Artificial Intelligence-Based Rural Black and Odorous Water Body Monitoring System and Its Early Warning Method

Abstract

The present invention provides a monitoring system for rural black and smelly water bodies based on artificial intelligence and an early warning method thereof. The system includes a housing with a cavity inside, and also includes a floating block, a telescopic detection component, a monitoring component, a micro heating component, an electric energy module and a control module; The method includes deploying the device at the water body to be monitored; constructing a BP (Back Propagation) artificial neural network model at the evaluation and early warning end, training and validating the model respectively using a training set and a validation set, and after optimization and adjustment, establishing a current situation evaluation and trend early warning model for rural black and smelly water bodies based on the BP artificial neural network; using the water body monitoring data to evaluate the current situation of the water body, predict the future change trend, and display it on the information display platform. This system is easy to operate and stable, and can realize self-measurement of water depth, self-adjustment of sampling points, self-heating and deicing in winter, and self-protection and self-cleaning of the instrument. It is used for the monitoring and early warning of rural black and smelly water bodies, and helps to improve the rural environmental supervision ability.

Description

Technical Field

[0001] The present invention belongs to the field of water body monitoring, and relates to a rural black and smelly water body monitoring system based on artificial intelligence and an early warning method thereof. Background Art

[0002] Rural black and smelly water bodies refer to water bodies within the administrative villages (communities) outside the urban built-up area or the urban development boundary with significantly abnormal colors or emitting strong (unpleasant) odors, which are one of the most prominent environmental problems strongly reflected by the rural masses at present.

[0003] Rural black and smelly water bodies are characterized by wide distribution, large quantity, large area, easy to return to black and smelly, and seasonal fluctuations. Traditional monitoring equipment and early warning methods mainly based on water body sections are difficult to meet the needs of the supervision and management of rural black and smelly water bodies.

[0004] At present, the monitoring of rural black and smelly water bodies mainly relies on artificial sampling and analysis, traditional water quality monitoring equipment, and remote sensing image recognition, etc. There are problems such as low sampling frequency, weak data processing ability, slow response speed, and difficulty in monitoring ice formation in winter, making it difficult to achieve real-time monitoring and trend prediction.

[0005] At the same time, affected by factors such as poor traffic accessibility of rural black and smelly water bodies, more silt around the water bodies, and scattered village distributions, it is not convenient for on-site artificial sampling. With the development of Internet of Things, cloud computing, big data, and artificial intelligence technologies, they have been applied in aspects such as online monitoring and intelligent early warning of rivers, lakes, and urban water bodies. However, since the treatment work of rural black and smelly water bodies is still in its infancy, there are still deficiencies in using intelligent means to carry out monitoring and early warning of rural black and smelly water bodies, facing problems such as lack of miniaturized and intelligent monitoring devices, poor stability and reliability of the monitoring system, low data processing efficiency, and the need to optimize data analysis and early warning model algorithms. Summary of the Invention

[0006] The first object of the present invention is to provide a rural black and smelly water body monitoring system based on artificial intelligence that is convenient to use and has high stability in view of the above problems existing in the prior art.

[0007] The second object of the present invention is to provide an early warning method using the above water body monitoring system.

[0008] The first object of the present invention can be achieved by the following technical solutions:

[0009] A rural black and smelly water body monitoring system based on artificial intelligence includes a housing with a cavity inside, and also includes a floating block, a telescopic detection component, a monitoring component, a micro heating component, an electric energy module, and a control module;

[0010] The above floating block is fixedly connected to the outside of the housing, and under the action of the floating block, the housing can stably float on the water surface of the water body to be monitored;

[0011] The above-mentioned micro-heating component is connected to the outside of the housing;

[0012] The above-mentioned electric energy module is fixedly connected to the upper part of the housing and the electric energy module is connected to the micro-heating component. When the electric energy module operates, the temperature of the housing can be increased through the micro-heating component;

[0013] The above-mentioned control module and monitoring component are both connected inside the housing;

[0014] The above-mentioned telescopic detection component is connected to the bottom of the housing and the telescopic detection component can sample the water body near the housing;

[0015] The above-mentioned monitoring component can monitor and analyze the sampled water body, and the water body monitoring information at the monitoring component can be sent to the controller.

