Artificial intelligence drainage basin water temperature early warning system and method

Abstract

The invention provides an artificial intelligence watershed water temperature early warning system and method, and relates to the technical field of communication early warning, the artificial intelligence watershed water temperature early warning system comprises a multi-source data acquisition and transmission unit, a data edge calculation preprocessing unit and a grading early warning and decision support platform, the multi-source data acquisition and transmission unit acquires water temperature data of a to-be-detected water area through a plurality of built water temperature detection devices, and each water temperature detection device comprises a floating plate, an angle indication regulation and control unit and an early warning monitoring unit. And multi-source real-time fusion is carried out on the acquired data by virtue of the water temperature detection equipment, so that the resource scheduling efficiency is improved. And the water temperature detection equipment can simultaneously obtain temperature data of a static water body and a flowing water body, retards the water body in a high-speed flowing state and then collects the water body, so that the reliability of early warning information is improved, and the early warning depth range can be regulated and controlled.

Description

Technical Field

[0001] The present invention relates to the technical field of communication warning, and particularly to an artificial intelligence basin water temperature warning system and method. Background Technique

[0002] Water temperature is an important parameter of the aquatic ecosystem, directly affecting the survival and reproduction of fish, plankton and plants. When the water temperature exceeds 25°C, it is easy to cause algal blooms and damage the water body ecological balance. Water temperature monitoring also provides a scientific basis for reservoir operation, agricultural irrigation and industrial water use. By adjusting the water discharge volume, the downstream water temperature can be controlled, and the irrigation time can be optimized to avoid the adverse effects of low or high temperature on crop growth. Therefore, temperature monitoring and warning is not only an important tool for ecological protection and resource management, but also a key infrastructure for coping with climate change and ensuring public health.

[0003] In the existing artificial intelligence basin water temperature warning scheme, a fixed threshold is adopted for the warning threshold of temperature, ignoring climate change and ecological adaptability. Moreover, the original data is obtained through manual sampling, resulting in insufficient timeliness. On the other hand, for the collection of original data in the water temperature warning process, there is a lack of interference from the water flow velocity state on the collected data. The turbulence of the water body with high-speed flow cannot fully absorb heat due to water flow scouring, and at the same time, noise signals will be generated due to vibration. While the static water body will cause a "thermal boundary layer" to form on the surface of the sensor, hindering heat conduction. Therefore, there are certain errors in conventional water temperature detection equipment, and the temperature monitored will also be interfered when the top of the water temperature detection equipment is blocked. Summary of the Invention

[0004] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide an artificial intelligence basin water temperature warning system and method to solve the problems raised in the above background technology. The present invention generates a dynamic ecological threshold, reducing the ecological misjudgment rate. With the help of the water temperature detection equipment, multi-source real-time fusion of the collected data is carried out, and the resource scheduling efficiency is improved. Moreover, the water temperature detection equipment can simultaneously obtain the temperature data of static water bodies and flowing water bodies, and slow down the water body in a high-speed flowing state before collecting, improving the reliability and accuracy of the warning information, and can flexibly adjust the warning depth range, and provides a function of directly observing and judging the monitoring depth, expanding the acquisition channels and accuracy of the collected parameters.

[0005] To achieve the above object, the present invention is realized through the following technical solutions: An artificial intelligence basin water temperature early warning system, the early warning system includes a multi-source data collection and transmission unit, a data edge computing and preprocessing unit, and a hierarchical early warning and decision support platform. The multi-source data collection and transmission unit communicates and transmits through a narrowband Internet of Things, and the multi-source data collection and transmission unit collects water temperature data of the water area to be measured through a plurality of built water temperature detection devices. The water temperature detection device includes a floating plate, an angle indication and regulation unit, and an early warning and monitoring unit. A plurality of floating rods are installed at the bottom of the floating plate. A guide sleeve is provided at one end of the floating plate. A guide post is inserted into the inside of the guide sleeve. An installation frame is welded to the top of the guide post. An adjustment groove is provided on the surface of the floating plate. The side of the adjustment groove is provided with an angle indication and regulation unit, and an early warning and monitoring unit is inserted into the inside of the adjustment groove. The early warning and monitoring unit includes a support plate, a sampling switching module, a diversion mechanism, and a water temperature detection module. The data edge computing and preprocessing unit is equipped with an artificial intelligence analysis and prediction core, and an optimized knowledge base is established in the hierarchical early warning and decision support platform.

