Micro water quality detection box based on microfluidic technology and image recognition

Abstract

The invention discloses a micro-fluidic technology and image recognition-based miniature water quality detection box, which is characterized in that to-be-detected liquid is dropwise added into a micro-fluidic detection chip through a sampling pump, and a camera is used for shooting a color developing image of the micro-fluidic detection chip; one end of the conveyor belt is wound on the release reel, and the other end is wound on the recovery reel; a plurality of microfluidic detection chips are distributed on the conveyor belt; the conveying device is used for driving the releasing reel and the recycling reel to rotate; the control unit is used for controlling the conveying device, the sampling pump and the camera, calculating the airing time required by color development after liquid dropping of the microfluidic detection chip according to temperature and humidity information acquired by the temperature and humidity sensor, and analyzing a color development result of an image shot by the camera through an image recognition algorithm. The miniature water quality detection box can comprehensively detect the water quality of a sample, realizes high efficiency of water quality sampling, is high in detection result precision, and aims to solve the problems of complexity and high cost of traditional water quality sampling detection and instrument operation.

Description

Technical Field

[0001] The present invention belongs to the technical field of water quality detection, and in particular relates to a micro water quality detection box based on microfluidics technology and image recognition. Background Art

[0002] Water is a vital resource for human survival and social development, and water quality safety is directly linked to the ecological environment and public health. With the acceleration of industrialization and the intensification of environmental pollution, water quality testing has become increasingly important in areas such as water source monitoring, wastewater treatment, and industrial process control. Traditional water quality testing methods rely on manual sampling followed by laboratory analysis. These methods suffer from long testing cycles, poor real-time performance, and high labor costs, making them inadequate for dynamic water quality monitoring in complex environments.

[0003] In recent years, water quality detection devices based on sensor technology have gradually become a research hotspot. By integrating sensors such as pH, conductivity, dissolved oxygen, and heavy metal ions, these devices can monitor water quality parameters online in real time, significantly improving detection efficiency. However, existing technologies still have many problems that need to be solved: On the one hand, sensor performance is easily affected by factors such as the adhesion of pollutants in the water and electrolyte interference, resulting in reduced detection accuracy and shortened sensor lifespan. This requires frequent calibration and maintenance, increasing equipment operating costs. For example, in water with high turbidity or rich in biofilm, the sensor surface is easily contaminated, resulting in measurement deviations.

[0004] On the other hand, traditional detection devices have limited data processing capabilities. Most are simply combinations of independent sensors, lacking the ability to deeply integrate and analyze multi-parameter data. Faced with massive amounts of test data, data mining makes it difficult to predict water quality trends and trace pollution sources, hindering comprehensive decision-making support for water quality management.

[0005] In addition, existing detection devices generally lack intelligent fault diagnosis and adaptive adjustment functions, and their stability and reliability are insufficient in complex environments.

[0006] With the development of the Internet of Things, big data, and artificial intelligence technologies, the water quality testing field is placing higher demands on intelligent, integrated, and low-maintenance equipment. Achieving high-precision collaborative detection with sensor arrays, building efficient data processing and analysis models, and reducing the maintenance complexity of equipment in practical applications are currently pressing technical challenges. Summary of the Invention

[0007] The present invention provides a micro water quality detection kit based on microfluidics technology and image recognition. The micro water quality detection kit can comprehensively detect the water quality of samples, achieve efficient water quality sampling, and highly accurate test results. It aims to solve the problems of complexity and high cost of traditional water quality sampling and testing and instrument operation.

[0008] In order to achieve the above object, the present invention adopts the following specific technical solutions: A micro water quality detection box based on microfluidics and image recognition, comprising a housing and a sampling pump, a temperature and humidity sensor, a camera, a consumable roll, a release reel, a recovery reel, and a control unit installed in the housing; The temperature and humidity sensor is used to detect the temperature and humidity inside the housing; The sampling pump is used to drip the liquid to be tested into the microfluidic detection chip, and a dripping station is set at the bottom; The camera is set in the horizontal direction, with a relative detection station set on the left side, which is used to capture the microfluidic detection chip in the detection station in real time and take a color image of the microfluidic detection chip after adding the test liquid and drying it; The consumable roll includes a conveyor belt and a plurality of microfluidic detection chips distributed along the length of the conveyor belt; one end of the conveyor belt is wound on a release reel, and the other end is wound on a recovery reel; The conveyor is located at the bottom of the sampling pump and is used to drive the release reel and the recovery reel to rotate, thereby transferring and guiding the consumables roll from the release reel to the recovery reel so that the microfluidic detection chip passes through the dripping station and the detection station in sequence; The control unit is used to control the conveying device, sampling pump and camera. It calculates the drying time required for the microfluidic detection chip to develop color after dripping liquid based on the temperature and humidity information collected by the temperature and humidity sensor, and analyzes the color development results of the image taken by the camera through the image recognition algorithm.

