the lag and misjudgment of manual intervention. This data-driven intelligent adjustment not only improves the effect of reclaimed water reuse, but also reduces the risk of environmental pollution, ensures the healthy growth of crops, and provides important support for the sustainable development of agriculture.

[0126] Example 6

[0127] Please refer to Figure 2 , a sewage analysis and treatment method based on big data, comprising the following steps:

[0128] S1. According to the sensor group and instruments installed in agricultural sewage and crop soil, collect the composition data of sewage, soil and crops in real time, construct a sewage analysis system for pretreatment, obtain the composition content data group, and then store it in a distributed repository;

[0129] S2. Calculate according to the attribute data group, obtain the crop adaptability index swx and the dynamic pollution index lwb of sewage stratification, and then comprehensively calculate to obtain the crop tolerance index nsx for the evaluation of reclaimed water reuse;

[0130] S3. After the reclaimed water is reused, calculate according to the crop physiological data group to obtain the crop physiological status feedback index scl;

[0131] S4. Calculate according to the crop tolerance index nsx and the crop physiological status feedback index scl to obtain the crop reclaimed water growth status index hsz for the crop growth health assessment.

[0132] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A sewage analysis and treatment system based on big data, characterized in that: It includes a sewage monitoring module, a tolerance analysis module, a crop physiological analysis module, and a comprehensive status evaluation module; The sewage monitoring module is used to collect the composition data of sewage, soil, and crops in real time based on the sensor group and instruments installed in agricultural sewage and crop soil, construct a sewage analysis system for preprocessing, obtain a composition content data group, and then store it in a distributed repository; The tolerance analysis module is used to calculate based on the attribute data group. After obtaining the crop adaptability index swx and the sewage stratified dynamic pollution index lwb, it comprehensively calculates to obtain the crop tolerance index nsx for sewage reuse evaluation; The crop physiological analysis module is used to calculate based on the crop physiological data group after sewage reuse to obtain the crop physiological status feedback index scl; The comprehensive status evaluation module is used to calculate based on the crop tolerance index nsx and the crop physiological status feedback index scl to obtain the crop backwater growth status index hsz for crop growth health evaluation.

2. The sewage analysis and treatment system based on big data according to claim 1, characterized in that: The sewage monitoring module includes a data monitoring unit, a data processing unit, and a data storage unit; The data monitoring unit is used to collect the composition data of sewage, soil, and crops in real time based on the sensor group and instruments installed in agricultural sewage and crop soil; The sensor group includes a leaf reflectance spectrum sensor, a leaf moisture sensor, a temperature sensor, a soil humidity sensor, and a pH sensor; The instruments include a gas analyzer, a multi-parameter water quality detector, a permeameter, and a stomatal conductance meter.

3. The sewage analysis and treatment system based on big data according to claim 2, characterized in that: The data processing unit is used to construct a sewage analysis system, establish a communication connection between the sensor group and instruments and the sewage analysis system through wireless communication, and transmit the obtained composition data to the sewage analysis system in real time for data cleaning, denoising, data correction, data time synchronization, and dimensionless processing to obtain a composition content data group; The composition content data group includes an attribute data group and a crop physiological data group; The attribute data group includes a pollutant content data group and a soil composition data group The pollutant content data group includes the pollutant concentration cf and the environmental residual pollutant concentration wl; The soil composition data group includes the soil permeability ct and the soil pH; The crop physiological data group includes the stomatal conductance gs, the chlorophyll content cc, the leaf relative water content rc, the leaf temperature tl, and the soil humidity sm; The data storage unit is used to construct a distributed repository based on the sewage analysis system and store the composition content data group in the distributed repository in real time.

4. The sewage analysis and treatment system based on big data according to claim 3, characterized in that: The tolerance analysis module includes a preliminary analysis unit and a crop tolerance analysis unit; The preliminary analysis unit is used to calculate respectively based on the pollutant content data group and the soil composition data group to obtain the crop adaptability index swx and the sewage stratified dynamic pollution index lwb. The specific acquisition formulas are as follows; In the formula, e represents the exponential function, N represents the total number of pollutant types, cf i represents the concentration of the i-th pollutant in sewage, T i represents the optimal absorption concentration of crops for the i-th pollutant under standard conditions, wl i represents the environmental residual concentration of the i-th pollutant, α represents the pollutant hazard adjustment factor, and ∈ represents the minimum constant to prevent the denominator from being zero; wherein, cf i，0 represents the initial concentration of the i-th pollutant in the sewage, t represents the current monitoring time, t0 represents the initial time of sewage discharge, β represents the pollutant degradation rate factor, e represents the exponential function, λ represents the pollutant degradation attenuation factor, a1 represents the adjustment factor of pollutant degradation affected by the environment, and a2 represents the adjustment factor of the influence of soil pH on pollutant degradation.

