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📊 Bee Colony Data Analytics Lab

A live 3D hive of agent bees driven by an SIR-style infection model, paired with floating data-lab charts that turn population, temperature, mite load and forager traffic into a rolling colony health index with statistical control bands.

AI & Machine Learning3DAdvanced60 FPS

A sample colony of agent bees cycles through a Susceptible–Infected–Recovered infection model while a floating data-lab panel turns population, temperature, mite load and forager traffic into a live colony health index with rolling statistical control bands.

🔬 What It Demonstrates

Bee colour (gold / red / teal) shows each agent's SIR compartment; the health index blends infection load, thermal stress and forager throughput; the line chart's μ ± 2σ band and z-score flag statistically unusual readings, exactly as hive-monitoring dashboards do.

🎮 How to Use

Raise mite load or push temperature away from 35°C to watch infection spread and health drop. Pick which metric the chart tracks, then hit "Inject anomaly spike" to see the control band catch an out-of-range reading.

💡 Did You Know?

Real precision-apiculture research borrows exactly these tools from other fields: SIR models from epidemiology, control charts and z-scores from finance and quality engineering, and rolling averages from climate science.

⚙ Under the hood

Artificial IntelligenceMachine LearningSimulationAgent Based ModelingEpidemicsData AnalysisThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install