The funds will be used to support a current project by allowing us to extend an existing, working, singleunit honeybee activity monitoring prototype. This prototype contains a highquality digital camera, portable RaspberryPi computer for infield installation, power source and solar support, and custom machine learning software that tracks insect numbers, movement patterns and floralvisiting 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 environment? * 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?
Project Start Date
Tuesday, October 20, 2020
Project Completion Date
Friday, November 19, 2021
Journal Articles From Project
Frontier technologies for building and transforming Australian industries
HBE-Identify and develop technology for improved hive performance