Water quality detection device for environmental science and method of use thereof

Abstract

The application belongs to the technical field of water quality detection, and provides a novel water quality detection device for environmental science and a use method thereof.The device comprises a main body, a controller, sensors, a power device, a warning light and an antenna, a plurality of sensors are installed below the main body, the controller is installed in the inside of the main body, the power device is installed on the side of the main body, the warning light and the antenna are installed above the main body; the sensors comprise an inertial sensor and a plurality of water quality detection sensors. The scheme of the application does not require a detection personnel to board a ship to go to the inside area of a water body area to be detected, but can directly place the water quality detection device of the application in the water body area to be detected, so that the water quality detection device can automatically determine a suitable water quality sampling point and automatically detect in position, and is especially suitable for a water body area which is difficult for a detection personnel to enter, and can greatly improve the convenience, efficiency and safety of water quality detection.

Description

Technical Field

[0001] The present invention relates to the technical field of water quality detection, and in particular to a novel environmental science water quality detection device and a method for using the same. Background Art

[0002] In the field of environmental science, water quality testing is an important means of assessing and monitoring the health of water bodies. To improve the convenience of water quality testing, portable water quality testing devices are gradually being used. Water quality testers can carry portable water quality testing devices to conduct water quality tests on-site and obtain corresponding test results / reports, without having to collect water samples on-site and then return to the laboratory for testing.

[0003] However, the above-mentioned portable water quality testing device still requires the tester to manually collect water samples and then place the water samples in the portable water quality testing device for water quality analysis. In essence, the above-mentioned portable water quality testing device is only a water quality analyzer, which cannot fully reduce the labor intensity of water quality testing for the tester; moreover, when faced with certain waters that are not suitable for direct entry by the tester, the above-mentioned portable water quality testing device is also difficult to play a role. Summary of the Invention

[0004] In order to solve at least one of the above technical problems, the present invention specifically provides a new environmental science water quality detection device, usage method, electronic equipment, computer storage medium and computer program product.

[0005] The present invention provides a novel water quality detection device for environmental science, comprising a main body, a controller, sensors, a power unit, a warning light, and an antenna. Several sensors are mounted below the main body, the controller is mounted inside the main body, the power unit is mounted on the side of the main body, and the warning light and the antenna are mounted above the main body. The sensors include an inertial sensor and several water quality detection sensors. The inertial sensor is configured to detect a set of acceleration data of the water quality detection device. The controller is configured to determine a number of water quality sampling and detection points based on the acceleration data, generate a first control instruction, a second control instruction, and a third control instruction, control the power unit to activate and drive the water quality detection device to each of the water quality sampling and detection points in sequence based on the first control instruction, control the sensors to perform water quality analysis at each of the water quality sampling and detection points based on the second control instruction, and control the warning light and the antenna to activate based on the third control instruction. The controller is further configured to communicate with a handheld terminal of a detection personnel via the antenna to receive a fourth control instruction from the handheld terminal and transmit water quality analysis data to the handheld terminal.

[0006] Furthermore, the controller determines a number of water quality sampling and detection points based on a set of acceleration data, including: the controller performs curve fitting on each of the acceleration data to obtain an acceleration curve of the water quality detection device; identifies a peak aggregation sub-curve and a non-peak aggregation sub-curve from the acceleration curve, performs feature extraction on the peak aggregation sub-curve and the non-peak aggregation sub-curve to obtain a first acceleration feature and a second acceleration feature; inputs the first acceleration feature and the second acceleration feature into a throwing distance prediction model, and the throwing distance prediction model outputs a predicted throwing distance; determines a first interval distance according to the throwing distance, and determines a number of water quality sampling and detection points based on the first interval distance.

[0007] Furthermore, the throwing distance prediction model is constructed based on a physical deep learning algorithm, and the throwing distance prediction model includes an input layer, a hidden layer, a physical information layer, and an output layer; wherein the input layer is used to receive input data, and the input data includes the first acceleration feature and the second acceleration feature, as well as the mass and air resistance coefficient of the water quality detection device; the hidden layer is a multi-layer structure composed of multiple neurons, which is used to extract features from the input data and learn abstract representations of data to obtain abstract features; the output layer is used to predict and output the throwing distance of the water quality detection device based on the abstract features; the physical information layer is used to integrate physical laws into the loss function in the form of differential equations to ensure that network predictions conform to physical laws.

