Rural black and odorous water body monitoring system based on artificial intelligence and early warning method thereof

Abstract

The invention provides a rural black and odorous water body monitoring system based on artificial intelligence and an early warning method thereof, and the system comprises a shell with an inner cavity, and also comprises a floating block, a telescopic detection assembly, a monitoring assembly, a micro heating assembly, an electric energy module and a control module; the method comprises the following steps: arranging the device at a monitored water body; a BP (Back Propagat ion, BP) artificial neural network model is constructed at an evaluation and early warning end, the model is trained and verified by using a training set and a verification set, and after optimization and adjustment, a rural black and odorous water current situation evaluation and trend early warning model based on the BP artificial neural network is established; the water monitoring data are utilized to evaluate the current situation of the water, predict the future change trend and display the future change trend on the information display platform. The system is easy and convenient to operate and stable, water depth self-measurement, sampling point position self-adjustment, self-heating deicing in winter and instrument self-protection and self-cleaning can be achieved, the system is used for monitoring and early warning of rural black and odorous water, and the rural environment supervision capacity is improved.

Description

Technical Field

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

[0002] Rural black and smelly water bodies are water bodies with obviously abnormal colors or strong (unpleasant) odors within administrative villages (communities) outside urban built-up areas or urban development boundaries. They are one of the most prominent environmental problems that people in rural areas currently reflect strongly.

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

[0004] At present, the monitoring of black and odorous water bodies in rural areas mainly relies on manual 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 capability, slow response speed, and difficulty in monitoring winter ice, making it difficult to achieve real-time monitoring and trend prediction.

[0005] At the same time, due to factors such as poor accessibility to rural black and odorous water bodies, more silt around the water bodies, and scattered distribution of villages, it is not convenient to conduct manual on-site sampling. With the development of the Internet of Things, cloud computing, big data, and artificial intelligence technologies, they have been applied in online monitoring of rivers, lakes, and urban water bodies, as well as smart early warning. However, since the treatment of rural black and odorous water bodies is still in its infancy, the use of intelligent means to carry out monitoring and early warning of rural black and odorous water bodies is still insufficient. There is a lack of miniaturized and intelligent monitoring devices, poor stability and reliability of the monitoring system, low data processing efficiency, and data analysis and early warning model algorithms need to be optimized. Summary of the invention

[0006] The first purpose of the present invention is to provide an artificial intelligence-based rural black and odorous water monitoring system that is easy to use and has high stability in response to the above-mentioned problems existing in the prior art.

[0007] The second object of the present invention is to provide an early warning method using the above-mentioned 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 odorous water body monitoring system based on artificial intelligence includes 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;

[0010] 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;

[0011] The micro-heating assembly is connected to the outer side of the shell;

[0012] 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.

[0013] The control module and monitoring assembly are both connected inside the housing;

[0014] The telescopic detection assembly is connected to the bottom of the shell and can sample the water body near the shell;

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

[0016] In the above-mentioned artificial intelligence-based rural black and odorous water body monitoring system, 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 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 set information data range, the evaluation and early warning unit makes a corresponding early warning action. The above-mentioned information display platform is used to display the real-time information data monitored by the monitoring component.

[0017] In the above-mentioned artificial intelligence-based rural black and odorous water body monitoring system, the evaluation and early warning unit 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 above-mentioned early warning action can be obtained on the computer or mobile phone.

[0018] In the above-mentioned artificial intelligence-based rural black and odorous water body monitoring system, 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 connection 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.

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

[0020] In the above-mentioned artificial intelligence-based rural black and odorous water body monitoring system, the telescopic detection assembly includes a probe, telescopic cylinder one, telescopic cylinder two, telescopic cylinder three and a servo motor. The above-mentioned probe is in the shape of a long rod, the above-mentioned telescopic cylinder is set on the probe, the above-mentioned telescopic cylinder two is set on the telescopic cylinder one, the above-mentioned telescopic cylinder three is set on the telescopic cylinder two, and the above-mentioned 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.

[0021] Generally, the telescopic range of the telescopic detection assembly is 0-0.5 meters. Those skilled in the art can adjust the length of the telescopic tube to achieve a suitable telescopic length according to the actual water conditions (which can be detected by the sensor). For example, when the water depth is greater than 0.5 meters, the telescopic length is 0.5 meters, and when the water depth is less than 0.5 meters, the telescopic length is 1 / 2 of the water depth.

