Novel water quality detection device for environmental science and use method of novel water quality detection device

Abstract

The invention 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 lamp and an antenna, the sensors are installed below the main body, the controller is installed in the main body, the power device is installed on the side face of the main body, and the warning lamp and the antenna are installed above the main body; the sensor comprises an inertial sensor and a plurality of water quality detection sensors. According to the scheme provided by the invention, a detector does not need to take a ship to go to the internal area of the water body area to be detected, but can directly place the water quality detection device in the water body area to be detected, so that the water quality detection device can automatically determine a proper water quality sampling point position and automatically carry out in-place detection; the method is especially suitable for water body areas where detection personnel are difficult 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 use method thereof. Background Art

[0002] In the field of environmental science, water quality testing is an important means of evaluating and monitoring the health of water bodies. In order 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 testing 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 by 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 type of water quality detection device for environmental science, a method of use, an electronic device, a computer storage medium and a computer program product.

[0005] The present invention provides a novel water quality detection device for environmental science, the device comprising a main body, a controller, a sensor, a power device, a warning light and an antenna, wherein a plurality of the sensors are installed below the main body, the controller is installed inside the main body, the power device is installed on the side of the main body, and the warning light and the antenna are installed above the main body; the sensor comprises an inertial sensor and a plurality of 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 and obtain a plurality 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 device to start and drive the water quality detection device to go 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 also used to communicate with a handheld terminal of a detection personnel through the antenna to receive a fourth control instruction of the handheld terminal, and send 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 group of the 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 testing points based on the first spacing distance includes: determining a circle with the position of the water quality testing device as the center and N times the first spacing distance as the radius, determining the position of the water quality testing device as one of the water quality sampling and testing points, and then determining a plurality of water quality sampling and testing points on the circle with the first spacing distance respectively.

[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, and 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 detection personnel's handheld terminal via the antenna to prompt the detection personnel to enter a second interval distance.

[0010] Furthermore, a number of 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 one of the water quality sampling and detection points.

[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: a detection personnel places the water quality detection device in a water body 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 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; a computer program is stored on the storage medium, 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 preceding items; the computer program product contains executable computer program instructions.

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

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

[0017] Figure 1 It is a structural schematic diagram of a novel water quality detection device for environmental science provided by an embodiment of the present invention.

[0018] Figure 2 It 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 novel water quality detection device for environmental sciences. DETAILED DESCRIPTION

[0020] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art 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 also Figure 1 As shown, an embodiment of the present invention provides a new type of water quality detection device for environmental science, the device includes a main body, a controller, a sensor, a power device, a warning light and an antenna, several of the sensors are installed below the main body, the controller is installed inside the main body, the power device is installed on the side of the main body, and the warning light and the antenna are installed above the main body; the sensor includes 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 and obtain several 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 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, 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 also used to communicate with the handheld terminal of the detection personnel through the antenna to receive the fourth control instruction of the handheld terminal, and send water quality analysis data to the handheld terminal.

[0022] The above-mentioned water quality detection device of the present invention is equipped with a controller (not shown in the figure), a sensor, a power device, 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 device to drive the water quality detection device to each water quality sampling 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 detection personnel to take a ship to the internal area of ​​the water body to be detected. Instead, the water quality detection device of the present invention can be directly placed in the water body to be detected. The water quality detection device can automatically determine the appropriate water quality sampling point and automatically detect on site. It is particularly suitable for water areas that are difficult for detection personnel to enter, and can greatly improve the convenience, efficiency and safety of water quality detection.

[0024] Among them, the inertial sensor is mainly used to detect the acceleration of the water quality detection device, which can be any one of a MEMS accelerometer, an optical inertial sensor, and a mechanical inertial sensor. The water quality detection sensor can be set according to the detection needs, such as a pH sensor, a dissolved oxygen (DO) sensor, a turbidity sensor, a conductivity sensor, a heavy metal sensor, etc.

[0025] Furthermore, the controller determines a number of water quality sampling and detection points based on a group of the 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 this embodiment, in order to improve the accuracy of water quality detection, it is necessary to perform detection at different points in the water body area to be detected, and determine the final water quality analysis results 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 area of ​​the current water body area to be detected is large or small, and thus cannot directly determine the interval distance of each water quality sampling detection point. If the detection personnel manually determine and transmit the interval distance to the water quality detection device, it is too cumbersome and not conducive to efficient detection.

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

[0028] Then, feature extraction is performed on the peak clustering sub-curve and the non-peak clustering sub-curve respectively to obtain the first acceleration feature and the second acceleration feature, which characterize the change characteristics of the acceleration of the water quality detection device in the above two stages. The first acceleration feature includes acceleration features including but not limited to the maximum acceleration value, the average acceleration value, the number of peaks, the average value of the distance between peaks, etc., and the second acceleration feature mainly includes the maximum value of vertical acceleration. The two acceleration features are input into the pre-constructed throwing distance prediction model, and the throwing distance prediction model is used to analyze the motion state of the water quality detection device, so that the distance at which the water body detection device is thrown can be predicted, that is, how far the detection personnel threw the water quality detection device. The distance at which the detection personnel throws the water quality detection device is positively correlated with the area 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 will throw the water quality detection device, and vice versa. Based on the above correspondence, 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 takes the current position of the water quality detection device as the reference, and determines a number of water quality sampling and detection points around the water quality detection device based on the above interval distance.