[0016] In the above-mentioned rural black and smelly water body monitoring system based on artificial intelligence, the control module includes a controller, a data remote transmission unit, an evaluation and early warning unit, and an information display platform. The information data at the monitoring component can be input into the evaluation and early warning unit and the information display platform through the data remote transmission unit. The above-mentioned evaluation and early warning unit compares the received information data with the set information data. If the received information data is not within the range of the set information data, the evaluation and early warning unit makes corresponding early warning actions. The above-mentioned information display platform is used to display the real-time information data monitored at the monitoring component.

[0017] In the above-mentioned rural black and smelly water body monitoring system based on artificial intelligence, the evaluation and early warning unit is a corresponding water body monitoring early warning application program. The above-mentioned data remote transmission unit realizes the data conduction of the water body monitoring early warning application program in the way of mobile network, and the above-mentioned early warning actions can be obtained on the computer side or the mobile phone side.

[0018] In the above-mentioned rural black and smelly water body monitoring system based on artificial intelligence, the information display platform is a corresponding water body monitoring early warning application program. The above-mentioned data remote transmission unit realizes the data conduction of the water body monitoring early warning application program in the way of mobile network, and the real-time information data can be viewed on the computer side or the mobile phone side.

[0019] In the above-mentioned rural black and smelly water body monitoring system based on artificial intelligence, the monitoring component includes an ammonia nitrogen monitoring mechanism, a dissolved oxygen monitoring mechanism, and a transparency monitoring mechanism. The above-mentioned ammonia nitrogen monitoring mechanism, dissolved oxygen monitoring mechanism, and transparency monitoring mechanism all have corresponding telescopic detection components one by one.

[0020] In the above-mentioned rural black and odorous water body monitoring system based on artificial intelligence, the telescopic detection component includes a probe, a first telescopic cylinder, a second telescopic cylinder, a third telescopic cylinder and a servo motor. The probe is in the shape of a long rod. The first telescopic cylinder is sleeved on the probe. The second telescopic cylinder is sleeved on the first telescopic cylinder. The third telescopic cylinder is sleeved on the second telescopic cylinder. The servo motor is fixedly connected to the inside of the housing, and the piston rod of the servo motor is fixedly connected to the inner end of the probe.

[0021] Generally, the telescopic range of the telescopic detection component is 0 - 0.5 meters. Those skilled in the art can adjust the length of the telescopic cylinder according to the actual water body conditions (detected by sensors) to achieve an appropriate telescopic length. For example, when the water depth is greater than 0.5 meters, the telescopic length is 0.5 meters; when the water depth is less than 0.5 meters, the telescopic length is half of the water depth.

[0022] In the above-mentioned rural black and odorous water body monitoring system based on artificial intelligence, a protruding limit pin one is provided on the side of the probe. A recessed limit groove one is provided along the axial direction inside the first telescopic cylinder. The limit pin one is embedded in the limit groove one. A protruding limit pin two is provided on the outside of the first telescopic cylinder. A recessed limit groove two is provided along the axial direction on the inner side of the second telescopic cylinder. A protruding limit pin three is provided on the outside of the second telescopic cylinder. A protruding limit groove three is provided on the inner side of the third telescopic cylinder. The limit pin one is embedded in the limit groove one, the limit pin two is embedded in the limit groove two, and the limit pin three is embedded in the limit groove three.

[0023] An ice-breaking component is arranged on the outside of the detection component. The ice-breaking component includes a hollow rotating shaft sleeved on the outside of the third telescopic cylinder, and a plurality of blades fixed on the outer edge of the hollow rotating shaft. The inner side of the hollow rotating shaft and the third telescopic cylinder are connected through a ball bearing, and the outer side is engaged with a driving gear; the driving gear is connected to the output shaft of a driving motor, and the rotation of the hollow rotating shaft is realized through a gear combination method, so as to drive the blades to cut and break the ice.

[0024] In the above-mentioned rural black and odorous water body monitoring system based on artificial intelligence, the micro-heating component includes an inner heat-insulating layer and an outer electric heating layer. The inner heat-insulating layer is coated on the outside of the housing. The outer electric heating layer is coated on the outside of the inner heat-insulating layer and forms an installation cavity between the two; a plurality of water pipes are laid in the installation cavity, and the water pipes are attached to the outer electric heating layer. The outer electric heating layer heats the water in the water pipes. The water pipes are communicated with a plurality of one-way valves arranged on the outer electric heating layer. In the present invention, an air pump installed in the housing is used to inject gas into the water pipes, and a water pump installed in the housing is used to pump water from the outside of the housing and inject it into the water pipes; the water-gas mixture in the water pipes is discharged to the outside of the housing through the one-way valves, slightly disturbing the movement of the water body around the micro-disturbing device to achieve ice removal. Since the outer electric heating layer heats the water-gas mixture, the hot water flow will also efficiently remove the ice.

