Standard Data Platform for Autonomous Agriculture
The world's first interactive planning software for precision and autonomous agriculture
Operating a farm is costly, requiring the purchase of fertilizer, fuel, chemicals, machinery, and other materials. These energy-intensive inputs increase agricultural GHG emissions, which make up 12% of Canada’s total emissions, and lower net farm income. The combination of advancing climate change and declining net farm income is threatening the livelihoods of farmers and our global food supply. To truly move the needle on impacting net farm income and drive the adoption of digital tools, this sector needs a shift from an isolated, siloed view of disparate data layers to a more inclusive, collaborative view of multiple data layers. By providing the tools necessary to evaluate the dependencies between these data layers, this project can enable timely planning of farm operations that will empower smarter, faster and more sustainable food production.
How We Are Solving It
Led by Verge Ag in collaboration with Terramera, i-Opentech, Simon Fraser University, and Quantotech, this project will create the world’s first interactive operational planning platform for autonomous agriculture. The Standard Data Platform for Autonomous Agriculture will integrate three technology components: (1) a data commons framework that fosters innovative data reuse, integration, and visualization to enable characterization of fields, farms, machinery, soil, water, terrain, and weather, (2) a digital twin of the farm by automating the characterization of the fields to fully digitize and define the closed course of the field, and (3) a planning platform that simplifies operations planning to reduce in-field decision making. This platform will provide true performance insights that demonstrate a very clear ROI to users in a concise and easily accessible manner.
The platform will use analytic-ready data and digital tools that combine in-field activities, field terrain, crop and soil characterization and meteorological data to create a digital version of the farm and growing season. This technology will enable farmers to better plan their farming operations and make data-driven decisions based on economic and environmental factors.
These improvements will also impact the atmospheric, terrestrial, and biotic environmental systems associated with crop production, reducing the environmental impact of Canada’s agriculture sector.
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