[0009] Furthermore, the conveying device includes a release motor, a recovery motor and a guide wheel; The unwinding motor and the rewinding motor are arranged in parallel and are both fixedly mounted on the housing; the unwinding motor is used to drive the unwinding reel to rotate; the rewinding motor is used to drive the rewinding reel to rotate; The guide wheel is fixedly mounted on the housing and is used to guide the conveyor belt tensioned between the release reel and the recovery reel. The microfluidic detection chip passes through the dripping station and the detection station by winding and unwinding the two ends of the conveyor belt. The control unit controls the rotation of the unwinding motor and the rewinding motor.

[0010] Furthermore, the camera has an LED fill light that provides lighting at a 50Hz strobe frequency.

[0011] Furthermore, the sampling pump is used to accurately add 0.05 ml of the test liquid to the microfluidic detection chip.

[0012] Furthermore, the camera uses wide-angle imaging.

[0013] Furthermore, the control unit is a single chip microcomputer.

[0014] Furthermore, the housing further includes an internal bracket; The sampling pump, temperature and humidity sensor, camera, release motor, recovery motor and guide wheel are all fixedly installed on the bracket.

[0015] Compared with the prior art, the technical solution of the present invention has the following beneficial effects: 1. Significantly improve detection efficiency and real-time performance The microfluidic detection chip, combined with a sampling pump for precise sample addition (0.05ml / time), and automated conveyor positioning enable rapid sample processing, reducing single-test time to minutes. Adaptive control of ambient temperature and humidity (dynamically adjusting drying time based on AHT20 sensor data) eliminates manual intervention and ensures continuous testing, meeting the real-time monitoring needs of water sources, sewage treatment plants, and other locations.

[0016] 2. Significantly reduce operation and maintenance costs and resource waste The "correction tape" consumable roll design supports rapid replacement of microfluidic detection chips (including large and small wheels and recycling shafts) without the need for equipment disassembly or professional maintenance, reducing downtime; micro-volume detection technology (requiring only 0.05ml of sample) reduces reagent consumption by more than 90%, and combined with the chip recycling mechanism, effectively controls waste generation, in line with the concept of green testing.

[0017] 3. Breakthrough of traditional detection accuracy bottleneck Dual cameras are used for collaborative positioning to ensure that the position error of the detection chip is ≤0.1mm, eliminating manual operation deviation; the temperature and humidity compensation algorithm automatically corrects the color reaction parameters (such as extending the drying time in high temperature and high humidity environments), improving data reliability in different environments and avoiding misjudgments due to environmental fluctuations.

[0018] 4. Intelligent empowerment of water quality management decisions A 2-megapixel camera with wide-angle imaging and image recognition algorithm are used to automatically analyze multiple parameters (pH, heavy metals, etc.), replacing manual colorimetry with an identification accuracy rate of >95%. The test results are uploaded to the data cloud, with integrated support for historical trend analysis and pollution tracing, providing data support for water quality early warning and process optimization, and facilitating the construction of smart water systems.

[0019] 5. High compatibility and scene adaptability Through the low-voltage design of the peristaltic pump and camera (camera 5V, peristaltic pump 12V), it can be adapted to mobile power supply and is suitable for scenarios without fixed power supply such as the wild and pipeline networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of the internal structure of the micro water quality detection box of the present invention; Figure 2 Schematic diagram of the internal structure of the micro water quality detection box of the present invention; Figure 3 Schematic diagram of the internal structure of the micro water quality detection box of the present invention; Figure 4 It is a schematic diagram of the three-dimensional structure inside the micro water quality detection box of the present invention.

