A sewage detection and analysis method and system based on the Internet of Things

Abstract

The present invention discloses a sewage detection and analysis method and system based on the Internet of Things, which belongs to the field of sewage treatment technology, including a monitoring point construction module, a monitoring point parameter collection module, an equipment data collection module, an Internet of Things processing platform and a reminder module; by analyzing and processing the collected parameter information, it is judged whether the sewage treatment of each sewage treatment equipment meets the standard, and at the same time, a comprehensive analysis is performed based on the acquired equipment association information and parameter information to judge whether the operation status of each sewage treatment equipment is abnormal. In the case that the sewage treatment does not meet the standard, the present invention generates an influence coefficient based on the changes in the acquired water body temperature and the pH value of the water body, and performs a comprehensive analysis in combination with the acquired purification coefficient to judge whether the reason for the sewage treatment not meeting the standard is caused by the abnormal operation status of the sewage treatment equipment. In this way, when there is a problem with the equipment, timely feedback can be given to the management personnel to repair the equipment, thereby ensuring the sewage treatment efficiency.

Description

Technical Field

[0001] The present invention belongs to the technical field of sewage treatment, and in particular relates to a sewage detection and analysis method and system based on the Internet of Things. Background Art

[0002] Sewage treatment plants treat the generated sewage and discharge it after it is qualified, so as to reduce environmental pollution and protect human health. When sewage treatment plants treat sewage, they generally use multiple sewage treatment equipment for continuous treatment, and then finally test whether the water quality is qualified, and then discharge it after the water quality is qualified. Although this method can determine whether the sewage treatment meets the discharge standards, since the sewage treatment equipment is a continuous multiple treatment link, when the sewage treatment is unqualified, it is impossible to determine whether there is a problem in a certain sewage treatment link, and the inspectors need to check one by one, resulting in a lag in the discovery of the problem; in addition, when there is a problem with the existing sewage treatment equipment, the failure has already occurred, and the potential failure risk cannot be discovered, which will affect the effect of sewage treatment. Summary of the invention

[0003] The purpose of the present invention is to provide a sewage detection and analysis method and system based on the Internet of Things to solve the problems faced in the above-mentioned background technology.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] A sewage detection and analysis system based on the Internet of Things, the system comprising:

[0006] A monitoring point construction module, which is used to deploy water quality detectors at corresponding positions of each sewage treatment equipment according to the treatment distribution of the sewage treatment equipment, thereby constructing monitoring points;

[0007] A monitoring point parameter acquisition module, which is used to collect various parameter information detected by the water quality detector at the monitoring point;

[0008] An equipment data collection module, which is used to collect relevant information of each sewage treatment equipment in operation;

[0009] The Internet of Things processing platform is used to analyze and process the received and collected parameter information to generate a purification coefficient, and judge whether the sewage treatment of each sewage treatment equipment meets the standards according to the purification coefficient; at the same time, a comprehensive analysis is performed according to the purification coefficient and the acquired equipment-related information to judge whether the operation status of each sewage treatment equipment is abnormal;

[0010] The reminder module sends the analysis results to the management personnel to remind them to take measures to deal with the problem.

[0011] Furthermore, the associated information includes changes in water temperature and pH value of the water during the treatment process of the sewage treatment equipment.

[0012] Furthermore, the method for analyzing by the Internet of Things processing platform is:

[0013] Monitoring points are set at the water inlet and outlet of each sewage treatment equipment to obtain the pollution index W at the water inlet and outlet. in , W out ,in

[0014] By formula The purification coefficient G is obtained;

[0015] When G < 1, it means that the sewage treatment does not meet the standards;

[0016] Among them, n is the total number of water quality detection indicators, and i∈[1,n], is the content of the i-th detection index at the water inlet, is the weight coefficient of the i-th detection index at the water inlet, is the content of the i-th detection index at the outlet, is the weight coefficient of the i-th detection index at the outlet, G th is the purification threshold.

