Marine intelligent purse seine culture management equipment

Abstract

The invention relates to the technical field of marine aquaculture, in particular to marine intelligent purse seine aquaculture management equipment which comprises an automatic bait casting system, a water quality detection module, an underwater inspection module, an intelligent sensing module, a photovoltaic power supply system, a light inducing device and an informatization center control module. Through real-time monitoring and intelligent early warning, the risk of sudden change of water quality is reduced, accurate feeding is realized through combination of an automatic bait casting system and fish shoal behaviors, the bait utilization rate is improved, resource waste is reduced, the fish shoal state and the purse seine safety can be dynamically monitored through an underwater patrol module, management timeliness and visibility are enhanced, and the system is suitable for popularization and application. A photovoltaic power supply system and low-power-consumption equipment are adopted, the long-time stable operation capacity is achieved, and the device adapts to the complex open sea environment.

Description

Technical Field

[0001] The present invention relates to the field of marine aquaculture technology, and in particular to a marine intelligent enclosure aquaculture management device. Background Art

[0002] Enclosure aquaculture is a widely used method in marine aquaculture. It has the advantages of large aquaculture space and sufficient water exchange, and is particularly suitable for large-scale fish farming.

[0003] Traditional enclosure aquaculture generally has the following problems: First, the management method is backward. Most aquaculture still relies on manual inspection and feeding, which is inefficient and labor-intensive, and cannot meet the management needs of large-scale aquaculture; second, water quality monitoring is lagging behind, and there is a lack of real-time monitoring methods. Changes in water quality parameters cannot be grasped in a timely manner, which can easily lead to problems such as fish hypoxia and disease outbreaks; third, feeding is imprecise. The traditional timed and quantitative feeding method cannot be dynamically adjusted according to the feeding behavior of fish schools, resulting in feed waste or insufficient feeding; fourth, the early warning capability is poor. There is a lack of effective data analysis and anomaly detection methods, and risk factors such as damaged enclosures and fish escapes cannot be discovered in a timely manner; fifth, energy and layout are limited, power supply in the marine environment is difficult, and the long-term deployment stability of the system is insufficient.

[0004] Therefore, in response to the above problems, the present invention proposes a marine intelligent enclosure aquaculture management device, which is used to realize intelligent perception, automatic control and remote management of the enclosure aquaculture environment, improve aquaculture efficiency and safety, and reduce labor costs and management risks. Summary of the Invention

[0005] In order to overcome the problems of low aquaculture efficiency and safety in traditional enclosure aquaculture, the present invention proposes a marine intelligent enclosure aquaculture management device to solve the problems existing in the traditional method and improve aquaculture efficiency and safety.

[0006] The technical solution of the present invention is: a marine intelligent enclosure aquaculture management equipment, including an automatic feeding system, a water quality detection module, an underwater patrol module, an intelligent sensing module, a photovoltaic power supply system, a light attractant device and an information-based central control module; the automatic feeding system is used to automatically feed fish in a quantitative manner according to the activity status of the fish school or a preset program, the water quality detection module is used to collect the temperature, dissolved oxygen, pH value and turbidity parameters of the aquaculture water area in real time, the underwater video and underwater starlight high-definition camera is used to patrol the enclosure structure and the health status of the fish school, the intelligent sensing module is used to obtain environmental data and fish school behavior information, and transmit it to the information-based central control module, the photovoltaic power supply system provides power for the equipment, the light attractant device is used to attract fish schools to gather or assist in observation through light sources, the information-based central control module is used for data collection, processing, analysis and remote control, and transmits information to the management platform or terminal device through the wireless communication module.

[0007] Preferably, the automatic feeding system includes a camera recognition module and an AI behavior analysis unit, which collects real-time videos of fish activities and combines them with deep learning algorithms to calculate fish density, activity and feeding behavior, dynamically adjusts feeding timing and feeding amount, and integrates environmental sensors to monitor waves and flow parameters, automatically suspending feeding and starting equipment protection mode in bad weather.

[0008] Preferably, the water quality detection module adopts a floating multi-parameter integrated probe, which can simultaneously monitor pH value, dissolved oxygen, temperature, ammonia nitrogen, turbidity and conductivity, and is equipped with a self-cleaning function to prevent interference from biological attachment; data is transmitted to the central control system in real time via a low-power wide area network or Wi-Fi, supports a threshold alarm function, and automatically triggers the aerator or pushes early warning information to the management personnel when the water quality is abnormal.