[0021] Among them, 1-shell, 2-sampling pump, 3-camera, 4-release reel, 5-recovery reel, 6-temperature and humidity sensor, 7-guide wheel, 8-release motor, 9-recovery motor, 10-bracket. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] This embodiment provides a micro water quality detection kit based on microfluidics technology and image recognition, such as Figure 1 As shown in the structure, the micro water quality detection box includes a housing 1, a sampling pump 2, a camera 3, a release reel 4, a recovery reel 5, a temperature and humidity sensor 6, a consumable roll (not shown in the figure) and a control unit; the housing 1 can be a rectangular box with a door that can be opened and closed; the sampling pump 2, the camera 3, the release reel 4, the recovery reel 5, the temperature and humidity sensor 6, the consumable roll and the control unit are all installed in the housing 1; wherein: Temperature and humidity sensor 6 is used to monitor the temperature and humidity within housing 1, facilitating the calculation of the drying time of the microfluidic detection chip. Adafruit AHT20 temperature and humidity sensor 6 can be used for ambient temperature and humidity monitoring. It utilizes a standard I2C bus, a 3.3V voltage, I2C address 0x38, an operating temperature range of -40-85°C, and an operating relative humidity range of 0-100% RH. The data collected by temperature and humidity sensor 6 is primarily used to estimate the drying time of the microfluidic detection chip and determine the maximum sampling step size, thereby minimizing time waste and providing real-time detection results. Furthermore, temperature and humidity are parameters that influence the colorimetric reaction. Analyzing these parameters during training and recognition allows for a more accurate model, ensuring accurate detection results under varying environmental conditions (temperature and humidity within housing 1).

[0024] Sampling pump 2 is used to precisely drip 0.05ml of the test liquid onto the microfluidic detection chip. A dripping station is provided at the bottom. Sampling pump 2 uses a DC12V Intllab 220 model with a DC 12V operating voltage. During the first test, the camera 3 on the right calibrates the position, then the peristaltic pump is activated, dripping 0.05ml of the test liquid onto the microfluidic detection chip and waiting for testing. For subsequent tests, simply drip 0.05ml of the test liquid directly into the original location. Sampling pump 2 has a sampling tube extending from the housing 1 to allow the sample to be introduced into the housing 1.

[0025] Camera 3 is positioned horizontally, with the inspection station positioned to the left. It captures the microfluidic detection chip in real time and captures a color image of the chip after the test liquid is added and dried. Camera 3 uses the Shengyue Digital GS02LED Camera 3 module, which uses a built-in LED fill light with a 50Hz strobe frequency. The 5V drive voltage facilitates microcontroller control of the camera and lighting, miniaturizing the device. Camera 3 uses a 2-megapixel, 100-degree wide-angle lens for wide-angle imaging.

[0026] The consumable roll includes a conveyor belt and multiple microfluidic detection chips distributed along the length of the conveyor belt; the conveyor belt with the microfluidic detection chip is wound on a reel to form a roll; one end of the conveyor belt is wound on the release reel 4, and the other end is wound on the recovery reel 5; the consumable roll and the release reel 4 and the recovery reel 5 are used as a set, which is convenient for overall replacement; when in use, the release reel 4 wrapped with the consumable roll and the recovery reel 5 fixedly connected to one end of the consumable roll are installed in the shell 1.

[0027] The conveying device is located at the bottom of the sampling pump 2 and is used to drive the release reel 4 and the recovery reel 5 to rotate, so as to transfer and guide the consumables roll from the release reel 4 to the recovery reel 5 so that the microfluidic detection chip passes through the dripping station and the detection station in sequence. Figure 2 、 Figure 3 and Figure 4 As shown, the conveying device includes a release motor 8, a recovery motor 9 and a plurality of guide wheels 7; the unwinding motor and the recovery motor 9 are arranged in parallel and are both fixedly mounted on the housing 1; the unwinding motor is used to drive the release reel 4 to rotate; the recovery motor 9 is used to drive the recovery reel 5 to rotate; the guide wheels 7 are fixedly mounted on the housing 1 and are used to guide the conveyor belt tensioned between the release reel 4 and the recovery reel 5, and the microfluidic detection chip passes through the dripping station and the detection station by winding and unwinding at both ends of the conveyor belt. In this embodiment, as shown in FIG. Figure 2As shown, three guide wheels 7 are installed in the housing 1. The three guide wheels 7 are distributed at the three vertices of a right triangle, so that the conveyor belt passing around the three guide wheels 7 forms a horizontal section and a vertical section. The driving voltage of the unwinding motor and the rewinding motor 9 is 12V. When multiple guide wheels 7 are used to guide the conveyor belt, the guide wheels 7 can be selected with different diameters according to the actual position, such as Figure 4 As shown, the guide wheel 7 on the left and the two guide wheels 7 on the right have different diameters.