[0017] Furthermore, the method for the Internet of Things processing platform to determine whether the operation status of the sewage treatment equipment is abnormal is:

[0018] When the sewage treatment does not meet the standards, obtain the water temperature change curve T(t) and the pH value change curve PH(t) of the sewage treatment equipment during the treatment process;

[0019] By formula The influence coefficient V is obtained;

[0020] The theoretical impact value Vs is obtained by the formula Vs = f(G);

[0021] If Vs-V>V th When the sewage treatment equipment is considered to be operating abnormally;

[0022] Among them, τ1 and τ2 are proportional coefficients, t0 is the start time of the sewage treatment equipment treatment process, t1 is the end time of the sewage treatment equipment treatment process, T0(t) is the system preset standard water temperature change curve over time, PH0(t) is the system preset standard PH value change curve over time, f is the system preset conversion function, V this the reference impact value.

[0023] Furthermore, the Internet of Things processing platform is also used to analyze and judge the potential risks of the sewage treatment equipment according to the obtained purification coefficient, and the judgment method is:

[0024] Under the condition that the sewage treatment meets the standard, obtain the purification coefficient change curve G(t) of the sewage treatment equipment over time within a period Δt;

[0025] By formula Obtain the potential risk value Qz;

[0026] The obtained potential risk value Qz is compared with the system preset potential risk threshold Qz th For comparison:

[0027] When Qz>Qz th When the sewage treatment equipment is considered to have potential risks;

[0028] Among them, β1 and β2 are proportional coefficients, G xd (t) is the time-varying curve of the standard purification coefficient preset by the system, is the average risk value of the sewage treatment equipment within the period Δt, max{G i , Δt} is the maximum purification coefficient within the period Δt, min{G i , Δt} is the minimum purification coefficient within the period Δt.

[0029] Furthermore, the Internet of Things processing platform is also used to judge the sewage treatment stability of the entire sewage treatment equipment, and the judgment method is:

[0030] Obtain the purification coefficient G obtained by each sewage treatment equipment j ;

[0031] Then through the formula Find the overall fluctuation value W;

[0032] The obtained overall fluctuation value W is compared with the fluctuation threshold value W preset by the system th 1. W th 2. Compare:

[0033] When W∈(0, W th 1), the stability is considered to be good;

[0034] When W∈[W th 1.W th 2], the stability is considered to be general;

[0035] When W∈(W th 2, +∞), the stability is considered to be poor;

[0036] Where m is the total number of sewage treatment equipment, and j∈[1,m],

[0037] Furthermore, the reminder module is provided with three reminder instructions, which are respectively an alarm for unqualified sewage treatment, an alarm for abnormal sewage treatment equipment, and an early warning for abnormal sewage treatment equipment;

[0038] When G < 1, an alarm for unqualified sewage treatment is generated;

[0039] When Vs-V>V th When the abnormality alarm of sewage treatment equipment is generated;

[0040] When Qz>Qz th When an abnormal warning of sewage treatment equipment occurs, it generates

[0041] A sewage detection and analysis method based on the Internet of Things, wherein the analysis method is executed by the above-mentioned sewage detection and analysis system based on the Internet of Things.

[0042] Beneficial effects of the present invention:

[0043] The present invention sets monitoring points at the water inlet and outlet of each sewage treatment equipment, and determines whether the sewage treatment is qualified by detecting and analyzing the water quality of the water inlet and outlet. In this way, each sewage treatment equipment can be analyzed separately. When the sewage treatment does not meet the standards, it can be discovered at the first time which link of the sewage treatment has a problem, so as to prescribe the right medicine to ensure the sewage treatment efficiency.

[0044] In the case where the sewage treatment does not meet the standards, the present invention generates an influence coefficient based on the acquired changes in water temperature and pH value, and performs a comprehensive analysis in combination with the acquired purification coefficient to determine whether the reason for the sewage treatment not meeting the standards is due to an abnormal operation of the sewage treatment equipment. In this way, when problems occur in the equipment, timely feedback can be given to the management personnel to repair the equipment, thereby ensuring the sewage treatment efficiency.

[0045] The present invention can judge the potential risks of sewage treatment equipment, so as to timely discover possible problems of the equipment and handle them in time to reduce the occurrence of failures and ensure the sewage treatment efficiency.

