Intelligent treatment method and system based on wastewater monitoring

Abstract

The invention relates to the technical field of data management, in particular to an intelligent treatment method and system based on wastewater monitoring. An intelligent treatment method based on waste water monitoring comprises the following steps that S1, historical area data of a target area and a surrounding area are obtained, and according to the historical area data, an assisted treatment area with the capacity of assisting the target area in treating waste water is recognized; s2, adjusting the amount of active sludge returned from the secondary sedimentation tank to the exposure tank in the assisted treatment area in advance according to the capacity of the assisted treatment area for treating the wastewater in the target area; and S3, scheduling and managing the wastewater exceeding the target area treatment capacity according to the target area wastewater treatment capacity of each assistant treatment area. According to the method, historical wastewater treatment data, microbial population data and microbial treatment data are combined, and the wastewater treatment capacity of each surrounding area is accurately calculated by adopting a comprehensive evaluation formula, so that the most suitable assisted treatment area is selected.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to an intelligent processing method and system based on wastewater monitoring. Background Art

[0002] With the advancement of industrialization and urbanization, wastewater treatment has become an important task in environmental protection. Existing wastewater treatment technologies mainly include physical, chemical and biological treatment methods. Among them, biological treatment methods are widely used due to their high efficiency, environmental protection and economy. In particular, the use of microbial communities for wastewater treatment has become one of the mainstream technologies.

[0003] However, there are several major problems in actual application: inflexible wastewater scheduling and management: many current wastewater treatment systems lack an effective scheduling mechanism for wastewater that exceeds their treatment capacity, which is prone to uneven treatment or overload; unreasonable wastewater scheduling and management: many current wastewater treatment systems are prone to sending wastewater to unreasonable surrounding areas, reducing the speed and progress of wastewater treatment and wasting a lot of money; untimely treatment of surrounding areas: when wastewater is dispatched to surrounding areas, the wastewater treatment strategy needs to be temporarily adjusted, which reduces the efficiency of wastewater treatment. Summary of the invention

[0004] In order to overcome the shortcoming that wastewater treatment is difficult to flexibly assist in wastewater treatment through surrounding areas, the present invention provides an intelligent treatment method and system based on wastewater monitoring.

[0005] The technical solution is as follows: An intelligent treatment method based on wastewater monitoring includes the following steps:

[0006] S1: Acquire historical regional data of a target area and surrounding areas, and identify assisting treatment areas capable of assisting the target area in treating wastewater based on the historical regional data;

[0007] S2: Based on the assisted treatment area's capacity to treat wastewater from the target area, the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank in the assisted treatment area is adjusted in advance;

[0008] S3: Based on the capacity of each assisting treatment area to treat the wastewater in the target area, dispatch and manage the wastewater that exceeds the treatment capacity of the target area.

[0009] Preferably, obtaining historical area data of the target area and its surrounding areas, and identifying an assisting treatment area capable of assisting the target area in wastewater treatment based on the historical area data includes: the historical area data includes historical wastewater treatment data, microbial population data, and microbial treatment data of the target area and its surrounding areas, obtaining an evaluation value of the surrounding areas using a comprehensive evaluation formula, and taking the areas with evaluation values greater than a first preset threshold as the assisting treatment areas, where the microbial treatment data is used to obtain the simplicity of restoring the microbial population to the original microbial population in the corresponding surrounding areas.

[0010] Preferably, obtaining an evaluation value of the surrounding areas using a comprehensive evaluation formula and taking the areas with evaluation values greater than a first preset threshold as the assisting treatment areas includes: where the comprehensive evaluation formula is:

[0011] W = α1 * e P + α2 * (e―1) T + α3 * ln(y + 1);

[0012] In the formula, W is the evaluation value of the surrounding areas; α1, α2, and α3 are adjustment coefficients; P is the ability of the surrounding areas to treat the wastewater of the target area; T is the matching degree of the microbial population characteristics between the surrounding areas and the target area; y is the simplicity of restoring the microbial population to the original microbial population in the corresponding surrounding areas.