[0006] Further, the angle indication and regulation unit includes a spring rod, a first electric telescopic rod, and a pull rod. A base is attached to the surface of the floating plate. The two ends of the base are screwed with first electric telescopic rods. A sponge sleeve is sleeved on the surface of the pull rod. A spring rod is also welded to one side of the base.

[0007] Further, a telescopic sleeve is sleeved at the end of the spring rod. A top rod is integrally formed at the end of the telescopic sleeve. The top rod and the pull rod are parallel to each other. The spring rod and the first electric telescopic rod are parallel to each other. The two ends of the pull rod are fixed to the ends of the first electric telescopic rod.

[0008] Further, the bottom end of the support plate is fixedly connected to the diversion mechanism. The top end of the support plate is connected to the sampling switching mechanism. An indicator board is embedded on the surface of the support plate. A plurality of lamp beads are embedded in the indicator board.

[0009] Further, the diversion mechanism includes a slow-speed monitoring chamber and a sampling monitoring chamber. A diversion hole is provided on one side of the slow-speed monitoring chamber. A docking hole is provided on the side of the sampling monitoring chamber. The top ends of the slow-speed monitoring chamber and the sampling monitoring chamber are integrally formed with a plug-in sleeve. A linkage rod is inserted into the inside of the plug-in sleeve.

[0010] Further, the water temperature detection module is respectively embedded into the inside of the slow-speed monitoring chamber and the sampling monitoring chamber. Strip-shaped holes are provided on the surfaces of the slow-speed monitoring chamber and the sampling monitoring chamber. Metal filter meshes are embedded on the surfaces of the diversion hole and the docking hole.

[0011] Further, the water temperature detection module includes a sampling sleeve and a slow-down sleeve. A sliding rod is inserted on the side at the bottom end of the linkage rod. The sliding rod passes through the inside of the strip-shaped hole, and the sampling sleeve and the slow-down sleeve are respectively welded to the end of the sliding rod.

[0012] Further, temperature sensors are embedded in both the sampling sleeve and the slow-down sleeve. An extension rod is also inserted on the surface of the linkage rod. A cleaning plate is welded to the end of the extension rod. The cleaning plate is used to scrape and slide along the surfaces of the docking hole and the diversion hole. Both ends of the sampling sleeve move along the inner wall of the sampling monitoring chamber. One end of the slow-down sleeve abuts against the inner wall of the slow-down monitoring chamber, and the other end of the slow-down sleeve passes outwards from the other side of the slow-down monitoring chamber.

[0013] Further, the sampling switching module includes a second electric telescopic rod, a movable end plate and a fixed plate. The fixed plate is integrally formed at the top end of the support plate. The second electric telescopic rod is screwed on the surface of the fixed plate. The top end of the second electric telescopic rod is screwed with the movable end plate. The bottom surface of the movable end plate is welded to the top end of the linkage rod. A support frame is screwed on the surface of the floating plate. A rotating shaft is inserted at the top of the support frame. The rotating shaft passes through the inside of the support plate.

[0014] An early warning method using the above water temperature early warning system includes the following steps:

[0015] S1. Set up multiple groups of water temperature detection devices in the basin to be measured;

[0016] S2. Simultaneously obtain the water temperature data in the flowing state and the water temperature data in the static state in the basin through the water temperature detection devices;

[0017] S3. Analyze the correlation between historical water temperature and ecological events based on the LSTM model to generate a dynamic ecological threshold;

[0018] S4. The physical model simulates the heat pollution diffusion path, and the data model predicts local mutations. The two are cross-validated to reduce the false alarm rate;

[0019] S5. Set up a hierarchical response and resource allocation plan to achieve fully automatic hierarchical response processing;

[0020] S6. Conduct feedback learning on each early warning information and iterate the threshold.