[0025] Preferably, a filtering component is provided at the end of the water pipe to physically filter impurities in the water body.

[0026] The external electric heating layer can be made of flexible electric heating cloth, and its heating control can be achieved through a simple temperature control switch. For example, when the water temperature is less than or equal to 5°C, the electric heating wire will be powered on. When the water temperature is greater than 5°C, the electric heating wire will be powered off.

[0027] Of course, the temperature control switch is connected to the corresponding sensor. Since the temperature detection is a prior art, this part of the content will not be elaborated in the specification.

[0028] In the above-mentioned rural black and smelly water body monitoring system based on artificial intelligence, the number of the one-way valves is several, and the several one-way valves are uniformly arranged between the air supply pipe and the water supply pipe along the height direction of the housing.

[0029] In the above-mentioned rural black and smelly water body monitoring system based on artificial intelligence, the electric energy module includes a solar photovoltaic panel and a storage battery, and the above-mentioned air pump, water pump and electric heating cloth are all electrically connected to the storage battery.

[0030] The second object of the present invention can be achieved by the following technical solutions:

[0031] A rural black and smelly water body monitoring and early warning method based on artificial intelligence specifically includes the following steps:

[0032] Step S1, deploy the device at the water body to be monitored;

[0033] Step S2, construct a BP (Back Propagation, BP) artificial neural network model at the evaluation and early warning end, use the training set and the validation set to train and validate the model respectively, and after optimization and adjustment, establish a rural black and smelly water body current situation evaluation and trend early warning model based on the BP artificial neural network;

[0034] Step S3, retrieve the water body monitoring data at the monitoring component, use the current situation evaluation and trend early warning model to evaluate the current situation of the water body, predict the future change trend, and display the current situation evaluation result, future change trend and early warning response plan in the information display platform.

[0035] Compared with the prior art, the above-mentioned rural black and smelly water body monitoring system based on artificial intelligence and its early warning method have the following advantages:

[0036] (1) The system has the characteristics of small size, fast response, simple operation and stable system, can realize real-time monitoring and trend prediction, solves the practical problems such as large quantity and wide area of rural black and smelly water bodies and difficult monitoring in winter when the water freezes, and meets the needs of rural black and smelly water body monitoring management.

[0037] (2) It can realize functions such as self - measurement of water depth, self - adjustment of sampling and monitoring points, self - heating and de - icing during winter icing periods, and self - protection and self - cleaning of monitoring instruments. The solar photovoltaic panels can provide power for each electrical device in the monitoring system, meeting the needs of monitoring black and odorous waters in remote rural areas without power grid coverage. At the same time, it also reduces the later - stage monitoring and management costs of treated black and odorous waters.

[0038] (3) By constructing an evaluation and trend prediction model of the current situation of rural black and odorous waters based on the BP artificial neural network, a method for evaluating the current situation and warning of trends of rural black and odorous waters based on artificial intelligence has been developed, promoting the application of technologies such as the Internet of Things and artificial intelligence in the monitoring and warning methods of rural black and odorous waters.

[0039] (4) The water body visualization monitoring and warning platform can realize the display of data and charts for water body status evaluation and future trend warning, and provide warning response plans in a timely manner according to different warning colors, helping relevant management departments to timely understand the situation of rural black and odorous waters, facilitating timely tracking and response. Description of the Drawings

[0040] Figure 1 It is a sectional structural schematic diagram of the rural black and odorous water body monitoring system based on artificial intelligence.

[0041] Figure 2 It is a structural schematic diagram of the telescopic detection component in the rural black and odorous water body monitoring system based on artificial intelligence.

[0042] Figure 3 It is a structural schematic diagram of the micro - heating component in the rural black and odorous water body monitoring system based on artificial intelligence.

[0043] Figure 4 It is a structural schematic diagram of the blade part in the rural black and odorous water body monitoring system based on artificial intelligence.