[0013] Preferably, the ability of the surrounding areas to treat the wastewater of the target area includes: obtaining wastewater data of a preset historical period in the surrounding areas through the historical wastewater treatment data and inputting it into the treatment capacity evaluation formula to obtain the ability of each surrounding area to treat the wastewater of the target area, where the treatment capacity evaluation formula is:

[0014]

[0015] In the formula, P is the ability of the surrounding areas to treat the wastewater of the target area; N is the preset historical period; n is a year in the historical period of the surrounding areas; r is a day in the nth year of the surrounding areas; R is the preset number of days, ε0 is the standard wastewater treatment capacity corresponding to the rth day in the surrounding areas; ε r is the wastewater treatment volume of the rth day in the surrounding areas; β n is the weight adjustment coefficient of the nth year in the historical period of the surrounding areas.

[0016] Preferably, the matching degree of the microbial population characteristics between the surrounding areas and the target area includes: respectively obtaining the microbial species richness data of the target area and the surrounding areas and inputting it into the similarity analysis formula to obtain the matching degree of the microbial population characteristics between the surrounding areas and the target area, where the similarity analysis formula is:

[0017]

[0018] In the formula, T is the matching degree of the microbial community characteristics between the surrounding area and the target area; A i is the richness of the microbial community in the target area in the i-th microbial species; B i is the richness of the microbial community in the surrounding area in the i-th microbial species.

[0019] Preferably, adjusting in advance the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank in the assistance treatment area according to the wastewater treatment capacity of the target area in the assistance treatment area includes: obtaining the sedimentation velocity of sludge particles, the radius of sludge particles, the density of sludge particles, the density of the liquid, and the viscosity data of the liquid in the secondary sedimentation tank of the assistance treatment area, and using Stokes' law to obtain the sedimentation velocity of the sludge particles; according to the sedimentation velocity and the wastewater treatment capacity of the target area in the assistance treatment area, using the return amount adjustment formula to obtain the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank.

[0020] Preferably, obtaining the sedimentation velocity of sludge particles, the radius of sludge particles, the density of sludge particles, the density of the liquid, and the viscosity data of the liquid in the secondary sedimentation tank of the assistance treatment area, and using Stokes' law to obtain the sedimentation velocity of the sludge particles includes: where Stokes' law is:

[0021]

[0022] In the formula, S settling is the sedimentation velocity of the sludge particles; k is the radius of the sludge particles; L particle is the density of the sludge particles; L fluid is the density of the liquid; g is the acceleration due to gravity; σ is the viscosity data of the liquid.

[0023] Preferably, according to the sedimentation velocity and the wastewater treatment capacity of the target area in the assistance treatment area, using the return amount adjustment formula to obtain the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank includes: where the return amount adjustment formula is:

[0024]

[0025] In the formula, V return is the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank; μ is the adjustment coefficient; S0 is the preset standard sedimentation efficiency; S settling is the sedimentation velocity of the sludge particles.

[0026] Preferably, scheduling and managing the wastewater that exceeds the treatment capacity of the target area according to the treatment capacity of each assisted treatment area for the wastewater in the target area of treatment, includes: obtaining the evaluation values of each assisted treatment area, obtaining the assisted treatment sequence in the order from large to small according to the evaluation values, and allocating the wastewater volume according to the assisted treatment sequence and the treatment capacity of the wastewater in the target area of treatment corresponding to each assisted treatment area in the assisted treatment sequence.

[0027] Preferably, an intelligent treatment system based on wastewater monitoring further includes:

[0028] A data acquisition module, configured to collect historical wastewater treatment data, microbial population data, and microbial treatment data of the target area and the surrounding areas;

[0029] An assisted treatment area selection module, configured to select a suitable assisted treatment area according to a comprehensive evaluation formula;

[0030] A treatment capacity acquisition module, configured to obtain the treatment capacity of the wastewater in the target area of treatment for each surrounding area through a treatment capacity evaluation formula;

[0031] A microbial population matching degree calculation module, configured to calculate the similarity of the microbial species richness data through a similarity analysis formula to determine the adaptability of the microbial population;

[0032] A sludge return volume adjustment module, according to Stokes' law and the wastewater treatment capacity, uses a return volume adjustment formula to adjust the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank in the assisted treatment area;

[0033] A wastewater scheduling and management module, configured to schedule and manage the wastewater that exceeds the treatment capacity of the target area according to the treatment capacity of the wastewater in the target area of treatment for each assisted treatment area.

