Using machine learning to detect anomalies in beehives

BeeObserver collects sensor data from hives across Germany. We build a machine learning alarm system that alerts beekeepers when something goes wrong.

Modeling Open Data

Status: Finished
Project Period: October 2019 – February 2020
Outputs: Video Video Podcast Episode
Local Chapter: Rhein-Main, Bremen
Partner: Bee Observer BOB

Beekeepers, makers and researchers work together on the digital hive. In this way, risks and dangers for honey bees can be identified and reduced more quickly.
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Bees are crucial for the preservation of life on earth in its current form. The CorrelAid team helped the citizen science initiative BeeObserver to take bee observation and research to the next level by making sensor data usable and using machine learning to build an alarm system that alerts beekeepers in case of emergencies.