[0021] Advantages of the present invention:

[0022] 1. The artificial intelligence basin water temperature early warning method can generate a dynamic ecological threshold, provide automatic calibration at fixed intervals, reduce the ecological misjudgment rate, perform multi-source real-time fusion on the collected data with the help of water temperature detection devices, shorten the heat pollution response time, achieve fully automatic hierarchical response, and improve the resource scheduling efficiency.

[0023] 2. The artificial intelligence-based river basin water temperature early warning system can simultaneously obtain the temperature data of static water bodies and flowing water bodies, slow down the water bodies in a high-speed flowing state before collection, improve the reliability and accuracy of early warning information, and can flexibly adjust the early warning depth range through the sampling switching module at the top. While providing the function of monitoring depth adjustment, it avoids occlusion at the top of the water temperature detection and positioning, reducing the interference of external environmental factors on the collected water temperature data.

[0024] 3. The artificial intelligence-based river basin water temperature early warning system provides the function of directly observing and judging the monitoring depth, expanding the acquisition channels and accuracy of collection parameters. It can directly judge the current depth range of water temperature monitoring at a distance at night, and can automatically clean the indicator board for displaying depth data, making it more convenient and flexible to use. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is the principle block diagram of an artificial intelligence-based river basin water temperature early warning system of the present invention;

[0026] Figure 2 is the flowchart of an artificial intelligence-based river basin water temperature early warning method of the present invention;

[0027] Figure 3 is the structural diagram of the water temperature detection device built in an artificial intelligence-based river basin water temperature early warning system of the present invention;

[0028] Figure 4 is the schematic structural diagram of the angle indication and regulation unit part of the present invention;

[0029] Figure 5 is the schematic structural diagram of the early warning monitoring unit part of the present invention;

[0030] Figure 6 is the enlarged structural diagram of the diversion mechanism of the present invention;

[0031] Figure 7 is the cross-sectional view of the diversion mechanism part of the present invention;

[0032] Figure 8 is the schematic structural diagram of the water temperature detection module part of the present invention;

[0033] Figure 9 is the schematic structural diagram of the sampling switching module part of the present invention;

[0034] In the figure: 1. Floating plate; 2. Mounting frame; 3. Guide post; 4. Floating rod; 5. Angle indication and control unit; 6. Early warning and monitoring unit; 7. Guide sleeve; 8. Adjustment groove; 9. Base; 10. First electric telescopic rod; 11. Pull rod; 12. Sponge sleeve; 13. Spring rod; 14. Telescopic sleeve; 15. Thrust rod; 16. Support plate; 17. Sampling switching module; 18. Support frame; 19. Indicator board; 20. Lamp bead; 21. Flow guiding mechanism; 22. Water temperature detection module; 23. Slow speed monitoring bin; 24. Sampling monitoring bin; 25. Insertion sleeve; 26. Flow guiding hole; 27. Docking hole; 28. Linking rod; 29. Strip-shaped hole; 30. Sliding rod; 31. Sampling sleeve; 32. Slow speed sleeve; 33. Extension rod; 34. Cleaning plate; 35. Second electric telescopic rod; 36. Movable end plate; 37. Rotating shaft; 38. Fixed plate. Specific implementation manners

[0035] To make the technical means, creative features, achieved purposes and functions of the present invention easy to understand, the present invention will be further described below in conjunction with specific implementation manners.