[0046] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0048] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] In one embodiment, a sewage detection and analysis system based on the Internet of Things is disclosed, such as Figure 1 As shown, the detection and analysis system includes:

[0051] The monitoring point construction module is used to deploy water quality detectors at corresponding positions of each sewage treatment equipment according to the treatment distribution of the sewage treatment equipment, so as to construct monitoring points;

[0052] Monitoring point parameter collection module, which is used to collect various parameter information detected by the water quality detector at the monitoring point;

[0053] Equipment data collection module, the equipment data collection module is used to collect the relevant information of each sewage treatment equipment in operation, the relevant information includes the temperature change of the water body and the pH value change of the water body during the treatment process of the sewage treatment equipment;

[0054] The IoT processing platform is used to analyze and process the received parameter information to generate a purification coefficient, and judge whether the sewage treatment of each sewage treatment equipment meets the standards according to the purification coefficient; at the same time, a comprehensive analysis is conducted based on the purification coefficient and the acquired equipment-related information to judge whether the operation of each sewage treatment equipment is abnormal;

[0055] The reminder module sends the analysis results to the management personnel, reminding them to take measures to deal with the problem.

[0056] Through the above technical scheme, the present application sets monitoring points at the water inlet and outlet of each sewage treatment equipment, and determines whether the sewage treatment is qualified by detecting and analyzing the water quality of the water inlet and outlet. In this way, each sewage treatment equipment can be analyzed separately. When the sewage treatment does not meet the standards, it can be discovered at the first time which link of the sewage treatment has problems, so as to prescribe the right medicine to ensure the efficiency of sewage treatment. At the same time, when the sewage treatment does not meet the standards, the present application generates an influence coefficient based on the obtained changes in water temperature and pH value of the water body, and conducts a comprehensive analysis based on the obtained purification coefficient to determine whether the reason for the non-compliance of sewage treatment is due to abnormal operation of the sewage treatment equipment. In this way, when there is a problem with the equipment, timely feedback can be given to the management personnel to repair the equipment, thereby ensuring the efficiency of sewage treatment.

[0057] As an implementation mode of the present invention, the method for analyzing by the Internet of Things processing platform is:

[0058] Monitoring points are set at the water inlet and outlet of each sewage treatment equipment to obtain the pollution index W at the water inlet and outlet. in , W out ,in

[0059] By formula The purification coefficient G is obtained;

[0060] When G < 1, it means that the sewage treatment does not meet the standards;

[0061] Among them, n is the total number of water quality detection indicators, and i∈[1,n], is the content of the i-th detection index at the water inlet, is the weight coefficient of the i-th detection index at the water inlet, is the content of the i-th detection index at the outlet, is the weight coefficient of the i-th detection index at the outlet, G th is the purification threshold.

[0062] Through the above technical solution, this embodiment provides a specific method for the Internet of Things processing platform to determine whether the sewage treatment meets the standards. First, monitoring points are set at the water inlet and outlet of the sewage treatment equipment to obtain the pollution index W at the water inlet and outlet. in , W out ,in The pollution index of the water inlet can represent the pollution of the sewage before the sewage treatment equipment is upgraded, while the pollution index of the water outlet can represent the pollution of the sewage after the sewage treatment equipment is upgraded. Since there are many sewage detection indicators, and some detection indicators are related to each other, it is easy to have errors if only one detection indicator is analyzed. Therefore, the formula is used. as well as Comprehensive analysis of multiple detection indicators can improve the accuracy of detection and make the test results more representative. The purification coefficient G is obtained. It can be seen from the formula that the larger the pollution index between the water outlet and the water inlet, the better the sewage treatment effect. Therefore, when G < 1, it means that the difference between the pollution index between the water outlet and the water inlet is not large, which means that the sewage treatment effect is poor, and it is considered that the sewage treatment of the equipment in this link does not meet the standard. In this way, the pollution index can be obtained by comprehensive analysis based on the various detection indicators detected at the water inlet and the water outlet, and then the difference between the pollution index between the water outlet and the water inlet can be used to judge whether the sewage treatment is qualified, which can greatly improve the accuracy of the detection, make the detection results more representative, and facilitate subsequent judgments.

[0063] In the above technical solution, the weight coefficient And the purification threshold G th All of these can be determined based on the historical experience data of each sewage treatment link, so I will not elaborate on them here.