5. The sewage analysis and treatment system based on big data according to claim 4, wherein: The crop tolerance analysis unit includes a tolerance calculation unit and a sewage reuse evaluation unit; The tolerance calculation unit is used to perform a summary calculation based on the obtained crop adaptability index swx and the sewage stratified dynamic pollution index lwb to obtain the crop tolerance index nsx; The crop tolerance index nsx is obtained through the following formula; nsx = b1 * swx + b2 * lwb; In the formula, b1 and b2 respectively represent the weight factors of the crop adaptability index swx and the sewage stratification dynamic pollution index lwb, and 0 < b1 < 1, 0 < b2 < 1. The specific values are set by the user.

6. The sewage analysis and treatment system based on big data according to claim 5, wherein: The sewage reuse evaluation unit is used to extract the historical component content data set from the distributed repository, and calculate the mean value of the historical crop tolerance index nsx by the statistical method And set a preset first sewage reuse threshold A and a second sewage reuse threshold B, specifically: Then, conduct sewage reuse evaluation with the obtained crop tolerance index nsx; When the crop tolerance index nsx < the first sewage reuse threshold A, sewage reuse is prohibited; When the first sewage reuse threshold A ≤ the crop tolerance index nsx ≤ the second sewage reuse threshold B, the sewage needs to be treated before reuse, and at this time, crop physiological analysis is performed; When the crop tolerance index nsx > the second sewage reuse threshold B, the sewage can be directly reused, and at this time, crop physiological analysis is performed.

7. A sewage analysis and treatment system based on big data according to claim 6, characterized in that: The crop physiological analysis module is used to perform crop physiological analysis after sewage reuse; The crop physiological analysis is used to perform summary calculations based on the obtained crop physiological data group to obtain the crop physiological state feedback index scl, which is used to analyze the physiological conditions of crops in real time after sewage reuse; The crop physiological state feedback index scl is obtained through the following formula; where, gs thr , tl thr and sm thr represent the standard reference values of stomatal conductance gs, leaf temperature tl and soil moisture sm under normal growth conditions, respectively; cc max and rc max represent the peak values of chlorophyll content cc and relative water content rc of leaves of crops under the optimal growth state, respectively; e represents the exponential function, and c represents the temperature influence factor.

8. A sewage analysis and treatment system based on big data according to claim 7, characterized in that: The comprehensive state evaluation module includes a growth state analysis unit and a growth state evaluation unit; The growth state analysis unit is used to perform summary calculations based on the obtained crop tolerance index nsx and the crop physiological state feedback index scl to obtain the crop backwater growth state index hsz, and analyze the mutual influence between sewage quality and crop physiological state; The crop backwater growth state index hsz is obtained through the following formula; hsz = nsx * (1 - e β*scl ); In the formula, e represents the exponential function, and β represents the control coefficient of the sensitivity of the crop physiological state feedback index scl.

9. An sewage analysis and treatment system based on big data according to claim 8, characterized in that: The growth state evaluation unit is used to preset the crop physiological state threshold Z according to the crop growth industry standard, and perform crop growth health evaluation with the obtained crop backwater growth state index hsz. The specific evaluation scheme is as follows; When the crop backwater growth state index hsz ≤ the crop physiological state threshold Z, it means that the crop is damaged. At this time, crop damage information is generated, and the crop damage information is transmitted to relevant personnel, notifying to close the reused sewage outlet. After the sewage is treated, iterative analysis is performed through the tolerance analysis module; When the crop backwater growth state index hsz > the crop physiological state threshold Z, the crop grows healthily, and sewage reuse continues and monitoring is maintained.

10. A sewage analysis and treatment method based on big data, applied to a sewage analysis and treatment system based on big data according to any one of claims 1-9, characterized in that: It includes the following steps: S1. Based on the sensor group and instruments installed in agricultural sewage and crop soil, the component data of sewage, soil and crops are collected in real time, and a sewage analysis system is constructed for pretreatment to obtain the component content data group, which is then stored in the distributed repository; S2. Based on the attribute data group, calculations are performed to obtain the crop adaptability index swx and the sewage stratification dynamic pollution index lwb, and then the crop tolerance index nsx is comprehensively calculated for sewage reuse evaluation; S3. After sewage reuse, calculations are performed based on the crop physiological data group to obtain the crop physiological state feedback index scl; S4. Calculate based on the crop tolerance index nsx and the crop physiological state feedback index scl to obtain the crop backwater growth state index hsz for crop growth health assessment.

Images