[0036] Please refer to Figures 1 to 9 , the present invention provides the following technical solutions: An artificial intelligence watershed water temperature early warning system, the early warning system includes a multi-source data acquisition and transmission unit, a data edge computing and preprocessing unit, and a hierarchical early warning and decision support platform. The multi-source data acquisition and transmission unit communicates and transmits through narrowband Internet of Things, and the multi-source data acquisition and transmission unit collects water temperature data of the water area to be measured through a plurality of built water temperature detection devices. The water temperature detection device includes a floating plate 1, an angle indication and control unit 5 and an early warning and monitoring unit 6. A plurality of floating rods 4 are installed at the bottom of the floating plate 1. A guide sleeve 7 is opened at one end of the floating plate 1. A guide post 3 is inserted inside the guide sleeve 7. The top of the guide post 3 is welded with a mounting frame 2. An adjustment groove 8 is opened on the surface of the floating plate 1. An angle indication and control unit 5 is installed on the side of the adjustment groove 8, and an early warning and monitoring unit 6 is inserted inside the adjustment groove 8. The early warning and monitoring unit 6 includes a support plate 16, a sampling switching module 17, a flow guiding mechanism 21 and a water temperature detection module 22. An artificial intelligence analysis and prediction core is carried in the data edge computing and preprocessing unit, and an optimized knowledge base is established in the hierarchical early warning and decision support platform. This water temperature early warning system can collect and measure the water temperature of the water area to be measured, and communicate and transmit based on narrowband Internet of Things, so as to provide an early warning signal for water temperature anomalies.

[0037] When the present invention is used, first, a plurality of water temperature monitoring devices are set up in the water area to be measured. Each water temperature monitoring device is fixed at a position close to the shore through the mounting frame 2 at the top, and the floating plate 1 is limited and blocked by passing a guide rod through the guide hole on the floating plate 1, ensuring that the floating plate 1 can float along with the water level line, and at the same time, there will be no problems of rotation or horizontal movement. Subsequently, the angle indication control unit 5 can drive the bottom flow guiding mechanism 21 and the water temperature detection module 22 to sink into the underwater area, and with the help of two groups of temperature sensors in the water temperature detection module 22, the purpose of measuring the water temperature in the flowing state and the water temperature of the static water body is completed respectively. During this process, the sampling switching module 17 at the top is also used to change the monitoring state of the bottom water temperature detection module 22. The temperature sensor is an existing mature technology and does not belong to the protection scope of the present invention. Therefore, its internal structure, principle, and related parameters will not be elaborated herein.

[0038] In this embodiment, the angle indication control unit 5 includes a spring rod 13, a first electric telescopic rod 10, and a pull rod 11. A base 9 is attached to the surface of the floating plate 1. The first electric telescopic rods 10 are screwed at both ends of the base 9. A sponge sleeve 12 is sleeved on the surface of the pull rod 11. A spring rod 13 is also welded to one side of the base 9. The end of the spring rod 13 is sleeved with a telescopic sleeve 14. The end of the telescopic sleeve 14 is integrally formed with a top rod 15, and the top rod 15 and the pull rod 11 are parallel to each other. The spring rod 13 and the first electric telescopic rod 10 are parallel to each other. The two ends of the pull rod 11 are fixed to the end of the first electric telescopic rod 10. The bottom end of the support plate 16 is fixedly connected to the flow guiding mechanism 21, the top end of the support plate 16 is connected to the sampling switching mechanism, and an indicator plate 19 is embedded on the surface of the support plate 16. A plurality of lamp beads 20 are embedded in the indicator plate 19. This warning system provides the function of directly observing and judging the monitoring depth, expands the acquisition channels and accuracy of the collected parameters, can directly judge the current water temperature monitoring depth range at a distance at night, and can provide automatic cleaning treatment for the indicator plate 19 used to display the depth data, making it more convenient and flexible to use.

[0039] Specifically, in this application, the first electric telescopic rod 10 and the spring rod 13 are used to provide blocking or pulling force from both sides of the early warning monitoring unit 6 respectively, so as to control the tilting angle of the entire early warning monitoring unit 6, thereby changing the depth of the bottom water temperature detection module 22 underwater. An indicator board 19 and lamp beads 20 are arranged on the surface of the support plate 16. Therefore, when the support plate 16 is pulled by the pull rod 11, it will also move on the indicator board 19 and block the linearly distributed lamp beads 20 among them. Therefore, by directly observing the blocked position among the lamp beads 20 from a distance, the current tilting angle of the early warning monitoring unit 6 can be judged, and thus the approximate depth of the current water temperature detection module 22 underwater can be judged. This process can also perform periodic telescopic motion through the first electric telescopic rod 10, driving the sponge sleeve 12 on the pull rod 11 to slide along the surface of the indicator board 19, achieving the purpose of cleaning the surface of the indicator board 19 and ensuring that the distribution state of the lit lamp beads 20 is always kept highly clear.

