Step into the future of agriculture with FarmAssist. It makes planning crop rotations easy with AI-powered optimization of yield and profits based on soil data, market trends, location, and growth history. The simple yet powerful UI puts machine learning intelligence right into your fields. Make the industry work for you.

FarmAssist is a fully customizable, AI-powered crop management system leveraging soil data, satellite imaging, market trends, location data, and growth history sourced from a combination of user input and publically available APIs to optimize crop rotation. It is made up of the following key pages: Dashboard, Farm Map, Crop Rotation, Financial Analysis, Soil Data, and Plant Diagnosis. There is also an integrated AI chatbot named Farm Assistant, accessible from the bottom right corner of the screen on any page, to assist the user in learning about farming concepts such as crop rotation, soil quality, intercropping, or anything else. Dashboard provides an overview of all key features with links to the relevant detailed internal or external references. One of the widgets uses AI to project market trends for the farm's currently growing crops. Farm Map allows the user to search for satellite imaging of their farm and then draw the boundaries of each field and label them with their current crop. Crop Rotation utilizes AI to suggest tailored, optimized future crop rotations based on a selected focus such as profit or nutrients. Financial analysis estimates profit margins for currently planted crops using current USDA data to approximate both revenue and cost. Soil Data uses a trained machine learning model to predict what type of crops will grow best in soil with certain conditions input by the user such as pH, phosphorus, nitrogen, and potassium levels along with temperature, humidity, and more. Plant Diagnosis operates separately from the rest of the pages as a tool for farmers in the field. From a mobile device, the user can take a picture of a diseased crop and have an instant AI-powered diagnosis alongside suggested actions to resolve or minimize the disease. As a whole, the platform empowers agricultural workers to utilize AI for farming optimization without technical overcomplication.

Next.js, React, TypeScript, Shadcn UI, Supabase, Tailwind CSS, Lucide Icons, React Hooks, Canvas API, CSS, Google Maps API, Static Maps API, Geocoding functionality for coordinates, Supabase, Flask, USDA and OpenWeather API endpoints, Self Trained Crop Rotation Algorithmic Model, Plant Disease Diagnosis using AI and external API, Self trained Soil Analysis machine learning model