Method and system for detecting water environment quality using a portable detection device

Abstract

A method and system for detecting water environment quality using a portable detection device is disclosed. [Solution] The water environment quality detection method and system using a portable detection device divides a water body into sub-detection areas and determines sampling points, thereby generating a driving track for the detector and guiding the detector to carry the portable detection device and conduct sequential sampling inspections. After obtaining water quality samples and data, the detection data and samples are analyzed to obtain the water quality status, a water environment quality detection report is generated and transmitted to the person in charge's terminal, thereby improving the comprehensiveness and accuracy of water environment quality inspection.

Description

[Technical Field]

[0001] The present invention relates to the technical field of water environment detection, and more particularly to a method and system for detecting water environment quality using a portable detection device. [Background technology]

[0002] With the rapid promotion of urbanization, water pollution is becoming increasingly serious. Traditional water environmental quality detection methods have problems such as insufficient sampling point coverage and long detection periods, making it difficult to meet the needs of modern water environmental management.

[0003] A similar prior art is a Chinese patent application published as CN118584078A, which discloses a multi-point distributed water body water quality measurement method, system, equipment and storage medium, which only analyzes a single type of influencing factor, and the detected water quality data is single, making it impossible to accurately evaluate the water quality situation. Summary of the Invention [Means for solving the problem]

[0004] In order to further solve the above technical problems, a method and system for detecting water environment quality using a portable detection device is provided, which has at least the following beneficial effects: 1. Divide the water body into multiple sub-detection areas and determine representative sampling points for each area to ensure the comprehensiveness and representativeness of the monitoring data, while generating movement tracks for the detectors, improving sampling efficiency and coverage. During the sampling detection process, anomalies are identified from the detected data, and when anomalies occur, sampling points can be adjusted appropriately, reducing the number of sampling points and reducing the workload, while also tracing the pollution source and improving detection efficiency. Missing parameter data can be estimated and supplemented based on upstream or downstream sampling point data and water flow conditions, improving data completeness and detection accuracy. 2. By combining various on-site water quality parameters, water surface images, and laboratory detection results, a more comprehensive and in-depth analysis and evaluation of water quality can be carried out, thereby improving the accuracy and comprehensiveness of water environment quality detection. [Brief explanation of the drawings]

[0005] [Figure 1] 2 is a flowchart of a method for detecting water environment quality using a portable detection device of the present invention. [Figure 2] 1 is a modularized configuration diagram of the water environment quality detection device of the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0006] FIG. 1 is a flowchart of an embodiment of a method for detecting water environment quality using a portable detection device provided by the present invention, which includes the following steps: Step 1: Based on the length and width of the detected water area, divide the detected water area into N1 sub-detection areas, and identify the sampling points and coordinates of each sub-detection area, where N1 is a positive integer greater than or equal to 1.

[0007] The size, shape, and water characteristics of the water area to be detected are different, and the water area can be divided into smaller sub-areas to be detected by different detectors, thereby increasing the detection speed and enabling more accurate detection.

[0008] Step 2: Obtain the location information of each of the N1 detectors, generate a first running trajectory by scanning all sampling points in a first point set based on the location information of the arbitrary detector, and send the first running trajectory to the first mobile terminal of the arbitrary detector, where the first point set is a set of sampling points in the sub-detection area corresponding to the arbitrary detector.

[0009] The first driving path is the shortest, fastest, and least expensive route, allowing each inspector to efficiently access each data sampling point, even if they are unfamiliar with the road conditions, and avoiding oversights. At the same time, the driving path and sampling point data can be recorded, facilitating review and audit, and increasing the transparency and reliability of the work.

[0010] Step 3: An arbitrary detector sequentially transports the portable detection device to each sampling point in the first point set based on the first driving trajectory, and uses the portable detection device to perform sampling and detection at each sampling point, obtain water quality samples and detection data, and transmit the detection data to the water environmental quality detection platform.

[0011] The portable detection device is a portable water environment quality detection device with multiple support frames, and has various sensing devices for detecting water quality, including a flow meter, a pH meter, and / or an acidity or alkalinity meter.

[0012] The portable detection device has advantages such as light weight and fast detection speed, can be carried and operated in various environments, does not require the installation of detection equipment in the water area, and is highly economical.

