New generation of AI to assess threat levels from wild animals to poultry populations

Operating a free-range poultry farm offers substantial rewards, yet it presents a significant challenge: protecting the flock from wild predators. Due to increasing public demand for higher animal welfare standards, farms are permitting chickens to roam more freely. Consequently, the birds are exposed to a greater threat from animals such as foxes, martens, and birds of prey.

For agricultural producers, losses attributed to predation are not merely distressing - they constitute a considerable financial burden. Even small, sporadic losses rapidly accumulate, posing a major financial risk to the enterprise.

Traditional defense methods, such as electric fences or guard dogs, are often insufficient. They are associated with high costs, demand continuous management, and, crucially, are reactive in nature, only responding after an attack has commenced. This is the context in which Artificial Intelligence (AI) represents a significant shift, enabling farms to transition from damage mitigation to proactive prevention.

The Problem of Wildlife-Poultry Conflict

In Europe, poultry (especially free-range and organic systems) are exposed to multiple predator threats:

• Birds of prey (hawks, buzzards, goshawks) often attack hens in open runs or at dusk/dawn.

• Mammalian predators such as red foxes, martens, badgers, and mustelids may breach enclosures.

• Ground predators or nocturnal predators like weasels, stoats, or feral cats contribute to smaller but cumulative losses.

• Snakes and reptiles in southern European zones occasionally prey on chicks or eggs.

Because poultry systems in Europe increasingly favor more natural, free-range modalities (for welfare and consumer demand), exposure to predators is rising.

From economic and production standpoints:

• In an online survey of 27 European farms experiencing predation, the average predation mortality rate was 3.7 % of hens (on organic/free-range farms), while total mortality averaged 12.2 % (PubMed);

• In controlled field experiments in France, control groups (no mitigation) saw ~5.5 % losses due to avian predation; total mortality in treatment vs control groups was ~8.0 % vs 8.3 % (ResearchGate);

• In the UK, reported average losses to foxes in free-range chicken/turkey operations are low (~0.04 % in some surveys), but sporadic severe losses (up to 5 %) have been documented (ResearchGate).

Even though the percentages may seem small, when scaled across thousands or tens of thousands of birds, the total poultry loss (in terms of eggs lost, feed invested, replacement cost, logistic disruption) becomes nontrivial.

Why Simple Fences Don't Work

The reason traditional farm security methods often fail against persistent predators is fourfold. Simple alarm systems usually activate only after a predator is already inside the chicken coop or actively attacking. Standard motion sensors frequently trigger warnings for non-threats like wind or a deer which causes farm staff to start ignoring the alerts and miss an actual danger. Employing human patrols to guard large properties around the clock is too costly and inefficient. Current regulations concerning animal welfare and conservation rightly restrict the use of lethal control methods pushing the agriculture industry to find effective non harmful solutions.

Monitoring Wildlife to Protect Poultry

The advanced security system relies on very accurate, up-to-the-minute data, provided by specialised tools like the Wild Animal Monitoring System (WAMS) developed by Rinisoft.  This system is vital because it ensures the farm is protected without accidentally frightening or annoying harmless animals.

At its heart, WAMS uses powerful object-recognition software (based on advanced models like YOLOv11) that can identify every moving object near the farm's border in real-time.

1. Categorisation: The AI models are taught to sort all wildlife into three groups:

·        Ground Threats: Animals on the land that could harm the chickens (e.g., foxes).

·        Air Threats: Bird species that hunt (e.g., eagles, hawks).

·        Harmless Wildlife: Non-threatening animals the alarm systems should ignore.

2. Specialized Detection: To provide reliable protection both day and night, special models were created for both colour and infrared (black-and-white) images.

Crucially, to spot high-flying dangers like circling vultures, the system uses a clever technique. Instead of just trying to identify the bird's shape, the system analyses the physics of its flight. By measuring the characteristic circular or elliptical motion - the 'curl' of the bird's movement pattern - it can identify a circling bird of prey even from a distance, distinguishing it from harmless, straight-flying birds.

The entire system works instantly in a continuous cycle designed for quick decisions:

1.     Sensing: Cameras, microphones, and motion detectors constantly send data.

2.     Classification: Every moving object is quickly and accurately identified (e.g., Fox, Hawk, or Not a Threat).

3.     Threat Scoring: An algorithm calculates a risk level based on how dangerous the species is, how close it is, the time of day, and its suspicious behaviour (e.g., stalking behaviour gets a very high score).

4.     Automated Response: If the Threat Score goes above a safe limit, the system immediately triggers a safe, non-harmful deterrent that matches the threat:

o   Visual: Bright lights or strobe lights turn on.

o   Acoustic: Alarm sirens or specific recordings of predator distress calls are played.

AI Threat Detection and Response Pipeline

This smart monitoring system directly solves the problem of negative interaction between wild animals and chickens by acting as a risk filter.

Because WAMS is excellent at telling the difference between a real threat and a non-threat, it dramatically cuts down on unnecessary alarms. This means deterrents are only used when absolutely required, reducing stress on farm staff and, importantly, on the local wildlife population.

The system logs every verified sighting. This provides valuable, continuous information on how predators move and behave. This data can be shared with environmental experts to help plan for better coexistence, ensuring protective measures don't just push the wildlife problems onto a neighbour's property.

By pinpointing the exact species and location, the system can choose the best, most effective, and specific deterrent (like using a certain distress call for a certain bird), which ensures efficiency and promotes ethical wildlife management.

Strategic Advantages and the Future

Switching to AI-based assessment offers big benefits for both the farm owner and the surrounding environment:

·        Proactive Prevention: Losses are kept to a minimum because the threat is stopped before it gets close to the flock.

·        Ethical Practices: The commitment to non-harmful deterrents fits perfectly with strict European animal welfare and conservation rules.

·        Financial Benefits: While there's an initial setup cost, this is quickly balanced by saving money on labour, reducing chicken deaths, and limiting damage to farm buildings.

The future of profitable and wildlife-friendly poultry farming completely relies on adopting smart, ethical, and locally adapted AI solutions. This creates a winning situation for everyone - protecting farming livelihoods while also safeguarding nature.

Conclusion

AI threat assessment is rapidly turning farm security from a constant, reactive worry into a smart, proactive science. By accurately spotting and safely deterring predators, sophisticated systems like WAMS are leading the way toward a more balanced and harmonious relationship between commercial farming and the region's diverse wildlife. This technology is about more than just protecting chickens; it's about setting a new, ethical standard for modern agriculture.