[0064] As an implementation mode of the present invention, the method for the Internet of Things processing platform to determine whether the operation status of the sewage treatment equipment is normal is:

[0065] When the sewage treatment does not meet the standards, obtain the water temperature change curve T(t) and the pH value change curve PH(t) of the sewage treatment equipment during the treatment process;

[0066] By formula The influence coefficient V is obtained;

[0067] The theoretical impact value Vs is obtained by the formula Vs = f(G);

[0068] If Vs-V>V th When the sewage treatment equipment is considered to be operating abnormally;

[0069] Among them, τ1 and τ2 are proportional coefficients, t0 is the start time of the sewage treatment equipment treatment process, t1 is the end time of the sewage treatment equipment treatment process, T0(t) is the system preset standard water temperature change curve over time, PH0(t) is the system preset standard PH value change curve over time, f is the system preset conversion function, V th is the reference impact value.

[0070] Through the above technical solution, this embodiment provides a specific method for the Internet of Things processing platform to determine whether the operation status of the sewage treatment equipment is abnormal. When the sewage treatment does not meet the standards, it may be that there is a problem with the sewage treatment equipment itself, or it may be affected by environmental factors. Therefore, in order to timely determine whether the operation status of the sewage treatment equipment is abnormal, this embodiment first obtains the water temperature change curve T(t) of the sewage treatment equipment during the treatment process, and the pH value change curve PH(t) of the water body during the treatment process, and then uses the formula The influence coefficient V is obtained, and then the theoretical influence value Vs is obtained through the formula Vs=f(G), where f is the conversion function preset by the system. The size of the influence coefficient indicates the size of the impact on sewage treatment. It can be seen from the formula that the smaller the difference between the water temperature change in the sewage treatment process and the standard water temperature change or the difference between the pH value change of the water body and the standard pH value change, the smaller the impact on sewage treatment. In other words, when the influence coefficient V is smaller, the purification coefficient G of the sewage treatment equipment should be larger. Therefore, when the sewage treatment does not meet the standards, the obtained purification coefficient is substituted into the conversion function preset by the system to obtain the theoretical influence value. When the sewage treatment does not meet the standards, that is, when G is small, its theoretical influence value should be large. In fact, the influence coefficient is small, and the gap between it and the theoretical influence value is large, which means that there is a problem with the equipment itself. Therefore, when Vs-V>V th In this way, when sewage treatment does not meet the standards, it can be directly judged whether the sewage treatment equipment is abnormal based on the impact coefficient and purification coefficient. When there is a problem with the equipment, the equipment abnormality can be discovered immediately without manual inspection, and maintenance reminders can be made, thus ensuring the efficiency of sewage treatment in a timely manner.

[0071] In the above technical solution, the standard water temperature variation curve T0(t) preset by the system and the standard pH value variation curve PH0(t) preset by the system can be formulated according to the experimental simulation data, and the proportional coefficients τ1, τ2 and the reference influence value V th It can be determined based on historical experience data, and the system preset conversion function f can be determined after analyzing historical data and experimental data, which will not be described in detail here.

[0072] As an implementation mode of the present invention, the Internet of Things processing platform is also used to analyze and judge the potential risks of the sewage treatment equipment according to the obtained purification coefficient, and the judgment method is:

[0073] When the sewage treatment meets the standards, obtain the purification coefficient change curve G(t) of the sewage treatment equipment over time within a period Δt;

[0074] By formula Obtain the potential risk value Qz;

[0075] The obtained potential risk value Qz is compared with the system preset potential risk threshold Qz th For comparison:

[0076] When Qz>Qz th When the sewage treatment equipment is considered to have potential risks;

[0077] Among them, β1 and β2 are proportional coefficients, G xd (t) is the time-varying curve of the standard purification coefficient preset by the system, is the average risk value of the sewage treatment equipment within the period Δt, max{G i , Δt} is the maximum purification coefficient within the period Δt, min{G i , Δt} is the minimum purification coefficient within the period Δt.