[0013] Specifically, in step 3, before sampling and detection are performed for each sampling point, the first coordinate of the first mobile terminal of any detecting person is obtained in real time, and it is determined whether the first coordinate is within the preset range of any sampling point of the first point set; if so, a detection signal is sent to move the any detecting person to any of the sampling points to perform sampling and detection.

[0014] When the detector is within a preset range of any sampling point, a detection signal is issued to guide the detector to quickly find the correct sampling point, thereby improving work efficiency.

[0015] Specifically, the detection data includes various water quality parameters, and step 3 includes: Step 31: After obtaining the first detection data of any sampling point, compare the value of each water quality parameter in the first detection data with the corresponding standard range to determine whether all water quality parameters meet the corresponding standard range. If YES, move to the next sampling point according to the first traveling trajectory; if NO, proceed to step 32, where the water quality parameters include temperature, pH value, dissolved oxygen value, acidity or alkalinity, electrical conductivity and / or turbidity.

[0016] Step 32: Obtain a second sampling point and generate a second driving trajectory, and an arbitrary detector transports the portable detection device to the second sampling point according to the second driving trajectory, where the second sampling point is located upstream of the arbitrary sampling point and is a sampling point that is a preset distance away from the arbitrary sampling point.

[0017] Step 33: Sampling and detection is performed at the second sampling point, and after obtaining the second detection data of the second sampling point, the values ​​of each water quality parameter in the second detection data are respectively compared with the corresponding standard ranges to determine whether all water quality parameters meet the corresponding standard ranges; if NO, define the second sampling point as an arbitrary sampling point; then return to step 32; if YES, proceed to step 34.

[0018] Step 34: Obtain a third sampling point, generate a third driving trajectory, and have an arbitrary detector transport the portable detection device to the third sampling point according to the third driving trajectory, where the third sampling point is a sampling point in the first point set and located adjacent to and downstream of the second sampling point.

[0019] Step 35: Sampling and detection is performed at the second sampling point, and after obtaining the third detection data of the third sampling point, the values ​​of each water quality parameter of the third detection data are compared with the corresponding standard ranges to determine whether all water quality parameters meet the corresponding standard ranges. If YES, define the third sampling point as the second sampling point, and then return to step 34. If NO, end the sampling and detection operation.

[0020] For example, seven sampling points are set up in the detection area from downstream to upstream, A1 to A7, detection starts from A1, and after obtaining the detection data from A1, the water quality parameter value is compared with the reference range. If it matches, it is determined that the water quality is normal, and sampling point A2 is detected. If not, it is determined that the water quality is abnormal. Sampling point A4, upstream of A1 and a predetermined distance from A1, is selected as the second sampling point. If the water quality of A4 is abnormal, A7 is selected as the second sampling point. If the water quality of A4 is normal, it is determined that the pollution source is between A1 and A4. Sampling point A3, downstream of A4, is selected as the third sampling point, and A3 is sampled and detected. If the water quality of A3 is abnormal, it is determined that the pollution source is near A3. If the water quality of A3 is normal, a sampling point between A1 and A3 is detected.

[0021] This method can ensure effective detection in water environments and quickly locate pollution sources, while adaptively adjusting the number of detection times, reducing unnecessary intermediate steps, and improving detection efficiency.

[0022] Step 4: After receiving all the detection data in the detection water area, process and analyze all the detection data to obtain a first detection result.

[0023] The first detection result includes a third detection result and a fourth detection result.

[0024] Specifically, the detection data includes various water quality parameters, and step 4 includes: Step 411: construct a first parameter type set that includes all water quality parameter types.

[0025] Step 412: extracting any detection data, obtaining a second parameter type set corresponding to the any detection data, and determining whether the second parameter type set is equal to the first parameter type set; if NO, extracting parameter types that do not belong to the second parameter type set from the first parameter type set and defining them as first parameter types, where the second parameter type set is a set of parameter types of all water quality parameters in the any detection data.

[0026] Step 413: define a sampling point corresponding to any detection data as a fourth sampling point, and obtain a fifth sampling point based on the coordinates of the fourth sampling point, where the fifth sampling point is located upstream or downstream of the fourth sampling point and the detection data includes a water quality parameter corresponding to the first parameter type.

[0027] Step 414: Obtain a first water quality parameter value corresponding to the first parameter type at the fifth sampling point, obtain the water flow velocity and distance between the fourth sampling point and the fifth sampling point, and calculate a second water quality parameter value corresponding to the first parameter type at the fourth sampling point based on the first water quality parameter value, the water flow velocity and the distance.