[0044] In the figure, 1. housing; 2. controller; 3. data remote transmission unit; 4. evaluation and warning unit; 5. information display platform; 6. ammonia nitrogen monitoring mechanism; 7. dissolved oxygen monitoring mechanism; 8. transparency monitoring mechanism; 9. probe; 9a. limit pin one; 10. telescopic cylinder one; 10a. limit groove one; 10b. limit pin two; 11. telescopic cylinder two; 11a. limit groove two; 11b. limit pin three; 12. telescopic cylinder three; 12a. limit groove three; 13. servo motor; 14. inner thermal insulation layer; 15. outer electric heating layer; 16. water pipe; 17. hollow rotating shaft; 18. one - way valve; 19. filter screen; 20. power module; 21. floating block; 22. self - cleaning component; 23. driving motor; 24. blade; 25. driving gear. Detailed Implementation Modes

[0045] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to 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. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] It should be noted that when a component is referred to as being "mounted on" another component, it can be directly mounted on the other component or there may also be an intermediate component. When a component is considered to be "disposed on" another component, it can be directly disposed on the other component or there may be an intermediate component at the same time. When a component is considered to be "fixed to" another component, it can be directly fixed to the other component or there may be an intermediate component at the same time.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used in the description of the present invention in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "or / and" used herein includes any and all combinations of one or more of the related listed items.

[0048] As Figure 1 and Figure 2 and Figure 3 and Figure 4 As shown, the rural black and odorous water body monitoring system based on artificial intelligence includes a housing 1 with a cavity inside, and also includes a floating block 21, a telescopic detection component, a monitoring component, a micro heating component, an electric energy module 20 and a control module;

[0049] The above-mentioned floating block 21 is fixedly connected to the outside of the housing 1, and under the action of the floating block 21, the housing 1 can stably float on the water surface of the water body to be monitored;

[0050] The above-mentioned micro heating component is connected to the outside of the housing 1;

[0051] The above-mentioned electric energy module is fixedly connected to the upper part of the housing 1, and the electric energy module 20 is connected to the micro heating component. When the electric energy module 20 operates, the temperature of the housing 1 can be increased through the micro heating component;

[0052] The above-mentioned control module and monitoring component are both connected inside the housing 1;

[0053] The above-mentioned telescopic detection component is connected to the bottom of the housing 1, and the telescopic detection component can sample the water body near the housing 1;

[0054] The above-mentioned monitoring component can monitor and analyze the sampled water body, and the water body monitoring information at the monitoring component can be sent to the controller 2.

[0055] The water body monitoring frequency is once a day. According to the relationship between rural black and smelly water bodies and temperature, the higher the temperature, the more serious the black and smelly phenomenon. The monitoring time is selected at the time of the highest temperature within a day. For example, the above-mentioned monitoring time is selected at 14:00.

[0056] The control module includes a controller 2, a data remote transmission unit 3, an evaluation and early warning unit 4, and an information display platform 5. The information data at the monitoring component can be input to the evaluation and early warning unit and the information display platform 5 through the data remote transmission unit. The above-mentioned evaluation and early warning unit 4 compares the received information data with the set information data. If the received information data is not within the range of the set information data, the evaluation and early warning unit 4 makes corresponding early warning actions. The above-mentioned information display platform 5 is used to display the real-time information data monitored at the monitoring component.

[0057] The evaluation and early warning unit 4 is a corresponding water body monitoring early warning application program. The above-mentioned data remote transmission unit 3 realizes the data conduction of the water body monitoring early warning application program in the way of mobile network, and the above-mentioned early warning actions can be obtained on the computer side or the mobile phone side.

[0058] The information display platform 5 is a corresponding water body monitoring early warning application program. The above-mentioned data remote transmission unit 3 realizes the data conduction of the water body monitoring early warning application program in the way of mobile network, and the real-time information data can be viewed on the computer side or the mobile phone side.

[0059] The monitoring component includes an ammonia nitrogen monitoring mechanism 6, a dissolved oxygen monitoring mechanism 7, and a transparency monitoring mechanism 8. The above-mentioned ammonia nitrogen monitoring mechanism 6, dissolved oxygen monitoring mechanism 7, and transparency monitoring mechanism 8 all have corresponding telescopic detection components one by one.

