A sensor driven approach to assessing health in honey bee colonies

Summary

This project aims to optimise honey bee colony health by developing low-cost sensor arrays. 
The supervisory team for this project also includes Dr Ash Rahman (Data61) and Dr John Roberts (CSIRO).
A complimentary scholarship for this project is available. To find out more, refer to the Postgraduate Research Stipend and Supplementary Scholarship in Digital Agriculture Data61.

Supervisor(s)

Dr Tanya Latty

Research Location

School of Life and Environmental Sciences

Program Type

PHD

Synopsis

We intend to develop an integrated monitoring system that detects colony problems before they are otherwise apparent. We are looking for a student to develop integrated sensor arrays that can monitor and analyse honey bee colony parameters such as humidity, acoustic activity, brood temperature, forager activity and colony weight. While a few such systems exist commercially, they are prohibitively expensive, do not necessarily monitor the most relevant hive parameters, and lack sophisticated, data-driven analysis. Second, we want to combine sensor technology and analysis techniques to develop a user-friendly decision tool that helps beekeepers optimise colony health through early detection of potential problems. This project would be ideally suited to a student with a background in engineering and computer science and with a strong interest in honey bees.

Additional Information

The supervisory team for this project also includes Dr Ash Rahman (Data61) and Dr John Roberts (CSIRO).

A complimentary scholarship for this project is available. To find out more, refer to the Postgraduate Research Stipend and Supplementary Scholarship in Digital Agriculture Data61.

In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include: 

  • Confidential disclosure and registration of a disability that may hinder your performance in your degree; 
  • Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.); 
  • Ability to perform independently and/or with minimal supervision; 
  • Ability to undertake certain physical tasks (e.g. heavy lifting);  
  • Ability to undertake observatory, sensory and communication tasks; 
  • Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden); 
  • Ability to work in confined spaces or at heights; Ability to operate heavy machinery (e.g. farming equipment); 
  • Hold or acquire an Australian driver’s licence; 
  • Hold a current scuba diving license; 
  • Hold a current Working with Children Check; 
  • Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.).
You must consult with your nominated supervisor regarding any identified inherent requirements before completing your applicaion.

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Keywords

digital, agriculture, Data61, CSIRO, Life and Environmental, pollination, swarm intelligence, social insects, native bees, honey bees, ants, entomology, applied entomology

Opportunity ID

The opportunity ID for this research opportunity is: 2352

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