[0028] Step 415: supplementing the first parameter type and the second water quality parameter value with the detection data of the fourth sampling point to generate fourth detection data; analyzing the fourth detection data to obtain a first analysis result.

[0029] Step 416: After traversing all the detection data, a third detection result is generated.

[0030] For example, an adjustment coefficient based on the water flow velocity and distance is set in advance, and the product of this adjustment coefficient and the value of the first water quality parameter is set as the second water quality parameter.

[0031] After traversing all the detection data, it is determined whether the water quality parameters of any sampling points meet the reference range, and the water environment detection results of the sampling points are obtained based on the determination results.

[0032] Due to the sensor cost and the advantages of specific sensor technologies of different manufacturers, different sensor devices are installed in the portable detection devices of different manufacturers, and to ensure the comprehensiveness of the detection, the detector may carry different portable detection devices. If any water quality parameter of any sampling point is missing, the missing water quality parameter of that sampling point can be supplemented with the water quality parameter of the other sampling point to ensure the comprehensiveness and accuracy of the evaluation.

[0033] Specifically, the detection data includes a water surface image of the sampling point, and step 4 includes the following steps: Step 421: A first preprocessing is performed on the water surface image, and the image is defined as a first image.

[0034] Step 422: input the first image into a preliminary training model to generate a second image.

[0035] Step 423: calculate a pixel difference value between the first pixel value of the i-th pixel point in the first image and the second pixel value of the i-th pixel point in the second image, and use the pixel difference value as the pixel value of the i-th pixel point in the third image. After traversing all pixel points in the first image, generate a third image, where i is a positive integer between 1 and I, and I is the total number of pixel points in the first image.

[0036] Step 424: Calculate the average pixel value of all pixel points in the third image, and determine whether the average pixel value is greater than or equal to the first preset value. If YES, determine that the water quality of the sampling points corresponding to the water surface image is abnormal; if NO, determine that the water quality of the sampling points corresponding to the water surface image is normal.

[0037] Step 425: After traversing all the water surface images, a fourth detection result is generated.

[0038] Specifically, the method for generating the preliminary training model is as follows: acquiring a first water surface image when the water quality at the sampling point corresponding to the water surface image is normal; The method includes training a neural network model using the first water surface image to obtain a generative model, and using the generative model as a preliminary training model.

[0039] Illustratively, the first pre-processing may include noise removal and / or rotation correction, etc., to improve the quality of the image data and provide an accurate image for subsequent analysis.

[0040] The preliminary training model is trained based on water surface images when the water quality is normal, compresses the water surface image into a low-dimensional internal representation through an encoder, and attempts to reconstruct the water surface image from this internal representation through a decoder. The first water surface image can be obtained by inputting the first water surface image into the preliminary training model.

[0041] If the water quality at the sampling point corresponding to the first image is normal, the preliminary training model can reconstruct the first image to generate a nearly blank third image, i.e., a third image with little difference between the first and second images. If the water quality at the sampling point corresponding to the first image is abnormal, the preliminary training model cannot reconstruct the first image, and a third image with significant difference between the first and second images and distinctive content is generated. If the average pixel value of the third image is equal to or greater than the first preset value, it indicates a significant difference between the first and second images and abnormal water quality at the sampling point.

[0042] Step 5: Perform detection analysis on all water quality samples in the test water area to obtain second detection results.

[0043] Specifically, step 5 includes the following steps: Step 51: Extract any water quality sample as a detection sample, and perform a second pre-treatment on the detection sample to generate an analysis target sample.

[0044] Step 52: Create an observation sample based on the sample to be analyzed, and automatically acquire N2 detection images at different magnifications, where N2 is a positive integer greater than or equal to 1.

[0045] Step 53: Select an image to be analyzed from the N2 detected images, perform image recognition on the image to be analyzed, and confirm all the preset types of organisms in the image to be analyzed and the number of organisms of each preset type.

[0046] Step 54: Analyzing any of the water quality samples based on all of the preset types of organisms and the number of organisms of each of the preset types to obtain a second analysis result.

[0047] Step 55: After traversing all the water quality samples, a second detection result is generated.

[0048] Illustratively, the second pretreatment includes sample concentration, sample dilution, pH adjustment, and the like.

