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📡 IoT Smart Hive Monitoring: Sensor Fusion & Anomaly Detection (2D)

2D beehive IoT sensor lab: a live weight time-series driven by nectar-flow foraging cycles, a bee-cluster thermoregulation homeostat holding the 34.5°C brood nest against ambient swings, and rule-based anomaly detection that flags swarming, robbing and thermal stress.

Entomology & Insect Behaviour2DModerate60 FPS📱 Mobile-adapted⇄ 3D version
2d-iot-smart-hive-monitoring-and-asset-tracking-lab ↗ Open standalone

This 2D companion strips the IoT beehive lab down to the sensor feeds a real apiary dashboard actually watches: a hive-weight time series driven by a forager-activity curve and nectar-flow rate, a bee-cluster thermoregulation homeostat that fights to hold the 34.5°C brood-nest setpoint against whatever ambient temperature you dial in — reporting the fanning effort as it saturates — and an internal-humidity trace shaped by nectar curing. A disturbance button lets you trigger a sudden colony-strength loss (a swarm or robbing event), instantly visible as a weight cliff and a thermoregulation capacity drop, and a rule-based anomaly detector fires the same alerts a commercial hive-scale system would: rapid weight loss and thermal-stress warnings, logged with a timestamp.

⚙ Under the hood

2D beehive IoT sensor lab: a live weight time-series driven by nectar-flow foraging cycles, a bee-cluster thermoregulation homeostat holding the 34.5°C brood nest against ambient swings, and rule-based anomaly detection that flags swarming, robbing and thermal stress.

beeshiveiotsensorsanomaly detectionthermoregulationapiaries

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install

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