[0022] In the above-mentioned artificial intelligence-based rural black and smelly water body monitoring system, 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 telescopic cylinder 1 has a protruding limit pin 2 on the outside, the telescopic cylinder 2 has a concave limit groove 2 on the inside along its axial direction, the telescopic cylinder 2 has a protruding limit pin 3 on the outside, the telescopic cylinder 3 has a protruding limit groove 3 on the inside, 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.

[0023] An ice-breaking assembly is arranged on the outside of the detection assembly, and the ice-breaking assembly includes a hollow rotating shaft sleeved on the outside of the telescopic cylinder three, 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 telescopic cylinder three are connected by a ball bearing, and the outer side is meshed with a driving gear; the driving gear is connected to an output shaft of a driving motor, and the rotation of the hollow rotating shaft is realized by a gear combination, thereby driving the blades to cut and break ice.

[0024] In the above-mentioned artificial intelligence-based rural black and odorous water body monitoring system, the micro-heating component includes an inner insulation layer and an outer electric heating layer, the inner insulation layer is coated on the outside of the shell, and the outer electric heating layer is coated on the outside of the inner insulation layer and forms an installation cavity between the two; a number 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. The water pipes are connected to a plurality of one-way valves arranged on the outer electric heating layer. In the present invention, an air pump installed in the shell is used to inject gas into the water pipe, and a water pump installed in the shell is used to pump water from the outside of the shell and inject water into the water pipe; the water-gas mixture in the water pipe 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. Since the outer electric heating layer heats the water-gas mixture, the hot water flow will also efficiently de-ice.

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

[0026] The outer 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 energized. When the water temperature is greater than 5°C, the electric heating wire will be de-energized.

[0027] Of course, the temperature control switch is connected to the corresponding sensor. Since detecting temperature is a prior art, this part will not be described in detail in the specification.

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

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

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

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

[0032] Step S1, deploying the device at the monitored water body;

[0033] Step S2, constructing a BP (Back Propagation, BP) artificial neural network model at the assessment 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 odorous water body status assessment 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 status assessment and trend 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 warning response plans on the information display platform.

[0035] Compared with the existing technology, this rural black and odorous water 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, easy operation and stable system. It can realize real-time monitoring and trend prediction, solve the practical problems of large volume and wide area of ​​black and odorous water in rural areas and difficulty in monitoring due to freezing in winter, and meet the needs of monitoring and management of black and odorous water in rural areas.

[0037] (2) It can realize functions such as self-measurement of water depth, self-adjustment of sampling monitoring points, self-heating and de-icing during the winter ice period, and self-protection and self-cleaning of monitoring instruments. The solar photovoltaic panels can provide power for various electrical equipment in the monitoring system to meet the needs of black and odorous water body monitoring in remote rural areas without grid coverage. At the same time, it also reduces the cost of subsequent monitoring and maintenance of the treated black and odorous water bodies.

[0038] (3) By constructing a rural black and odorous water body status assessment and trend prediction model based on BP artificial neural network, a rural black and odorous water body status assessment and trend early warning method based on artificial intelligence was developed, which promoted the application of Internet of Things, artificial intelligence and other technologies in rural black and odorous water body monitoring and early warning methods.

[0039] (4) The water body visual monitoring and early warning platform can realize the data and chart display of water body status assessment and future trend warning, and provide early warning response plans in a timely manner based on different warning colors, helping relevant management departments to promptly grasp the situation of black and odorous water bodies in rural areas, so as to facilitate timely tracking and response. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a schematic diagram of the cross-sectional structure 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 This 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 This is a structural diagram of the blade in the rural black and odorous water body monitoring system based on artificial intelligence.

[0044] In the figure, 1. shell; 2. controller; 3. data remote transmission unit; 4. evaluation and early 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 slot one; 10b. limit pin two; 11. telescopic cylinder two; 11a. limit slot two; 11b. limit pin three; 12. telescopic cylinder three; 12a. limit slot three; 13. servo motor; 14. inner insulation layer; 15. outer electric heating layer; 16. water pipe; 17. hollow shaft; 18. one-way valve; 19. filter; 20. power module; 21. float; 22. self-cleaning component; 23. drive motor; 24. blade; 25. drive gear. DETAILED DESCRIPTION

[0045] 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.

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

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention 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 related listed items.

[0048] like Figure 1 and Figure 2 and Figure 3 and Figure 4 As shown, the rural black and odorous water monitoring system based on artificial intelligence includes a shell 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 floating block 21 is fixedly connected to the outside of the housing 1 and can make the housing 1 float stably on the surface of the monitored water body under the action of the floating block 21;

[0050] The micro-heating assembly is connected to the outer side of the housing 1;

[0051] The 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 is in operation, the temperature of the housing 1 can be increased through the micro-heating component.

