Industry Development Grant_Alan Dorin
Project code: PRJ-012993
Project stage: Closed
Project start date: Tuesday, October 20, 2020
Project completion date: Friday, November 19, 2021
Jounral Articles From Project: Multi-point computer vision reveals the fruits of labour from different insect pollinators TBC (Issue: TBC on 31/12/2021)
National Priority: HBE-Identify and develop technology for improved hive performance.
The funds will be used to support a current project by allowing us to extend an existing,
working, single-unit honeybee activity monitoring prototype. This prototype contains a highquality
digital camera, portable Raspberry-Pi computer for in-field installation, power source
and solar support, and custom machine learning software that tracks insect numbers,
movement patterns and floral-visiting behaviours of individual honeybees using machine
learning and data analysis.
Hive placement with respect to crop and unmanaged vegetation – Where should hives be
placed with respect to managed and unmanaged floral resources to ensure adequate forage
is available to maintain required bee nutrition while maintaining pollination outcomes?
* Hive numbers and effectiveness – How strong is the foraging in specific regions of a
polytunnel? Are more or less bees required in a region for good pollination outcomes? How
long do bees spend on flowers? How successfully do bees navigate within the polytunnel
* The suitability of bees for particular crops in particular regions and climates – Are bees
visiting the crops? Or do they prefer to visit nearby unmanaged floral resources such as
weeds and wildflowers?
* Bee activity levels – Are bees behaving within polytunnels as healthy foragers are
expected to behave? Or are they sluggish, confused, disoriented, heat stressed?