anomaly detection

Unsupervised Anomaly Detection on Multisensory Data from Honey Bee Colonies

Beekeepers face the situation that the health state of honey bee colonies is inherently difficult to observe without stressing the bees by opening the hive. We address this problem by proposing an approach that relies on a sensor setup to gather multisensory data inside the bee colony and focus on the detection of outliers in the data stream as indicators of critical situations during the colony's development.

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