An intelligent cleaning ship system for water areas

Abstract

The utility model relates to a water area intelligent cleaning ship system, relate to ship control technical field, including ship body, setting visual unit at bow, and setting main control unit and communication unit on ship body, the ship body is along the bow side and is provided with the grab device at the ship side, the visual unit is composed of binocular high definition camera and image processing module, binocular high definition camera is electrically connected with image processing module, the main control unit is composed of microcontroller and propulsion motor, microcontroller is electrically connected with visual unit, propulsion motor and grab device, the system uses binocular high definition camera to combine NVIDIA Jetson Nano image processing module, is based on triangulation principle and YOLOv5s algorithm, and fuses with laser radar data, realizes high accuracy identification to floating garbage, can also obtain target three -dimensional coordinate and water surface scene panorama simultaneously, so important data support is provided for accurate capture and path planning.

Description

Technical Field

[0001] This utility model relates to the field of ship control technology, and more specifically, to an intelligent waterway cleaning vessel system. Background Technology

[0002] In recent years, China has placed significantly greater emphasis on ecological and environmental governance. For example, the Environmental Protection Law of the People's Republic of China and the Action Plan for Water Pollution Prevention and Control ("Water Ten Measures") explicitly require improvements in the environmental governance of rivers, lakes, and other water bodies. Unmanned surface vessel (USV) technology, as an emerging method, has attracted considerable attention from local governments and enterprises. Fully automated cleaning USVs, with their low cost and high efficiency, have become an important tool for clearing floating debris, and their market penetration rate is gradually increasing.

[0003] Currently, net-type cleaning vessels and ordinary electric salvage cleaning vessels are commonly used equipment for waterway cleaning operations. Net-type cleaning vessels use V-shaped or U-shaped nets installed at the front of the hull to physically intercept floating garbage on the water surface. The nets, made of high-strength synthetic fibers, can effectively capture large floating objects such as plastic bottles and packaging bags. Some vessel models are also equipped with conveyor belts or lifting devices to achieve automatic garbage collection. However, these cleaning vessels have obvious limitations: their targets are limited to large floating objects on the water surface, and they are unable to handle tangled objects, accumulated garbage, or garbage attached to the shore or aquatic plants; they lack intelligent recognition capabilities, relying entirely on garbage to drift naturally into the net, and cannot actively locate scattered or highly mobile garbage, nor can they distinguish between garbage and harmless floating objects, easily leading to mis-interception or omission.

[0004] Ordinary electric salvage and cleaning boats mainly rely on electric power and manual control to complete operations. Their hulls are made of corrosion-resistant materials, and their power systems are powered by batteries. They collect garbage through deflectors, interception nets, or roller-type mesh belts at the bow. However, these cleaning boats also have many shortcomings: the gripping device structure is fixed, making it difficult to accurately grab scattered or irregularly floating garbage, and the speed adjustment method is crude and cannot be flexibly adjusted according to actual operational needs, resulting in low operational efficiency.

[0005] Therefore, in view of the above-mentioned technical shortcomings, an intelligent waterway cleaning boat system is proposed. Utility Model Content

[0006] The present invention aims to address the aforementioned technical deficiencies by proposing an intelligent waterway cleaning vessel system. This system integrates functions such as intelligent identification, autonomous grasping, and hull plate adjustment to achieve efficient cleaning of garbage in urban and scenic waterways.

[0007] This utility model provides an intelligent waterway cleaning boat system, including a hull, a vision unit installed at the bow, and a main control unit and a communication unit installed on the hull. The hull is equipped with a grabbing device along the front side of the hull. In use, the grabbing device is used to grab water debris from the river surface. The vision unit consists of a binocular high-definition camera and an image processing module. The binocular high-definition camera is electrically connected to the image processing module. In use, the image processing module is used to receive the images transmitted by the binocular camera and generate coordinates after processing the transmitted images. The main control unit consists of a microcontroller and a propulsion motor. The microcontroller is electrically connected to the vision unit, the propulsion motor, and the grasping device. The drive shaft of the propulsion motor is connected to the propeller connecting shaft of the hull. In use, the grasping device is used to receive images and coordinates from the vision unit and perform grasping actions. The communication unit consists of a wireless communication module, which is electrically connected to the microcontroller. In use, the microcontroller can interact with an external remote monitoring platform through the wireless communication module.

