AI Fish Counter: The Complete Guide to Automatic Fish Fry Counting for Modern Hatcheries

Counting fish fry may seem like a simple task, but for commercial hatcheries, it is one of the most important and time-consuming operations throughout the production cycle.

Every day, fish farms need to count fry before selling, transporting, stocking ponds, or transferring fish between production systems. A small counting mistake may appear insignificant when dealing with a few hundred fish, but the impact becomes much larger when hatcheries handle tens of thousands or even millions of fry.

A difference of only a few percent can create problems that affect profitability, customer relationships, and production planning.

For many years, hatcheries have relied on traditional methods such as manual counting, volume estimation, and weight sampling. These methods are still used because they are simple and require little investment. However, as aquaculture production becomes larger and more professional, these traditional approaches are becoming increasingly difficult to manage.

Workers become tired after counting for long periods.

Fish move continuously and are difficult to count individually.

Different operators may produce different results.

Customers may question whether the delivered quantity is correct.

These challenges have created a demand for a more reliable solution.

An AI Fish Counter provides a new approach by combining industrial cameras, computer vision, intelligent image processing, and automated counting technology. Instead of estimating the number of fish from samples, an automatic fish counting machine analyzes fish as they pass through the counting area and generates a digital counting result.

Modern fish counters are not designed simply to replace manual labor.

Their larger purpose is to help hatcheries create a more standardized production process with better accuracy, better records, and better control over daily operations.

The Fordy FC300mini Fish Counter is designed specifically for counting small fish fry from approximately 1 to 5 cm. It uses a high-definition camera to capture images and videos from the counting area, while an independently developed AI algorithm analyzes the image data and displays the counting result in real time.

This guide explains how AI fish counting technology works, why it is becoming increasingly important in aquaculture, what affects counting accuracy, and how hatcheries can choose the right fish counting machine for their needs.

Why Counting Fish Fry Is More Difficult Than Most People Think

In aquaculture, accurate fish counting affects almost every stage of production.

Before fish are sold, hatcheries need to know the exact quantity being delivered.

Before transportation, operators need to estimate the correct loading density.

Before stocking ponds, farmers need reliable numbers to calculate biomass, feeding plans, and expected production.

A mistake at the beginning of the process can create problems months later.

However, counting live fish is much more complicated than counting stationary objects.

Fish are constantly moving.

They swim at different speeds.

They overlap with each other.

Their body shapes change depending on direction and angle.

Water movement, lighting conditions, and fish behavior can all influence the counting process.

This is why fish counting has always been a challenge in aquaculture.

Traditional Fish Counting Method 1: Manual Counting

Manual counting is the oldest method used by hatcheries.

Workers collect fish samples, count them by hand, and estimate the total quantity based on their experience.

For small quantities, this method may be practical.

However, when the number of fish increases, the limitations become obvious.

Imagine a hatchery preparing an order of 100,000 tilapia fry.

A worker must maintain concentration while counting thousands of small, active fish. After several hours, fatigue naturally increases the chance of mistakes.

Different workers may also produce different results.

One person may count faster but make more errors.

Another person may count more carefully but require much more time.

The final number depends heavily on human experience and working conditions.

For commercial hatcheries, this creates a challenge because production needs repeatability.

A customer ordering 50,000 fry today should receive the same level of counting reliability as another customer ordering the same quantity tomorrow.

Manual counting makes this difficult.

Traditional Fish Counting Method 2: Volume Estimation

Another common method is volume estimation.

Instead of counting every fish, hatchery workers count a small sample inside a container or cup.

They then calculate the estimated total quantity based on the average number of fish in that sample.

For example:

If one small container contains approximately 500 fry, and a larger container holds 20 times that volume, the estimated quantity would be around 10,000 fry.

This method is faster than counting every fish individually.

However, it depends on an important assumption:

The fish distribution must remain consistent.

In reality, fish are not perfectly uniform.

Some areas of the container may contain more fish than others.

Fish size differences can also influence the result because larger fry occupy more space than smaller fry.

This means volume estimation can provide a useful approximation, but it is difficult to achieve the same consistency required for large-scale commercial production.

Traditional Fish Counting Method 3: Weight Estimation

Weight-based counting is another widely used approach.

The operator first counts a small sample of fish and measures its weight.

Then, the total weight of the batch is used to estimate the total number of fish.

This method can be faster when dealing with large quantities.

However, weight does not always represent an exact number of fish.

Several factors can affect the calculation:

Fish size variation
Different growth rates
Water attached to fish during weighing
Species body shape differences
Uneven batches

Two groups of fish with the same total weight may still contain different numbers of individuals.

For hatcheries selling fish by quantity, these differences can become a commercial problem.

The Hidden Problems Caused by Inaccurate Fish Counting

Many hatcheries focus only on the time required to count fish.

However, the real cost of inaccurate counting is much larger.

Counting errors influence:

Sales accuracy
Customer trust
Transportation planning
Stocking density
Production records
Farm profitability

Incorrect Sales Quantity

For many hatcheries, fish are sold by the number of fry rather than by weight.

If the actual quantity is lower than the recorded quantity, the hatchery may lose revenue.

If the actual quantity is higher, the hatchery may deliver extra fish without receiving additional payment.

A small error repeated across hundreds of orders can create significant financial losses.

Customer Disputes

Fish transportation creates another challenge.

Once fish leave the hatchery, it becomes difficult for customers to verify the original quantity.

If a buyer believes the delivered number is lower than expected, both sides may struggle to determine what happened.

A standardized counting process helps reduce these disagreements.

Digital counting records provide a clearer reference compared with estimation methods.

Incorrect Stocking Density

Fish stocking density directly affects aquaculture performance.

Too many fish in one pond can increase:

Oxygen demand
Disease risk
Feed competition
Water quality problems

Too few fish may reduce production efficiency and waste available farming space.

Reliable counting at the beginning of the production cycle helps farmers make better management decisions.

Increased Labor Costs

Counting fish manually requires time.

During busy seasons, hatcheries may need additional workers only for counting and packing preparation.

An automatic fish counting machine allows employees to focus on other important tasks, such as:

Fish health management
Water quality control
Feeding
Packing
Transportation preparation

The goal is not simply to reduce labor.

The goal is to use labor more efficiently.

Why AI Fish Counters Are Becoming Important in Modern Aquaculture

Aquaculture is becoming more data-driven.

Modern farms increasingly rely on accurate information to improve efficiency.

Farm managers want to know:

How many fish were produced?

How many were transferred?

How many were sold?

How many survived?

How much feed was required?

Without accurate initial counting, later data analysis becomes unreliable.

AI fish counting technology provides a bridge between traditional aquaculture practices and digital farm management.

By combining cameras, artificial intelligence, and automated data processing, fish counters help hatcheries move from estimation-based production toward measurement-based management.

The purpose of an AI Fish Counter is not only counting fish.

It is creating a more reliable production system.

How AI Fish Counters Solve the Problems of Traditional Counting

Traditional fish counting methods have supported aquaculture for many years.

However, as hatcheries become larger, the requirements for accuracy, speed, and traceability continue to increase.

A modern commercial hatchery is not only producing fish.

It is managing inventory.

Every fish represents production cost, feed investment, growing time, and future revenue.

This means counting is no longer just a simple labor task.

It has become an important part of farm management.

AI Fish Counters solve this challenge by changing the way fish quantity is measured.

Instead of relying on human estimation, an automatic fish counting machine uses image-based analysis to identify fish as they pass through a controlled counting area.

The process is consistent.

The result is repeatable.

The data can be recorded.

This is why artificial intelligence is becoming increasingly valuable in aquaculture operations.