[0009] Preferably, the underwater patrol module is composed of a high-definition starlight camera and a multi-beam sonar device. The sonar device generates a heat map of fish distribution through 3D scanning, tracks the movement trajectory of fish and the structural integrity of the enclosure in real time, combines AI algorithms to identify damage to the enclosure or abnormal aggregation behavior of fish, and synchronizes the data to the central control platform to generate a visual report.

[0010] Preferably, the intelligent perception module includes a waterproof high-definition camera, a sonar array and an environmental sensor. It runs a lightweight AI model through an edge computing device to analyze fish feeding frequency, disease characteristics and environmental safety in real time. It supports local storage of key data and compressed upload to reduce network load, while providing nighttime infrared monitoring capabilities.

[0011] Preferably, the photovoltaic power supply system adopts a combination of photovoltaic panels and lithium iron phosphate energy storage batteries. The system has a built-in power management unit, which can dynamically allocate power priority and switch to low power consumption mode in continuous rainy weather to ensure that the equipment continues to operate for more than 30 days.

[0012] Preferably, the light attractant device consists of a waterproof LED light array and an intelligent controller, which can emit light sources in the 470nm to 530nm band. The light intensity and strobe mode can be preset according to the habits of fish species or dynamically adjusted through AI. The light group is arranged in the middle water layer of the enclosure to indirectly attract fish by attracting plankton, while assisting night-time video monitoring.

[0013] Preferably, the information-based central control module adopts a cloud-edge collaborative architecture, deploys a lightweight database and rule engine on the edge to achieve real-time data filtering and rapid response, and integrates machine learning models on the cloud platform to analyze long-term water quality trends, fish growth curves and feed conversion rates, generate optimized breeding recommendations, support multiple protocols such as Modbus and MQTT, is compatible with third-party device access, and provides mobile App remote control functions.

[0014] Preferably, the equipment also includes an automatic fence cleaning device, which includes a high-pressure air compressor, corrosion-resistant alloy nozzles and a rotary spray mechanism. The nozzles are arranged in a ring along the fence support. The high-pressure water / air spray is activated by timing or remote commands to remove attachments. The system is equipped with a flow sensor and a pressure feedback mechanism, which can automatically adjust the cleaning intensity to adapt to different degrees of dirt.

[0015] Preferably, the equipment adopts a modular design, and each subsystem is connected to the information-based central control module via a standardized interface.

[0016] Beneficial effects of the present invention:

[0017] 1. This equipment realizes real-time monitoring and intelligent early warning of water quality in the aquaculture area, reducing the risk of sudden changes in water quality.

[0018] 2. The automatic feeding system combines fish behavior to achieve precise feeding, improving bait utilization and reducing resource waste.

[0019] 3. Through the underwater patrol module, the status of fish schools and the safety of the purse seine can be dynamically monitored, enhancing the timeliness and visibility of management.

[0020] 4. It adopts photovoltaic power supply system and low-power equipment, has the ability to operate stably for a long time, and can adapt to the complex environment of the open sea.

[0021] 5. The information-based central control module realizes integrated control and remote operation and maintenance, significantly reducing manual intervention and improving management efficiency.

[0022] 6. The overall equipment structure is modular and highly integrated, making it easy to deploy and maintain, and suitable for a variety of marine aquaculture scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Shown is a schematic diagram of the system structure of the present invention;

[0024] Figure 2 Shown is a schematic diagram of the grid structure of the present invention;

[0025] Figure 3 Shown is a schematic diagram of the structure of the intelligent management device of the present invention;

[0026] Figure 4 Shown is a schematic diagram of the horizontal plate structure of the present invention;

[0027] Figure 5 Shown is a schematic diagram of the support structure of the present invention;

[0028] Figure 6 What is shown is a schematic diagram of the workflow of the present invention.