[0078] Through the above technical solution, this embodiment provides a method for the Internet of Things processing platform to judge the potential risks of sewage treatment equipment. Specifically, when the sewage treatment meets the standards, the purification coefficient of the sewage treatment equipment is obtained over time within a period Δt. The curve G(t) is then obtained through the formula The potential risk value Qz is obtained, the formula It can represent the cumulative change of the purification coefficient relative to the standard purification coefficient in a period of time. The larger the value, the greater the risk of the equipment. The formula represents the ratio of the difference between the maximum purification coefficient and the minimum purification coefficient to the mean value in a period of time. The larger the value, the greater the risk of the equipment. Therefore, the potential risk value Qz obtained is compared with the potential risk threshold Qz preset by the system. th For comparison: When Qz>Qz th In this way, the potential risks of sewage treatment equipment can be judged, so as to timely discover possible problems of the equipment and deal with them in time to reduce the occurrence of failures and ensure the efficiency of sewage treatment.

[0079] In the above technical solution, the time-varying curve of the standard purification coefficient preset by the system can be drawn up according to the experimental simulation data, and the proportional coefficients β1, β2 and the potential risk threshold Qz preset by the system th It can be determined based on historical experience data, so I will not go into details here.

[0080] As an implementation mode of the present invention, the Internet of Things processing platform is also used to judge the sewage treatment stability of the entire sewage treatment equipment, and the judgment method is:

[0081] Obtain the purification coefficient G obtained by each sewage treatment equipment j ;

[0082] Then through the formula Find the overall fluctuation value W;

[0083] The obtained overall fluctuation value W is compared with the fluctuation threshold value W preset by the system th 1. W th 2. Compare:

[0084] When W∈(0, W th 1), the stability is considered to be good;

[0085] When W∈[W th 1.W th 2], the stability is considered to be general;

[0086] When W∈(W th 2, +∞), the stability is considered to be poor;

[0087] Where m is the total number of sewage treatment equipment, and j∈[1,m],

[0088] Through the above technical solution, this embodiment provides a specific method for the Internet of Things processing platform to judge the sewage treatment stability of the entire sewage treatment equipment. First, the purification coefficient G obtained by each sewage treatment equipment is obtained. j , and then through the formula Calculate the overall fluctuation value W. From the formula, it can be seen that when the difference in the purification coefficients of various sewage treatment equipment is relatively small, it means that the sewage treatment stability of the entire sewage treatment equipment is better. Therefore, the overall fluctuation value W obtained is compared with the fluctuation threshold value W preset by the system. th 1. W th 2. Compare: When W∈(0, W th 1), then the stability is considered to be good. When W∈[W th 1.W th 2], the stability is considered to be general. When W∈(W th2, +∞), the stability is considered to be poor. In this way, the sewage treatment stability of the entire sewage treatment equipment can be analyzed according to the obtained purification coefficient, so as to facilitate the corresponding management of the entire sewage treatment system.

[0089] It should be noted that the fluctuation threshold W th 1. W th 2 It can be determined based on historical experience data, which will not be elaborated here.

[0090] As an embodiment of the present invention, the reminder module is provided with three reminder instructions, which are respectively an alarm for unqualified sewage treatment, an alarm for abnormal sewage treatment equipment, and an early warning for abnormal sewage treatment equipment;

[0091] When G<1, it means that the sewage treatment does not meet the standard, and an alarm of unqualified sewage treatment is generated to remind the management personnel; when Vs-V>V th When Qz>Qz, it is considered that the sewage treatment equipment is operating abnormally, and an abnormal sewage treatment equipment alarm is generated to remind the management personnel; th When the sewage treatment equipment is considered to have potential risks, an abnormal warning of the sewage treatment equipment is generated to remind the management personnel. In this way, the management personnel can handle the corresponding actions according to the different reminder instructions of the alarm, thus facilitating management and maintenance.

[0092] A sewage detection and analysis method based on the Internet of Things is executed by the above-mentioned sewage detection and analysis system based on the Internet of Things.