[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 testing device can automatically predict the area size of the water area to be tested 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 should be noted that the first acceleration feature is directly related to the throwing distance. When the throw is thrown over a long distance, the highest point of the parabola is higher, resulting in a larger maximum acceleration, average acceleration, and number of peaks after falling into the water, while the average distance between peaks is smaller. Otherwise, the feature is the opposite. The second acceleration feature can also be used to indirectly analyze the height of the highest point of the parabola. The larger the maximum vertical acceleration, the higher the corresponding highest point of the parabola. Otherwise, the feature is the opposite.

[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 uses a physics-based deep learning algorithm (Physics-Informed Neural Networks, PINNs) to construct the above-mentioned throwing distance prediction model, which incorporates the physical laws corresponding to the object's motion equation, and uses multiple sets of training data to train the throwing distance prediction model until it meets the standard. The throwing distance prediction model can predict the throwing distance of the water quality detection device based on the above input data. The physical laws embedded in the model of the present invention can guide the training direction of the model, and can complete the training of the model more efficiently and accurately compared to the traditional training method that relies only 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 testing points based on the first spacing distance includes: determining a circle with the position of the water quality testing device as the center and N times the first spacing distance as the radius, determining the position of the water quality testing device as one of the water quality sampling and testing points, and then determining a plurality of water quality sampling and testing points on the circle with the first spacing distance respectively.

[0035] In this embodiment, refer to Figure 2 As shown, a circle is determined with the position of the water quality detection device as the center and the first interval distance multiple of N as the radius, where N can be 0.6, 0.8, or other values ​​less than 1. Several water quality sampling and detection points with a straight-line distance (not arc distance) equal to the first interval distance are determined on the circle, and the current position of the water quality detection device is also determined as a water quality sampling and detection 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, and 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 detection personnel's handheld terminal via 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 detection device falls into the water and stabilizes, but this is based on the premise that the detection personnel directly throw the water quality detection device into the water area to be detected. In fact, the detection personnel may not throw the water quality detection device, but place it in the shore area and make relevant adjustments manually. In the latter case, it is not appropriate to directly use the above method to analyze the interval 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 fluctuates up and down in the water body, which also indicates 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 according to the manually input interval distance, and stop when each 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 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 one of the water quality sampling and detection points.

[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. In the process of moving, 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 stops for water quality sampling and analysis until a preset number of points are reached for water quality sampling and analysis, and then 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 body area to be detected can be determined according to the current orientation of the water quality detection device, and the detection personnel can manually determine the orientation. The autonomous motion of the water quality detection device can also be realized based on an inertial sensor, specifically using the inertial navigation principle. Since inertial navigation is a mature existing technology, it will not be described here.

[0042] See also 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 comprises the following steps: a detection personnel places the water quality detection device in a water body 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 the 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 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.

[0044] The embodiment of the present invention further discloses a computer storage medium, which is applied to the novel environmental science water quality detection device as described in any of the above items; a computer program is stored on the storage medium, and the computer program is executed by a processor.

[0045] The embodiment of the present invention further discloses a computer program product, which is applied to the novel environmental science water quality detection device as described in any of the preceding items; the computer program product contains executable computer program instructions.

[0046] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0047] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable load balancing device, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0048] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may 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 may 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 processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0050] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A new type of water quality detection device for environmental science, characterized by: The device includes a main body, a controller, a sensor, a power device, 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 device 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 and obtain several 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 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, 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 also used to communicate with a handheld terminal of a detection personnel through the antenna to receive a fourth control instruction of the handheld terminal, and send water quality analysis data to the handheld terminal.

2. A novel environmental science water quality detection device according to claim 1, characterized in that: The controller determines a number of water quality sampling and detection points based on a group of acceleration data, including: the controller performs curve fitting on each acceleration data to obtain the 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 casting distance prediction model, and the casting distance prediction model outputs a predicted casting distance; determines a first interval distance according to the casting distance, and determines a number of water quality sampling and detection points based on the first interval distance.

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

5. A novel environmental science water quality detection device 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, and 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 via the antenna to prompt the detection personnel to enter a second interval distance.

6. A novel environmental science water quality detection device according to claim 5, characterized in that: Based on the second interval distance, a number of water quality sampling and detection points are determined, including: taking the position of the water quality detection device as a reference, moving toward 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 novel environmental science water quality detection device as claimed in any one of claims 1 to 6, characterized in that: The method comprises 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, 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 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 the 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 of the handheld terminal and sends water quality analysis data to the handheld terminal.

8. An electronic device, characterized in that: Applicable to a new type of environmental science water quality detection device as described in any one of claims 1-6; the electronic device comprises: 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 novel environmental science water quality detection device as described in any one of claims 1-6; a computer program is stored on the storage medium, and the computer program is executed by a processor.

10. A computer program product, characterized in that: Applicable to the novel 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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