[0034] Advantages of the present invention:

[0035] 1. By combining historical wastewater treatment data, microbial population data, and microbial treatment data, the present invention accurately calculates the wastewater treatment capacity of each surrounding area by using a comprehensive evaluation formula, so as to select the most suitable assisted treatment area; this comprehensive evaluation method is more scientific and comprehensive than the traditional single wastewater volume evaluation, improving the accuracy and efficiency of wastewater treatment;

[0036] 2. By introducing the analysis of the microbial population matching degree, the present invention considers the similarity of the microbial population characteristics between the target area and the assisted area, effectively improving the adaptability and stability of wastewater treatment; compared with the traditional technology, it can better adapt to the treatment conditions of each area and optimize resource utilization;

[0037] 3. The present invention calculates the sedimentation velocity of sludge particles through Stokes' law, and dynamically adjusts the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank in combination with the wastewater treatment capacity of the assistance treatment area. This adjustment method can accurately control the amount of sludge according to the actual situation, and can adjust in advance the amount of sludge returned from the secondary sedimentation tank in the surrounding area, avoiding the problems of inaccurate and untimely adjustment of the sludge return amount in the traditional method.

[0038] 4. The present invention uses an intelligent scheduling management method for wastewater distribution to ensure that wastewater can be reasonably distributed to each treatment area, thereby reducing the problems of uneven or overloaded wastewater treatment load. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flow chart of an intelligent treatment method based on wastewater monitoring according to the present invention;

[0040] Figure 2 It is a system diagram of an intelligent treatment system based on wastewater monitoring according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] Referring to the embodiments herein means that the specific features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0042] Embodiment 1: An intelligent treatment method based on wastewater monitoring, as Figure 1 and Figure 2 shown, includes the following steps:

[0043] S1: Obtain the historical area data of the target area and the surrounding areas, and identify the assistance treatment areas with the ability to assist the target area in treating wastewater according to the historical area data;

[0044] The historical area data includes the historical wastewater treatment data, microbial population data, and microbial treatment data of the target area and the surrounding areas. The evaluation value of the surrounding areas is obtained using a comprehensive evaluation formula, and the areas with an evaluation value greater than the first preset threshold are used as the assistance treatment areas. The microbial treatment data is used to obtain the simplicity of restoring the microbial population to the original microbial population in the corresponding surrounding area.

[0045] It should be noted that, first of all, the system will collect and store historical area data of the target area and its adjacent surrounding areas, including historical wastewater treatment data: recording the wastewater treatment capacity and treatment effect of the target area and its surrounding areas in different time periods, and these data include the daily wastewater treatment volume, pollutant concentration, and treatment methods in the preset historical years; microbial population data: including information on the types, quantities, and activities of microbial populations in the target area and its surrounding areas, and through the above data, the system helps to understand the microbial community characteristics of each area, and further evaluate its potential contribution to wastewater treatment; microbial treatment data: mainly refers to the role played by microbial populations in wastewater treatment, such as the efficiency of microbial degradation of pollutants, the adaptability of microorganisms under different wastewater components, and the competition relationship among various microorganisms. Through the efficiency of microbial degradation of pollutants, the adaptability of microorganisms under different wastewater components, and the competition relationship among various microorganisms, the system helps to understand the treatment effect of microbial populations on different types of wastewater, so as to provide a basis for the subsequent selection of assisted treatment areas; and obtain the simplicity degree when treating the wastewater of the target area, and the simplicity degree is determined by the number of microbial species added or reduced to the wastewater of the corresponding surrounding area when restoring the microbial population to the original microbial population of the corresponding surrounding area. When the number of added or reduced microbial species is less, the simplicity degree is higher.