From Manual Estimation to Intelligent Fish Counting

The biggest difference between traditional counting and AI counting is the way information is collected.

Traditional methods usually follow this process:
Sample Fish
↓
Manual Counting
↓
Estimate Total Quantity
↓
Record Result
The final number depends on the accuracy of the sample and the experience of the operator. AI fish counting follows a different approach:

Fish Movement
↓
Camera Capture
↓
Image Processing
↓
AI Analysis
↓
Automatic Counting
↓
Digital Record

The machine does not estimate the total number from a small sample.

It analyzes fish passing through the counting area directly.

This creates a more standardized process that is less affected by human fatigue or individual counting habits.

How Does an AI Fish Counter Actually Work?

Many people see an AI Fish Counter as a simple machine with a camera and display screen.

However, behind this simple operation is a complete image-analysis process.

The operator only needs to introduce fish into the counting channel.

The system automatically captures images, analyzes the fish movement, calculates the quantity, and displays the result.

The Fordy FC300mini uses a high-definition camera to capture images and videos from the counting area. The collected image data is transferred to the built-in computer, where an independently developed AI algorithm analyzes and processes the images to obtain the number of fish. The counting result and image process are displayed in real time.

The complete workflow can be understood through several key stages.

AI Fish Counting Workflow

Stage	Process	Function
1	Fish Enter the Counting Area	Fish fry move through the water channel into the detection area.
2	Industrial Camera Capture	The camera continuously records images and video of fish movement.
3	Image Data Acquisition	The captured visual information is transmitted to the computer system.
4	Image Processing	The system improves image quality and prepares data for AI analysis.
5	AI Fish Recognition	The algorithm analyzes visual features and identifies fish within the counting area.
6	Continuous Video Analysis	The system processes fish movement through multiple frames to maintain stable counting.
7	Automatic Counting Result	The software calculates the total number of fish passing through the system.
8	Data Recording	Counting history can be reviewed for production management.

Step 1: Fish Enter the Counting Area

The first requirement for accurate counting is creating a controlled environment.

Fish cannot be counted reliably if they move randomly in a large tank or crowded container.

An AI Fish Counter creates a specific inspection area where fish pass through one controlled pathway.

The water flow guides the fry through the camera view.

This allows the system to analyze fish movement under more stable conditions.

The design principle is similar to many industrial inspection systems.

Instead of trying to analyze everything in a complicated environment, the system creates a standardized process where every object passes through the same detection point.

For fish hatcheries, this means every fry has a better opportunity to be recognized by the camera.

Step 2: Industrial Camera Captures Fish Images and Video

The camera is one of the most important components of an AI fish counting system.

Unlike human eyes, a computer requires digital image data.

The camera continuously captures the fish movement inside the counting area.

The system does not depend on a worker watching and manually pressing a button.

Instead, the computer receives a continuous stream of visual information.

The Fordy FC300mini uses a 720p camera with a 30 fps frame rate for image acquisition.

This allows the system to analyze fish movement in real time.

A stable camera position is also important.

When the camera angle remains fixed, the software receives consistent image information from every batch.

This improves repeatability between different counting sessions.

Step 3: Image Data Acquisition and Processing

A camera image is not immediately ready for counting.

Before artificial intelligence can analyze the fish, the image data needs to be processed.

Environmental factors can affect image quality.

Examples include:

Water reflection
Small bubbles
Different lighting conditions
Background variation
Fish movement speed

Image processing helps create clearer visual information.

Typical image-processing tasks include:

Improving contrast
Reducing unwanted visual noise
Enhancing fish outlines
Separating fish from the background
Preparing images for AI recognition

The purpose of this stage is simple:

Give the AI system a cleaner image so it can make a more reliable decision.

A human can quickly recognize a fish even when the image is not perfect.

A computer requires much more structured visual information.

Step 4: AI Fish Recognition

After image processing, the system begins analyzing the fish.

This is where artificial intelligence becomes important.

Instead of counting only based on simple shapes or fixed patterns, AI-based systems can analyze multiple visual characteristics.

These may include:

Fish body outline
Length
Shape
Position
Movement pattern
Visual differences between fish and background

The AI algorithm learns from previously prepared image data and uses this information to recognize fish during operation.

This allows the machine to handle real-world conditions better than simple counting methods.

For example, two fish may appear slightly different because one is turning while another is moving straight.

A traditional image filter may struggle with this difference.

An AI-based system can analyze more complex visual information.

Step 5: Continuous Video Analysis Instead of Single Image Counting

One important advantage of AI fish counting is that the system analyzes video rather than relying on one single image.

A single image only shows a moment.

Video shows movement.

This difference is important because fish are living animals.

They move.

They change direction.

They interact with each other.

By analyzing continuous image sequences, the software can better understand fish movement through the counting area.

This helps improve counting stability and reduces errors caused by temporary changes in position.

The FC300mini manual confirms that the system captures both images and videos from the counting area and processes the image/video data through AI algorithms.

Why AI Image Analysis Is Suitable for Fish Counting

Fish counting is a perfect application for machine vision because fish have several characteristics that can be detected visually.

Compared with weighing or volume estimation, image-based counting provides direct observation.

The system can analyze:

Individual fish appearance
Body length differences
Movement through the counting area
Quantity passing through the channel

This makes AI counting especially useful for hatcheries where fish quantity matters more than total weight.

For example, a customer purchasing 50,000 tilapia fry does not only need a certain weight of fish.

They need a certain number of individual fish.

That is exactly where automatic fish counting provides value.

Why Fish Length Selection Matters in AI Counting

One important factor that many buyers overlook is fish size.

AI recognition depends on visual information.

A 1 cm fry and a 5 cm fry do not create the same image characteristics.

Their:

Body size
Shape proportion
Swimming behavior
Camera appearance

can be significantly different.

Therefore, selecting the correct fish-length setting is important.

The FC300mini software allows users to select the appropriate fish length according to the actual fry body size. The manual recommends selecting the value closest to the real fish length because excessive differences in fish size may affect algorithm accuracy.

This is one reason professional hatcheries usually grade fish before counting large commercial batches.

A more uniform batch allows the AI system to work under more predictable conditions.

The Future of Fish Counting: From Quantity Measurement to Digital Aquaculture

The development of AI Fish Counters represents a larger change happening across aquaculture.

Modern farms are moving from experience-based management toward data-based management.

In the past, many decisions depended on:

Worker experience
Visual estimation
Manual records

Today, farms increasingly use:

Automatic counting
Digital records
Smart feeding systems
Water monitoring
Production databases

Fish counting is one of the first steps in building a more intelligent hatchery.

Accurate quantity data creates the foundation for better planning throughout the entire production cycle.

Why AI Fish Counters Achieve Higher Accuracy Than Manual Counting

When people search for an AI Fish Counter, one of the first questions they ask is:

“How accurate is it?”

Accuracy is naturally the most important concern.

A fish hatchery does not invest in automatic counting equipment simply because it looks advanced.

The real value comes from whether the machine can provide more reliable results than traditional counting methods.

However, understanding fish counter accuracy requires looking beyond a single percentage.

A professional fish counting system is not only about artificial intelligence.

It depends on the complete system:

Camera quality
Image processing
Software algorithm
Fish size selection
Water condition
Operating method
Fish behavior

All of these factors work together to determine the final result.

Understanding Fish Counter Accuracy

Many advertisements use simple accuracy numbers.

For example:

“99% accuracy”

“99.9% accuracy”

However, a responsible evaluation requires asking:

Under what conditions?

For which fish size?

For which species?

At what counting speed?

In what water environment?

The accuracy of any vision-based counting system depends on the quality of the image information it receives.

If the camera cannot clearly see the fish, no algorithm can completely solve the problem.