[0040] In this embodiment, the diversion mechanism 21 includes a slow-speed monitoring chamber 23 and a sampling monitoring chamber 24. A diversion hole 26 is opened on one side of the slow-speed monitoring chamber 23, and a docking hole 27 is opened on the side of the sampling monitoring chamber 24. An insertion sleeve 25 is integrally formed at the top of the slow-speed monitoring chamber 23 and the sampling monitoring chamber 24, and a linkage rod 28 is inserted into the interior of the insertion sleeve 25. The water temperature detection module 22 is respectively embedded in the interiors of the slow-speed monitoring chamber 23 and the sampling monitoring chamber 24, and strip-shaped holes 29 are opened on the surfaces of the slow-speed monitoring chamber 23 and the sampling monitoring chamber 24. Metal filter meshes are embedded on the surfaces of the diversion hole 26 and the docking hole 27. The water temperature detection module 22 includes a sampling sleeve 31 and a slow-speed sleeve 32. A sliding rod 30 is inserted into the side of the bottom end of the linkage rod 28, and the sliding rod 30 passes through the interior of the strip-shaped hole 29. Sampling sleeves 31 and slow-speed sleeves 32 are respectively welded to the ends of the sliding rod 30. Temperature sensors are embedded in the interiors of the sampling sleeve 31 and the slow-speed sleeve 32. An extension rod 33 is also inserted into the surface of the linkage rod 28, and a cleaning plate 34 is welded to the end of the extension rod 33. The cleaning plate 34 is used to scrape and slide along the surfaces of the docking hole 27 and the diversion hole 26. Both ends of the sampling sleeve 31 move along the inner wall of the sampling monitoring chamber 24, one end of the slow-speed sleeve 32 abuts against the inner wall of the slow-speed monitoring chamber 23, and the other end of the slow-speed sleeve 32 passes outwards from the other side of the slow-speed monitoring chamber 23. This structure can simultaneously obtain the temperature data of static water bodies and flowing water bodies, slow down the water body in a high-speed flowing state and then collect it, improving the reliability and accuracy of the early warning information. And through the sampling switching module 17 at the top, the early warning depth range can be flexibly adjusted. While providing the monitoring depth adjustment function, it avoids occlusion at the top of the water temperature detection and positioning, reducing the interference of external environmental factors on the collected water temperature data.

[0041] Specifically, the support plate 16 drives the slow-speed monitoring chamber 23 and the sampling monitoring chamber 24 at the bottom to change their depths, and can pass through the slow-speed monitoring chamber 23 and the sampling monitoring chamber 24 as the water flows. In the process of passing through, they can enter the water temperature detection module 22, so that the specific temperature of the water inside it can be monitored by the water temperature detection module 22. A flat guide hole 26 is opened on one side of the slow-speed monitoring chamber 23, and the cross-sectional area of the inner slow-speed sleeve 32 is larger than the corresponding area of the guide hole 26. Therefore, through this difference, the flow rate of the water entering the slow-speed sleeve 32 is reduced, but it still maintains a flowing state, so as to achieve the purpose of temperature monitoring of the flowing water body, and through the sampling sleeve 31, it can be in contact with the slow-speed monitoring chamber 23. After the docking hole 27 is docked, part of the water enters the interior of the sampling sleeve 31. Subsequently, the sampling sleeve 31 is pulled up by controlling the sampling switching module 17 until the two ends of the sampling sleeve 31 are offset from the docking hole 27. The two ends of the sampling sleeve 31 can be blocked, and the water extracted inside can remain in a static state, and the temperature can be measured in this static state, and finally multi-source data can be obtained, avoiding the problem that the turbulence of high-speed flowing water cannot fully absorb heat due to water scouring, and the noise signal is generated due to vibration. It also avoids the problem that the static water will cause a "thermal boundary layer" to form on the sensor surface to hinder heat conduction. After the collected data is transmitted, the generated early warning signal is more accurate and reliable.