[0046] Among them, the comprehensive evaluation formula is:

[0047] W = α1*e P +α2*(e―1) T +α3*ln(y + 1);

[0048] In the formula, W is the evaluation value of the surrounding area; α1, α2, and α3 are adjustment coefficients; P is the ability of the surrounding area to treat the wastewater of the target area; T is the matching degree of the microbial population characteristics between the surrounding area and the target area; y is the simplicity degree of restoring the microbial population to the original microbial population of the corresponding surrounding area.

[0049] It should be noted that W is the evaluation value of the surrounding area, which measures whether the area is suitable for assisting in treating the wastewater of the target area; P is the ability of the surrounding area to treat the wastewater of the target area, which is calculated through historical wastewater treatment data, specifically the total ability of the surrounding area to treat the wastewater of the target area in the past preset time; T is the matching degree of the microbial population characteristics between the surrounding area and the target area; that is, by comparing the microbial species and quantities of the two areas, the similarity of their wastewater treatment is judged, so as to judge whether it can efficiently treat the wastewater of the target area without destroying the original microbial species; y is the simplicity degree of restoring the microbial population to the original microbial population of the corresponding surrounding area;

[0050] Based on the historical wastewater treatment data, obtain the wastewater data of the surrounding areas for a preset historical period, and input it into the treatment capacity evaluation formula to obtain the capacity of each surrounding area to treat the wastewater in the target area. The treatment capacity evaluation formula is as follows:

[0051]

[0052] In the formula, P is the capacity of the surrounding area to treat the wastewater in the target area; N is the preset historical period; n is one year in the historical period of the surrounding area; r is a day in the nth year of the surrounding area; R is the preset number of days, ε0 is the standard wastewater treatment capacity corresponding to the rth day in the surrounding area; ε r is the wastewater treatment volume on the rth day in the surrounding area; β n is the weight adjustment coefficient for the nth year in the historical period of the surrounding area.

[0053] It should be noted that the system first collects the wastewater treatment data of the surrounding areas within a preset historical period (such as the past three years). These data include the wastewater treatment capacity and actual treatment volume information for each day of each year. Among them, P is the capacity of the surrounding area to treat the wastewater in the target area, and a higher value indicates a stronger ability of the area to treat wastewater, which is suitable for assisting in the wastewater treatment of the target area; N is the preset historical period, such as the past three years, which is used to reflect the long-term treatment capacity of the surrounding area; n is one year in the historical period of the surrounding area, such as the first, second, or third year in the past; R is the preset number of days, which is the preset number of days interval; ε0 is the standard wastewater treatment capacity corresponding to the rth day in the surrounding area, usually referring to the maximum treatment capacity of the area on that day and in that year under normal conditions; ε r is the wastewater treatment volume on the rth day in the surrounding area, which records the wastewater treatment capacity in the actual operation of the area on the rth day; β n is the weight adjustment coefficient for the nth year in the historical period of the surrounding area, which reflects the difference in the importance of the data for each year. An example above is: N is 3 years, R is 10 days, r day is the 100th day, r + R is the 110th day, then sum up the capacity of the surrounding area to treat the wastewater in the target area from the 100th day to the 110th day. Through the weight adjustment of β n for each year, avoid the error caused by increasing or adjusting the treatment capacity of the surrounding area. Finally, what is obtained is the total amount of wastewater that can assist in treating the target area from the 100th day to the 110th day after weighted averaging for the past 3 years; by calculating the total amount of wastewater in the 100th to 110th days of the area's history on the 99th day, judge the capacity of the area to treat the wastewater in the target area during this future period.

[0054] Respectively obtain the microbial species richness data of the target area and the surrounding areas, and input it into the similarity analysis formula to obtain the matching degree of the microbial population characteristics between the surrounding area and the target area. The similarity analysis formula is as follows:

[0055]

[0056] Wherein, T is the matching degree of the microbial community characteristics between the surrounding area and the target area; A i is the richness of the microbial community in the target area for the i-th microbial species; B i is the richness of the microbial community in the surrounding area for the i-th microbial species.

