Camera-Guided Fish Feeding Control to Cut Waste and Undernutrition
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Solution Overview
Problem
Current manual feeding systems for fish in aquaculture are time-consuming, expensive, and prone to errors due to reliance on human observation, which can lead to either food waste or inadequate nutrition for the fish, affecting their health and the quality of the final product.
Innovation Solution
An automated feeding system that uses a submersible camera to monitor fish activity and feed distribution, adjusting feeding parameters based on sensed conditions to optimize feeding rates and minimize waste, with a control unit processing image data to determine when to start, increment, or stop feeding, ensuring the right amount of food is provided.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual observation and adjustment of feed is used, then feeding levels can be monitored, but the process is time-consuming and expensive requiring workers on site
Solution Approach 1:
The patent replaces manual mechanical observation with an automated imaging system using cameras and computer processing. The system captures images of fish and feed, automatically analyzes feeding behavior, and controls feed delivery without human intervention, eliminating the need for workers to be on site while maintaining monitoring precision.
Solution Approach 2:
The system enables self-service automation where the feeding system monitors and adjusts itself. The computer automatically processes images, determines feeding status, and controls the feeding mechanism based on predefined criteria, making the system self-regulating without requiring external human operation.
2Productivity
If more food is provided to fish, then growth requirements are met, but food waste increases and expenses increase
Solution Approach 1:
The system implements continuous feedback by capturing images during feeding, analyzing whether fish are actively consuming feed, and automatically adjusting or stopping feed delivery based on real-time observations. This feedback loop ensures feed is provided only when needed, preventing waste while meeting growth requirements.
Solution Approach 2:
The feeding system transitions from static predetermined feeding schedules to dynamic real-time adjustment. The system continuously adapts feed delivery based on current feeding conditions observed in images, making the feeding rate variable and responsive to actual fish behavior rather than following a fixed plan.
3Loss of substance
If less food is provided to fish, then food waste is reduced, but fish health and product quality are affected
Solution Approach 1:
The system uses real-time visual feedback to monitor fish feeding behavior and health status. By continuously observing whether fish are actively feeding and their general condition, the system ensures minimum nutritional requirements are met while avoiding excessive feeding, thus maintaining fish health while reducing waste.
4Extent of automation
If cameras are used to monitor fish activity, then automated monitoring is possible, but cameras may not be correctly positioned or adverse weather conditions decrease observer availability
Solution Approach 1:
The system employs multiple cameras positioned at different locations and angles to monitor the fish pen from various perspectives. This multi-camera setup ensures that at least one camera maintains reliable viewing conditions regardless of weather, lighting, or positioning issues affecting individual cameras, thereby ensuring continuous monitoring availability.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for the automated feeding of fish. In some implementations, a corresponding method may include obtaining meal configuration data including one or more parameters indicating a meal plan for feeding farmed fish; executing the meal plan based on the meal configuration data; receiving sensor data from one or more sensors during execution of the meal plan; and adjusting the execution of the meal plan based on the sensor data from the one or more sensors.