[0042] In this embodiment, the sampling switching module 17 includes a second electric telescopic rod 35, a movable end plate 36 and a fixed plate 38, wherein the fixed plate 38 is integrally formed at the top of the support plate 16, the second electric telescopic rod 35 is screwed on the surface of the fixed plate 38, the movable end plate 36 is screwed on the top of the second electric telescopic rod 35, the bottom surface of the movable end plate 36 is welded to the top of the linkage rod 28, the support frame 18 is screwed on the surface of the floating plate 1, the top of the support frame 18 is plugged with a rotating shaft 37, and the rotating shaft 37 passes through the inside of the support plate 16. Specifically, after starting the second electric telescopic rod 35, the movable end plate 36 at the top is lifted upward, and the linkage rod 28 at the bottom can be pulled to drive the water temperature monitoring module at the end to be lifted, thereby realizing the above-mentioned sampling process of the water body, and the surfaces of the guide hole 26 and the docking hole 27 can also be scraped and cleaned by the extension rod 33 and the cleaning plate 34 at the same time.

[0043] This embodiment also provides an early warning method using the above water temperature early warning system, comprising the following steps:

[0044] S1. Build multiple groups of water temperature detection equipment in the watershed to be tested. Each water temperature monitoring equipment is fixed at a position close to the shore through a mounting frame 2 at the top;

[0045] S2. With the help of two groups of temperature sensors in the water temperature detection module 22, the purpose of measuring the water temperature in the flowing state and the water body temperature in the static state is completed respectively;

[0046] S3. Analyze the correlation between historical water temperature and ecological events based on the LSTM model to generate a dynamic ecological threshold. When the water temperature exceeds the 95% quantile of the same period in history and lasts for 6 hours, an alarm is triggered;

[0047] S4. The physical model simulates the heat pollution diffusion path, and the data model predicts local mutations. The two cross-validate to reduce the false alarm rate, and locate the root cause of the anomaly to improve the efficiency of responsibility tracing;

[0048] S5. Set a hierarchical response and resource allocation plan to achieve fully automatic hierarchical response processing. After the alarm is triggered, link with the environmental protection department to limit emissions and activate emergency resources;

[0049] S6. After each early warning event, optimize the model parameters through reinforcement learning (PPO algorithm) and dynamically update the threshold.

[0050] Through this method, a dynamic ecological threshold can be generated, providing automatic calibration at a fixed period, reducing the ecological misjudgment rate. With the help of the water temperature detection device, multi-source real-time fusion of the collected data is carried out, shortening the response time of heat pollution, achieving fully automatic hierarchical response, and improving the resource scheduling efficiency.

[0051] The above shows and describes the basic principles, main features and advantages of the present invention. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic features of the present invention, the present invention can be implemented in other specific forms.

[0052] In addition, it should be understood that although this specification is described according to embodiments, not every embodiment only contains an independent technical solution. This narrative way of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. An artificial intelligence-based river basin water temperature early warning system, characterized in that: The early warning system includes a multi-source data acquisition and transmission unit, a data edge computing and preprocessing unit, and a hierarchical early warning and decision support platform. The multi-source data acquisition and transmission unit communicates and transmits through narrowband Internet of Things, and the multi-source data acquisition and transmission unit collects the water temperature data of the water area to be measured through a plurality of built water temperature detection devices. The water temperature detection device includes a floating plate, an angle indication and regulation unit, and an early warning monitoring unit. A plurality of floating rods are installed at the bottom of the floating plate. A guide sleeve is provided at one end of the floating plate. A guide post is inserted into the inside of the guide sleeve. An installation frame is welded to the top of the guide post. An adjustment groove is provided on the surface of the floating plate. The angle indication and regulation unit is installed on the side of the adjustment groove, and the early warning monitoring unit is inserted into the inside of the adjustment groove. The early warning monitoring unit includes a support plate, a sampling switching module, a diversion mechanism, and a water temperature detection module. The data edge computing and preprocessing unit is equipped with an artificial intelligence analysis and prediction core, and an optimized knowledge base is established in the hierarchical early warning and decision support platform.

