20 docs tagged with "Digital Agriculture"

System Architecture

What Version 1.2.0 Adds

TapisUI provides a research oriented frontend to interact with Tapis and tenant components. In this case, the ICICLE extension extends TapisUI with custom branding

Background:

A collaborative machine learning platform for agricultural data analysis and model training with privacy-preserving features.

The GNN Food Flow Portal is a Streamlit web app for exploring county-level U.S. food-flow predictions from the GNN FoodFlow Model. Version 1.2.0 includes the original parallel SCTG-specific model exploration workflow plus a new multi-task GNN what-if portal for one-to-one and one-to-many county scenario analysis.

Harvest is a tool designed to allow multiple types of stake holders in the digital agriculture space further their own unique goals from research to increases of the bottom line. Harvest allows for the creation of pipelines where users can preprocess their data, train models on HPC resources, infer on models to get insights on farm fields, and some visualizations to give an at a glance understand of what is happening on the field.

How to Upload a Dataset

Run the Portal Locally

Quick Guide

View the main TapisUI wiki to learn how to deploy and test TapisUI extensions locally.

Problem Description:

The Decentralized Microservice Drone System for Digital Agriculture is a distributed, scalable platform designed to orchestrate autonomous drone operations for agricultural field missions. The system captures, processes, and analyzes aerial imagery and video data to support precision agriculture, crop monitoring, and field management operations.

This tapis ui extension enables additional icicle specific branding and tabs on tapisui.

- The prerequisites to use Harvest are an Internet browser and contacting us at icicle_harvest@osu.edu for a trial account.

Getting Started with the Food Security Sandbox

Explore Parallel Model Food Flows

Prerequisites

Overview

This project provides an open-source orchestration engine designed to automate and scale the transformation of raw Unmanned Aerial Systems (UAS) imagery into structured, AI-ready datasets for agricultural research.