[0008] Furthermore, the determining of the plurality of water quality sampling and detection points based on the first spacing distance includes: determining a circle with the position of the water quality detection device as the center and N multiples of the first spacing distance as the radius, determining the position of the water quality detection device as one of the water quality sampling and detection points, and then determining a plurality of water quality sampling and detection points on the circle with the first spacing distance.

[0009] Furthermore, the controller determines a number of water quality sampling and detection points based on a set of the acceleration data, and also includes: the controller performs real-time curve fitting on each of the acceleration data to obtain a real-time acceleration curve of the water quality detection device; if the real-time acceleration curve is identified as the peak aggregation sub-curve, a fifth control instruction is generated; wherein, the fifth control instruction is transmitted to the handheld terminal of the detection personnel through the antenna to prompt the detection personnel to enter a second interval distance.

[0010] Furthermore, a number of the water quality sampling and detection points are determined based on the second interval distance, including: taking the position of the water quality detection device as a reference, moving toward the center of the water area to be detected, and each time the second interval distance is reached, the corresponding position point is determined as a water quality sampling and detection point.

[0011] The present invention also provides a method for using the aforementioned new type of water quality detection device for environmental science, the method comprising the following steps: the detection personnel places the water quality detection device in the water area to be detected; the inertial sensor detects a set of acceleration data of the water quality detection device, and the controller determines a number of water quality sampling and detection points based on the acceleration data, and generates a first control instruction, a second control instruction, and a third control instruction; the controller controls the power device to start and drive the water quality detection device to each of the water quality sampling and detection points in turn based on the first control instruction, and controls the sensor to perform water quality analysis at each of the water quality sampling and detection points based on the second control instruction, and controls the warning light and antenna to start based on the third control instruction; the controller communicates with the detection personnel's handheld terminal through the antenna to receive the fourth control instruction of the handheld terminal, and sends water quality analysis data to the handheld terminal.

[0012] The present invention also provides an electronic device, which is applied to the new environmental science water quality detection device as described in any of the above items; the electronic device includes: a memory storing executable program code; a processor coupled to the memory; and the processor calls the executable program code stored in the memory.

[0013] The present invention also provides a computer storage medium, which is applied to the novel environmental science water quality detection device as described in any of the above items; the storage medium stores a computer program, and the computer program is executed by a processor.

[0014] The present invention also provides a computer program product, which is applied to the novel environmental science water quality detection device as described in any of the above items; the computer program product contains executable computer program instructions.

[0015] The solution of the present invention does not require testing personnel to take a ship to the inner area of ​​the water body to be tested. Instead, the water quality testing device of the present invention can be directly placed in the water body to be tested. The water quality testing device can automatically determine the appropriate water quality sampling point and automatically conduct on-site testing. It is particularly suitable for water bodies that are difficult for testing personnel to enter, and can greatly improve the convenience, efficiency and safety of water quality testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 The present invention provides a novel water quality detection device for environmental science.

[0018] Figure 2 This is a schematic diagram of determining a plurality of water quality sampling and detection points based on a first spacing distance provided by an embodiment of the present invention.

[0019] Figure 3 The present invention provides a flow chart of a method for using a novel water quality detection device for environmental science. DETAILED DESCRIPTION

[0020] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0021] See Figure 1 As shown, an embodiment of the present invention provides a novel water quality detection device for environmental science, the device comprising a main body, a controller, sensors, a power unit, a warning light, and an antenna. Several sensors are mounted below the main body, the controller is mounted inside the main body, the power unit is mounted on the side of the main body, and the warning light and the antenna are mounted above the main body. The sensors comprise an inertial sensor and several water quality detection sensors. The inertial sensor is configured to detect a set of acceleration data of the water quality detection device. The controller is configured to determine a number of water quality sampling and detection points based on the acceleration data, generate a first control instruction, a second control instruction, and a third control instruction, control the power unit to start and drive the water quality detection device to each of the water quality sampling and detection points in sequence based on the first control instruction, control the sensor to perform water quality analysis at each of the water quality sampling and detection points based on the second control instruction, and control the warning light and the antenna to start based on the third control instruction. The controller is further configured to communicate with a handheld terminal of a detection personnel via the antenna to receive a fourth control instruction from the handheld terminal and send water quality analysis data to the handheld terminal.