2. The artificial intelligence-based basin water temperature early warning system according to claim 1, wherein: The angle indication and regulation unit includes a spring rod, a first electric telescopic rod, and a pull rod. A base is attached to the surface of the floating plate. The first electric telescopic rods are screwed at both ends of the base. A sponge sleeve is sleeved on the surface of the pull rod. A spring rod is also welded on one side of the base.

3. The artificial intelligence-based basin water temperature early warning system according to claim 2, wherein: The end of the spring rod is sleeved with a telescopic sleeve. A top rod is integrally formed at the end of the telescopic sleeve. The top rod and the pull rod are parallel to each other. The spring rod and the first electric telescopic rod are parallel to each other. The two ends of the pull rod are fixed to the ends of the first electric telescopic rod.

4. An artificial intelligence-based basin water temperature early warning system according to claim 2, characterized in that: The bottom end of the support plate is fixedly connected to the diversion mechanism. The top end of the support plate is connected to the sampling switching mechanism. An indicator board is embedded on the surface of the support plate. A plurality of lamp beads are embedded in the indicator board.

5. An artificial intelligence-based basin water temperature early warning system according to claim 4, characterized in that: The diversion mechanism includes a slow speed monitoring bin and a sampling monitoring bin. A diversion hole is provided on one side of the slow speed monitoring bin. A docking hole is provided on the side of the sampling monitoring bin. The slow speed monitoring bin and the sampling monitoring bin are integrally formed with a plug-in sleeve at the top. A linkage rod is inserted into the inside of the plug-in sleeve.

6. The artificial intelligence-based basin water temperature early warning system according to claim 5, wherein: The water temperature detection module is respectively embedded in the slow speed monitoring bin and the sampling monitoring bin. Strip-shaped holes are provided on the surfaces of the slow speed monitoring bin and the sampling monitoring bin. Metal filter meshes are embedded on the surfaces of the diversion hole and the docking hole.

7. An artificial intelligence-based basin water temperature early warning system according to claim 6, characterized in that: The water temperature detection module includes a sampling sleeve and a slow speed sleeve. A sliding rod is inserted into the side of the bottom end of the linkage rod. The sliding rod passes through the inside of the strip-shaped hole. The ends of the sliding rod are respectively welded with a sampling sleeve and a slow speed sleeve.

8. An artificial intelligence-based river basin water temperature early warning system according to claim 7, characterized in that: Temperature sensors are embedded in the sampling sleeve and the slow speed sleeve. An extension rod is also inserted into the surface of the linkage rod. A cleaning plate is welded to the end of the extension rod. The cleaning plate is used for scraping and sliding along the surfaces of the docking hole and the diversion hole. The two ends of the sampling sleeve move along the inner wall of the sampling monitoring bin. One end of the slow speed sleeve abuts against the inner wall of the slow speed monitoring bin, and the other end of the slow speed sleeve passes outwards from the other side of the slow speed monitoring bin.

9. An artificial intelligence-based basin water temperature early warning system according to claim 5, characterized in that: The sampling switching module includes a second electric telescopic rod, a movable end plate and a fixed plate. The fixed plate is integrally formed at the top of the support plate. The second electric telescopic rod is screwed on the surface of the fixed plate. The movable end plate is screwed at the top of the second electric telescopic rod. The bottom surface of the movable end plate is welded to the top end of the linkage rod. The support frame is screwed on the surface of the floating plate. The rotating shaft is inserted at the top of the support frame. The rotating shaft passes through the inside of the support plate.

10. A warning method using the water temperature warning system as described in claim 1, characterized in that, It includes the following steps: S1. Build multiple groups of water temperature detection devices in the basin to be measured; S2. Simultaneously obtain the water temperature data in the flowing state and the water temperature data in the static state in the basin through the water temperature detection devices; S3. Analyze the correlation between historical water temperature and ecological events based on the LSTM model to generate a dynamic ecological threshold; S4. The physical model simulates the heat pollution diffusion path, and the data model predicts local mutations. The two are cross-validated to reduce the false alarm rate; S5. Set a hierarchical response and resource allocation plan to achieve fully automatic hierarchical response processing; S6. Conduct feedback learning on each warning message and iterate the threshold.

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