[0052] The above control module and monitoring component are connected in the housing 1;

[0053] The telescopic detection assembly is connected to the bottom of the housing 1 and 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 frequency of water body monitoring is once a day. According to the relationship between black and smelly water in rural areas and temperature, the higher the temperature, the more serious the black and smelly phenomenon. The monitoring time is selected when the temperature is the highest in a day. For example, the above 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 into the evaluation and early warning unit and the information display platform 5 via the data remote transmission unit. The 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 set information data range, the evaluation and early warning unit 4 makes a corresponding early warning action. The information display platform 5 is used to display the real-time information data monitored by the monitoring component.

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

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

[0059] The monitoring components include an ammonia nitrogen monitoring mechanism 6, a dissolved oxygen monitoring mechanism 7 and a transparency monitoring mechanism 8. The ammonia nitrogen monitoring mechanism 6, the dissolved oxygen monitoring mechanism 7 and the transparency monitoring mechanism 8 all have telescopic detection components corresponding thereto.

[0060] Since the ammonia nitrogen monitoring mechanism 6, the dissolved oxygen monitoring mechanism 7 and the transparency monitoring mechanism 8 are all existing technologies, their structural technical features are not described in detail in the embodiment.

[0061] The telescopic detection assembly includes a probe 9, a telescopic cylinder 10, a telescopic cylinder 2 11, a telescopic cylinder 3 12 and a servo motor 13. The probe 9 is in the shape of a long rod. The telescopic cylinder 10 is sleeved on the probe, the telescopic cylinder 2 11 is sleeved on the telescopic cylinder 1 9, the telescopic cylinder 3 12 is sleeved on the telescopic cylinder 2 11, and the servo motor 13 is fixedly connected in 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 assembly is 0-0.5 meters. Those skilled in the art can adjust the length of the telescopic tube to achieve a suitable telescopic length according to the actual water conditions (which can be detected by the sensor). For example, when the water depth is greater than 0.5 meters, the telescopic length is 0.5 meters, and when the water depth is less than 0.5 meters, the telescopic length is 1 / 2 of the water depth.

[0063] The probe side has a protruding limit pin 9a, the telescopic cylinder 10 has a concave limit groove 10a along its axial direction, the limit pin 9a is embedded in the limit groove 10a, the telescopic cylinder 10 has a protruding limit pin 2 10b on the outside, the telescopic cylinder 2 11 has a concave limit groove 2 11a on the inside along its axial direction, the telescopic cylinder 2 11 has a protruding limit pin 3 11b on the outside, the telescopic cylinder 3 12 has a protruding limit groove 3 12a on the inside, the limit pin 9a is embedded in the limit groove 10a, the limit pin 2 10b is embedded in the limit groove 2 11a, and the limit pin 3 11b is embedded in the limit groove 3 12a.

[0064] An ice-breaking assembly is arranged on the outside of the detection assembly, and the ice-breaking assembly includes a hollow rotating shaft 17 sleeved on the outside of the telescopic cylinder three 12, and a plurality of blades 24 fixed to the outer edge of the hollow rotating shaft 17. The inner side of the hollow rotating shaft 17 and the telescopic cylinder three 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 by a gear combination, thereby driving the blades 24 to cut and break ice.

[0065] The micro-heating assembly includes an inner insulation layer 14 and an outer electric heating layer 15. The inner insulation layer 14 is coated on the outside of the shell 1, and the outer electric heating layer 15 is coated on the outside of the inner insulation layer 14 to form an installation cavity between the two. A plurality of water pipes 16 are laid in the installation cavity, and the water pipes 16 are attached to the outer electric heating layer 15, and the outer electric heating layer 15 heats the water in the water pipes 16. The water pipes 16 are connected to a plurality of one-way valves 18 arranged on the outer electric heating layer 15. In the present invention, an air pump installed in the shell is used to inject gas into the water pipes 16, and a water pump installed in the shell 1 is used to pump water from the outside 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. Since the outer electric heating layer heats the water-gas mixture, the hot water flow will also efficiently de-ice.

[0066] The micro-heating component covers 1 / 2-4 / 5 of the shell. When the system is used in areas with lower annual average temperature such as the central and western regions, the area of ​​the micro-heating component adopts a larger value; when the system is used in areas with higher annual average temperature such as the eastern region, the area of ​​the micro-heating component adopts a smaller value.

[0067] Preferably, a filter assembly is provided at the end of the water pipe 16 to physically filter impurities in the water.