[0022] The water quality detection device of the present invention is equipped with a controller (not shown in the figure), a sensor, a power unit, a warning light and an antenna. When in use, the detection personnel can place the water quality detection device in the water body. The controller of the water quality detection device can automatically determine a number of water quality sampling points based on the inertial data detected by the inertial sensor, and control the power unit to drive the water quality detection device to each water quality sampling and detection point one by one to perform water quality analysis, and then transmit the water quality analysis data back to the handheld terminal of the detection personnel on the shore through the antenna.

[0023] Therefore, the solution of the present invention does not require testing personnel to take a ship to the internal area of ​​the water body to be tested. Instead, the water quality testing device of the present invention can be directly placed in the water body to be tested. The water quality testing device can automatically determine the appropriate water quality sampling point and automatically conduct on-site testing. It is particularly suitable for water bodies that are difficult for testing personnel to enter, and can greatly improve the convenience, efficiency and safety of water quality testing.

[0024] Inertial sensors are primarily used to detect the acceleration of water quality testing devices. They can be any of a MEMS accelerometer, an optical inertial sensor, or a mechanical inertial sensor. Water quality testing sensors can be customized based on testing needs, such as pH sensors, dissolved oxygen (DO) sensors, turbidity sensors, conductivity sensors, and heavy metal sensors.

[0025] Furthermore, the controller determines a number of water quality sampling and detection points based on a set of acceleration data, including: the controller performs curve fitting on each of the acceleration data to obtain an acceleration curve of the water quality detection device; identifies a peak aggregation sub-curve and a non-peak aggregation sub-curve from the acceleration curve, performs feature extraction on the peak aggregation sub-curve and the non-peak aggregation sub-curve to obtain a first acceleration feature and a second acceleration feature; inputs the first acceleration feature and the second acceleration feature into a throwing distance prediction model, and the throwing distance prediction model outputs a predicted throwing distance; determines a first interval distance according to the throwing distance, and determines a number of water quality sampling and detection points based on the first interval distance.

[0026] In the embodiment, in order to improve the accuracy of water quality detection, it is necessary to detect at different points of the water body area to be detected respectively, and determine the final water quality analysis result based on multiple detection results. At the same time, the area of the water body area to be detected also has different sizes. For a large area of water body area, the interval distance between each sampling point should be larger, and for a small area of water body area, the interval distance between each sampling point should be smaller. However, the water quality detection device cannot directly distinguish whether the water body area to be detected is large or small, and thus cannot directly determine the interval distance between each water quality sampling detection point. If the interval distance is manually determined and transmitted to the water quality detection device by the detection personnel, it is too cumbersome and not conducive to efficient detection.

[0027] In view of the above technical problems, the present application first performs curve fitting on each acceleration data obtained by detection, so as to obtain an acceleration curve of the water quality detection device after being thrown. The acceleration curve is divided into a wave peak aggregation sub-curve and a non-wave peak aggregation sub-curve. The non-wave peak aggregation sub-curve corresponds to the acceleration of the water quality detection device in the process of flying in the air, and the wave peak aggregation sub-curve corresponds to the acceleration of the water quality detection device after falling into the water. Obviously, the acceleration curve in the process of flying in the air is significantly smoother than the acceleration curve after falling into the water. Therefore, by identifying the aggregation degree of the wave peak in the acceleration curve, the wave peak aggregation sub-curve and the non-wave peak aggregation sub-curve can be identified.

[0028] Then, the wave peak aggregation sub-curve and the non-wave peak aggregation sub-curve are respectively subjected to feature extraction to obtain first acceleration features and second acceleration features. The first acceleration features and the second acceleration features represent the variation characteristics of the acceleration of the water quality detection device in the above two stages. The first acceleration features include, but are not limited to, acceleration maximum value, acceleration average value, wave peak number, average value of wave peak distance, etc. The second acceleration features mainly include the maximum value of the vertical acceleration. The two acceleration features are input into a pre-constructed throwing distance prediction model. By analyzing the motion state of the water quality detection device by the throwing distance prediction model, the distance that the water body detection device is thrown, i.e. the distance that the detection personnel throws the water quality detection device, can be predicted. The distance that the detection personnel throws the water quality detection device is positively correlated with the size of the water body area to be detected. That is, the larger the area of the water body area to be detected, the farther the detection personnel throws the water quality detection device, and vice versa. Based on the above corresponding relationship, the throwing distance prediction model can predict the throwing distance, and then based on the determined throwing distance and the corresponding positive correlation interval distance, the controller determines a plurality of water quality sampling detection points around the water quality detection device based on the current position of the water quality detection device as a reference.