[0049] The preset organism types include a first bacterial colony, which indicates good water quality, and a second bacterial colony, which indicates poor water quality. The system identifies only organisms that can be used to determine water quality, improving identification efficiency. The system automatically adjusts the microscope magnification and collects detection images at different magnifications, reducing reliance on the observer's personal experience and subjective judgment and improving detection accuracy.

[0050] Specifically, in step 53, selecting an image to be analyzed from the N2 detected images includes the following steps: Step 531: extracting an arbitrary detection image, obtaining a total number of first pixel points in the arbitrary detection image, calculating a first ratio between the number of pixel points in the arbitrary detection image whose pixel value is equal to or greater than a second preset value and the first total number of pixel points, and calculating a second ratio between the number of pixel points in the arbitrary detection image whose pixel value is equal to or less than a third preset value and the first total number of pixel points.

[0051] Step 532: Determine whether the first ratio is less than a fourth preset value and the second ratio is less than a fifth preset value; if yes, determine that any detected image is an image that meets the criteria.

[0052] Step 533: After traversing all the detected images, one image that satisfies all the criteria is selected according to the preset criteria and is set as the image to be analyzed.

[0053] Preferably, a slide glass is prepared using clean water and observed, and an image is obtained at any magnification using the average pixel value of the image as the reference value, the product of the reference value and a first coefficient (e.g., 0.85) as the second preset value, and the product of the reference value and a second coefficient (e.g., 0.15) as the third preset value.

[0054] If the first ratio is equal to or greater than the fourth preset value, the detected image does not contain enough microorganisms and is not suitable for observation. If the second ratio is equal to or greater than the fifth preset value, the image contains contaminants and is not suitable for observation. After scanning all the detected images, the image to be analyzed is selected based on the image resolution, uniformity, etc.

[0055] Each image that meets the criteria can be analyzed, and the analysis results can be the average number of organisms of all preset types and each preset type, and based on this result, the water quality sample can be analyzed to obtain a second analysis result.

[0056] Step 6: Based on the first detection result and the second detection result, the water quality status of each sampling point in the detection water area is confirmed, and a water environment quality detection report is generated.

[0057] The first and second detection results are integrated, including the physical detection results, chemical detection results, biological detection results, collection time, detection time, etc. of each sampling point, and then the integrated data is comprehensively analyzed to evaluate the overall water environment quality of the water area under detection, and a water environment quality detection report is generated based on the integration and evaluation results.

[0058] Water environment quality detection based on multiple indicators can effectively improve the comprehensiveness and accuracy of detection.

[0059] Step 7: The water environment quality detection report is sent to the second mobile terminal of the person in charge.

[0060] FIG. 2 shows a block diagram of one embodiment of a water environment quality system using a portable detection device provided by the present invention. As shown in FIG. 2, the system: an area division module 101, which divides the detected water area into N1 sub-detection areas according to the length and width of the detected water area, and identifies the sampling points and coordinates of each sub-detection area, where N1 is a positive integer greater than or equal to 1; a trajectory generation module 102 for respectively obtaining position information of N1 detectors, generating a first running trajectory by scanning all sampling points in a first point set based on the position information of any detector, and sending the first running trajectory to a first mobile terminal 20 of the any detector, where the first point set is a set of sampling points in a sub-detection area corresponding to the any detector; A portable detection device (40) is used by any detector to sequentially transport the portable detection device to each sampling point in the first point set according to the first travel trajectory, and perform sampling and detection at each sampling point using the portable detection device (40), obtain water quality samples and detection data, and transmit the detection data to the water environment quality detection platform (10); a first detection module 103, which receives all the detection data in the detection water area, processes and analyzes all the detection data, and obtains a first detection result; a second detection module 104 for detecting and analyzing all water quality samples in the test water area and obtaining second detection results; a report generation module 105 for checking the water quality status of each sampling point in the detection water area based on the first detection result and the second detection result, and generating a water environment quality detection report; and a report sending module 106 for sending the water environment quality detection report to the second mobile terminal 30 of the person in charge.

