School of Science

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Digital agriculture

Digital agriculture science and technology research focuses on the application of technologies to improve the productivity and sustainability of agricultural and related industries. The research draws on expertise across computing and agricultural science. The focus is to promote research & Innovation and education to support Agricultural industries, ensuring that the industry remains internationally competitive.

It leverages from on-the-ground facilities through a collaboration with the Shire of Boyup Brook at Rylington Park. (https://www.boyupbrook.wa.gov.au/community/your-community/rylington-park.aspx). The group works closely in the three main vectors driven by the state government WAAC (https://waagresearch.org.au/).

Key Research and Capacity Building Areas

Improving agricultural production, sustainability, market access and profitability of the agriculture industry by tactical in-season farm and environmental data collection and monitoring
Optimising smart farm technologies practices for improved productivity and sustainability
Capacity building through research training of M.Sc. and PhD students

Expertise in the following areas.

Sensor Networks and drone technologies
Agricultural data management
Computer Science techniques
Geospatial Technologies

Current Projects and Research Interests

Tactical in-season farm and environmental surveillance

Using drone/sensors with high-throughput data analysis to automate collection of crop-growth components for on-farm decision making.
Vertical Fencing for the detection of predators and feral animals
Image Processing of Wheat Heads using L-systems
Visualisation and 3D Image generation of Crop determinants (Coffee, Wheat)
Trilateration of animal tags using Ground-Based Low Powered Networks (LoRa)
Remote Water Tank monitoring using Lidar sensors and LoRaWAN
Monitoring of extreme conditions across the farm (Frost, Extreme Heat) using IoT based sensor networks

Smart Farm Technologies

Scoping Review of Ag Smart Systems and Decision Support Tools
Drone Codes of Conduct and Farm Management practices
Vertical Farming using IoT sensors for Micro Herbs and Edible Plants
Review of Drone Technologies, Image Resolution and Aerial Standardisation Factors
Honey pots and sensor security
Securing Data on farms
Deep Learning Techniques for Crop Image Detection
Wheat production modelling. (L-systems)