[0028] The control unit is used to control the conveyor, sampling pump 2, and camera 3. It calculates the drying time required for color development after liquid dripping onto the microfluidic detection chip based on the temperature and humidity information collected by the temperature and humidity sensor 6. It also analyzes the color development results using an image recognition algorithm based on the images captured by camera 3. The control unit controls the rotation of the conveyor's unwinding and rewinding motors 9, maintaining a constant tension between the release reel 4 and the rewinding reel 5 by controlling their rotational speeds. The control unit can be a single-chip microcomputer.

[0029] The shell 1 of the above-mentioned micro water quality detection box also includes an internal bracket 10; the sampling pump 2, temperature and humidity sensor 6, camera 3, release motor 8, recovery motor 9 and guide wheel 7 are supported by the internal bracket 10, and the sampling pump 2, temperature and humidity sensor 6, camera 3, release motor 8, recovery motor 9 and guide wheel 7 are all fixedly mounted on the bracket 10. The bracket 10 can be a support plate, and the sampling pump 2, temperature and humidity sensor 6, camera 3, release motor 8, recovery motor 9 and guide wheel 7 are supported at a suitable position and height by the bracket 10. The sampling pump 2 is located at the highest point, and the release motor 8 and recovery motor 9 are located at the sampling Below the pump 2, the camera 3 is located on the right side of the recovery motor 9, and the temperature and humidity sensor 6 is located above the camera 3 and as close as possible to the microfluidic detection chip to detect the actual environmental temperature and humidity of the microfluidic detection chip; the guide wheel 7 is distributed above and to the right side of the recovery motor 9 and the guide wheel 7, and is used to guide the conveyor belt of the consumable roll so that the conveyor belt forms a horizontal section below the sampling pump 2 and a vertical section on the left side of the camera 3. The dripping station is located directly below the sampling pump 2 and is formed by the horizontal section of the conveyor belt. The detection station is opposite to the camera 3 and is located on the left side of the camera 3. The detection station is formed on the vertical section of the conveyor belt.

[0030] In the aforementioned micro water quality testing kit, the movement of the release motor 8 and the recovery motor 9 is controlled by a single-chip microcomputer. During the initial test, they work in conjunction with the camera 3 to calibrate the microfluidic detection chip. After the microfluidic detection chip is left to stand for color development and drying, the single-chip microcomputer controls the release motor 8 and the recovery motor 9 to rotate, cooperating with the camera 3 to transport the microfluidic detection chip to the testing station. Subsequent testing processes require only static waiting. After color development is complete, the developed microfluidic detection chip is transported to the testing station for inspection. After the inspection is complete, as the release motor 8 and the recovery motor 9 continue to rotate, the tested microfluidic detection chip is reeled into the recovery reel 5 and collected there as waste. To replace the detection chip, simply remove the existing release reel 4 and recovery reel 5 and replace them with the release reel 4 and recovery reel 5 with a consumable roll (similar to correction tape).

[0031] The conveyor belt is activated simultaneously with the camera 3 module. During the first inspection, the microcontroller controls the release motor 8 and the recovery motor 9 based on the image captured by camera 3. When the first inspection chip reaches the position directly opposite camera 3, the microcontroller controls the release motor 8 and the recovery motor 9 to stop. The time required for the chip to develop color and dry is calculated based on the temperature and humidity data. After drying, the release motor 8 and the recovery motor 9 are controlled to move. When the inspection chip appears directly opposite camera 3, the release motor 8 and the recovery motor 9 are controlled to stop. At this point, the chip has been inspected. After image recognition, the lights are turned off to save power, and the drying time is calculated, waiting for the second inspection to start.

[0032] The method of using the above-mentioned micro water quality detection kit is as follows: Step 1: System Initialization and Environmental Calibration: Power on the device, and the MCU automatically reads the data from the temperature and humidity sensor 6. The chip's drying time is calculated based on the real-time temperature and humidity (for example, 30 seconds at 25°C and 50% RH, extended according to the algorithm in high-temperature and high-humidity environments). The right camera 3 is turned on, and the LED fill light provides illumination at a 50Hz strobe frequency.