[0060] Since the ammonia nitrogen monitoring mechanism 6, the dissolved oxygen monitoring mechanism 7, and the transparency monitoring mechanism 8 are all prior arts, their structural technical features will not be described in detail in the embodiments.

[0061] The telescopic detection component includes a probe 9, a first telescopic cylinder 10, a second telescopic cylinder 11, a third telescopic cylinder 12, and a servo motor 13. The above-mentioned probe 9 is in the shape of a long rod. The above-mentioned first telescopic cylinder 10 is sleeved on the probe. The above-mentioned second telescopic cylinder 11 is sleeved on the first telescopic cylinder 9. The above-mentioned third telescopic cylinder 12 is sleeved on the second telescopic cylinder 11. The above-mentioned servo motor 13 is fixedly connected to the inside of the housing 1, and the piston rod of the servo motor 13 is fixedly connected to the inner end of the probe 9.

[0062] Generally, the telescopic range of the telescopic detection component is 0 - 0.5 meters. Those skilled in the art can adjust the length of the telescopic cylinder according to the actual water body situation (which can be detected by sensors) to achieve a suitable telescopic length. For example, when the water depth is greater than 0.5 meters, the telescopic length is 0.5 meters; when the water depth is less than 0.5 meters, the telescopic length is 1 / 2 of the water depth.

[0063] The side of the probe has a protruding limit pin 9a. Along its axial direction, there is a recessed limit groove 10a inside the first telescopic cylinder 10. The limit pin 9a is embedded in the limit groove 10a. On the outside of the first telescopic cylinder 10, there is a protruding limit pin 10b. Along its axial direction, there is a recessed limit groove 11a on the inner side of the second telescopic cylinder 11. On the outside of the second telescopic cylinder 11, there is a protruding limit pin 11b. On the inner side of the third telescopic cylinder 12, there is a protruding limit groove 12a. The limit pin 9a is embedded in the limit groove 10a, the limit pin 10b is embedded in the limit groove 11a, and the limit pin 11b is embedded in the limit groove 12a.

[0064] An ice-breaking component is arranged outside the detection component. The ice-breaking component includes a hollow rotating shaft 17 sleeved outside the third telescopic cylinder 12, and a plurality of blades 24 fixed on the outer edge of the hollow rotating shaft 17. The inner side of the hollow rotating shaft 17 and the third telescopic cylinder 12 are connected by a ball bearing, and the outer side is meshed with a driving gear 25. The driving gear 25 is connected to the output shaft of a driving motor 23, and the rotation of the hollow rotating shaft 17 is realized through a gear combination method, so as to drive the blades 24 to cut and break ice.

[0065] The micro-heating component includes an inner heat-insulating layer 14 and an outer electrothermal layer 15. The inner heat-insulating layer 14 is coated outside the housing 1, and the outer electrothermal layer 15 is coated outside the inner heat-insulating layer 14 and forms an installation cavity therebetween. A plurality of water pipes 16 are laid in the installation cavity, and the water pipes 16 are attached to the outer electrothermal layer 15. The outer electrothermal layer 15 heats the water in the water pipes 16. The water pipes 16 are communicated with a plurality of one-way valves 18 arranged on the outer electrothermal layer 15. In the present invention, an air pump installed in the housing is used to inject gas into the water pipes 16, and a water pump installed in the housing 1 is used to pump water from the outside of the housing and inject it into the water pipes. The water-gas mixture in the water pipes is discharged to the outside of the housing through the one-way valve, and the water body around the micro-disturbing device moves, realizing ice removal. Since the outer electrothermal layer heats the water-gas mixture, the hot water flow will also efficiently remove ice.

[0066] The micro-heating component covers 1 / 2 - 4 / 5 of the housing. When the system is applied to areas with relatively low average annual temperatures such as the central and western regions, a larger value is adopted for the area of the micro-heating component; when the system is applied to areas with relatively high average annual temperatures such as the eastern region, a smaller value is adopted for the area of the micro-heating component.

[0067] Preferably, a filtering component is arranged at the end of the water pipe 16 to physically filter impurities in the water body.

[0068] The outer electrothermal layer 15 can adopt a flexible electrothermal cloth, and its heating control can be realized through a simple control switch. For example, when the water body temperature is less than or equal to 5°C, the electric heating wire will be powered on. When the water body temperature is greater than 5°C, the electric heating wire will be powered off.