This is why professional fish counter manufacturers usually define accuracy together with operating conditions.

The Fordy FC300mini manual provides a reference accuracy of approximately 98% for its intended application range of non-transparent fish fry from 1 to 5 cm.

This means that under suitable operating conditions, with correct parameter selection and proper operation, the machine can provide highly consistent counting results for small fish fry.

Why AI Counting Is More Consistent Than Manual Counting

The biggest advantage of AI fish counting is not simply speed.

It is consistency.

A human worker may count differently depending on:

Experience level
Fatigue
Working hours
Lighting conditions
Fish activity
Batch size

The same person may even produce different results when counting the same batch at different times.

An AI Fish Counter follows the same process every time.

The camera captures the fish.

The software analyzes the image data.

The system calculates the result.

The procedure does not become tired after several hours of operation.

This makes automatic counting especially valuable for commercial hatcheries that need repeatable results every day.

Why Counting Every Fish Is Better Than Estimating From Samples

Traditional methods usually depend on estimation.

A worker counts a small sample and uses that information to calculate the total quantity.

This approach can work when the batch is small and uniform.

However, larger batches create more uncertainty.

An AI Fish Counter works differently.

Instead of estimating from a sample, it observes fish passing through the counting area and calculates the quantity automatically.

This reduces dependence on assumptions.

For example:

A hatchery preparing a shipment of 100,000 fry does not need to estimate the number based on several cups of fish.

The machine counts the fish as they pass through the detection area.

This provides a more direct measurement method.

Six Important Factors That Affect Fish Counting Accuracy

An AI Fish Counter is a precision tool.

However, like all computer vision systems, its performance depends on the environment where it operates.

Understanding these factors helps hatcheries achieve better results.

1. Fish Size Consistency

Fish size is one of the most important factors affecting AI recognition.

A fish counter does not understand fish the same way humans do.

Humans can easily recognize that a small fish and a larger fish belong to the same species.

A computer analyzes visual characteristics.

When fish sizes are similar, the system receives more consistent image information.

When a batch contains very different sizes, the algorithm needs to recognize a wider range of body shapes.

This increases the difficulty of image analysis.

For this reason, hatcheries should avoid mixing extremely small fry with much larger fingerlings during one counting process.

The FC300mini allows users to select the fish length setting according to the actual fry body length. The manual recommends choosing the value closest to the real fish size because large differences in fish length may affect algorithm accuracy.

Before counting, measuring a small sample of fish is a simple but effective practice.

2. Fish Density and Overlapping

Fish are living animals.

They do not always swim in a perfectly separated line.

Sometimes several fish may pass through the camera area together.

When fish overlap, the visible body area becomes more complicated.

This can make recognition more difficult.

The solution is not always increasing machine speed.

In many cases, a controlled feeding speed produces better results than forcing too many fish through the channel.

A stable flow allows the camera to capture clearer images.

For commercial hatcheries, the best operating speed is usually the speed that balances:

Accuracy
Fish welfare
Processing efficiency

3. Water Clarity

Water quality directly affects image quality.

The camera needs a clear view of the fish.

Problems such as:

Suspended particles
Excess feed residue
Dirt
Excessive bubbles
Cloudy water

can reduce image contrast.

When the image becomes unclear, the AI system receives less reliable information.

Before counting, operators should ensure that the water inside the counting area is clean enough for the fish body outline to be clearly visible.

Good water clarity improves both recognition stability and daily operating efficiency.

4. Camera Cleanliness

The camera is the “eye” of the fish counter.

If the camera surface becomes dirty, the image quality decreases.

Common causes include:

Water marks
Biological deposits
Fish mucus
Dust
Long-term residue

Even a powerful algorithm cannot compensate for a blurred image.

Regular cleaning is therefore an important part of maintaining counting performance.

The FC300mini manual recommends cleaning the camera area when image quality becomes unclear and recommends regular cleaning of the fry counting channel after use.

Simple maintenance can significantly extend stable operation.

5. Lighting Conditions

Computer vision depends on visual contrast.

Lighting that changes constantly can make image recognition more difficult.

Examples include:

Direct sunlight
Strong shadows
Flickering lights
Outdoor weather changes

A controlled indoor environment is usually better for AI counting equipment.

The FC300mini includes internal LED lighting, and the manual recommends checking that the LED lights are operating normally without flickering before use.

Stable lighting allows the camera to collect more consistent image information.

6. Correct Fish Model Selection

Different fish species can have different body shapes.

Even fish with similar lengths may appear different to an AI system.

For example:

A trout fry

A tilapia fry

A carp fry

may have different body proportions and movement characteristics.

Selecting the appropriate model helps the software analyze the correct visual characteristics.

The FC300mini software includes model selection options that allow users to choose the suitable fish type.

For a new species, hatcheries should ideally test a small sample before processing large commercial quantities.

Why a Realistic Accuracy Claim Is More Valuable Than an Extreme Number

In the aquaculture industry, reliability is more important than marketing numbers.

A statement such as “99.9% accuracy in all situations” may sound attractive, but it does not explain the operating conditions.

Professional users understand that every measurement system has limitations.

A better approach is to explain:

The tested application range
Recommended fish size
Suitable operating conditions
Factors affecting performance

This gives customers a realistic expectation and helps them achieve better results.

For the FC300mini, the recommended application is clear:

Fish length: approximately 1–5 cm
Non-transparent fry
Controlled counting environment
Correct size selection

When the machine is used within its designed conditions, it can provide reliable counting support for hatchery operations.

How Hatcheries Can Improve Fish Counting Results

The machine itself is only one part of the process.

Good operation habits are equally important.

Professional hatcheries usually follow several basic practices:

Prepare Fish Before Counting

Before counting a commercial batch:

Remove excessive debris
Separate extremely different fish sizes
Confirm the fish species
Measure average length

Preparation improves consistency.

Test Before Large Batches

Before counting thousands of fish, run a small test.

Compare the result with a manually verified sample.

This confirms that:

The correct model is selected
Water flow is suitable
Fish size matches the setting
The camera view is clear

A short test can prevent larger problems later.

Maintain Regular Cleaning

A clean machine is a more reliable machine.

After each counting session:

Clean the channel
Remove fish residue
Check the camera surface
Dry the equipment

The FC300mini manual recommends cleaning the equipment regularly and keeping it dry after use.

Accuracy Is Only One Part of a Good Fish Counting System

A good fish counter is not only measured by accuracy.

Commercial hatcheries also care about:

Processing speed
Ease of operation
Data records
Maintenance requirements
After-sales support
Compatibility with their fish species

The best machine is not always the one with the largest advertised number.

It is the one that matches the hatchery’s real production requirements.

Applications of AI Fish Counters in Modern Aquaculture

An AI Fish Counter is not only a counting device.

For modern aquaculture businesses, it is a tool that improves production control, sales accuracy, and operational efficiency.

From hatcheries selling millions of fry to farms transferring fingerlings between production systems, accurate fish counting plays an important role throughout the entire aquaculture supply chain.

The value of automatic fish counting becomes especially clear when fish quantity directly affects business decisions.

A hatchery needs accurate numbers before selling.

A farmer needs accurate numbers before stocking.

A transport company needs accurate numbers before loading.

A researcher needs accurate numbers before conducting trials.

In all these situations, reliable counting creates better management decisions.

1. Fish Hatchery Sales and Fry Distribution

Fish hatcheries are one of the most common applications for automatic fish counters.

Every day, hatcheries prepare orders for customers who purchase fry and fingerlings.

The customer usually cares about one key question:

“How many fish will I receive?”

Traditionally, hatcheries answered this question through manual counting or estimation.

