OAS Future Vision

We are starting the OAS Digital Twin project to port the globally standard DSSAT model to a modern architecture on a 1:1 basis. Through rigorous cross-validation, we guarantee 100% mathematical equivalence and build a next-generation simulation engine that adds infinite scalability on top of verified reliability.

• OAS-DSL (Domain Specific Language): Provides an intuitive Fluent Interface specialized for agricultural modeling (e.g., Crop.When(Stage.Flowering)...)
• Dynamic Compiler: Instantly compiles user scripts or AI-generated code at runtime using Roslyn to reflect in simulations
• RAG Coding Assistant: Converts natural language commands like "Apply the high-temperature damage formula for rice" into executable C# code

We hyper-connect all plant information from research institutes and general users through OAS Growth Chamber and Cloud to accumulate vast growth big data. Through virtual simulation with accumulated data and mathematical models, we precisely derive optimal recipes for special purposes such as plant treatment, medicinal components, and specific trait enhancement. Furthermore, we perform preemptive simulations for climate crises like global warming and special environmental conditions, preparing for stable food production anytime, anywhere.

We extract core patterns from AI models that have learned accumulated big data and complex biochemical mechanisms, and apply Explainable AI (XAI) and Symbolic Regression technology to reversely derive hidden 'new mathematical growth formulas.' Through the process of human agronomists verifying and agreeing on these new laws discovered by AI, we continuously evolve into a 'White-box' model that anyone can understand, rather than an unknowable 'Black-box.' Through this, we scientifically elucidate even unknown areas that existing formulas could not explain, and develop the AgSharp engine into a next-generation research tool that becomes smarter on its own.

Our technology is not limited to specific crops. Together with scientists, we apply new mathematical models to various plants, and aim for an open research platform that can digitize and simulate growth models of other biological species such as mushrooms, seaweed, and insects.

OAS becomes the brain of agricultural humanoid robots. By calculating optimal cultivation methods through simulation, robots independently decide planting timing and plant, decide harvest timing and harvest, opening the era of Fully Autonomous Farming.