[0093] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A sewage detection and analysis system based on the Internet of Things, characterized in that: The system comprises: A monitoring point construction module, which is used to deploy water quality detectors at corresponding positions of each sewage treatment equipment according to the treatment distribution of the sewage treatment equipment, thereby constructing monitoring points; A monitoring point parameter acquisition module, which is used to collect various parameter information detected by the water quality detector at the monitoring point; An equipment data collection module, which is used to collect relevant information of each sewage treatment equipment during operation, and the relevant information includes changes in water temperature and pH value of the water during the treatment process of the sewage treatment equipment; The Internet of Things processing platform is used to analyze and process the received and collected parameter information to generate a purification coefficient, and judge whether the sewage treatment of each sewage treatment equipment meets the standards according to the purification coefficient; at the same time, a comprehensive analysis is performed according to the purification coefficient and the acquired equipment-related information to judge whether the operation status of each sewage treatment equipment is abnormal; A reminder module, which sends the analysis results to the management personnel to remind them to take measures to deal with the problem; The method for analyzing the IoT processing platform is as follows: monitoring points are set at the water inlet and outlet of each sewage treatment equipment to obtain the pollution index W at the water inlet and outlet. in , W out ; in, By formula The purification coefficient G is obtained; When G < 1, it means that the sewage treatment does not meet the standards; Among them, n is the total number of water quality detection indicators, and i∈[1,n], is the content of the i-th detection index at the water inlet, is the weight coefficient of the i-th detection index at the water inlet, is the content of the i-th detection index at the outlet, is the weight coefficient of the i-th detection index at the outlet, G th is the purification threshold; The method for the Internet of Things processing platform to determine whether the operation status of the sewage treatment equipment is abnormal is: When the sewage treatment does not meet the standards, obtain the water temperature change curve T(t) and the pH value change curve PH(t) of the sewage treatment equipment during the treatment process; By formula The influence coefficient V is obtained; The theoretical impact value Vs is obtained by the formula Vs = f(G); If Vs-V>V th When the sewage treatment equipment is considered to be operating abnormally; Among them, τ1 and τ2 are proportional coefficients, t0 is the start time of the sewage treatment equipment treatment process, t1 is the end time of the sewage treatment equipment treatment process, T0(t) is the system preset standard water temperature change curve over time, PH0(t) is the system preset standard PH value change curve over time, f is the system preset conversion function, V th is the reference impact value; The Internet of Things processing platform is also used to analyze and judge the potential risks of the sewage treatment equipment according to the obtained purification coefficient, and the judgment method is: Under the condition that the sewage treatment meets the standard, obtain the purification coefficient change curve G(t) of the sewage treatment equipment over time within a period Δt; By formula Obtain the potential risk value Qz; The obtained potential risk value Qz is compared with the system preset potential risk threshold Qz th For comparison: When Qz>Qz th When the sewage treatment equipment is considered to have potential risks; Among them, β1 and β2 are proportional coefficients, G xd (t) is the time-varying curve of the standard purification coefficient preset by the system, is the average risk value of the sewage treatment equipment within the period Δt, max{G i , Δt} is the maximum purification coefficient within the period Δt, min{G i , Δt} is the minimum purification coefficient within the period Δt.

2. A sewage detection and analysis system based on the Internet of Things according to claim 1, characterized in that: The Internet of Things processing platform is also used to judge the sewage treatment stability of the entire sewage treatment equipment, and the judgment method is: Obtain the purification coefficient G obtained by each sewage treatment equipment j ; Then through the formula Find the overall fluctuation value W; The obtained overall fluctuation value W is compared with the fluctuation threshold value W preset by the system th 1. W th 2. Compare: When W∈(0, W th 1), the stability is considered to be good; When W∈[W th 1.W th 2], the stability is considered to be general; When W∈(W th 2, +∞), the stability is considered to be poor; Where m is the total number of sewage treatment equipment, and j∈[1,m], 3. A sewage detection and analysis system based on the Internet of Things according to claim 2, characterized in that: The reminder module is provided with three reminder instructions, namely, sewage treatment unqualified alarm, sewage treatment equipment abnormal alarm and sewage treatment equipment abnormal warning; When G < 1, an alarm for unqualified sewage treatment is generated; When Vs-V>V th When the abnormality alarm of sewage treatment equipment is generated; When Qz>Qz th When an abnormality warning of sewage treatment equipment is generated.

4. A sewage detection and analysis method based on the Internet of Things, characterized in that: The analysis method is performed by the sewage detection and analysis system based on the Internet of Things as described in any one of claims 1-3.

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