However, as order quantities increase, these methods become difficult to maintain.

A commercial hatchery may need to prepare:

10,000 fry orders
50,000 fry orders
100,000+ fry orders

within a short period.

Manual counting slows down the packing process and increases the possibility of mistakes.

An AI Fish Counter allows hatchery workers to count fish automatically before packing.

The operator can monitor the counting process in real time while the system records the final quantity.

This creates a more professional sales process.

For customers, accurate counting improves confidence.

For hatcheries, it reduces the risk of under-delivery or over-delivery.

2. Fish Fry Transportation

Transportation is another important application.

Before fish are placed into bags, tanks, or transport containers, the hatchery must determine the correct number of fish.

The quantity affects:

Oxygen requirements
Water volume
Transport density
Survival rate
Delivery planning

Overloading transport containers can increase stress and reduce survival.

Underloading wastes transportation capacity.

Accurate counting helps operators create a better balance between fish welfare and transportation efficiency.

The Fordy fish counter is designed for production, sales, and transportation processes involving fry and fingerlings.

For hatcheries shipping fish over long distances, reliable counting before shipment provides an important quality-control step.

3. Pond Stocking and Nursery Management

Fish stocking density is one of the most important factors in aquaculture management.

The number of fish introduced into a pond or tank affects:

Growth rate
Oxygen demand
Feeding strategy
Water quality
Disease risk

If the stocking number is inaccurate, farm managers may make incorrect decisions later.

For example:

A pond expected to contain 50,000 fingerlings may actually contain significantly fewer or more fish.

This affects all future calculations.

Automatic fish counting helps farmers establish a more accurate starting point.

Once the initial population is known, managers can better evaluate:

Survival rate
Growth performance
Feed conversion
Harvest expectations

Accurate counting is therefore not only a sales requirement.

It is also a production management tool.

4. Tilapia Hatcheries

Tilapia is one of the world’s most widely farmed fish species.

Large-scale tilapia production depends heavily on efficient fry management.

Hatcheries often handle large quantities of small fry during:

Nursery transfer
Customer sales
Stocking preparation
Export shipments

Because tilapia fry are commonly sold by quantity, counting accuracy directly affects commercial transactions.

An AI Fish Counter designed for small fry can help tilapia hatcheries improve daily workflow by reducing manual counting requirements.

The FC300mini is designed for small non-transparent fry between approximately 1 and 5 cm, making it suitable for many early-stage hatchery applications.

Before purchase, hatcheries should confirm:

Average tilapia fry length
Size variation
Daily counting volume
Required counting speed

5. Trout and Salmon Hatcheries

Cold-water species such as trout and salmon require careful management during early growth stages.

Because these fish often have high commercial value, accurate inventory control is especially important.

Hatcheries need reliable information during:

Fry production
Fingerling transfer
Stocking preparation
Research programs

The challenges are similar:

Fish move quickly
Quantities can be large
Manual counting requires significant labor

AI-based counting systems provide a more standardized method for tracking fish populations.

However, because salmonids can differ significantly in body shape and size during growth, testing the actual fish size range before purchase is recommended.

A suitable fish counter should always be selected according to:

Species
Total body length
Expected quantity
Water conditions

6. Ornamental Fish Production

Ornamental fish farms often handle smaller quantities than food-fish hatcheries, but accuracy is still important.

Many ornamental fish are sold based on:

Individual quantity
Size category
Customer order requirements

Manual counting can be stressful for delicate species.

An automatic counting system can reduce handling time and improve order preparation efficiency.

For breeders exporting ornamental fish internationally, accurate counting also helps create more reliable shipping records.

7. Research Facilities and Aquaculture Experiments

Scientific research requires accurate data.

When researchers conduct experiments involving:

Feed comparison
Growth analysis
Stocking density studies
Water treatment evaluation

the initial number of fish must be accurate.

If the starting population is incorrect, the final research data may also become unreliable.

Automatic fish counters provide researchers with a more consistent method for establishing experimental groups.

This helps reduce variation caused by manual counting errors.

8. Government Hatcheries and Large Production Centers

Large government or commercial hatcheries often produce fish for:

Restocking programs
Public aquaculture projects
Community farming programs
Commercial distribution

These operations usually require detailed production records.

The number of fish produced, transferred, and released must often be documented.

Automatic counting supports better record management by providing repeatable counting procedures.

The FC300mini includes a history interface that allows operators to review previous counting records.

AI Fish Counter Applications by Production Stage

Production Stage	Counting Purpose	Main Benefit
Hatchery Production	Count newly produced fry	Improve inventory accuracy
Sales Preparation	Confirm customer order quantity	Reduce disputes
Transportation	Determine loading quantity	Improve transport planning
Pond Stocking	Record initial population	Improve farm management
Research	Create accurate experimental groups	Improve data reliability

Why More Hatcheries Are Moving Toward Automated Fish Counting

The transition from manual counting to AI counting is part of a larger trend in aquaculture.

Modern farms are becoming more automated.

They are adopting:

Automatic feeders
Water quality monitoring systems
Smart aeration control
Digital farm records
AI-based management tools

Fish counting is one of the most basic but important steps in this transformation.

Without accurate numbers, other production data becomes less reliable.

A farm cannot accurately calculate survival rate if the initial quantity is uncertain.

A hatchery cannot accurately manage sales if delivered numbers are estimated.

An operator cannot optimize stocking density without knowing the real population.

AI fish counters provide the foundation for more precise aquaculture management.

Choosing the Right Fish Counter for Your Application

Not every hatchery needs the same type of fish counter.

The correct model depends on several factors:

Fish length
Fish species
Daily counting volume
Required speed
Production environment

A small fry hatchery has different requirements from a fingerling producer.

A farm counting 5,000 fish per day has different needs from a facility handling hundreds of thousands.

Before purchasing, consider the actual production situation rather than simply choosing the largest machine.

The next section explains how to select the right fish counter model and introduces the Fordy FC300mini, FC360, and FC600 series.

How to Choose the Right AI Fish Counter Model for Your Hatchery

Choosing an AI Fish Counter is not only about selecting the machine with the highest speed or the largest capacity.

The most important question is:

Does the fish counter match your actual production requirements?

Different hatcheries handle different fish sizes, species, and production volumes.

A machine designed for tiny fry may not be the best choice for larger fingerlings.

A large fish counter may be unnecessary for a hatchery that mainly sells small fry.

The correct model should match:

Fish body length
Fish species
Daily counting volume
Production environment
Transportation requirements
Future expansion plans

Before purchasing an automatic fish counting machine, hatchery operators should first understand their actual application.

Three Important Questions Before Buying a Fish Counter

1. What Is the Actual Fish Length Range?

Fish length is the first factor to consider.

Many buyers focus on fish weight because it is commonly used in aquaculture.

However, AI vision systems analyze the visible characteristics of fish.

The total body length is more important than weight.

For example:

Two groups of tilapia may both weigh 100 kg, but if one group contains smaller fry and the other contains larger fingerlings, they may require completely different counting systems.

Before choosing a machine, measure:

Minimum fish length
Maximum fish length
Average fish length
Size variation within one batch

This information helps determine the most suitable model.

2. How Many Fish Do You Need to Count?

The required counting capacity depends on your business scale.

A small hatchery selling several thousand fry per day has different requirements from an export-oriented farm handling hundreds of thousands of fish.

Consider:

Daily production volume
Number of customer orders
Transportation schedule
Packing speed
Number of workers available

The goal is not always choosing the fastest machine.

The goal is choosing a machine that fits your workflow.

3. What Species Are You Counting?

Different fish species have different body shapes.