[0057] It should be noted that T is the matching degree of the microbial community characteristics between the surrounding area and the target area; A i is the richness of the microbial community in the target area for the i-th microbial species, representing the quantity of this microbial species in the target area; B i is the richness of the microbial community in the surrounding area for the i-th microbial species, representing the quantity of this microbial species in the surrounding area; if the microbial species richness in the target area and the surrounding area is closer, it indicates that the microbial community characteristics of the two are more similar, and they can better cooperate in wastewater treatment.

[0058] S2: According to the ability of the assisting treatment area to treat the wastewater in the treatment target area, adjust in advance the amount of activated sludge returned from the secondary sedimentation tank to the aeration tank in the assisting treatment area;

[0059] Obtain the sedimentation velocity, radius of the sludge particles, density of the sludge particles, density of the liquid, and liquid viscosity data of the sludge particles in the secondary sedimentation tank of the assisting treatment area, and use Stokes' law to obtain the sedimentation velocity of the sludge particles; according to the sedimentation velocity and the ability of the assisting treatment area to treat the wastewater in the treatment target area, use the return amount adjustment formula to obtain the amount of activated sludge returned from the secondary sedimentation tank to the aeration tank.

[0060] It should be noted that for the wastewater treatment ability of the assisting treatment area, adjust in advance the amount of activated sludge returned from the secondary sedimentation tank to the aeration tank, so that when the wastewater in the target area reaches this area, it can be directly treated to accelerate the wastewater treatment process.

[0061] Among them, Stokes' law is:

[0062]

[0063] In the formula, S settling is the sedimentation velocity of the sludge particles; k is the radius of the sludge particles; L particle is the density of the sludge particles; L fluid is the density of the liquid; g is the acceleration due to gravity; σ is the liquid viscosity data.

[0064] It should be noted that S settlingis the sedimentation velocity of the sludge particles, representing the sinking velocity of the sludge particles in the liquid; k is the radius of the sludge particles, which affects the sedimentation velocity; L particle is the density of the sludge particles, which affects the sedimentation acceleration during the sedimentation process; L fluid is the density of the liquid, which affects the relative motion between the particles and the liquid.

[0065] Among them, the return amount adjustment formula is:

[0066]

[0067] In the formula, V return is the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank; μ is the adjustment coefficient; S0 is the preset standard sedimentation efficiency; S settling is the sedimentation velocity of the sludge particles.

[0068] It should be noted that the return amount adjustment formula is used to calculate the amount of activated sludge that needs to be returned to the exposure tank. Among them, V return is the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank, and this amount needs to be dynamically adjusted according to the treatment requirements of the wastewater in the target area and the sedimentation velocity in the assistance area; S0 is the preset standard sedimentation efficiency, and S settling is the sedimentation velocity of the sludge particles, which is the actual sedimentation velocity calculated according to Stokes' law; The daily average ability to treat the wastewater in the target area is obtained through the above formula, making the adjustment accurate, ensuring that the activated sludge in the wastewater treatment process is always in the optimal state, thereby improving the overall wastewater treatment efficiency.

[0069] S3: According to the ability of each assistance treatment area to treat the wastewater in the target area, schedule and manage the wastewater that exceeds the treatment capacity of the target area.

[0070] Obtain the evaluation values of each assistance treatment area, obtain the assistance treatment sequence in the order from large to small according to the evaluation values, and allocate the wastewater volume according to the assistance treatment sequence and the ability of each assistance treatment area corresponding to the assistance treatment sequence to treat the wastewater in the target area.

[0071] It should be noted that each assistance treatment area is sorted according to its evaluation value, from the area with the largest evaluation value to the area with the smallest evaluation value; areas with large evaluation values usually mean that they have high treatment capacity or high wastewater treatment efficiency and can better bear the wastewater beyond the treatment capacity of the target area; after determining the treatment sequence of the assistance treatment areas, the system will reasonably allocate the wastewater beyond the treatment capacity of the target area according to the wastewater treatment capacity of each area. For example, the allocation ratio: each assistance treatment area determines the allocated wastewater volume according to the ratio of its evaluation value and wastewater treatment capacity; sequential allocation, that is, allocation in sequence, so that the wastewater is allocated and completed within the first few collaborative treatment areas; by introducing the evaluation and priority sorting mechanism of wastewater treatment capacity, the problem of how to reasonably allocate the wastewater beyond the treatment capacity of the target area is effectively solved.

