Machine Learning and Waggle Dances

by | Jan 19, 2021 | Connected Nature | 0 comments

Towards the end of last year we were lucky enough to be successful in a bid to the South West Creative Technology Network’s Data Prototyping Programme. This means that we’re being supported until the end of March to develop an exciting collaboration between us and Pollenize.

You can read more about all the successful projects on the SWCTN website but, in a nutshell, the focus of the project is to find non-intrusive ways of using bee behaviour to gather environmental intelligence data: this could lead to both further research around the drivers of insect decline, and help people take action by rewilding areas that are signposted by the bees’ behaviour.

Some scientists have already been able to decode the ‘waggle dance’ which is the bee’s method of communicating the location of forage to each other. This was done in a lab environment though, and so one thing we’re interested in is the possibility that this can be done in real beehives.

To do this we will be experimenting with different cameras, perhaps even helping Pollenize to redesign their hives, and perhaps using other data the hives can give us (for example sound, vibration, and other environmental factors) to build up a much more rich representation of what is going on without disturbing the bees. Combining these datasets with things like pollen analysis and ground observations might be able to produce very specific maps of where bees are feeding. 

There’s a lot of work to be done (in fact we’re hiring for a couple of roles to help us) and we can’t wait to see where this project takes us, but for now we’d love to connect with anyone with an interest in the project. Get in touch through our contact page if you’d like to chat and sign up to our newsletter for regular updates on this project and all the other work we’re developing during 2021.

Bee photo by Delia Giandeini on Unsplash



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