[0029] Therefore, this embodiment of the present invention does not require the tester to manually input the interval distance. Instead, the controller of the water quality detection device can automatically predict the area size of the water area to be detected based on the acceleration curve after throwing detected by the inertial sensor, and then determine the appropriate interval distance, which can greatly improve the efficiency of water quality analysis.

[0030] It's important to note that the first acceleration characteristic is directly related to the throwing distance. Longer distances result in a higher parabola's highest point, leading to higher maximum acceleration, average acceleration, and number of peaks after impact, while the average distance between peaks decreases. The opposite characteristic occurs when the acceleration is higher. The second acceleration characteristic can also be used to indirectly analyze the height of the parabola's highest point. A higher maximum vertical acceleration corresponds to a higher parabola's highest point, and vice versa.

[0031] Furthermore, the throwing distance prediction model is constructed based on a physical deep learning algorithm, and the throwing distance prediction model includes an input layer, a hidden layer, a physical information layer, and an output layer; wherein the input layer is used to receive input data, and the input data includes the first acceleration feature and the second acceleration feature, as well as the mass and air resistance coefficient of the water quality detection device; the hidden layer is a multi-layer structure composed of multiple neurons, which is used to extract features from the input data and learn abstract representations of data to obtain abstract features; the output layer is used to predict and output the throwing distance of the water quality detection device based on the abstract features; the physical information layer is used to integrate physical laws into the loss function in the form of differential equations to ensure that network predictions conform to physical laws.

[0032] In this embodiment, the present invention utilizes a physics-based deep learning algorithm (Physics-Informed Neural Networks, PINNs) to construct the aforementioned casting distance prediction model. This casting distance prediction model incorporates the physical laws corresponding to the object's equation of motion. The casting distance prediction model is trained using multiple sets of training data until it meets the required criteria. The casting distance prediction model can then predict the casting distance of a water quality testing device based on the aforementioned input data. The physical laws embedded in the present invention's model can guide the model's training direction, enabling more efficient and accurate model training compared to traditional training methods that rely solely on training data.

[0033] The hidden layer may be a fully connected layer, a convolutional layer, or other types of layers, which is not specifically limited in the present invention.

[0034] Furthermore, the determining of the plurality of water quality sampling and detection points based on the first spacing distance includes: determining a circle with the position of the water quality detection device as the center and N multiples of the first spacing distance as the radius, determining the position of the water quality detection device as one of the water quality sampling and detection points, and then determining a plurality of water quality sampling and detection points on the circle with the first spacing distance.

[0035] In this embodiment, referring to Figure 2 As shown, a circle is determined with the location of the water quality testing device as the center and a first interval distance multiple of N as the radius. N can be a value less than 1, such as 0.6, 0.8, etc. Several water quality sampling and testing points are then determined on the circle, each with a straight-line distance (not an arc distance) equal to the first interval distance. The current location of the water quality testing device is also determined as a water quality sampling and testing point (i.e., point 1 in the figure).

[0036] Furthermore, the controller determines a number of water quality sampling and detection points based on a set of the acceleration data, and also includes: the controller performs real-time curve fitting on each of the acceleration data to obtain a real-time acceleration curve of the water quality detection device; if the real-time acceleration curve is identified as the peak aggregation sub-curve, a fifth control instruction is generated; wherein, the fifth control instruction is transmitted to the handheld terminal of the detection personnel through the antenna to prompt the detection personnel to enter a second interval distance.

[0037] In this embodiment, the curve fitting is performed after the water quality testing device has landed and stabilized. However, this is based on the premise that the tester directly throws the water quality testing device into the water area to be tested. In fact, the tester may not throw the water quality testing device, but instead place the water quality testing device near the shore and manually adjust the relevant adjustments. In the latter case, it is not appropriate to directly use the above method to analyze the separation distance.