[0029] Explanation of the accompanying symbols: 1. Bracket; 2. Fixing plate; 3. Support rod; 4. Mounting groove; 5. Intelligent management device; 6. Feeding tube; 7. Camera; 8. Sensor; 9. Flushing pipe; 10. Horizontal board; 11. Support plate; 12. Fence. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 The present invention provides an embodiment: a marine intelligent enclosure aquaculture management device, comprising an automatic feeding system, a water quality detection module, an underwater patrol module, an intelligent sensing module, a photovoltaic power supply system, a light attractant device and an information-based central control module; the automatic feeding system is used to automatically feed fish in a fixed quantity according to the activity status of the fish school or a preset program; the water quality detection module is used to collect water quality parameters such as temperature, dissolved oxygen, pH value, turbidity, etc. in the aquaculture water area in real time; the underwater video and underwater starlight high-definition camera are used to patrol the enclosure structure and the health status of the fish school; the intelligent sensing module is used to obtain environmental data and fish school behavior information, and transmit them to the information-based central control module; the photovoltaic power supply system provides power for the equipment; the light attractant device is used to attract fish schools to gather or assist in observation through light sources; the information-based central control module is used for data acquisition, processing, analysis and remote control, and transmits information to a management platform or terminal device through a wireless communication module.

[0032] The automatic feeding system includes a camera recognition module and an AI behavior analysis unit. It collects real-time videos of fish activities and uses deep learning algorithms to calculate fish density, activity and feeding behavior, dynamically adjusting the feeding timing and feeding amount. It also integrates environmental sensors to monitor ocean parameters such as waves and flow rate, and automatically suspends feeding and activates equipment protection mode in bad weather.

[0033] Furthermore, the automatic bait feeding system is described in detail:

[0034] The automatic feeding system also includes an automatic feeding machine, a motor control module, a bait storage bucket, and a rotating / vibrating feeding mechanism. The system supports two working modes, which can be flexibly switched according to the breeding needs. The details are as follows:

[0035] Timed feeding: Set fixed feeding times according to the breeding cycle, such as feeding at 8:00, 12:00 and 17:00 every day. The controller automatically triggers the feeding machine to run, and the feeding amount is dynamically adjusted according to the growth stage of the fish, such as 100g each time for juveniles and 500g each time for adult fish;

[0036] Intelligent feeding: Cameras capture fish behavior and use lightweight YOLO or CNN models to analyze fish density, activity, and feeding status in real time. When fish concentration reaches a threshold and activity increases, the system automatically triggers feeding and calculates the feed amount based on the school size. Furthermore, AI can identify floating leftover bait and dynamically reduce subsequent feeding amounts to avoid waste.

[0037] By feeding with the above method, the amount can be controlled based on the motor running time (e.g. 3 seconds of rotation corresponds to about 300g of feed) or a weighing module can be added to feedback the total amount of feeding to accurately control the feeding amount.

[0038] The automatic feeding system is connected to the central control system (information platform) to achieve:

[0039] Remotely set feeding parameters;

[0040] View video / fish status in real time;

[0041] Get each feeding record, time, and amount;

[0042] Abnormal warning, such as insufficient bait or low battery.

[0043] The water quality detection module uses a floating multi-parameter integrated probe that can simultaneously monitor pH, dissolved oxygen, temperature, ammonia nitrogen, turbidity and conductivity, and is equipped with a self-cleaning function to prevent interference from biological attachment; data is transmitted to the central control system in real time via a low-power wide area network or Wi-Fi, supports a threshold alarm function, and automatically triggers the aerator or pushes early warning information to management personnel when the water quality is abnormal. It is powered by a combination of photovoltaic panels and batteries and supports low-power operation.

[0044] Furthermore, the water quality detection module is described in detail:

[0045] The system uses a floating sensor platform to monitor multi-parameter water quality, supports low-power continuous operation, remote data upload and local storage, and is compatible with multiple communication methods, facilitating deployment expansion and unified management.

[0046] Among them, the monitoring parameters and modules are as follows:

[0047]

[0048]

[0049] Among them, the software and platform functions are as follows:

[0050] Function illustrate Real-time data monitoring Visual display of current parameters on the Web / App side Data alarm Support threshold alarm (such as ammonia nitrogen exceeding the standard) push Data storage Local + cloud, support daily / weekly / monthly export AI analysis (optional) Predict water quality trends and automatically adjust related equipment (such as aerators) Multi-point deployment Multiple floating devices can be deployed at the same time, and the platform is centrally managed

[0051] The underwater patrol module consists of a high-definition starlight camera and a multi-beam sonar device. The sonar device generates a heat map of fish distribution through 3D scanning, tracks the movement trajectory of fish and the structural integrity of the enclosure in real time, combines AI algorithms to identify damage to the enclosure or abnormal aggregation behavior of fish, and synchronizes the data to the central control platform to generate a visual report.