[0008] Preferably, the microcontroller is an STM32 series microcontroller, and is equipped with a timer and counter module. The main control unit also includes a motor driver. The microcontroller is electrically connected to the motor driver, and the motor driver is electrically connected to the propulsion motor.

[0009] Preferably, the image processing module can be a Nano core board, and the wireless communication module can be a Wi-Fi module, a LoRa wireless communication module, and a 4G communication module for data communication.

[0010] Preferably, the vision unit further includes a lidar, which is electrically connected to the microcontroller. In use, the lidar can acquire the distance and outline of obstacles in real time.

[0011] Preferably, the grasping device is a multi-degree-of-freedom robotic arm, which includes an actuator and a path planning module. The actuator is a 5-degree-of-freedom servo motor, and the path planning module consists of an Arduino control module and a ROS robot operation module. In use, the robotic arm can perform grasping actions according to the path planning module.

[0012] Preferably, the hull is also equipped with a power supply module, which consists of a high-capacity lithium battery pack and a solar photovoltaic panel. In use, the power supply module is used to provide power support for the shipboard equipment.

[0013] Preferably, the bow of the hull is also provided with a guide rail and an electric push rod. The electric push rod includes at least two push rods and is provided on the hull. The telescopic rod of the electric push rod passes through the guide rail and extends toward the bow. At the same time, a lifting device is provided at the end of the electric push rod facing the bow. The lifting device can be any one of an electric telescopic rod or a screw jack. Both the electric push rod and the lifting device are electrically connected to the microcontroller. Below the lifting device is a box-shaped hull plate. The upper surface of the hull plate is connected to the lifting end of the lifting device. In use, the lifting device can move the hull plate up and down.

[0014] Preferably, the hull is also equipped with a water quality monitoring module and a positioning module. The water quality monitoring module consists of a pH sensor, a dissolved oxygen sensor, a turbidity sensor and a signal converter. The pH sensor, dissolved oxygen sensor and turbidity sensor are installed in the bottom of the hull or in the sampling chamber. At the same time, the signal converter, pH sensor, dissolved oxygen sensor and turbidity sensor are all electrically connected to the signal converter.

[0015] Preferably, the positioning module consists of a GPS, a Beidou navigation receiver, and an IMU inertial measurement unit. In use, the positioning module enables the cleaning vessel to perform coordinate positioning and to plan its path using the positioning coordinates.

[0016] The beneficial effects of this utility model are as follows: 1. Compared with existing technologies, this system uses a binocular high-definition camera combined with an NVIDIA Jetson Nano image processing module, based on the principle of triangulation and the YOLOv5s algorithm, and fuses with LiDAR data to achieve high-precision identification of floating debris. At the same time, it can also acquire the target's three-dimensional coordinates and a panoramic view of the water surface scene, thus providing important data support for accurate grasping and path planning.

[0017] 2. By employing a multi-degree-of-freedom robotic arm architecture and coordinating the work of vision units, this system enables the cleaning vessel to achieve high-precision garbage grabbing in complex aquatic environments. It can automatically identify and grab various types of floating garbage, effectively improving cleaning efficiency and automation levels, and significantly reducing human intervention.

[0018] 3. This system, by installing hull plates and lifting devices at the bow, enables the initial centralized collection of large areas of floating debris, improving the efficiency of debris collection and enhancing the ship's resistance to capsizing under wind and wave conditions, thereby effectively improving the ship's reliability and adaptability. Attached Figure Description

[0019] Figure 1 This is a structural diagram of the hull of an intelligent waterway cleaning boat system according to the present invention.

[0020] Figure 2 This is a schematic diagram of the connection of an intelligent waterway cleaning boat system according to the present invention.

[0021] Figure 3 This diagram shows the connection between the main control unit, power supply module, and water quality monitoring module in this solution.

[0022] Figures 1-3 In the main control unit: 1-hull; 11-grabbing device; 12-guide rail; 13-electric push rod; 14-lifting device; 15-hull plate; 2-microcontroller; 21-motor driver; 22-propulsion motor; 3-communication unit; 4-visual communication module; 5-vision unit; 6-binocular high-definition camera; 7-image processing module; 8-lidar; 9-water quality monitoring module; 10-pH sensor; 11-dissolved oxygen sensor; 12-turbidity sensor; 13-signal converter; 14-power supply module; 15-lithium battery pack; 16-solar photovoltaic panel; 17-power conversion module; 18-positioning module. Detailed Implementation

[0023] The technical solution of this utility model will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of this utility model, and not all embodiments. Based on the embodiments of this utility model, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this utility model.