[0038] Specifically, after the water quality detection device is started, the present invention controls the inertial sensor to detect the acceleration data and perform real-time curve fitting. If the acceleration curve obtained by fitting meets the characteristics of the peak aggregation sub-curve, it means that the water quality detection device has entered the water at this time and is fluctuating up and down in the water body, which also means that the detection personnel have not thrown the water quality detection device. In this way, it is impossible to directly determine the area size of the water body area to be detected. At this time, the fifth control instruction is generated to transmit a prompt message to the handheld terminal of the detection personnel, prompting them to manually input the interval distance. The water quality detection device can then drive to the center of the water body area to be detected based on the manually input interval distance, and stop every time an interval distance is reached to perform water quality sampling and analysis until the water quality sampling and analysis of a predetermined number of points are completed.

[0039] Furthermore, a number of the water quality sampling and detection points are determined based on the second interval distance, including: taking the position of the water quality detection device as a reference, moving toward the center of the water area to be detected, and each time the second interval distance is reached, the corresponding position point is determined as a water quality sampling and detection point.

[0040] In this embodiment, different from the aforementioned method of drawing a circle, since the water quality detection device is currently located on the shore, the water quality detection device should be controlled to gradually move toward the center of the water area to be detected. During the movement, each time the second interval distance is reached, the corresponding position point is determined as one of the water quality sampling and detection points, and then the device is moored for water quality sampling and analysis until the water quality sampling and analysis of the preset number of points is reached, and the device returns to the shore automatically or under the control of the handheld terminal.

[0041] It should be noted that the center of the water area to be tested can be determined based on the current orientation of the water quality testing device, and the tester can manually determine the orientation. The autonomous motion of the water quality testing device can also be achieved based on inertial sensors, specifically using the principle of inertial navigation. Since inertial navigation is a mature existing technology, it will not be described in detail here.

[0042] See Figure 3 As shown, a method for using a new type of water quality detection device for environmental science according to an embodiment of the present invention includes the following steps: a detection personnel places the water quality detection device in a water area to be detected; an inertial sensor detects a set of acceleration data of the water quality detection device, and the controller determines a number of water quality sampling detection points based on the acceleration data, and generates a first control instruction, a second control instruction, and a third control instruction; the controller controls the power device to start and drive the water quality detection device to each of the water quality sampling detection points in turn based on the first control instruction, and controls the sensor to perform water quality analysis at each of the water quality sampling detection points based on the second control instruction, and controls the warning light and antenna to start based on the third control instruction; the controller communicates with the detection personnel's handheld terminal through the antenna to receive the fourth control instruction of the handheld terminal, and sends water quality analysis data to the handheld terminal.

[0043] An embodiment of the present invention also discloses an electronic device, which is applied to the new environmental science water quality detection device as described in any of the previous items; the electronic device includes: a memory storing executable program code; a processor coupled to the memory; and the processor calls the executable program code stored in the memory.

[0044] The embodiment of the application further discloses a computer storage medium, which is applied to the water quality detection device for environmental science, and the computer program is stored on the storage medium and is run by a processor.

[0045] The embodiment of the application further discloses a computer program product, which is applied to the water quality detection device for environmental science, and the computer program product contains computer program instructions which can be run.

[0046] Various embodiments of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a special-purpose computer chip, a computer having a related kernel that executes particular instructions (perhaps reassigned based on a kernel identifier), a hard-wired circuit, a computer having associated firmware, software, and / or combinations thereof. These various embodiments can each be implemented in one or more computer programs that are executable on a programmable system including at least one programmable processor that can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0047] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general or special purpose computer, special purpose computer, or other programmable computing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces a means for implementing the functions / operations specified in the flowcharts and / or block diagrams. The program code can execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0048] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0049] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not a limitation herein.

[0050] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A water quality detection device for environmental science, characterized by: The device includes a main body, a controller, sensors, a power unit, a warning light and an antenna, wherein several sensors are installed below the main body, the controller is installed inside the main body, the power unit is installed on the side of the main body, and the warning light and the antenna are installed above the main body; the sensors include an inertial sensor and several water quality detection sensors; wherein the inertial sensor is used to detect a set of acceleration data of the water quality detection device; the controller is used to determine a number of water quality sampling and detection points based on the acceleration data, generate a first control instruction, a second control instruction, and a third control instruction, control the power unit to start and drive the water quality detection device to each of the water quality sampling and detection points in sequence based on the first control instruction, control the sensor to perform water quality analysis at each of the water quality sampling and detection points based on the second control instruction, and control the warning light and the antenna to start based on the third control instruction; and the controller is further used to communicate with the handheld terminal of the inspection personnel through the antenna to receive a fourth control instruction from the handheld terminal and send water quality analysis data to the handheld terminal.