Claims

1. Step 1: Dividing the detected water area into N1 sub-detection areas based on the length and width of the detected water area, and determining the sampling points and coordinates of each sub-detection area, where N1 is a positive integer greater than or equal to 1; Step 2: acquiring position information of each of the N1 detectors, generating a first travel trajectory by scanning all sampling points in a first point set based on the position information of any of the detectors, and sending the first travel trajectory to a first mobile terminal of the any of the detectors, wherein the first point set is a set of sampling points in a sub-detection area corresponding to any of the detectors; Step 3: any of the detectors sequentially transports a portable detection device to each sampling point in the first point set according to the first driving trajectory, and uses the portable detection device to sample and detect at each sampling point, obtain water quality samples and detection data, and send the detection data to the water environment quality detection platform; Step 4: after receiving all the detection data in the detection water area, processing and analyzing all the detection data to obtain a first detection result; Step 5: performing detection and analysis on all water quality samples in the detection water area and obtaining a second detection result; Step 6: based on the first detection result and the second detection result, confirm the water quality status of each sampling point in the detection water area, and generate a water environment quality detection report; and (7) transmitting the water environment quality detection report to a second mobile terminal of the person in charge.

2. In step 3, before sampling and detecting for each sampling point, the first coordinate of the first mobile terminal of any of the detectors is obtained in real time, and it is determined whether the first coordinate is within a predetermined range of any of the sampling points in the first point set. If so, a detection signal is issued to instruct any of the detectors to move to any of the sampling points to perform sampling and detecting.

3. The detection data includes various water quality parameters, and step 3 includes: Step 31: After obtaining the first detection data of a given sampling point, compare the value of each water quality parameter in the first detection data with the corresponding reference range to determine whether all water quality parameters are within the corresponding reference range. If the answer is YES, move to the next sampling point according to the first traveling path. If the answer is NO, proceed to step 32, where the water quality parameters include temperature, pH value, dissolved oxygen value, acidity or alkalinity, electrical conductivity, and / or turbidity. Step 32: obtaining a second sampling point and generating a second travel trajectory, and any of the detectors transporting a portable detection device to the second sampling point according to the second travel trajectory, where the second sampling point is located upstream of any of the sampling points and is a sampling point separated by a preset distance from any of the sampling points; Step 33: Sampling and detecting the second sampling point, obtaining second detection data of the second sampling point, comparing the values ​​of each water quality parameter in the second detection data with the corresponding standard range, respectively, to determine whether all water quality parameters are in line with the corresponding standard range; if NO, defining the second sampling point as an arbitrary sampling point; then returning to step 32; if YES, proceeding to step 34; Step 34: acquiring a third sampling point and generating a third travel trajectory, and any of the detectors transporting a portable detection device to the third sampling point according to the third travel trajectory, wherein the third sampling point is a sampling point in the first point set and located adjacent to and downstream of the second sampling point; 2. The method for detecting water environment quality using a portable detection device according to claim 1, further comprising: performing sampling and detection at the second sampling point, obtaining third detection data for the third sampling point, comparing the values ​​of each water quality parameter of the third detection data with the corresponding reference ranges, respectively, to determine whether all water quality parameters conform to the corresponding reference ranges; if yes, defining the third sampling point as the second sampling point; and then returning to step 34; if no, terminating the sampling and detection operation in step 35.

4. The detection data includes various water quality parameters, and step 4 includes: constructing 411 a first parameter type set that includes all water quality parameter types; Step 412: extracting any of the detection data, obtaining a second parameter type set corresponding to the any of the detection data, determining whether the second parameter type set is equal to the first parameter type set, and if NO, extracting parameter types that do not belong to the second parameter type set from the first parameter type set and defining them as first parameter types, where the second parameter type set is a set of parameter types of all water quality parameters in any of the detection data; Step 413: defining a sampling point corresponding to any of the detection data as a fourth sampling point, and acquiring a fifth sampling point based on the coordinates of the fourth sampling point, the fifth sampling point being located upstream or downstream of the fourth sampling point, and the detection data including a water quality parameter corresponding to the first parameter type; Step 414: obtaining a first water quality parameter value corresponding to the first parameter type at the fifth sampling point, obtaining a water flow velocity and a distance between the fourth sampling point and the fifth sampling point, and calculating a second water quality parameter value corresponding to the first parameter type at the fourth sampling point based on the first water quality parameter value, the water flow velocity and the distance; Step 415: supplementing the first parameter type and the second water quality parameter value to the detection data of the fourth sampling point to generate fourth detection data; and analyzing the fourth detection data to obtain a first analysis result. The method for detecting water environment quality using a portable detection device according to claim 1 , further comprising: step 416 of generating a third detection result after traversing all the detection data.