A suitable fish counter should be evaluated according to:

Fish shape
Swimming behavior
Transparency
Size range
Water conditions

Before ordering, professional hatcheries usually provide:

Fish photos
Short videos
Fish length information
Expected counting volume

This allows the supplier to confirm whether the selected model is suitable.

Fordy AI Fish Counter Product Series

Fordy provides different AI fish counting machines designed for different fish size ranges.

The three main models include:

Model	Recommended Fish Size	Main Application
FC300mini	1–5 cm fry	Small fry counting, hatchery sales, transportation preparation
FC360	3–15 cm fish	Fingerlings, juvenile fish, medium-size aquaculture operations
FC600	5–20 cm fish	Larger fingerlings, stocking, transfer, and commercial production

The official Fordy fish counter product range includes FC300mini, FC360, and FC600 models covering different fish-size applications.

Fordy FC300mini: AI Fish Counter for 1–5 cm Fry

For hatcheries producing small fry, the biggest challenge is usually handling large quantities of very small fish.

Tiny fry are difficult to count manually because:

They move quickly
They are easily mixed together
Individual recognition is difficult
Manual counting requires long working hours

The Fordy FC300mini is designed specifically for small fish fry from approximately 1 to 5 cm.

Product page:

Fordy FC300mini Smart Fish Counter 1–5cm High Accuracy Fry Counting Machine

The FC300mini uses a high-definition camera and AI image analysis system to automatically count fry as they pass through the counting area.

Its main specifications include:

Fish Size	1–5 cm fry
Accuracy	Up to 98% under suitable conditions
Camera	720p, 30 fps
Power Supply	AC 220V / 50Hz
Rated Power	300W
Application	Non-transparent fish fry

The FC300mini is particularly suitable for:

Tilapia hatcheries
Small fry production
Nursery farms
Fish sales preparation
Fry transportation

For hatcheries where the majority of fish are between 1 and 5 cm, choosing a specialized fry counter is usually more effective than using a larger machine.

Fordy FC360: AI Fish Counter for 3–15 cm Fingerlings

As fish grow, their body size and movement characteristics change.

A machine designed for tiny fry may not provide the best working efficiency for larger fingerlings.

The Fordy FC360 is designed for fish between approximately 3 and 15 cm.

Product page:

Fordy Auto Big Fish Counter FC360 3–15cm High Precision Fish Fingerling Counter

This model is suitable for farms that need to count:

Larger fry
Fingerlings
Juvenile fish

Typical applications include:

Nursery transfer
Fingerling sales
Pond stocking
Commercial fish farming

Compared with very small fry, larger fish are easier to handle physically, but manual counting still becomes inefficient when quantities increase.

The FC360 provides an automated method for farms that need faster and more standardized fingerling counting.

Fordy FC600: AI Fish Counter for 5–20 cm Fish

For larger fingerlings and juvenile fish, the counting requirements are different.

Larger fish occupy more space and require a larger counting channel.

The Fordy FC600 is designed for fish approximately 5–20 cm.

Product page:

AI Auto Fish Counter FC600 Accurate Counting for 5–20 cm Fish

The FC600 is suitable for:

Fingerling farms
Grow-out operations
Fish transfer
Large-scale stocking preparation

Its larger application range makes it suitable for operations handling bigger fish where traditional counting methods become slow and labor-intensive.

Typical users include farms producing:

Tilapia fingerlings
Trout juveniles
Salmon juveniles
Carp
Other medium-sized fish

FC300mini vs FC360 vs FC600 Comparison

Feature	FC300mini	FC360	FC600
Fish Size	1–5 cm	3–15 cm	5–20 cm
Main Target	Fry	Fingerlings	Larger fingerlings
Typical Use	Hatchery production and fry sales	Nursery transfer and juvenile fish	Stocking, transfer, larger fish management
Best Choice For	Small fish specialists	Medium-size fish operations	Larger fish production systems

Which Fordy Fish Counter Should You Choose?

A simple selection rule:

Choose FC300mini if:

Your fish size is mainly 1–5 cm
You operate a hatchery producing fry
You sell large quantities of small fish
Your main problem is manual fry counting

Choose FC360 if:

Your fish size is mainly 3–15 cm
You handle fingerlings
You need counting during transfer or sales
You want a machine covering a wider size range

Choose FC600 if:

Your fish size is mainly 5–20 cm
You manage larger juvenile fish
You need higher-capacity counting for commercial operations
You count fish during stocking or transfer

Selecting the Right Model Is More Important Than Choosing the Biggest Machine

A common mistake is assuming that a larger machine is always better.

In reality, AI fish counters are designed around specific operating ranges.

A machine optimized for small fry may provide better results for hatchery applications than a larger system designed for bigger fish.

The best choice is the model that matches:

Your current fish size
Your production volume
Your operating environment
Your future business plans

A correct match improves efficiency, reduces unnecessary investment, and helps the machine deliver more stable performance.

Best Practices for Installing and Operating an AI Fish Counter

Choosing the right fish counter is only the first step.

To achieve reliable counting performance over the long term, the machine must also be installed correctly and operated under suitable conditions.

Unlike traditional mechanical equipment, an AI Fish Counter combines optics, electronics, software, and water-flow management into one system.

A stable working environment helps the camera capture clearer images, allowing the AI algorithm to perform more consistently.

Fortunately, daily operation is much simpler than many hatchery owners expect.

Once the machine is properly installed and configured, most counting tasks can be completed by a single operator.

Preparing the Installation Environment

Before installing an automatic fish counter, evaluate the working area rather than simply looking for an available space.

The counting station should provide a stable environment for both the equipment and the fish.

A suitable installation area should have:

A stable power supply
Clean water for the circulation system
Adequate drainage
A flat and vibration-free floor
Good ventilation
Protection from direct rain and excessive sunlight

Although the FC300mini is designed for aquaculture environments, it contains a camera, touchscreen, and onboard computer.

The user manual lists an IPX3 protection rating, which means the machine should be installed in a covered working area instead of being exposed directly to heavy rain or continuous water spray.

A simple roof over the counting station is usually enough to provide a much more stable operating environment.

Maintain Stable Water Flow

Many first-time users assume that increasing the water flow will improve counting speed.

In reality, excessive flow often reduces counting stability.

The purpose of the water system is not to push fish through the machine as quickly as possible.

Instead, it should create a smooth and continuous movement through the counting channel.

A stable flow offers several advantages:

Fish remain more evenly distributed
Less overlapping occurs
The camera captures clearer images
Operators can monitor the counting process more easily

Think of the counting channel as a highway.

When traffic flows steadily, every vehicle passes smoothly.

When too many vehicles arrive at once, congestion occurs.

The same principle applies to fish movement.

Avoid Sudden Changes in Fish Density

One of the most common operating mistakes is pouring an entire bucket of fry into the counting channel at once.

Doing so increases the chance that fish will overlap within the camera’s field of view.

Instead, introduce fish gradually.

A controlled feeding rate allows the system to analyze each group more consistently.

Although this may appear slightly slower, it often improves overall efficiency because fewer counting interruptions occur.

For commercial hatcheries, consistent operation is usually more valuable than maximum instantaneous speed.

Confirm the Fish Length Before Every Batch

One advantage of the FC300mini is that operators can select the fish length before counting.

This setting helps the AI algorithm analyze fish more accurately.

Rather than relying on fish weight, always measure the actual body length.

For example:

1 cm fry
2 cm fry
3 cm fry
5 cm fry

The selected value should be as close as possible to the average length of the batch.

The user manual recommends selecting the nearest body-length setting and notes that excessive variation in fish size may reduce counting accuracy.

As a best practice, measure several fish from each batch before beginning large commercial orders.

