Kann KI einzelne Bienen in einem Bienenstock mithilfe von Computervision verfolgen und ihre Rollen vorhersagen ?

Soziale Insekten wie Bienen zeigen komplexe Verhaltensweisen, die von individuellen und gruppenbezogenen Dynamiken abhängen. Kürzlich entwickelte KI-Systeme, die mit Videodaten aus Bienenstöcken trainiert wurden, können einzelne Bienen im Laufe der Zeit identifizieren und verfolgen, selbst bei Verdeckungen. Diese Modelle können Rollen wie Sammlerin, Amme oder Putzbiene anhand von Bewegungsmustern und Interaktionen klassifizieren. Diese Errungenschaft fördert unser Verständnis von kollektiver Intelligenz und bietet Werkzeuge für die ökologische Überwachung.

Background

Computer vision has been increasingly applied to the study of bee behavior, enabling researchers to track individual bees within a hive using cameras and machine learning algorithms. These systems analyze movement patterns and interactions, allowing classification of roles such as forager, nurse, or guard bee. Early work established that movement trajectories and social interactions correlate with functional specialization in colonies; for example, foragers exhibit distinct flight patterns and interaction networks compared to nurses, which remain closer to brood cells. By 2018, systems demonstrated the ability to identify and follow specific bees through occlusions using spatio-temporal deep learning models trained on hive video data. These models leverage behavioral signatures—such as path regularity, interaction frequency, and spatial preferences within the hive—to infer roles with reported accuracies above 85% in controlled settings. The approach builds on foundational studies in social insect ethology, which mapped behavioral repertoires using manual observation and RFID tagging, but extends those methods with scalable, non-invasive computer vision. Active research continues to improve occlusion handling, real-time performance, and generalization across hive configurations and bee species. Source: Proceedings of the National Academy of Sciences, 2018.