[0033] Step 2: Chip positioning and sample loading for the first test: The consumable roll carrying the test chip is installed on the conveyor device (similar to the correction tape replacement mechanism); the single-chip microcomputer controls the release motor 8 and the recovery motor 9 to rotate, thereby driving the conveyor belt to unwind from the release reel 4, and the recovery reel 5 retracts the conveyor belt at the other end, and the camera 3 captures the chip position in real time; when the chip moves to face the camera 3, the stop signal is triggered; the peristaltic pump is started, and 0.05ml of the water sample to be tested is accurately added to the chip detection area; the conveyor belt stops, and the system waits for the color development reaction to complete according to the drying time calculated in step 1.

[0034] Step 3: Image Recognition and Data Acquisition: After color development is complete, the microcontroller controls the release motor 8 and the recovery motor 9 to rotate. The chip is then transported via a conveyor belt to the inspection station directly opposite camera 3, with the LED fill light fully illuminated. Camera 3 captures a 2-megapixel wide-angle image (100° field of view) and uses an image recognition algorithm to analyze the color development results (e.g., colorimetric determination of pH and heavy metal concentration). Once recognition is complete, the LED light is immediately turned off to conserve power, and the data is uploaded to the cloud or local storage.

[0035] Step 4: Waste recovery and continuous testing: The chips that have completed the test are rolled up to the recovery reel 5 for centralized storage along with the movement of the conveyor belt; no repositioning is required for subsequent testing: 0.05ml of new sample is directly added in situ, and the system automatically reuses the calibrated position parameters; when the chip is exhausted, the entire consumable roll (including the release reel 4, the recovery reel 5, the consumable roll and the unused test chip) is replaced.

[0036] The principle of the above-mentioned micro water quality detection box using image recognition algorithm to perform water quality detection is as follows: 1. Image Acquisition Collection method: Use industrial cameras or other cameras 3 to take pictures; Key points: (1) Ensure lighting consistency. Ensure that lighting conditions are stable and uniform, and avoid shadows and highlights, because lighting can significantly affect color perception. Using a standard light box or a stable light source environment is the best practice; (2) Background selection. Use a neutral, non-reflective background to avoid background color interfering with the judgment of sample color; (3) Clear focus. Ensure that the image is clear and details are visible; (4) Image resolution. Select the appropriate resolution based on the analysis requirements, ensuring both details and computational efficiency.

[0037] 2. Image preprocessing, including: Noise Reduction: Use filters (such as Gaussian filtering and median filtering) to remove random noise from the image.

[0038] Contrast Enhancement: Use methods such as histogram equalization or adaptive histogram equalization (CLAHE) to enhance image contrast and make color differences more obvious.

[0039] Color Space Conversion: Depending on your analysis needs, you may need to convert an image from the RGB color space to another space, such as HSV (hue, saturation, value), Lab (CIELAB, a color space closer to human perception), or grayscale. HSV is useful for separating color and brightness information, while Lab is more intuitive for calculating color differences. This feature is currently in the experimental stage.

[0040] Geometric Correction: If the shooting angle causes the image to be deformed, a perspective transformation or an affine transformation is required to correct it.

[0041] 3. Target area positioning and segmentation, including: Thresholding: When the background and target colors differ significantly, segmentation is performed by setting a color or grayscale threshold. This can be set manually or using an adaptive thresholding method.

[0042] Edge Detection: Use operators such as Sobel and Canny to detect the edges of the target area, and then find the area through contour analysis.

[0043] Region Growing: Starting from a seed point, neighboring pixels are merged into a region based on color similarity.

[0044] Morphological Operations: Use operations such as erosion, dilation, opening, and closing to remove small noise points, fill area holes, and connect broken areas.

[0045] Template Matching: If the shape of the colored area is fixed, use the template image to search for matching positions in the original image.

[0046] Machine learning methods: Use trained Resnet101, transformer, timm classifier or object detection model to locate and segment complex color areas.

[0047] Fourth, color feature extraction aims to extract values or vectors that can represent the color characteristics of the located area, including: Color Histogram: Calculates the pixel distribution of each channel in a specific color space (such as HSV or Lab). Histogram similarity can be compared across different regions.