[0024] As attached Figure 1 To be continued Figure 3 A smart water cleaning boat system includes a hull 1, a main control unit, a communication unit, and a vision unit. The hull 1 has a gripping device 11 installed along the front side of the hull. In use, the gripping device 11 can grab water debris on the river surface. The main control unit and the communication unit are located inside the hull 1, and the vision unit is located at the bow of the hull 1. In use, the main control unit is used to control the propulsion speed of the hull 1, the communication unit is used to remotely control the main control unit, and the vision unit is used to identify the debris on the water surface and record its coordinate information.

[0025] The main control unit includes: microcontroller 2, motor driver 21 and propulsion motor 22. The microcontroller 2 can be an STM32 series microcontroller, which is equipped with timer and counter modules. During installation, the microcontroller 2 is electrically connected to the motor driver 21, and the motor driver 21 is electrically connected to the propulsion motor 22. At the same time, the drive shaft of the propulsion motor 22 is also connected to the propeller connecting shaft at the hull 1.

[0026] During use, users can flexibly set the PWM period from 1ms to 2ms using the STM32's built-in timer module and adjust the duty cycle parameter in real time as needed. Dynamic adjustment of the duty cycle changes the duration of the high-level power supply to the propulsion motor 22, thereby achieving precise control of the propulsion motor 22's speed. After the PWM signal output by the microcontroller 2 is transmitted to the motor driver 21, the motor driver 21 finely adjusts the power output of the propulsion motor 22 according to the duty cycle command. This allows the propulsion motor 22 to achieve smooth and continuous stepless speed regulation under different operating conditions, such as stationary, low speed (cleaning state), medium speed, and high speed (cruising / returning), effectively meeting the power requirements of diverse operating scenarios.

[0027] The wireless communication module 3 is electrically connected to the microcontroller 2, and the external remote monitoring platform (such as the platform's early warning center or the user's mobile phone) interacts remotely with the microcontroller 2 through the wireless communication module 3. The wireless communication module 3 can use a Wi-Fi module, a LoRa wireless communication module, or a 4G communication module for data communication. To ensure communication quality, the cleaning vessel can communicate with the shore-based early warning center via Wi-Fi, LoRa, or 4G.

[0028] During operation, the Wi-Fi module is suitable for short-range, high-speed debugging, the LoRa module enables long-range, low-power command transmission, and the 4G module supports real-time image transmission, multi-sensor data feedback, and remote task assignment. Simultaneously, users can view real-time details such as the cleaning vessel's location, operational status, and task progress via a terminal (platform early warning center or user's mobile phone), and remotely control and schedule it. Furthermore, the system automatically uploads task status data, including coordinates, speed, garbage collection volume, and water quality monitoring data, according to a preset cycle. Upon detecting obstacles, abnormal positioning, or equipment malfunctions, the system immediately triggers an alarm mechanism and records detailed logs.

[0029] The vision unit includes: a binocular high-definition camera 4, an image processing module 41, and a lidar 42. The binocular high-definition camera 4 is electrically connected to the image processing module 41, and the binocular high-definition camera 4, the image processing module 41, and the lidar 42 are also electrically connected to the microcontroller 2. Meanwhile, the image processing module 41 can be a Nano core board (such as NVIDIA Jetson Nano).

[0030] In practical use, the binocular high-definition camera 4 transmits the synchronously acquired left and right images to the image processing module 41 (Nano core board) via an interface. Based on the triangulation principle, pixel disparity is calculated, a 3D depth map is generated, and the (X,Y,Z) coordinates of the target in the camera coordinate system are output. Triangulation is a mature technology widely used in stereo vision for calculating target depth. Simultaneously, the Nano core board runs the YOLOv5 target detection algorithm to identify and classify common floating waste such as plastic bottles and packaging bags in real time, ensuring highly reliable detection results through a confidence-based screening mechanism. It is important to note that YOLOv5, as a single-stage target detection algorithm, has formed a complete technical system in the field of image recognition. The YOLOv5 target detection algorithm and the triangulation principle for calculating pixel disparity designed here are both existing, well-known technologies. After the detected 2D bounding box and depth map data are fused in spatial coordinates on the Nano core board, the generated 3D coordinate data is transmitted to the main STM32 microcontroller 2 via serial bus as input parameters for path planning and robotic arm control. At the same time, the labeled image data is synchronously uploaded to a remote monitoring platform or local storage system for job recording and data analysis. In addition, after the lidar 42 is connected to the microcontroller 2, it can acquire the distance and contour information of obstacles in real time and fuse them with the visual recognition results to form a panoramic view of the water scene. When an obstacle or non-grasping target is detected, the system automatically calls the navigation algorithm (position and attitude information provided by GNSS and IMU) to perform path detour or heading adjustment.