[0052] The intelligent perception module includes a waterproof high-definition camera, a sonar array and environmental sensors. It runs a lightweight AI model through edge computing devices to analyze fish feeding frequency, disease characteristics and environmental safety in real time. It supports local storage of key data and compressed upload to reduce network load, while providing nighttime infrared monitoring capabilities and remote access to images and results.

[0053] Furthermore, the underwater patrol module is described in detail:

[0054] The waterproof high-definition camera includes an above-water camera and an underwater camera. The above-water camera monitors the safety of the area and the dynamics of the fish school, while the underwater camera combines AI to identify the status of the fish school. The sonar array and environmental sensors include sonar / radar sensors to assist underwater perception.

[0055] The sensing types and devices are as follows:

[0056]

[0057]

[0058] From the above, we can see that the video is frame-captured and AI-analyzed through the edge box;

[0059] The AI model can detect the following states:

[0060] Fish population and density (baiting aid);

[0061] Feeding action frequency (precise control of bait amount);

[0062] Abnormal behavior (decreased activity, abnormal grouping);

[0063] Water clarity (indirectly determined by turbidity).

[0064] Describe sonar perception (3D density mapping):

[0065] Install underwater multi-beam sonar to generate cross-sectional images;

[0066] Supports fish echo tracking and volume estimation;

[0067] Combined with underwater positioning, it can analyze: the depth layer where fish are concentrated, the direction and frequency of their activity, and the behavior of fish escaping or leaving the school.

[0068] AI Analysis and Edge Computing:

[0069] All data is analyzed locally first, and only results / alarms are uploaded: this reduces communication pressure and lowers power consumption.

[0070] Support for local model deployment:

[0071] Real-time preview (video + fish density);

[0072] Historical behavior analysis curve;

[0073] Push baiting suggestions;

[0074] Alarm management (such as low density / underwater movement).

[0075] The photovoltaic power supply system uses a combination of photovoltaic panels and lithium iron phosphate energy storage batteries; the system has a built-in power management unit that can dynamically allocate power priorities and switch to low-power mode in continuous rainy weather to ensure that the equipment continues to operate for more than 30 days. The photovoltaic power supply system provides power for baiting, water quality detection, perception, communication systems, etc., and also supports automatic switching in the event of abnormal power outages.

[0076] The light attractant device consists of a waterproof LED light array and an intelligent controller, which can emit light sources in the 470nm to 530nm band. The light intensity and strobe mode can be preset according to the habits of fish species or dynamically adjusted through AI; the light group is arranged in the middle water layer of the enclosure, indirectly attracting fish by attracting plankton, and assisting night-time video monitoring.

[0077] Further, the selection of LED is as follows:

[0078] Wavelength: Blue light (470nm) and turquoise (500-530nm) are preferred, suitable for most freshwater / saltwater fish;

[0079] Power: 10W~30W per lamp, supporting cluster lighting;

[0080] Protection level: IP68, suitable for long-term underwater use;

[0081] Anti-corrosion treatment: stainless steel or anti-corrosion coating is used, resistant to seawater corrosion.

[0082] The information-based central control module adopts a cloud-edge collaborative architecture, deploys a lightweight database and rule engine on the edge to achieve real-time data filtering and rapid response; the cloud platform integrates machine learning models to analyze long-term water quality trends, fish growth curves and feed conversion rates, and generate optimized breeding recommendations; it supports multiple protocols such as Modbus and MQTT, is compatible with third-party device access, and provides mobile App remote control functions.

[0083] The automatic fence cleaning device includes a high-pressure air compressor, corrosion-resistant alloy nozzles and a rotary spray mechanism. The nozzles are arranged in a ring along the fence support. High-pressure water / air spray is activated through timing or remote commands to remove attachments. The system is equipped with a flow sensor and a pressure feedback mechanism, which can automatically adjust the cleaning intensity to adapt to different levels of dirt.

