Computing Techniques for Crop Pest Monitoring

Project Outline:

1. The partner for this project will be with Department of Primary Industries and Regional Development (DPIRD) and several Farmer Groups
2. This project will look the use of images to map crop growth patterns across paddocks to determine changes in crop health (caused by poor nutrition herbicide damage, pest damage).
3. The project will use In-season monitoring of crop growth using UAVs and geospatial techniques including video and sensor technologies to monitor crop health.
4. The project will use
   1. Techniques such as image processing will be used determine changes in the crop damage;
   2. Ndvi images and ground truthing will also be used to validate
   3. These techniques will used to determine if they can be upscaled to predict patterns across the cropping regions of WA

Desired Skills:

1. Skills in Database Programming, and Artificial Intelligent systems and Advanced Computer Programming.  (Essential)
2. R and other languages (Desirable)
3. GIS technologies ArcGIS  (Essential)
4. Experience in Plant Science, Agriculture/Horticulture an advantage (Desirable)
5. Good oral and report writing skills (Essential)
6. Able to work in team environment  (Essential)
7. Good project management skills (Essential)
8. Drivers license

Project Area: Computing and Agriculture (Digital Agriculture Research Group)

Supervisor(s): Dr Leisa Armstrong, Professor Dean Diepeveen

Project level: Honours, Masters, PhD

Funding: Applicant should apply for ECUHDR or RTP Scholarship and Honours Scholarship available

Start date: Semester 1 2022