[0031] The gripping device 11 adopts a multi-degree-of-freedom robotic arm architecture based on Arduino control, integrating actuators and path planning modules. The actuators use a 5-degree-of-freedom servo structure, which can accurately complete operations such as rotation, lifting, and gripping. The path planning supports dual modes of Arduino control system and ROS robot operating system. The former meets basic control requirements, while the latter relies on the rosserial_arduino library to realize complex path planning and multi-degree-of-freedom collaborative control. The robotic arm communicates stably with the microcontroller 2 through the I2C interface. During system operation, the binocular camera recognition system, in conjunction with YOLO series algorithms, first acquires the spatial coordinates of the target waste, which are then converted into task points in the robotic arm's working coordinate system by the main control system. Subsequently, the path planning module is activated, running a path planning algorithm to generate the shortest collision-free path and calling a grasping posture optimization algorithm to determine the optimal grasping angle by combining the target angle, shape, and obstacle information. Finally, it outputs a grasping sequence command containing parameters such as time step and servo motor rotation angle. During the execution phase, the multi-servo motor system controls the robotic arm's various degrees of freedom to move in coordination according to the commands, providing real-time feedback on servo motor positions to ensure action accuracy and support dynamic adjustments. After the waste is grasped, it is transferred to the ship's sorting and disposal compartment. After the action is completed, the system automatically records the waste type, grasping time, and location data for review and analysis, and the robotic arm resets to standby. Meanwhile, this system, based on a robotic arm and vision collaborative architecture, can effectively resist coordinate offset problems caused by dynamic targets or water flow disturbances. Furthermore, through deep collaboration between path planning and grasping posture optimization algorithms, it achieves a grasping success rate of over 85% in experimental environments. Additionally, it's important to note that Arduino control technology is a well-known, existing technology widely used in motor drive and sensor control scenarios, possessing strong open-source characteristics and a mature application foundation. ROS is also an existing open-source robot operating system, providing hardware abstraction, device control, and inter-process communication functions. Communication between Arduino and ROS can be achieved through libraries such as rosserial_arduino.

[0032] Furthermore, the actuators of the multi-degree-of-freedom robotic arm architecture can also be pneumatically driven systems, that is, cylinder extension and retraction controlled by solenoid valves (such as pneumatic manipulators in the prior art). This design allows the original servo motor (5-DOF servo motor) drive to be replaced, thus improving the robotic arm's corrosion resistance and reliability in humid environments.

[0033] Furthermore, the cleaning vessel system also includes a power supply module 6, which consists of a large-capacity lithium battery pack 61, a solar photovoltaic panel 62, and a power conversion module 63. The lithium battery pack 61 serves as the main power source for the vessel, providing continuous power to the propulsion motor 22, robotic arm, binocular camera, and various sensors. The solar photovoltaic panel 62 is installed on the top of the hull 1, using sunlight during the day to charge the battery, reducing the consumption of the lithium battery power, or maintaining the system operation under low load. The power conversion module 63 is responsible for DC-DC step-up / step-down and MPPT control to optimize power utilization.

[0034] In addition, to ensure power supply safety, power supply module 6 can also be equipped with a battery management module for monitoring voltage, current, and temperature, as well as an energy dispatch system. This enables power distribution management, automatic load identification and switching logic, and provides stable 5V / 12V voltage output to different modules. The system has a low-power standby mechanism, which can be woken up periodically or by task triggering. In terms of implementation, the main battery pack prioritizes powering high-load modules (such as propulsion motor 22 and robotic arm), while medium-load devices such as vision units and sensors can be powered by solar energy or woken up from standby. When there are no tasks, the system automatically enters a low-power standby mode to reduce unnecessary power consumption. The system monitors the voltage and current of each module in real time. If the voltage is detected to be below the safety threshold, a power alarm will be triggered or the hull 1 will be instructed to return automatically. At the same time, power data will be uploaded to a remote platform for status recording and maintenance prediction. This power supply module 6 design enhances the endurance of the cleaning vessel, making it particularly suitable for long-term daytime cruising. Its intelligent management and fault-tolerant protection functions can prevent system paralysis due to exhaustion of a single path. The structure is simple and reliable, making it suitable for mass deployment in large-area water application scenarios. Finally, it should be noted that the technologies involved in the aforementioned power supply module 6, such as battery management, energy dispatch, and low-power standby, are all existing well-known technologies, and their specific implementation processes and configuration parameters will not be elaborated further.