[0084] The automatic fence cleaning device includes a high-pressure air compressor, corrosion-resistant alloy nozzles and a rotary spray mechanism. The nozzles are arranged in a ring along the fence support, and high-pressure water / air spray is activated through timing or remote commands to remove attachments; the system is equipped with a flow sensor and a pressure feedback mechanism, which can automatically adjust the cleaning intensity to adapt to different levels of dirt. By driving the nozzles for directional spraying, the attachments on the fence are periodically cleaned to keep the fence clean and permeable.

[0085] Further, the automatic seine cleaning device is described in detail:

[0086] An air compressor, mounted on a buoy platform, delivers pressurized air to the nozzles, which are fixed to a bracket at a preset angle. The nozzles deliver a powerful impact jet to the surface of the net, effectively flushing away biofouling such as algae, shellfish, and silt. Automatic net washing can be initiated at preset intervals or by a cleaning command from the information-based central control module, ensuring regular net cleaning and reducing the frequency of manual cleaning. This improves the operational stability and efficiency of aquaculture facilities.

[0087] By fixing the automatic net washing device on the fence structure bracket and coordinating with the high-pressure air compressor system to spray water, the fence surface can be cleaned and maintained efficiently and with low manpower, extending the service life of the fence, reducing the water flow resistance and water quality deterioration risk caused by biological attachment, and greatly improving the stability and automation level of the aquaculture environment.

[0088] See also Figure 2-Figure 5 , describe the device in detail:

[0089] The equipment includes multiple groups of brackets 1, and multiple fixing plates 2 are evenly fixedly connected to the surfaces of both ends of the brackets 1. The fixing plates 2 on each two adjacent brackets 1 are commonly fixedly connected to the support rod 3. Each bracket 1 is provided with a mounting groove 4, and multiple intelligent management devices 5 are slidably connected in the mounting groove 4. Each intelligent management device 5 is provided with a feeding tube 6, a camera 7, a camera 8 and a flushing tube 9. The upper ends of the surfaces of the multiple groups of brackets 1 are commonly fixedly connected with a horizontal plate 10. There are six horizontal plates 10. Five support plates 11 are fixedly connected to the upper end of each horizontal plate 10. The surfaces of the support plates 11 located on the same horizontal plate 10 are commonly fixedly connected with multiple fences 12.

[0090] For further information, see Figure 6 , the detailed working process of this equipment is as follows:

[0091] After the equipment is started, the water quality detection module monitors key parameters of the aquaculture waters in real time, such as dissolved oxygen, pH value, temperature, and turbidity, and uploads them to the information-based central control module through low-power communication technology. At the same time, the intelligent perception module collects fish distribution, feeding behavior, and enclosure structure status through underwater cameras and sonar equipment, and conducts preliminary analysis in combination with AI edge computing.

[0092] The information-based central control module integrates water quality data, fish behavior, and equipment operating status, and uses built-in AI models to conduct comprehensive assessments. For example:

[0093] If the dissolved oxygen is lower than the threshold, the oxygenation equipment will be automatically activated or the feeding strategy will be adjusted;

[0094] If the AI detects active feeding of fish, it triggers the automatic feeding system to accurately deliver feed;

[0095] If the sonar finds that the seine is damaged, it will immediately sound an alarm and dispatch the underwater patrol module for inspection.

[0096] The system performs automated execution and feedback:

[0097] The automatic feeding system adjusts feeding amount and frequency according to instructions and records consumption data;

[0098] Light-attracting devices activate light sources in specific wavelengths at night to attract fish to gather for easier monitoring or feeding.

[0099] The automatic seine cleaning system starts high-pressure cleaning according to schedule or based on dirt detection to maintain the transparency of the seine;

[0100] Underwater patrol robots conduct regular inspections or controlled operations, transmitting high-definition images and 3D scanning data.

[0101] All of the above data is synchronized to the remote management platform via 4G / satellite communication. Farmers can view the real-time status and receive warnings (such as abnormal water quality and equipment failure) through a mobile app or computer, and manually adjust the equipment remotely, such as forcing oxygenation or suspending feeding. The system supports historical data backtracking and breeding report generation to assist in long-term optimization of management strategies.