[0069] The one-way valves are arranged on the side wall and the bottom of the housing, and the number is 10 - 50. The ratio of the number of one-way valves on the side wall to the number of one-way valves on the bottom is 5:1. The more the number of one-way valves, the higher the micro-perturbation efficiency of the discharged water and air flow on the surrounding water body of the device, and the better the de-icing effect. When the system is applied to areas with relatively low average annual temperatures such as the central and western regions, a larger value is adopted for the number of one-way valves; when the system is applied to areas with relatively high average annual temperatures such as the eastern region, a smaller value is adopted for the number of one-way valves.

[0070] The electric energy module includes a solar photovoltaic panel and a storage battery, and the above-mentioned air pump, water pump and electric heating cloth are all electrically connected to the storage battery.

[0071] In this embodiment, self-cleaning components 22 are provided at the lower ports of the first telescopic cylinder, the second telescopic cylinder and the third telescopic cylinder, and the self-cleaning components 22 are hard brush rollers.

[0072] As another solution, it is also feasible that the self-cleaning component 22 is a spiral brush roller. Of course, according to the actual situation, it is also feasible to combine the hard brush roller with the spiral brush roller.

[0073] The rural black and smelly water body monitoring and early warning method based on artificial intelligence includes the following steps:

[0074] Step S1, deploying the device at the water body to be monitored;

[0075] Step S2, constructing a BP (Back Propagation, BP) artificial neural network model at the evaluation and early warning end, using the training set and the validation set to train and validate the model respectively, and after optimization and adjustment, establishing a rural black and smelly water body current situation evaluation and trend early warning model based on the BP artificial neural network;

[0076] Step S3, retrieving the water body monitoring data at the monitoring component, using the current situation evaluation and trend early warning model to evaluate the current situation of the water body, predict the future change trend, and display the current situation evaluation result, the future change trend and the early warning response plan in the information display platform.

[0077] The evaluation and early warning unit includes a data storage and processing end and an evaluation and early warning end, and can realize the current situation evaluation and trend early warning of the water body.

[0078] The data storage and processing end is used for data storage and pre-processing for carrying out the current situation evaluation and trend early warning of the water body. Among them, data storage includes monitoring data, historical sample data, evaluation and prediction data, etc.; data pre-processing includes content such as removing outliers (data anomalies caused by weather such as rainfall) of water body transparency, dissolved oxygen and ammonia nitrogen concentration, normal distribution test, and normalization standard processing.

[0079] The evaluation and early warning terminal is used to conduct the current situation evaluation and trend early warning of water bodies, including neural network model construction, model training and verification, current situation evaluation and trend early warning.

[0080] Neural network model construction: This model consists of three layers, namely one input layer, one hidden layer, and one output layer. Among them, the input layer contains three neurons, corresponding to three evaluation indicators: water body transparency, dissolved oxygen, and ammonia nitrogen concentration. The hidden layer is set with three neurons, and the output layer uses two neurons. That is, the topological structure of the water body current situation evaluation and trend early warning model is 3∶3∶2.

[0081] Model training and verification: Using the historical monitoring sample data (input layer) and evaluation results (output layer) of black and odorous water bodies in other surrounding rural areas, according to the principle of equal division of the number of samples, the water body historical monitoring sample data and the corresponding evaluation results are randomly divided into a training set and a verification set. Train and construct the neural network model for water body current situation evaluation to obtain the water body current situation evaluation results. Using the monitoring sample data and evaluation results of the past 30 - 60 days of the deployed monitoring system, sort them day by day in chronological order. Use the monitoring sample data and the corresponding evaluation results in the first half of the time range as the training set, and use the monitoring sample data and the corresponding evaluation results in the second half of the time range as the verification set. Train and construct the neural network model for water body trend early warning to predict the evaluation results of the water body in the next 7 - 15 days. Use the training set data to train the neural network, and adjust the model parameters through multiple iterations; use the verification set data to evaluate the model performance, and the evaluation indicators include mean square error, coefficient of determination, correlation coefficient, etc. According to the verification and evaluation results, further improve the model accuracy by adjusting the network structure (such as adjusting the number of hidden layer nodes), learning rate, number of training rounds, etc.

