Authors: Sarath Babu, Vincent Lee, Joscif Raigne, and Hongwei Zhang (Iowa State University), Yatish S. M., Matt Lieber, and Hari Subramoni (The Ohio State University), and Martin Kandes (San Diego Supercomputer Center) Modern agricultural AI relies on timely, high-quality field data. Yet collecting and processing this data in real time, especially in rural environments, remains … Continue reading ARA-to-ICICLE: Remote Data Sourcing for Agricultural AI Processing

We’re excited to share that the December 2025 ARA Newsletter is now available! This edition highlights ARA milestones, community insights, and the newest capabilities unlocked through the ARA wireless living lab.

In the AIIRA national AI institute, Prof. Soumik Sarkar (Mechanical Engineering) and Prof. Asheesh “Danny” Singh (Agronomy) at Iowa State University leverages ARA to investigate how networked agricultural ground vehicles, remote sensing and computing, and machine learning can automate labor-intensive field scouting—transforming hours of manual assessment into near-real-time analysis and decision-making. Traditional field scouting and … Continue reading “Amiga”: Accelerating Field Scouting with ARA’s FutureG Connectivity 

Author: Joshua Ofori Boateng  The Center for Wireless, Communities and Innovation (WiCI) at Iowa State University has taken a significant step forward in improving the coverage and reliability of next generation random access (RA) procedure with the development of AraRACH: Enhancing NextG Random Access Reliability in Programmable Wireless Living Labs. By leveraging real‑world data from the ARA wireless living lab, they devised a slot‑based scheduling framework that reschedules RA messages into full downlink and uplink slots, unlocking all 14 … Continue reading Enhancing NextG Random Access Reliability in Programmable Wireless Living Labs

Authors: Zack Murry (University of Missouri), Alicia Esquivel Morel (University of Missouri), and Kate Keahey (Argonne National Laboratory) Introduction As 5G networks expand beyond urban centers, it is also critical to understand how they perform in rural edge environments, where connectivity can be intermittent and infrastructure sparse. This project, conducted as part of the REU … Continue reading 5G in Practice: Measuring Rural Wireless Technology for Edge Devices in Distributed Computation Workloads