%0 Conference Paper %1 10.1007/978-3-031-17718-7_1 %A Davidson, Padraig %A Steininger, Michael %A Lautenschlager, Florian %A Krause, Anna %A Hotho, Andreas %B Sensor Networks %C Cham %D 2022 %E Ahrens, Andreas %E Prasad, RangaRao Venkatesha %E Benavente-Peces, César %E Ansari, Nirwan %I Springer International Publishing %K %P 1--20 %T Anomaly Detection in Beehives: An Algorithm Comparison %X Sensor-equipped beehives allow monitoring the living conditions of bees. Machine learning models can use the data of such hives to learn behavioral patterns and find anomalous events. One type of event that is of particular interest to apiarists for economical reasons is bee swarming. Other events of interest are behavioral anomalies from illness and technical anomalies, e.g. sensor failure. Beekeepers can be supported by suitable machine learning models which can detect these events. %@ 978-3-031-17718-7

@inproceedings{10.1007/978-3-031-17718-7_1, abstract = {Sensor-equipped beehives allow monitoring the living conditions of bees. Machine learning models can use the data of such hives to learn behavioral patterns and find anomalous events. One type of event that is of particular interest to apiarists for economical reasons is bee swarming. Other events of interest are behavioral anomalies from illness and technical anomalies, e.g. sensor failure. Beekeepers can be supported by suitable machine learning models which can detect these events.}, added-at = {2023-12-13T06:34:07.000+0100}, address = {Cham}, author = {Davidson, Padraig and Steininger, Michael and Lautenschlager, Florian and Krause, Anna and Hotho, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/2f15bc8dd813ef9c03d2f2a09049a70cd/admin}, booktitle = {Sensor Networks}, editor = {Ahrens, Andreas and Prasad, RangaRao Venkatesha and Benavente-Peces, C{\'e}sar and Ansari, Nirwan}, interhash = {af215e64c4f44582a797ec2250ecb0de}, intrahash = {f15bc8dd813ef9c03d2f2a09049a70cd}, isbn = {978-3-031-17718-7}, keywords = {}, pages = {1--20}, publisher = {Springer International Publishing}, timestamp = {2023-12-13T06:34:07.000+0100}, title = {Anomaly Detection in Beehives: An Algorithm Comparison}, year = 2022 }