[0072] Embodiment 2: On the basis of Embodiment 1, an intelligent treatment system based on wastewater monitoring includes:

[0073] A data acquisition module, configured to collect historical wastewater treatment data, microbial population data, and microbial treatment data of the target area and surrounding areas;

[0074] An assistance treatment area selection module, configured to select a suitable assistance treatment area according to a comprehensive evaluation formula;

[0075] A treatment capacity acquisition module, configured to obtain the capacity of each surrounding area to treat the wastewater of the target area through a treatment capacity evaluation formula;

[0076] A microbial population matching degree calculation module, configured to calculate the similarity of microbial species richness data through a similarity analysis formula to determine the adaptability of the microbial population;

[0077] A sludge return volume adjustment module, which adjusts the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank in the assistance treatment area according to Stokes' law and wastewater treatment capacity using a return volume adjustment formula;

[0078] A wastewater scheduling management module, configured to perform scheduling management on the wastewater beyond the treatment capacity of the target area according to the capacity of each assistance treatment area to treat the wastewater of the target area.

[0079] The above are only examples of the present invention and are not intended to limit the present invention. All equivalent replacements made within the principle of the present invention shall be included within the protection scope of the present invention. The content not elaborated in detail in the present invention belongs to the prior art well-known to those skilled in the art.

Claims

1. An intelligent treatment method based on wastewater monitoring, characterized in that, It includes the following steps: S1: Obtain the historical area data of the target area and the surrounding areas, and identify the assisted treatment areas with the ability to assist the target area in treating wastewater based on the historical area data; S2: Adjust in advance the amount of activated sludge returned from the secondary sedimentation tank to the aeration tank in the assisted treatment areas according to the ability of the assisted treatment areas to treat the wastewater of the target area; S3: Conduct scheduling management on the wastewater exceeding the treatment capacity of the target area according to the ability of each assisted treatment area to treat the wastewater of the target area.

2. The intelligent processing method based on wastewater monitoring according to claim 1, wherein The obtaining of the historical area data of the target area and the surrounding areas, and the identification of the assisted treatment areas with the ability to assist the target area in treating wastewater based on the historical area data include: The historical area data includes the historical wastewater treatment data, microbial population data, and microbial treatment data of the target area and the surrounding areas. The evaluation value of the surrounding areas is obtained using a comprehensive evaluation formula, and the areas with an evaluation value greater than the first preset threshold are used as the assisted treatment areas. The microbial treatment data is used to obtain the simplicity of restoring the microbial population to the original microbial population in the corresponding surrounding areas.

3. An intelligent processing method based on wastewater monitoring according to claim 2, characterized in that, The obtaining of the evaluation value of the surrounding areas using the comprehensive evaluation formula and using the areas with an evaluation value greater than the first preset threshold as the assisted treatment areas includes: The comprehensive evaluation formula is: W = α1*e P + α2*(e – 1) T + α3*ln(y + 1); In the formula, W is the evaluation value of the surrounding areas; α1, α2, α3 are adjustment coefficients; P is the ability of the surrounding areas to treat the wastewater of the target area; T is the matching degree of the microbial population characteristics between the surrounding areas and the target area; y is the simplicity of restoring the microbial population to the original microbial population in the corresponding surrounding areas.

4. An intelligent processing method based on wastewater monitoring according to claim 3, characterized in that, The ability of the surrounding areas to treat the wastewater of the target area includes: Through the historical wastewater treatment data, obtain the wastewater data of a preset historical period in the surrounding areas and input it into the treatment capacity evaluation formula to obtain the ability of each surrounding area to treat the wastewater of the target area. The treatment capacity evaluation formula is: Wherein, P is the capacity of the surrounding area to treat the wastewater in the target area; N is the preset historical period; n is one year in the historical period of the surrounding area; r is one day in the nth year of the surrounding area; R is the preset number of days, ε0 is the standard wastewater treatment capacity corresponding to the rth day in the surrounding area; ε r is the wastewater treatment volume on the rth day in the surrounding area; β n is the weight adjustment coefficient in the nth year of the historical period of the surrounding area.