[0082] Current situation evaluation and trend early warning: According to the national water body quality evaluation standards and classification, use the optimized model to evaluate the current situation of water quality, predict and early warn the water quality change trend, and formulate early warning response plans.

[0083] Water body quality evaluation standards and classification: According to the national water body determination standards, and considering the actual monitoring and evaluation results of water bodies, the water body evaluation standards are divided into three categories: normal water bodies (transparency ≥ 25 cm, dissolved oxygen ≥ 2 mg / L, ammonia nitrogen ≤ 8 mg / L), slightly black and odorous water bodies (10 cm ≤ transparency < 25 cm, 0.2 mg / L ≤ dissolved oxygen < 2 mg / L, 8 mg / L < ammonia nitrogen ≤ 15 mg / L), and black and odorous water bodies (transparency < 10 cm, dissolved oxygen < 0.2 mg / L, ammonia nitrogen > 15 mg / L), corresponding to three states: green, orange, and red respectively; among them, when the water depth is less than 25 cm, the transparency index is taken as 40% of the water depth.

[0084] The current situation assessment of water bodies adopts the single-factor evaluation method, and the black and odorous type of the evaluated water body is determined by the item with the highest category among the 3 evaluation indicators. Based on the daily monitoring data provided by the rural black and odorous water body monitoring system based on artificial intelligence, relying on the current situation assessment model of water bodies based on the BP artificial neural network, the black and odorous status of the water body is evaluated.

[0085] Early warning of the water quality trend of water bodies. According to the 30-60-day monitoring data provided by the rural black and odorous water body monitoring system based on artificial intelligence, relying on the water body trend early warning model based on the BP artificial neural network, the black and odorous status of the water body in the next 7-15 days is predicted to clarify the water body status.

[0086] Response plan for water body trend early warning. For water bodies with a normal early warning result, give the water body a "green" label and establish a "long-term and stable improvement" mechanism for the water body; for water bodies with a slightly black and odorous early warning result, give the water body an "orange" label, establish a "long-term and stable improvement" mechanism, and put forward plan contents such as strengthening the daily monitoring and management of the water body, finding out the reasons for the slight black and odor, and taking necessary measures; for water bodies with a black and odorous early warning result, give the water body a "red" label, prompt the need to carry out on-site sampling and monitoring of the water body and check the early warning result, input the check result on the information display platform, if the check is correct, put forward the analysis and diagnosis of the black and odor causes, and take one or more process combination measures such as sewage interception and source control, dredging, water system connection, and ecological restoration.

[0087] The information display platform includes a visual interaction platform, mobile information applications, etc. The visual interaction platform is used to display the current situation monitoring data of the water quality at the monitoring points, the change curve of the water quality monitoring data in the past 30-60 days, the water quality monitoring prediction and early warning information in the next 7-15 days, and the response plans under different early warning scenarios. The mobile information application uses mobile network interconnection technology to display the above information on mobile phones through the water body monitoring early warning application APP.

[0088] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0089] Those of ordinary skill in the art in this technical field should recognize that the above embodiments are only used to illustrate the present invention, rather than to limit the present invention. As long as appropriate changes and variations are made to the above embodiments within the scope of the spirit of the present invention, they fall within the scope of the present invention claimed.

Claims

1. A rural black and odorous water monitoring system based on artificial intelligence, comprising a shell with a cavity inside, a floating block, a telescopic detection component, a monitoring component, a micro-heating component, an electric energy module and a control module; The floating block is fixedly connected to the outer side of the shell and can make the shell float stably on the surface of the monitored water body under the action of the floating block; The micro-heating assembly is connected to the outer side of the shell; The electric energy module is fixedly connected to the upper part of the shell and is connected to the micro-heating component. When the electric energy module is in operation, the shell temperature can be increased through the micro-heating component. The control module and monitoring assembly are both connected inside the housing; The telescopic detection assembly is connected to the bottom of the shell and can sample the water body near the shell; The above monitoring component can monitor and analyze the sampled water body, and the water body monitoring information at the monitoring component can be sent to the controller; The micro-heating assembly comprises an inner insulation layer and an outer electric heating layer, wherein the inner insulation layer is coated on the outer side of the shell, and the outer electric heating layer is coated on the outer side of the inner insulation layer to form an installation cavity between the two; a plurality of water pipes are laid in the installation cavity, and the water pipes are attached to the outer electric heating layer, and the outer electric heating layer heats the water in the water pipes, and the water pipes are connected with a plurality of one-way valves arranged on the outer electric heating layer, and an air pump installed in the shell is used to inject gas into the water pipes, and a water pump installed in the shell is used to pump water from the outer side of the shell and inject water into the water pipes; the water-gas mixture in the water pipes is discharged to the outside of the shell through the one-way valve, and the water body around the micro-disturbance device moves to achieve deicing, and since the outer electric heating layer heats the water-gas mixture, the hot water flow will also efficiently de-ice; The micro-heating component covers 1 / 2 to 4 / 5 of the shell.