2. The water quality detection device for environmental science according to claim 1, characterized in that: The controller determines a number of water quality sampling and detection points based on a set of acceleration data, including: the controller performs curve fitting on each acceleration data to obtain an acceleration curve of the water quality detection device; identifies a peak aggregation sub-curve and a non-peak aggregation sub-curve from the acceleration curve, performs feature extraction on the peak aggregation sub-curve and the non-peak aggregation sub-curve to obtain a first acceleration feature and a second acceleration feature; inputs the first acceleration feature and the second acceleration feature into a throwing distance prediction model, and the throwing distance prediction model outputs a predicted throwing distance; determines a first interval distance according to the throwing distance, and determines a number of water quality sampling and detection points based on the first interval distance.

3. The water quality detection device for environmental science according to claim 2, characterized in that: The throwing distance prediction model is constructed based on a physical deep learning algorithm, and the throwing distance prediction model includes an input layer, a hidden layer, a physical information layer, and an output layer; wherein the input layer is used to receive input data, and the input data includes the first acceleration feature and the second acceleration feature, as well as the mass and air resistance coefficient of the water quality detection device; the hidden layer is a multi-layer structure composed of multiple neurons, which is used to extract features from the input data and learn abstract representations of data to obtain abstract features; the output layer is used to predict and output the throwing distance of the water quality detection device based on the abstract features; the physical information layer is used to integrate physical laws into the loss function in the form of differential equations to ensure that network predictions conform to physical laws.

4. The water quality detection device for environmental science according to claim 3, characterized in that: Based on the first spacing distance, several water quality sampling and detection points are determined, including: a circle is determined with the position of the water quality detection device as the center and N multiples of the first spacing distance as the radius, the position of the water quality detection device is determined as one of the water quality sampling and detection points, and then several water quality sampling and detection points are determined on the circle with the first spacing distance.

5. The water quality detection device for environmental science according to claim 4, characterized in that: The controller determines a number of water quality sampling and detection points based on a set of acceleration data, and also includes: the controller performs real-time curve fitting on each acceleration data to obtain a real-time acceleration curve of the water quality detection device. If the real-time acceleration curve is identified as the peak aggregation sub-curve, a fifth control instruction is generated; wherein, the fifth control instruction is transmitted to the handheld terminal of the detection personnel through the antenna to prompt the detection personnel to enter a second interval distance.

6. The water quality detection device for environmental science according to claim 5, characterized in that: Based on the second interval distance, several water quality sampling and detection points are determined, including: taking the position of the water quality detection device as a reference, moving towards the center of the water body area to be detected, and each time the second interval distance is reached, the corresponding position point is determined as a water quality sampling and detection point.

7. A method for using the environmental science water quality detection device according to any one of claims 1 to 6, characterized in that: The method includes the following steps: a tester places the water quality detection device in a water area to be tested; an inertial sensor detects a set of acceleration data of the water quality detection device, determines a number of water quality sampling and detection points based on the acceleration data, and generates a first control instruction, a second control instruction, and a third control instruction; the controller controls the power device to start and drive the water quality detection device to each of the water quality sampling and detection points in sequence based on the first control instruction, controls the sensor to perform water quality analysis at each of the water quality sampling and detection points based on the second control instruction, and controls the warning light and antenna to start based on the third control instruction; The controller communicates with the handheld terminal of the inspector through the antenna to receive the fourth control instruction from the handheld terminal and sends water quality analysis data to the handheld terminal.

8. An electronic device, characterized in that: Applicable to the environmental science water quality detection device as described in any one of claims 1-6; the electronic device includes: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory.

9. A computer storage medium, characterized in that: Applicable to the environmental science water quality detection device as described in any one of claims 1-6; the storage medium stores a computer program, and the computer program is executed by a processor.

10. A computer program product, characterized in that: Applicable to the environmental science water quality detection device as described in any one of claims 1-6; the computer program product contains executable computer program instructions.

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