Select the Correct Fish Model

Some hatcheries produce only one species throughout the year.

Others may work with tilapia, carp, trout, catfish, or ornamental fish at different times.

If the software includes multiple fish models, confirm that the correct model is selected before starting the counting session.

This small step can improve consistency because different species may have different body proportions and swimming characteristics.

For new species that have not been tested previously, it is always advisable to perform a small verification run before processing a large commercial batch.

Monitor the Live Counting Screen

Unlike manual counting, an AI Fish Counter provides visual feedback throughout the entire process.

Operators should occasionally observe:

Fish movement
Water flow
Live camera image
Current counting total

If the fish begin to crowd together or the water becomes cloudy, adjustments can be made immediately rather than waiting until the end of the batch.

This real-time visibility is one of the practical advantages of intelligent counting systems.

Daily Cleaning Protects Long-Term Accuracy

Image quality is directly related to counting performance.

Even a small amount of residue on the camera window can reduce image clarity.

After each working day, operators should clean:

The counting channel
Camera viewing window
Water inlet
Water outlet
External surfaces

Only soft cloths and clean water should be used around the camera area.

Avoid abrasive cleaning tools that could scratch transparent surfaces.

The FC300mini manual recommends cleaning the counting channel regularly and wiping the camera window whenever the displayed image becomes unclear.

Routine cleaning usually requires only a few minutes but helps maintain consistent image quality over time.

Shut Down the System Properly

Because the FC300mini contains an embedded computer, the machine should always be shut down through the software interface.

Disconnecting the power supply directly while the operating system is running may interrupt software processes.

The user manual specifically recommends using the system shutdown function instead of unplugging the machine directly.

Following this procedure helps protect stored counting records and extends the service life of the onboard computer.

Common Mistakes When Using an AI Fish Counter

Most counting problems are not caused by the AI algorithm itself.

Instead, they result from unsuitable operating conditions.

The following table summarizes several common mistakes and practical solutions.

Common Issue	Possible Cause	Recommended Solution
Unstable counting result	Fish size varies significantly	Grade fish before counting and select the correct size setting.
Reduced counting consistency	Too many fish enter simultaneously	Feed fish into the counting channel more gradually.
Blurry live image	Camera window or channel requires cleaning	Clean the camera viewing area and counting channel.
Lower image quality	Cloudy water or excessive bubbles	Replace the water and maintain a stable flow.
Different results between batches	Incorrect fish-length parameter	Measure the average fish length before each batch.
Unexpected software behavior	Improper shutdown procedure	Always power off the system through the software menu.

Building a Standard Operating Procedure (SOP)

As production grows, successful hatcheries rely less on individual experience and more on standardized procedures.

Creating a simple SOP for fish counting helps ensure that every operator follows the same workflow.

A typical SOP may include:

Check water quality.
Inspect and clean the counting channel.
Turn on the system.
Verify the LED lighting and live camera image.
Select the correct fish model.
Select the correct fish-length parameter.
Start water circulation.
Introduce fish gradually.
Monitor the live counting process.
Review the final result and save the record.
Clean and dry the machine after use.

Following the same process every day improves repeatability and makes operator training much easier.

Integrating AI Fish Counting into a Smart Hatchery

An AI Fish Counter delivers the greatest value when it becomes part of a complete hatchery workflow.

For example:

Fish are counted automatically.
The quantity is confirmed before packing.
Fish are transferred into transport tanks.
Automatic feeders can later be configured according to stocking numbers.
Aeration equipment can be planned according to fish density.
Production records become easier to maintain.

Instead of treating fish counting as an isolated task, modern hatcheries increasingly use it as the starting point for digital production management.

This approach not only improves counting accuracy but also creates more reliable operational data for the entire farm.

For hatcheries working primarily with 1–5 cm fry, the FC300mini provides a compact solution designed specifically for this size range. Product specifications and additional images are available on the official product page:

👉 https://iaerator.com/product/fordy-ky-efc300mini-smart-fish-counter-high-accuracy-fry-counting-machine-for-aquaculture-1-5cm-fry/

Operations handling 3–15 cm fingerlings can learn more about the FC360 here:

👉 https://iaerator.com/product/fordy-auto-big-fish-counter-3-15cm-high-precision-fish-fingerling-counter-high-accuracy-304-stainless-steel-220v/

For larger 5–20 cm juvenile fish, the FC600 product page provides detailed specifications and application examples:

👉 https://iaerator.com/product/ai-auto-fish-counter-fc600-accurate-counting-for-5-20-cm-fish/

Frequently Asked Questions About AI Fish Counters

Choosing an AI Fish Counter is an important investment for any hatchery or aquaculture business. Below are answers to some of the most common questions from hatchery managers, fish farmers, distributors, and aquaculture professionals.

What is an AI Fish Counter?

An AI Fish Counter is an automated machine that uses industrial cameras and computer vision technology to count fish as they move through a designated counting channel.

Unlike traditional methods based on manual counting or volume estimation, AI fish counters analyze image data in real time and automatically calculate the number of fish passing through the system.

The goal is to improve counting efficiency while providing more consistent and traceable results.

How accurate is an AI Fish Counter?

Accuracy depends on several factors, including:

Fish size
Water clarity
Camera image quality
Fish density
Correct software settings
Operating method

Under recommended operating conditions, the Fordy FC300mini provides a reference accuracy of approximately 98% for non-transparent fish fry between 1 and 5 cm.

Rather than focusing only on a percentage, operators should follow proper installation and operating procedures to achieve the most consistent results.

Can the machine count different fish species?

Yes.

AI Fish Counters are suitable for many freshwater and marine species, provided the fish size falls within the supported range of the selected model.

Typical applications include:

Tilapia
Trout
Salmon
Carp
Catfish
Sea bass
Sea bream
Many other hatchery species

If you are unsure whether your fish species is suitable, it is recommended to provide photos or videos together with the average body length before purchasing.

Which fish size should I measure before choosing a model?

Always measure the total body length, not the weight.

Fish counters analyze the visual appearance of fish rather than their mass.

As a general guide:

Model	Recommended Fish Length
FC300mini	1–5 cm
FC360	3–15 cm
FC600	5–20 cm

If your fish fall outside these ranges, contact the manufacturer to discuss a suitable configuration.

Can one machine count every fish size?

No.

Different models are designed for different fish-length ranges.

A machine optimized for 1–5 cm fry is not necessarily the best choice for 20 cm fingerlings.

Selecting the correct model helps the AI algorithm operate within its intended application range.

How many fish can an AI Fish Counter process?

The actual throughput depends on:

Fish size
Fish density
Water flow
Operator feeding speed

Instead of maximizing speed, operators should aim for a stable and continuous flow to maintain consistent counting performance.

Can transparent fish larvae be counted?

Very transparent larvae are generally more difficult for any vision-based counting system because they provide limited visual contrast.

The FC300mini is intended for non-transparent fish fry within the recommended size range.

If you need to count transparent larvae or newly hatched fry, it is best to discuss your application with the supplier before purchasing.

Does water quality affect counting accuracy?

Yes.

Clear water helps the camera capture better images.

Poor water quality may reduce image clarity because of:

Suspended particles
Foam
Air bubbles
Excess feed
Mud
Organic debris

Maintaining clean water is one of the simplest ways to improve counting consistency.

Can one operator run the machine?

Yes.

Under normal conditions, one trained operator can complete most counting tasks.

The operator mainly needs to:

Prepare the fish
Select the correct settings
Monitor the live image
Feed fish steadily through the counting channel
Review the counting result

Is operator training difficult?

No.

Most users become familiar with the basic workflow after a short period of training.