[0068] The outer electric heating layer 15 can be made of flexible electric heating cloth, and its heating control can be achieved through a simple 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.

[0069] The one-way valves are set on the side wall and bottom of the shell, with a number of 10-50, and the ratio of the number of side wall one-way valves to the number of bottom one-way valves is 5:1. The more one-way valves there are, the higher the efficiency of the discharged water flow in micro-disturbance of the water body around the device, and the better the deicing effect. When the system is applied to areas with lower annual average temperatures such as the central and western regions, the number of one-way valves is larger; when the system is applied to areas with higher annual average temperatures such as the eastern region, the number of one-way valves is smaller.

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

[0071] In this embodiment, a self-cleaning component 22 is provided at the lower end of the telescopic cylinder 1, the telescopic cylinder 2 and the telescopic cylinder 3, and the self-cleaning component 22 is a hard bristle brush roller.

[0072] As another scheme, it is also feasible that the self-cleaning assembly 22 is a spiral brush roller. Of course, according to actual conditions, it is also feasible to combine the bristle brush roller with the spiral brush roller.

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

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

[0075] Step S2, constructing a BP (Back Propagation, BP) artificial neural network model at the assessment 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 odorous water body status assessment and trend early warning model based on the BP artificial neural network;

[0076] Step S3, retrieve the water body monitoring data at the monitoring component, use the current status assessment and trend 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 warning response plans on the information display platform.

[0077] The assessment and early warning unit includes a data storage and processing terminal and an assessment and early warning terminal, which can realize the current status assessment and trend warning of the water body.

[0078] The data storage and processing end is used for data storage and pre-processing of water status assessment and trend warning. Among them, data storage includes monitoring data, historical sample data, evaluation and prediction data, etc.; data pre-processing includes water transparency, removal of abnormal values ​​of dissolved oxygen and ammonia nitrogen concentration (data anomalies caused by rain and other weather conditions), normal distribution test, normalization standard processing, etc.

[0079] The assessment and early warning end is used to carry out water body status assessment and trend warning, including neural network model construction, model training and verification, status assessment and trend warning.

[0080] Neural network model construction,This model consists of three layers, namely, an input layer, a hidden layer and an output layer.,Among them, the input layer contains three neurons, corresponding to the three evaluation indicators of water transparency,,dissolved oxygen and ammonia nitrogen concentration, three neurons are set in the hidden layer, and two neurons are used in the output layer, that is, the topological structure of the water status assessment and trend 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 rural areas in the surrounding area, according to the principle of equal number of samples, the historical monitoring sample data of water bodies and the corresponding evaluation results are randomly divided into training set and verification set, and the neural network model for water body status assessment is trained and constructed to obtain the water body status assessment results. Using the monitoring sample data and evaluation results of the past 30-60 days of the deployment of the monitoring system, sorted by day in chronological order, the monitoring sample data and the corresponding evaluation results of the first half of the time range are used as the training set, and the monitoring sample data and the corresponding evaluation results of the second half of the time range are used as the verification set, and the water body trend warning neural network model is trained and constructed to predict the evaluation results of the water body in the next 7-15 days. The training set data is used to train the neural network, and the model parameters are adjusted through multiple iterations; the verification set data is used to evaluate the model performance, and the evaluation indicators include mean square error, determination coefficient, correlation coefficient, etc. According to the verification and evaluation results, the network structure (such as adjusting the number of hidden layer nodes), learning rate, training rounds, etc. are adjusted to further improve the model accuracy.

[0082] Current status assessment and trend warning: According to the national water quality evaluation standards and classification, the optimized model is used to assess the current water quality status, predict and warn of water quality change trends, and formulate early warning response plans.

[0083] The water quality evaluation standards and classification are based on the national water body determination standards and take into account the actual monitoring and assessment 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 smelly 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 smelly water bodies (transparency < 10 cm, dissolved oxygen < 0.2 mg / L, ammonia nitrogen > 15 mg / L), which correspond to the three states of 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 water status assessment adopts a single factor evaluation method, and the black and smelly type of the water body is determined by the highest category of the three evaluation indicators. The black and smelly status of the water body is assessed based on the daily monitoring data provided by the rural black and smelly water body monitoring system based on artificial intelligence and the water status assessment model based on BP artificial neural network.

[0085] Water quality trend warning, based on 30-60 days of monitoring data provided by the rural black and odorous water body monitoring system based on artificial intelligence, relies on the water body trend warning model based on BP artificial neural network to predict the black and odorous condition of the water body in the next 7-15 days and clarify the water body status.