[0035] Furthermore, a guide rail 12 and an electric push rod 13 are provided at the bow of the hull 1. At least two electric push rods 13 are mounted on the hull 1, and their telescopic arms pass through the guide rail 12 and extend towards the bow. A lifting device 14 is provided at the bow-facing end of the electric push rod 13. This lifting device 14 can be either an electric telescopic rod or a screw jack. Below the lifting device 14 is a hull plate 15, the upper surface of which is connected to the lifting end of the lifting device 14. In use, the lifting device 14 can move the hull plate 15 up and down. For ease of salvage, the hull plate 15 can be designed as a filter screen to facilitate water filtration during salvage. Both the electric push rod 13 and the lifting device 14 are electrically connected to a microcontroller 2. This design allows the microcontroller 2 to easily issue operating commands to the lifting device 14 and the electric push rod 13.

[0036] In addition, the hull plate 15 can be designed as a box structure. This design allows garbage on the water surface to be lifted along with the water to the bow of the ship. After being lifted, it is convenient for the robotic arm to grab the garbage and can also suppress the drift of the garbage. On the other hand, when the hull plate 15 is raised, the freeboard height can be increased, which can improve the equipment's anti-capsulation ability during wind and waves or during the acceleration phase of navigation.

[0037] like Figure 2 and Figure 3The intelligent water cleaning boat system in this solution also includes a water quality monitoring module 5 and a positioning module 7 connected to the microcontroller 2. The water quality monitoring module 5 includes a pH sensor 51, a dissolved oxygen sensor 52, a turbidity sensor 53, and a signal converter 54. The pH sensor 51, dissolved oxygen sensor 52, and turbidity sensor 53 are installed on the bottom of the boat or in the sampling chamber, and are all electrically connected to the signal converter 54, which in turn is electrically connected to the microcontroller 2. During use, these sensors periodically collect key indicators such as pH value, dissolved oxygen concentration, and turbidity at intervals of several seconds to tens of seconds. (If further equipped with the water quality monitoring module 5, parameters such as nitrogen, phosphorus, and heavy metals can also be detected.) The raw data collected is transmitted to the main control unit, filtered, averaged, and compared with the system's built-in thresholds (such as pH value exceeding the 6.0-8.5 range and dissolved oxygen below 4.0 mg / L). Once a value exceeds the limit, the system immediately marks the abnormal time point and GPS positioning information. Meanwhile, all monitoring data is uploaded to the monitoring center in real time via wireless communication module 3 for analysis and decision-making.

[0038] The positioning module 7 includes a GPS / BeiDou navigation receiver and an IMU (Inertial Measurement Unit). The former acquires global / regional coordinates, while the latter uses a gyroscope and accelerometer for attitude estimation. In operation, the GPS module collects latitude and longitude information in real time for global positioning, while the IMU module collects information on the ship's attitude and acceleration changes to assist in short-term inertial navigation when the signal is unstable. The fusion of these two modules forms a stable attitude calculation, providing a basis for path planning and obstacle avoidance, thus supporting preset mission paths. On the other hand, dynamic obstacle avoidance and route reconstruction are performed by combining the recognition results from the vision unit and the LiDAR 42, thereby automatically completing the entire closed-loop process of takeoff, navigation, target clearing, and path return.

[0039] In addition, the cleaning vessel can communicate with the shore-based monitoring center via Wi-Fi, LoRa, and 4G. Its technical advantages are reflected in the following: the combination of GNSS and IMU enhances the continuity of positioning in urban obstructed environments. This combined navigation technology is a well-known existing technology. By using a filter to fuse GNSS and IMU data, it can achieve real-time correction and state estimation, so that the positioning has both the global reference of GNSS and the high-frequency dynamic response capability of IMU.

