Digital Twins in Agriculture: Virtual Farm Model for Enhancing Crop Health, Productivity, and Sustainability.

This project aims to translate essential knowledge from TRL 3 to 5 and develop intellectual property required to commercialise a digital twin (DT) platform for sustainable agriculture, including pest and disease management.

This AEA commercial-translation proposal will produce an essential prototype and IP protection of a brand new, globally unique digital twin (DT) agricultural platform for improved decision-making of Australian farmers to foster business profit and environmental friendliness. Increasing plant disease outbreaks threaten the vulnerable food security on the globe. At the forefront of agricultural innovation and as core innovation, the software is organised as cohesive advice from multiple ‘virtual experts’, via being the embedment multi-agent generative system (MAGS), which will leverage the Internet of Things (IoT) and DT to create virtual farm models. MAGS-decision-making via predictive insights aims to enhance crop health and farm profitability, exemplified for two major Australian farm products: canola and vine.

• The project is co-funded by the Australian Department of Education through Australia’s Economic Accelerator (AEA) Ignite initiative. Its primary goal is to develop a Digital Twin (DT) agricultural platform that will enhance decision-making for Australian farmers, promoting both business profitability and environmental sustainability.
• The project integrates a variety of sensors, each designed to measure different physical and chemical parameters, such as humidity, temperature, salinity, orientation, and wind speed, placed at strategic locations across the estate. Concurrently, the project will develop a Digital Twin software prototype, marking a significant advancement toward commercialisation. This innovation holds great potential for enhancing the agricultural sector.
•  The software is designed as a cohesive consultation system of multiple ‘virtual experts’ (sensors) through the embedded Multi-Agent Generative System (MAGS). By leveraging the Internet of Things (IoT) and Digital Twin (DT) technology, it will create dynamic virtual farm models to support informed decision-making.