[0086] The water trend warning response plan, for normal water bodies with the warning result, the water body will be marked with a "green" mark, and a "long-term cleaning" mechanism for the water body will be established; for slightly black and smelly water bodies with the warning result, the water body will be marked with an "orange" mark, and a "long-term cleaning" mechanism will be established, and the plan contents include strengthening daily monitoring and management of water bodies, finding out the causes of slightly black and smelly water bodies, and taking necessary measures; for black and smelly water bodies with the warning result, the water body will be marked with a "red" mark, indicating the need to conduct on-site sampling and monitoring of water bodies and verify the warning results, and enter the verification results in the information display platform. If the verification is correct, it is proposed to conduct analysis and diagnosis of the causes of black and smelly water, as well as to adopt one or more combination of process measures such as intercepting pollution and controlling sources, clearing silt and dredging, connecting water systems, and ecological restoration.

[0087] The information display platform includes a visual interactive platform and mobile information applications. The visual interactive platform is used to display the current water quality monitoring data of the monitoring points, the curve chart of the water quality monitoring data change in the past 30-60 days, the water quality monitoring forecast 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 the mobile phone through the water body monitoring and early warning application APP.

[0088] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0089] Those skilled in the art should recognize that the above embodiments are only used to illustrate the present invention, and are not intended to limit the present invention. As long as they are within the spirit of the present invention, appropriate changes and modifications to the above embodiments are within the scope of protection claimed by the present invention.

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 monitoring component can monitor and analyze the sampled water, and the water monitoring information at the monitoring component can be sent to the controller.

2. The rural black and smelly water monitoring system based on artificial intelligence according to claim 1 is characterized in that: 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. The rural black and smelly water monitoring system based on artificial intelligence according to claim 2 is characterized in that: The evaluation and early warning unit is a corresponding water body monitoring and early warning application program. The above-mentioned data remote transmission unit realizes data communication of the water body monitoring and early warning application program in the form of a mobile network, and the above-mentioned early warning action can be obtained on a computer or a mobile phone.

4. The rural black and smelly water monitoring system based on artificial intelligence according to claim 3 is characterized in that: The information display platform is a corresponding water body monitoring and early warning application program. The above-mentioned data remote transmission unit realizes data transmission of the water body monitoring and early warning application program in the form of a mobile network, and real-time information data can be viewed on a computer or a mobile phone.

5. The rural black and smelly water monitoring system based on artificial intelligence according to claim 4 is characterized in that: 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, the dissolved oxygen monitoring mechanism and the transparency monitoring mechanism all have telescopic detection components corresponding to them.

6. The rural black and smelly water monitoring system based on artificial intelligence according to claim 5 is characterized in that: The telescopic detection assembly includes a probe, telescopic cylinder 1, telescopic cylinder 2, telescopic cylinder 3 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 2 is sleeved on the telescopic cylinder 1, the telescopic cylinder 3 is sleeved on the telescopic cylinder 2, and 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. The rural black and odorous water monitoring system based on artificial intelligence according to claim 6 is characterized in that: 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 telescopic cylinder 1 has a protruding limit pin 2 on the outside, the telescopic cylinder 2 has a concave limit groove 2 on the inside along its axial direction, the telescopic cylinder 2 has a protruding limit pin 3 on the outside, the telescopic cylinder 3 has a protruding limit groove 3 on the inside, 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. The rural black and odorous water monitoring system based on artificial intelligence according to claim 7 is characterized in that: The micro-heating assembly includes an inner insulation layer and an outer electric heating layer. The inner insulation layer is coated on the outside of the shell, and the outer electric heating layer is coated on the outside of the inner insulation layer to form an installation cavity between the two. A number 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. The water pipes are connected to a plurality of one-way valves arranged on the outer electric heating layer. In the present invention, 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 outside 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. Since the outer electric heating layer heats the water-gas mixture, the hot water flow will also efficiently de-ice.

9. The rural black and odorous water monitoring system based on artificial intelligence according to claim 8 is characterized in that: The number of the one-way valves is several, and the several one-way valves are evenly distributed along the height direction of the shell and arranged between the air supply pipe and the water supply pipe.

10. A rural black and odorous water body monitoring and early warning method based on artificial intelligence, specifically comprising the following steps: Step S1, deploying the device at the monitored water body; Step S2, constructing a BP (Back Propagation, BP) artificial neural network model at the assessment 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 odorous water body status assessment and trend early warning model based on the BP artificial neural network; Step S3, retrieve the water body monitoring data at the monitoring component, use the current status assessment and trend 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 warning response plans on the information display platform.

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