The user interface is designed to simplify common operations such as:

Fish model selection
Fish-length setting
Real-time counting
History review

Fordy also provides remote technical support if assistance is required during installation or operation.

Does the machine save counting records?

Yes.

The FC300mini includes a history interface that allows previous counting records to be reviewed.

When Does Investing in an AI Fish Counter Make Sense?

Not every fish farm needs an automatic fish counter.

For very small hatcheries processing only a few thousand fry occasionally, manual counting may still be practical.

However, as production expands, automation becomes increasingly valuable.

An AI Fish Counter is generally worth considering if your hatchery:

Processes large batches of fry every day.
Frequently prepares commercial shipments.
Needs consistent inventory records.
Wants to reduce dependence on manual counting.
Is expanding production capacity.
Plans to modernize farm management.

Conversely, if fish counting is only performed occasionally and involves small quantities, investing in automation may not yet provide a meaningful return.

Choosing equipment based on actual operational needs is always more important than purchasing the largest or most advanced machine available.

Automation Is About More Than Saving Labor

The biggest benefit of an AI Fish Counter is not replacing workers.

It is improving the overall quality of hatchery management.

Reliable counting supports:

Better production planning
More accurate customer deliveries
Improved inventory management
More consistent stocking records
Better production analysis
Increased confidence in operational data

As aquaculture continues to adopt digital technologies, accurate data is becoming just as valuable as efficient equipment.

An AI Fish Counter is one of the first steps toward building a smarter hatchery, where production decisions are based on reliable information rather than estimates.

Buyer’s Checklist: 10 Questions to Ask Before Purchasing an AI Fish Counter

Purchasing an AI Fish Counter is a long-term investment.

The right machine should not only match your current production but also support the future growth of your hatchery.

Before requesting a quotation, take a few minutes to answer the following questions.

Doing so will help you choose the right model and avoid unnecessary costs.

1. What Is the Actual Length of Your Fish?

This is the most important question.

Many buyers initially tell suppliers the fish weight.

However, AI fish counters recognize fish visually rather than by weight.

For this reason, always provide:

Minimum fish length
Maximum fish length
Average fish length

If possible, measure at least 20–30 fish from different batches.

A representative average gives a much better basis for equipment selection.

2. Are All Fish Approximately the Same Size?

Uniform fish are generally easier to count than mixed-size batches.

If one batch contains fish ranging from 2 cm to 12 cm, counting performance may be less consistent than when all fish are within a narrow size range.

Many hatcheries already grade fish before sale.

If grading is part of your workflow, mention this when discussing your application with the supplier.

3. Which Species Are You Counting?

Different species have different body shapes and swimming characteristics.

For example:

Tilapia
Trout
Salmon
Carp
Catfish
Sea Bass
Sea Bream

Although many species can be counted successfully, providing this information allows the supplier to recommend the most appropriate configuration.

4. How Many Fish Do You Count Per Day?

Production volume affects equipment selection.

Ask yourself:

Do you count fish every day?
Only during shipping?
During stocking?
During grading?

Typical production levels might include:

Daily Volume	Suggested Consideration
Less than 10,000 fish	Manual counting may still be practical in some situations.
10,000–50,000 fish	Automation can improve consistency and reduce labor.
More than 50,000 fish	An AI Fish Counter is often worth evaluating.

These figures are examples only. The most suitable solution depends on your workflow rather than quantity alone.

5. How Will the Fish Counter Fit into Your Existing Workflow?

A fish counter should simplify production—not complicate it.

Think about where counting currently takes place.

For example:

Broodstock Tank

↓

Hatching

↓

Nursery

↓

Grading

↓

Fish Counting

↓

Packing

↓

Transportation

↓

Customer

Installing the fish counter at the correct stage reduces unnecessary fish handling.

6. Who Will Operate the Machine?

Most hatcheries only need one operator.

However, consider:

Operator experience
Staff training
Daily workload
Shift arrangements

Creating a simple operating procedure helps maintain consistent results regardless of who is using the equipment.

7. Do You Need Remote Technical Support?

Modern fish counters combine hardware and software.

Good after-sales support is therefore just as important as the equipment itself.

Before purchasing, ask:

Is remote troubleshooting available?
Can software settings be adjusted remotely?
Is online training provided?
Are operating manuals included?

Fordy provides remote technical assistance for installation and operation, helping customers solve configuration questions without waiting for on-site service.

8. Are Spare Parts Readily Available?

Like any production equipment, fish counters require occasional maintenance.

Before purchasing, ask whether common replacement parts are available, such as:

Camera components
Sensors
Power supply parts
Touchscreen accessories
Water circulation components

Choosing a supplier with long-term spare-parts support helps reduce future downtime.

9. Can the Machine Grow with Your Business?

Many hatcheries expand over time.

Instead of asking:

“What do I need today?”

also consider:

“What will I need in three years?”

If you expect to move from fry production into fingerling production, choosing equipment with the appropriate application range may reduce future investment.

Fordy offers three main AI Fish Counter models to support different growth stages:

Model	Fish Length	Typical Application
FC300mini	1–5 cm	Fry hatcheries and nursery operations
FC360	3–15 cm	Fingerlings and juvenile fish
FC600	5–20 cm	Larger fingerlings and stocking operations

You can compare detailed specifications on the official product pages:

10. What Information Should You Prepare Before Requesting a Quotation?

Providing complete information helps suppliers recommend the correct model more quickly.

The following checklist is useful:

✅ Fish species

✅ Average fish length

✅ Photos of the fish

✅ Short video of the counting process (if available)

✅ Daily counting quantity

✅ Power supply (Voltage / Frequency)

✅ Delivery country

With this information, the supplier can evaluate whether a standard model is suitable or whether a customized solution would be more appropriate.

A Well-Chosen Fish Counter Is More Valuable Than the Most Expensive One

Many buyers assume that purchasing the largest or fastest machine is the safest choice.

In reality, the best solution is the one that matches your production needs.

Selecting equipment based on actual fish size, production volume, and operational workflow usually delivers better long-term value than simply choosing the model with the highest specifications.

Taking time to evaluate these questions before purchasing can help ensure that your AI Fish Counter becomes a productive part of your hatchery rather than just another piece of equipment.

10 Common Fish Counting Mistakes—and How to Avoid Them

Purchasing an AI Fish Counter is only the first step toward improving hatchery efficiency.

The quality of the counting results depends not only on the machine itself but also on how it is used.

After supporting hatcheries with different species, production scales, and operating environments, we have found that most counting issues are not caused by hardware failures or software defects.

Instead, they are usually the result of avoidable operating mistakes.

Understanding these common mistakes can help hatchery managers achieve more stable counting results, reduce unnecessary troubleshooting, and extend the service life of the equipment.

Mistake 1: Choosing a Fish Counter Based on Weight Instead of Length

This is one of the most common misunderstandings.

Many buyers initially ask:

“My fish weigh about 5 grams. Which model should I choose?”

While weight is important for farming, it is not the primary factor used by an AI vision system.

Computer vision analyzes what the camera can actually see.

Two fish with the same weight may have different body lengths depending on the species.

Likewise, fish with the same length can have different weights depending on their condition.

For this reason, always provide:

Average body length
Minimum body length
Maximum body length

This allows the supplier to recommend the most suitable model.

Mistake 2: Mixing Fish with Very Different Sizes

AI image recognition works best when the fish passing through the counting channel are relatively uniform.

Imagine counting a batch containing:

2 cm fry
5 cm fingerlings
10 cm juvenile fish

The camera receives very different visual information from each fish.

Although the system can analyze a range of sizes, large differences within the same batch increase the complexity of image recognition.

Whenever possible:

Grade fish first.
Count each size group separately.
Select the correct fish-length setting before each batch.