5. The intelligent processing method based on wastewater monitoring according to claim 3, wherein, The matching degree of the microbial population characteristics between the surrounding areas and the target area includes: Respectively obtain the microbial species richness data of the target area and the surrounding areas and input it into the similarity analysis formula to obtain the matching degree of the microbial population characteristics between the surrounding areas and the target area. The similarity analysis formula is: Where T is the matching degree of the microbial community characteristics between the surrounding area and the target area; A i is the richness of the microbial community in the target area for the i-th microbial species; B i is the richness of the microbial community in the surrounding area for the i-th microbial species.

6. The intelligent processing method based on wastewater monitoring according to claim 1, wherein The adjusting in advance the amount of activated sludge returned from the secondary sedimentation tank to the aeration tank in the assisted treatment areas according to the ability of the assisted treatment areas to treat the wastewater of the target area includes: Obtain the sedimentation velocity of the sludge particles, the radius of the sludge particles, the density of the sludge particles, the density of the liquid, and the viscosity data of the liquid in the secondary sedimentation tank of the assisted treatment areas, and use Stokes' law to obtain the sedimentation velocity of the sludge particles; According to the sedimentation velocity and the ability of the assisted treatment areas to treat the wastewater of the target area, use the return amount adjustment formula to obtain the amount of activated sludge returned from the secondary sedimentation tank to the aeration tank.

7. An intelligent processing method based on wastewater monitoring according to claim 6, characterized in that The obtaining of the sedimentation velocity of the sludge particles, the radius of the sludge particles, the density of the sludge particles, the density of the liquid, and the viscosity data of the liquid in the secondary sedimentation tank of the assisted treatment areas and using Stokes' law to obtain the sedimentation velocity of the sludge particles includes: Stokes' law is: Where S settling is the sedimentation velocity of the silt particles; k is the radius of the silt particles; L particle is the density of the silt particles; L fluid is the density of the liquid; g is the acceleration due to gravity; σ is the viscosity data of the liquid.

8. An intelligent processing method based on wastewater monitoring according to claim 7, characterized in that, According to the sedimentation rate and the ability of the assisted treatment area to treat the wastewater in the treatment target area, the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank is obtained using the return amount adjustment formula, including: The return amount adjustment formula is as follows: Where, V return is the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank; μ is the adjustment coefficient; S0 is the preset standard sedimentation efficiency; S settling is the sedimentation velocity of sludge particles.

9. An intelligent processing method based on wastewater monitoring according to claim 1, characterized in that, According to the ability of each assisted treatment area to treat the wastewater in the treatment target area, the wastewater exceeding the treatment capacity of the target area is scheduled and managed, including: obtaining the evaluation values of each assisted treatment area, obtaining the assisted treatment sequence in the order from largest to smallest evaluation value, and allocating the wastewater volume according to the assisted treatment sequence and the ability of each assisted treatment area corresponding to the assisted treatment sequence to treat the wastewater in the treatment target area.

10. An intelligent treatment system based on wastewater monitoring, according to any one of claims 1-9, an intelligent treatment method based on wastewater monitoring, characterized in that, Including: A data acquisition module for collecting historical wastewater treatment data, microbial population data, and microbial treatment data of the target area and the surrounding areas; An assisted treatment area selection module for selecting a suitable assisted treatment area according to the comprehensive evaluation formula; A treatment capacity acquisition module for obtaining the ability of each surrounding area to treat the wastewater in the treatment target area through the treatment capacity evaluation formula; A microbial population matching degree calculation module for calculating the similarity of the microbial species richness data through the similarity analysis formula to determine the adaptability of the microbial population; A sludge return amount adjustment module for adjusting the amount of activated sludge returned from the secondary sedimentation tank to the exposure tank in the assisted treatment area using the return amount adjustment formula according to Stokes' law and the wastewater treatment capacity; A wastewater scheduling management module for scheduling and managing the wastewater exceeding the treatment capacity of the target area according to the ability of each assisted treatment area to treat the wastewater in the treatment target area.

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