The University of Manchester's Research Apiary.

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Projects View all

Identification of Bees

By removing the ambient noise of the bees’ environment, an audio profile can be created for different bee species. Further, by using the same noise removal techniques, we are attempting to monitor bee health through the analysis of differences in multiple recordings.

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Real-Time Imaging, Motion Tracking and Audio Identification of Bees in Field Conditions

This project is investigating the feasibility of developing an advanced multi-modal system for remote daytime video tracking and acoustic characterisation of pollinating species in field conditions. The system will prove particularly beneficial in studying the behaviours of insects that have economic significance, for example pollinating bees, and by extension, insects that act as disease vectors. To exemplify the technology, the sensor system will initially address the challenge of dynamically mapping the exchange of pollinators from the floral field margins to the bulk crop.

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Historical Positioning

By monitoring bees from a rather far distance (10-20m) and calculating the historical trajectories, we can determine the health conditions and foraging preferences of bees and help improve pollination strategy. To achieve this, inflight behaviours and foraging patterns are detected by processing the video data with object tracking algorithms and classifiers. The video recording equipment is a 4k@60fps chromatic camera and a 2k@170Hz monochrome camera.

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