2. According to the artificial intelligence-based rural black and odorous water body monitoring system according to claim 1, the control module includes a controller, a data remote transmission unit, an evaluation and early warning unit and an information display platform. The information data at the monitoring component can be input into the evaluation and early warning unit and the information display platform via the data remote transmission unit. The evaluation and early warning unit compares the received information data with the set information data. If the received information data is not within the set information data range, the evaluation and early warning unit makes a corresponding early warning action. The information display platform is used to display the real-time information data monitored by the monitoring component.

3. According to the artificial intelligence-based rural black and odorous water body monitoring system according to claim 2, the evaluation and early warning unit is a corresponding water body monitoring and early warning application, and the above-mentioned data remote transmission unit realizes the data conduction of the water body monitoring and early warning application in the form of a mobile network, and the above-mentioned early warning action can be obtained on the computer or mobile phone.

4. According to the artificial intelligence-based rural black and odorous water body monitoring system according to claim 2, the information display platform is the corresponding water body monitoring and early warning application, and the above-mentioned data remote transmission unit realizes the data conduction of the water body monitoring and early warning application in the form of a mobile network, and the real-time information data can be viewed on the computer or mobile phone.

5. According to the artificial intelligence-based rural black and odorous water body monitoring system according to claim 1, the monitoring components include an ammonia nitrogen monitoring mechanism, a dissolved oxygen monitoring mechanism and a transparency monitoring mechanism, and the ammonia nitrogen monitoring mechanism, dissolved oxygen monitoring mechanism and transparency monitoring mechanism all have telescopic detection components corresponding to them one by one.

6. According to the artificial intelligence-based rural black and odorous water body monitoring system according to claim 1, the telescopic detection assembly includes a probe, telescopic cylinder one, telescopic cylinder two, telescopic cylinder three and a servo motor, the probe is in the shape of a long rod, the telescopic cylinder is sleeved on the probe, the telescopic cylinder two is sleeved on the telescopic cylinder one, the telescopic cylinder three is sleeved on the telescopic cylinder two, the servo motor is fixedly connected in the shell and the piston rod of the servo motor is fixedly connected to the inner end of the probe.

7. According to the artificial intelligence-based rural black and odorous water body monitoring system according to claim 6, the probe side has a protruding limit pin 1, the telescopic cylinder 1 has a concave limit groove 1 along its axial direction, the limit pin 1 is embedded in one place of the limit groove, the outer side of the telescopic cylinder 1 has a protruding limit pin 2, the inner side of the telescopic cylinder 2 has a concave limit groove 2 along its axial direction, the outer side of the telescopic cylinder 2 has a protruding limit pin 3, the inner side of the telescopic cylinder 3 has a protruding limit groove 3, the limit pin 1 is embedded in the limit groove 1, the limit pin 2 is embedded in the limit groove 2, and the limit pin 3 is embedded in the limit groove 3.

8. A rural black and odorous water body monitoring and early warning method based on artificial intelligence, using the rural black and odorous water body monitoring system based on artificial intelligence as described in claim 2 for monitoring, specifically comprising the following steps: Step S1, deploying the rural black and odorous water body monitoring system based on artificial intelligence at the monitored water body; Step S2, constructing a BP (Back Propagation, BP) artificial neural network model in the assessment and early warning unit, using the training set and the verification set to train and verify the model respectively, and after optimization and adjustment, establishing a rural black and odorous water body status assessment and trend early warning model based on the BP artificial neural network; Step S3, retrieving the water body monitoring data at the monitoring component, using the status assessment and trend early warning model to assess the current status of the water body, predict future change trends, and display the current status assessment results, future change trends and early warning response plans on the information display platform.

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