5. The detection data includes a water surface image of the sampling point, and step 4 includes: Step 421: performing a first pre-processing on the water surface image and defining it as a first image; inputting 422 the first image into a preliminary training model to generate a second image; Step 423: calculating a pixel difference value between a first pixel value of an i-th pixel point in the first image and a second pixel value of the i-th pixel point in the second image, and using the pixel difference value as the pixel value of the i-th pixel point in a third image; and generating the third image after traversing all pixel points in the first image, where i is a positive integer between 1 and I, and I is a total number of pixel points in the first image; Step 424: calculating an average pixel value of all pixel points in the third image, determining whether the average pixel value is equal to or greater than a first preset value, and if yes, determining that the water quality at the sampling points corresponding to the water surface image is abnormal, and if no, determining that the water quality at the sampling points corresponding to the water surface image is normal; The method for detecting water environment quality using a portable detection device according to claim 1 , further comprising: step 425 of generating a fourth detection result after traversing all the water surface images.

6. The method for generating a preliminary training model comprises: acquiring a first water surface image when the water quality at the sampling point corresponding to the water surface image is normal; The method for detecting water environment quality using a portable detection device as described in claim 5, characterized in that it includes training a neural network model using the first water surface image to obtain a generative model, and using the generative model as the preliminary training model.

7. Step 5 Step 51: extracting an arbitrary water quality sample as a detection sample and performing a second pretreatment on the detection sample to generate an analysis target sample; Step 52: preparing an observation sample based on the analysis target sample, and automatically acquiring N2 detection images at different magnifications, where N2 is a positive integer equal to or greater than 2; a step 53 of selecting an image to be analyzed from the N2 detected images, performing image recognition on the image to be analyzed, and identifying all of the organisms of the preset types in the image to be analyzed and the number of organisms of each preset type; analyzing any of the water quality samples based on all of the preset types of organisms and the number of organisms of each of the preset types to obtain a second analysis result; The method for detecting water environment quality using a portable detection device according to claim 1, further comprising: generating a second detection result after traversing all the water quality samples.

8. In the step 53, selecting an image to be analyzed from the N2 detected images includes: Step 531: extracting an arbitrary detected image, obtaining a total number of first pixel points in the arbitrary detected image, calculating a first ratio between the number of pixel points in the arbitrary detected image whose pixel value is equal to or greater than a second preset value and the first total number of pixel points, and calculating a second ratio between the number of pixel points in the arbitrary detected image whose pixel value is equal to or less than a third preset value and the first total number of pixel points; determining whether the first ratio is less than a fourth preset value and the second ratio is less than a fifth preset value, and if yes, determining that any of the detected images is a satisfying image; The method for detecting water environment quality using a portable detection device as described in claim 7, characterized in that it includes a step 533 of selecting one image from among images that satisfy all criteria according to predetermined criteria after traversing all detected images and setting it as the image to be analyzed.

9. A water environment quality detection system using a portable detection device for carrying out the method according to any one of claims 1 to 8, comprising: an area division module for dividing the detected water area into N1 sub-detection areas according to the length and width of the detected water area, and determining the sampling points and coordinates of each sub-detection area, where N1 is a positive integer greater than or equal to 1; a trajectory generation module that acquires position information of each of the N1 detectors, generates a first running trajectory by scanning all sampling points in a first point set based on the position information of any of the detectors, and sends the first running trajectory to a first mobile terminal of the any of the detectors, where the first point set is a set of sampling points in a sub-detection area corresponding to any of the detectors; Any of the detectors sequentially transports a portable detection device to each sampling point in the first point set according to the first travel trajectory, and uses the portable detection device to sample and detect at each sampling point, obtain water quality samples and detection data, and transmit the detection data to the water environment quality detection platform; a first detection module for receiving all the detection data in the detection water area, and then processing and analyzing all the detection data to obtain a first detection result; a second detection module for detecting and analyzing all water quality samples in the detection water area and obtaining a second detection result; a report generation module that checks the water quality status of each sampling point in the detection water area based on the first detection result and the second detection result, and generates a water environment quality detection report; and a report sending module for transmitting the water environment quality detection report to a second mobile terminal of a person in charge.

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