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Edge-compute removal of backgrounds from insect tracking videos

Primary supervisor

Adel Nadjaran Toosi


Background: Insects are vital components of natural and agricultural ecosystems that interact with plants in complex ways. Monitoring can help us understand these interactions to improve crop production, and to assist us to sustain our natural ecosystems as we change the Earth's climate. This technology is vital to inform our strategies to protect global food supplies and manage our national parks and forests.

Bees, wasps and flies are needed to pollinate our crops and wildflowers. Butterflies and moths can be excellent flower pollinators, but their caterpillars can completely eat through young crop plants. Wasps sometimes sting humans, but some species make excellent bio-control agents that hunt for caterpillars on our crops, saving the crop's leaves from being eaten to the stem. The world of plant-insect interactions is complex! How can we understand what will happen to these systems? How can we help make sure they are managed sustainably?

This project will develop a new component to our previous research on monitoring technology for insect-plant interactions that enables greater efficiency and more effective use of edge-compute monitoring devices. This technology will help us to explore how to improve greenhouse crop production by boosting pollination, enhancing natural bio-control agent behaviour, and suppress insects pests. This will help us to grow more food, use less chemicals, and reduce our impact on the environment.



Student cohort

Single Semester


Aim: Use edge compute power to extract backgrounds from videos of moving insects (in the hive or on crops outside of the hive) to save storage space and transmission costs for sending the captured video to offline processing.

Required knowledge

Computer programming (e.g. C++ Python or other languages) and experience with basic image processing

An interest (but not necessarily formal qualifications) in ecology, insects, plants, sustainability or food production

Linux Shell Scripting

Experience of  working with Raspberry Pis is a plus

Curiosity is required!