[0040] Furthermore, baffles (not shown) are installed on both sides of the propeller at the stern of the hull 1. This design allows the debris around the propeller to be separated by the baffles, thus enabling the cleaning boat to navigate stably.

[0041] Furthermore, a manual emergency stop button (not shown) is also provided on the hull 1. This manual emergency stop button can be connected to the microcontroller 2. In use, the user can use the manual emergency stop button to shut off the power source of the hull 1.

[0042] Finally, it should be noted that the above embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in this application, or make equivalent substitutions for some of the technical features. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be the protection scope of the claims.

Claims

1. A smart waterway cleaning vessel system, characterized in that, It includes the hull, a vision unit located at the bow, and a main control unit and communication unit located on the hull; The hull is equipped with a grabbing device along the front side of the hull. In use, the grabbing device is used to grab water debris from the river surface. The vision unit consists of a binocular high-definition camera and an image processing module. The binocular high-definition camera is electrically connected to the image processing module. In use, the image processing module is used to receive the images transmitted by the binocular camera and generate coordinates after processing the transmitted images. The main control unit consists of a microcontroller and a propulsion motor. The microcontroller is electrically connected to the vision unit, the propulsion motor, and the grasping device. The drive shaft of the propulsion motor is connected to the propeller connecting shaft of the hull. In use, the grasping device is used to receive images and coordinates from the vision unit and perform grasping actions. The communication unit consists of a wireless communication module, which is electrically connected to the microcontroller. In use, the microcontroller can interact with an external remote monitoring platform through the wireless communication module.

2. The intelligent water cleaning boat system according to claim 1, characterized in that: The microcontroller is specifically an STM32 series microcontroller, and is equipped with timer and counter modules. The main control unit also includes a motor driver. The microcontroller is electrically connected to the motor driver, and the motor driver is electrically connected to the propulsion motor.

3. The intelligent water cleaning boat system according to claim 1, characterized in that: The image processing module can be a Nano core board, and the wireless communication module can be a Wi-Fi module, a LoRa wireless communication module, or a 4G communication module for data communication.

4. The intelligent water cleaning boat system according to claim 1, characterized in that: The vision unit also includes a lidar, which is electrically connected to the microcontroller. In use, the lidar can acquire the distance and outline of obstacles in real time.

5. The intelligent water cleaning boat system according to claim 1, characterized in that: The grasping device is specifically a multi-degree-of-freedom robotic arm, which includes an actuator and a path planning module. The actuator is a 5-degree-of-freedom servo motor, and the path planning module consists of an Arduino control module and a ROS robot operation module. In use, the robotic arm can perform grasping actions according to the path planning module.

6. The intelligent water cleaning boat system according to claim 1, characterized in that: The hull is also equipped with a power supply module, which consists of a large-capacity lithium battery pack and a solar photovoltaic panel. In use, the power supply module is used to provide power support for the shipboard equipment.

7. The intelligent waterway cleaning vessel system according to claim 1, characterized in that: The bow of the hull is also provided with a guide rail and an electric push rod. There are at least two electric push rods, which are installed on the hull. The telescopic rods of the electric push rods pass through the guide rails and extend toward the bow. At the same time, a lifting device is provided at the end of the electric push rod facing the bow. The lifting device can be either an electric telescopic rod or a screw jack. Both the electric push rod and the lifting device are electrically connected to the microcontroller. Below the lifting device is a box-shaped hull plate. The upper surface of the hull plate is connected to the lifting end of the lifting device. In use, the lifting device can move the hull plate up and down.

8. The intelligent water cleaning boat system according to claim 1, characterized in that: The hull is also equipped with a water quality monitoring module and a positioning module (7). The water quality monitoring module consists of a pH sensor, a dissolved oxygen sensor, a turbidity sensor and a signal converter. The pH sensor, dissolved oxygen sensor and turbidity sensor are installed in the bottom of the ship or in the sampling chamber. At the same time, the signal converter, pH sensor, dissolved oxygen sensor and turbidity sensor are all electrically connected to the signal converter.

9. The intelligent water cleaning boat system according to claim 8, characterized in that: The positioning module (7) consists of a GPS, a Beidou navigation receiver and an IMU inertial measurement unit. When in use, the positioning module (7) enables the cleaning vessel to perform coordinate positioning and to plan the path using the positioning coordinates.

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