[0102] During this period, the photovoltaic power supply system continues to supply energy to each module, and the energy storage battery ensures operation in rainy weather. The central control module monitors the power of the equipment and dynamically adjusts power consumption, such as reducing the performance of non-critical modules to extend battery life, and reminding maintenance personnel to replace or recharge.

Claims

1. A marine intelligent enclosure aquaculture management device, characterized by: It includes an automatic feeding system, a water quality detection module, an underwater patrol module, an intelligent perception module, a photovoltaic power supply system, a light attractant and an information-based central control module; the automatic feeding system is used to automatically feed fish in a fixed quantity according to the activity status of the fish school or a preset program, the water quality detection module is used to collect the temperature, dissolved oxygen, pH value and turbidity parameters of the aquaculture water area in real time, the underwater vision module includes an underwater starlight camera for patrolling the enclosure structure and the health status of the fish school, the intelligent perception module is used to obtain environmental data and fish school behavior information, and transmit it to the information-based central control module, the photovoltaic power supply system provides power for the equipment, the light attractant is used to attract fish schools to gather or assist in observation through light sources, the information-based central control module is used for data collection, processing, analysis and remote control, and transmits information to the management platform or terminal device through the wireless communication module.

2. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The automatic feeding system includes a camera recognition module and an AI behavior analysis unit. It collects real-time videos of fish activities and combines them with deep learning algorithms to calculate fish density, activity and feeding behavior, dynamically adjusting the feeding timing and feeding amount. At the same time, it integrates environmental sensors to monitor wave and flow parameters, and automatically suspends feeding and activates equipment protection mode in bad weather.

3. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The water quality detection module uses a floating multi-parameter integrated probe that can simultaneously monitor pH, dissolved oxygen, temperature, ammonia nitrogen, turbidity and conductivity. It is equipped with a self-cleaning function to prevent interference from biological attachment. Data is transmitted to the central control system in real time via a low-power wide area network or Wi-Fi. It supports a threshold alarm function and automatically triggers the aerator or pushes early warning information to management personnel when the water quality is abnormal.

4. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The underwater patrol module consists of a high-definition starlight camera and a multi-beam sonar device. The sonar device generates a heat map of fish distribution through 3D scanning, tracks the movement trajectory of fish and the structural integrity of the enclosure in real time, combines AI algorithms to identify damage to the enclosure or abnormal aggregation behavior of fish, and synchronizes the data to the central control platform to generate a visual report.

5. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The intelligent perception module includes a waterproof high-definition camera, a sonar array and environmental sensors. It runs a lightweight AI model through edge computing devices to analyze fish feeding frequency, disease characteristics and environmental safety in real time. It supports local storage of key data and compressed upload to reduce network load, while providing nighttime infrared monitoring capabilities.

6. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The photovoltaic power supply system uses a combination of photovoltaic panels and lithium iron phosphate energy storage batteries. The system has a built-in power management unit that can dynamically allocate power priorities and switch to low-power mode in continuous rainy weather, ensuring that the equipment continues to operate for more than 30 days.

7. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The light attractant device consists of a waterproof LED light array and an intelligent controller, which can emit light sources in the 470nm to 530nm band. The light intensity and strobe mode can be preset according to the habits of fish species or dynamically adjusted through AI. The light group is arranged in the middle water layer of the enclosure to indirectly attract fish by attracting plankton, while also assisting in night-time video monitoring.

8. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The information-based central control module adopts a cloud-edge collaborative architecture, deploys a lightweight database and rule engine on the edge to achieve real-time data filtering and rapid response. The cloud platform integrates machine learning models to analyze long-term water quality trends, fish growth curves and feed conversion rates, and generate optimized breeding recommendations. It supports multiple protocols such as Modbus and MQTT, is compatible with third-party device access, and provides mobile App remote control functions.

9. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The equipment also includes an automatic fence cleaning device, which includes a high-pressure air compressor, corrosion-resistant alloy nozzles and a rotary spray mechanism. The nozzles are arranged in a ring along the fence support. High-pressure water / air spray is activated through timing or remote commands to remove attachments. The system is equipped with a flow sensor and pressure feedback mechanism, which can automatically adjust the cleaning intensity to adapt to different levels of dirt.

10. The marine intelligent enclosure aquaculture management equipment according to claim 1, characterized in that: The equipment adopts a modular design, and each subsystem is connected to the information control module via a standardized interface.

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