AI Intelligent Management System for Feeding Machines

By leveraging advanced sensing technologies and data analytics algorithms, the system monitors and integrates multiple environmental and biological parameters in real time during feeding, such as water quality indicators, surveillance footage, and identification results of aquaculture organisms’ behavioral states, while also collecting meteorological and hydrodynamic data. Combining this with nutritional requirement models and feeding behavior characteristics for different aquaculture species at various stages and under different environmental conditions, the intelligent decision-making module dynamically calculates the appropriate feed dosage and precisely controls the timing, frequency, and location of feeding. Users can remotely and in real time control the start/stop of the feeder and adjust the feeding rate via a dedicated mobile app, enabling instant management. The app also supports customizing work schedules, allowing the system to automatically execute tasks according to the plan, reducing manual intervention and increasing the level of automation.

AI Intelligent Management System for Feeding Machines

1. Feed storage capacity of the hopper: 80 kg
2. Maximum conveying distance: 80 m
3. Feeding accuracy: ±30 g
4. Number of pipelines: 8–16
5. Feed particle size: 1–5 mm
6. Maximum feeding efficiency: 50 kg/h
7. Supports remote operation and 4G data transmission.
8. Configure the Ethernet communication interface to communicate with the Intelligent Control CPU.

Product Features
Fault Diagnosis and Early Warning
Real-time monitoring of equipment operating status
Automatic anomaly alarm

Product feature
Real-time monitoring and integration of multi-dimensional parameters
Intelligent and Precise Feeding Decision-making
Remote Intelligent Control Function
Automation Task Execution and Management