A few extra minutes of preparation often leads to more consistent counting.

Mistake 3: Counting Immediately After Feeding

Fish behavior changes after feeding.

Some species become more active, while others gather closely together.

This creates a higher chance of overlapping fish in the counting channel.

If possible, allow fish to return to normal swimming behavior before beginning a large counting session.

Calmer fish generally move through the channel more evenly, making image analysis more consistent.

Mistake 4: Using Cloudy or Dirty Water

An AI Fish Counter relies on image quality.

If the camera cannot clearly distinguish the fish from the surrounding water, counting performance may decline.

Common causes include:

Mud
Uneaten feed
Algae
Suspended particles
Foam
Excessive bubbles

Before starting, check whether the fish body outline is clearly visible in the live camera image.

If you cannot see the fish clearly with your own eyes, the AI system is also working with reduced visual information.

Mistake 5: Ignoring Camera Maintenance

The camera is the primary sensing component of the fish counter.

Over time, water spots, mineral deposits, fish mucus, or dust may accumulate on the protective window.

Even a thin layer of residue can reduce image sharpness.

Develop a simple routine:

Inspect the camera before each working day.
Wipe the viewing window with a soft, lint-free cloth.
Never use abrasive materials or metal tools.
Replace damaged protective covers promptly if necessary.

Routine maintenance usually takes only a few minutes but helps maintain long-term image quality.

Mistake 6: Introducing Too Many Fish at Once

Many new operators assume that pushing more fish through the machine will improve productivity.

In reality, the opposite is often true.

When fish enter the counting area in dense groups:

Individual fish overlap.
Body outlines become harder to distinguish.
Water turbulence increases.
Operators may need to repeat the counting process.

A smooth, continuous flow generally produces better results than trying to maximize speed.

Think of the counting channel as a toll gate on a highway.

Traffic moves most efficiently when vehicles arrive at a steady pace rather than all at once.

Mistake 7: Forgetting to Update the Fish-Length Setting

Fish grow.

A hatchery that counted 2 cm fry last month may now be counting 4 cm fingerlings.

If the software settings are not updated accordingly, the AI algorithm may not be working under its intended conditions.

Before each production batch:

Measure several representative fish.
Confirm the average body length.
Update the software setting if necessary.

This simple habit helps maintain consistent performance over time.

Mistake 8: Skipping a Trial Run for a New Species

Every fish species has unique characteristics.

Body shape, swimming style, and coloration can vary significantly.

Whenever introducing a species that has not previously been counted on the system, perform a small validation run before processing a large commercial order.

Compare the machine result with a manually verified sample.

If everything matches expectations, continue with the full batch.

This approach is much safer than immediately processing tens of thousands of fish.

Mistake 9: Focusing Only on Maximum Speed

Many buyers ask:

“How many fish can it count per hour?”

Speed is important—but it should not be the only consideration.

A counting system that processes fish too quickly under unsuitable conditions may require repeated counting, reducing overall efficiency.

A better objective is:

Stable flow
Consistent image quality
Reliable results
Smooth workflow

The most productive hatcheries usually optimize the entire process rather than simply chasing the highest throughput.

Mistake 10: Expecting the Machine to Replace Good Hatchery Management

An AI Fish Counter is a powerful tool, but it cannot compensate for poor management practices.

Successful counting still depends on:

Healthy fish
Proper grading
Clean water
Correct operating procedures
Routine maintenance
Staff training

Think of the fish counter as part of a complete production system rather than a standalone solution.

When combined with good hatchery management, it can significantly improve consistency, efficiency, and record keeping.

Final Advice: Consistency Is More Important Than Speed

Across different hatcheries and fish species, one lesson remains the same:

The best counting results come from consistent operating conditions, not from pushing the machine to its limits.

Clean water, uniform fish size, proper software settings, and routine maintenance will almost always have a greater impact on long-term performance than trying to count fish as quickly as possible.

By following these practical recommendations, hatchery managers can maximize the value of their AI Fish Counter while building a more reliable and efficient production process.

AI Fish Counter Selection Matrix

If you already know the species you are raising, the table below provides a quick reference for selecting the most suitable Fordy AI Fish Counter.

Fish Species	Typical Length	Recommended Model	Typical Application
Tilapia Fry	1–5 cm	FC300mini	Hatchery production, nursery, fry sales
Catfish Fry	2–5 cm	FC300mini	Nursery management and transportation
Trout Fry	3–5 cm	FC300mini	Cold-water hatchery production
Salmon Fry	4–5 cm	FC300mini	Early-stage salmon hatcheries
Tilapia Fingerlings	5–10 cm	FC360	Pond stocking and commercial sales
Carp Fingerlings	8–15 cm	FC360	Commercial aquaculture
Sea Bass	6–12 cm	FC360	Marine hatcheries
Sea Bream	8–15 cm	FC360	Marine fingerling production
Salmon Juveniles	12–20 cm	FC600	Transfer and stocking
Trout Juveniles	10–20 cm	FC600	Commercial trout farms
Fish Larger Than 20 cm	20 cm+	Customized AI Fish Counter	Custom-designed according to fish size and production requirements

Final Recommendation

There is no single AI Fish Counter that is perfect for every hatchery.

The best solution depends on your fish, your production process, and your long-term growth plans.

As a simple guide:

Choose the FC300mini if your primary business involves counting fry between 1 and 5 cm, especially in hatcheries, nurseries, and fry transportation.
Choose the FC360 if you regularly work with fingerlings between 3 and 15 cm, where higher throughput and a wider size range are required.
Choose the FC600 if your operation focuses on 5–20 cm juvenile fish, pond stocking, fish transfers, or commercial grow-out production.
Choose a Customized AI Fish Counter if your fish are larger than 20 cm, if you handle multiple size ranges outside the standard models, or if your application has unique operational requirements.

Fordy’s engineering team can customize counting systems for larger species and special projects. Common custom ranges include:

20–30 cm fish
20–35 cm fish
30–50 cm fish
Large salmon
Large trout
Large carp
Other species upon request

To recommend the most suitable solution, we normally ask customers to provide:

Fish species
Average body length
Maximum body length
A few photos or a short video
Estimated daily counting volume

With this information, we can evaluate whether a standard model is suitable or whether a customized solution would provide better long-term performance.

Ready to Find the Right AI Fish Counter?

Selecting the right fish counter should be based on real production requirements—not guesswork.

Whether you operate a small hatchery producing thousands of fry each day or a commercial aquaculture facility processing hundreds of thousands of fingerlings, choosing equipment that matches your fish size and workflow will improve efficiency, consistency, and long-term operational management.

Explore the Fordy AI Fish Counter series to learn more:

FC300mini (1–5 cm Fry):
https://iaerator.com/product/fordy-ky-efc300mini-smart-fish-counter-high-accuracy-fry-counting-machine-for-aquaculture-1-5cm-fry/
FC360 (3–15 cm Fingerlings):
https://iaerator.com/product/fordy-auto-big-fish-counter-3-15cm-high-precision-fish-fingerling-counter-high-accuracy-304-stainless-steel-220v/
FC600 (5–20 cm Fish):
https://iaerator.com/product/ai-auto-fish-counter-fc600-accurate-counting-for-5-20-cm-fish/

If you’re unsure which model is best for your application, simply send us your fish species, average length, and a few photos or videos. Our team will recommend the most appropriate solution based on your actual production needs.

With over 35 years of experience in aquaculture equipment manufacturing, Fordy is committed to helping hatcheries around the world improve fish counting accuracy, reduce manual labor, and build more efficient, data-driven aquaculture operations.

Please contact Us: email:tim@futi.com
whatsapp:+86 13291610116