[0048] Color Mean / Median: Calculates the average or median value of all pixels in a region for a color channel (such as the red channel or Hue value). This is one of the most commonly used methods for quantifying color intensity or hue.

[0049] Color standard deviation: Calculates the variance of color values, reflecting the uniformity of color within an area.

[0050] Specific color ratio: The ratio of pixels of a specific color (such as red or blue) in the statistical area.

[0051] 5. Analysis and interpretation of results, including: Threshold judgment: Compare the extracted color features (such as mean, proportion) with the preset threshold to determine whether the color development result is positive, negative, or to which level it belongs.

[0052] Classification: If there are multiple possible color rendering results, use the trained Resnet101, transformer, and timm classifiers to classify the extracted features.

[0053] Quantitative analysis: The color mean or the proportion of a specific color can be directly used as a quantitative indicator.

[0054] Comparative analysis: Compare the color development characteristics of different samples, different time points or different treatment groups to find out the differences.

[0055] 6. Output and Reporting, including: Visualization: Mark the analysis area on the original image, overlay color bars, numerical labels, etc.

[0056] Data table: Generates a table containing sample ID, analysis area, color feature value, judgment results, etc.

[0057] Report generation: Automatically generate reports containing images, data, and analysis conclusions.

[0058] Obviously, those skilled in the art may make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the present invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims and their equivalents, the present invention is intended to include such modifications and variations.

Claims

1. A micro water quality detection kit based on microfluidics technology and image recognition, characterized in that: It includes a housing and a sampling pump, a temperature and humidity sensor, a camera, a consumable roll, a release reel, a recovery reel, and a control unit installed in the housing; The temperature and humidity sensor is used to detect the temperature and humidity inside the housing; The sampling pump is used to drip the liquid to be tested into the microfluidic detection chip, and a dripping station is set at the bottom; The camera is set in the horizontal direction, with a relative detection station set on the left side, which is used to capture the microfluidic detection chip in the detection station in real time and take a color image of the microfluidic detection chip after adding the test liquid and drying it; The consumable roll includes a conveyor belt and a plurality of microfluidic detection chips distributed along the length of the conveyor belt; one end of the conveyor belt is wound on a release reel, and the other end is wound on a recovery reel; The conveyor is located at the bottom of the sampling pump and is used to drive the release reel and the recovery reel to rotate, thereby transferring and guiding the consumables roll from the release reel to the recovery reel so that the microfluidic detection chip passes through the dripping station and the detection station in sequence; The control unit is used to control the conveying device, sampling pump and camera. It calculates the drying time required for the microfluidic detection chip to develop color after dripping liquid based on the temperature and humidity information collected by the temperature and humidity sensor, and analyzes the color development results of the image taken by the camera through the image recognition algorithm.

2. The micro water quality detection kit according to claim 1, wherein: The conveying device includes a release motor, a recovery motor and a guide wheel; The unwinding motor and the rewinding motor are arranged in parallel and are both fixedly mounted on the housing; the unwinding motor is used to drive the unwinding reel to rotate; the rewinding motor is used to drive the rewinding reel to rotate; The guide wheel is fixedly mounted on the housing and is used to guide the conveyor belt tensioned between the release reel and the recovery reel. The microfluidic detection chip passes through the dripping station and the detection station by winding and unwinding the two ends of the conveyor belt. The control unit controls the rotation of the unwinding motor and the rewinding motor.

3. The micro water quality detection kit according to claim 1, wherein: The camera has an LED fill light that provides lighting at a 50Hz strobe frequency.

4. The micro water quality detection kit according to claim 1, wherein: The sampling pump is used to accurately add 0.05 ml of the liquid to be tested to the microfluidic detection chip.

5. The micro water quality detection kit according to claim 1, wherein: The camera uses wide-angle imaging.

6. The micro water quality detection kit according to claim 1, wherein: The sampling pump is a peristaltic pump.

7. The micro water quality detection kit according to claim 1, wherein: The control unit is a single chip microcomputer.

8. The micro water quality detection kit according to any one of claims 1 to 7, characterized in that: The housing also includes an internal bracket; The sampling pump, temperature and humidity sensor, camera, release motor, recovery motor and guide wheel are all fixedly installed on the bracket.

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