Arslan Munir, Ph.D., associate professor in the Department of Electrical Engineering and Computer Science at Florida Atlantic University (FAU), has been awarded an $827,533 grant from the United States Department of Agriculture’s National Institute of Food and Agriculture. The funding will support a research project led by Munir that brings together FAU, Kansas State University, and Purdue University to develop an advanced computing framework for precision agriculture.
The project aims to create “FogAg,” a system based on edge and fog computing designed to enable real-time sensing and analysis of how water and nitrogen levels impact crop growth and yield. Managing these two critical inputs is a major challenge in agriculture due to their influence on both productivity and environmental health.
Munir explained that current smart agriculture tools often do not capture or respond to the complex interactions between water and nitrogen with enough precision or speed. The FogAg framework is intended to address this gap by integrating new developments in edge/fog computing, cyber-physical systems, and multi-modal sensing. The goal is to provide farmers with timely data for site-specific decisions about fertilizer and irrigation use.
“Receiving this USDA grant is an important milestone in our pursuit of transformative agricultural technologies,” said Munir. “Our goal with FogAg is to create an intelligent, adaptable and energy-efficient framework that empowers farmers with the data they need to make timely, site-specific decisions. By capturing and analyzing the nuanced interactions between water and nitrogen stressors, we aim to not only increase crop yield and quality but also reduce the environmental impact of modern agriculture. This project represents our deep commitment to leveraging advanced computing systems in service of sustainable food production.”
The FogAg system will feature a three-tiered architecture connecting IoT devices, fog computing nodes, and cloud servers for distributed processing. A component called Neuro-Sense will allow for energy-efficient signal and image processing tailored to changing field conditions.
Researchers plan to build a multi-modal sensing platform including LED-based multispectral imaging, near-infrared point measurement sensors, and dielectric soil sensors using frequency response technology. These devices are expected to gather comprehensive data on plant canopy as well as soil health.
“These tools will enable sensing above, below and within the plant canopy, capturing a comprehensive picture of crop and soil health,” said Munir.
Data collected through these sensors will be processed using machine learning methods such as convolutional neural networks for image analysis. Predictive models will then generate variable-rate recommendations for fertilizer and irrigation application based on both real-time field data and historical information.
The team expects that implementing real-time management strategies for water and nitrogen could help improve resource efficiency while reducing costs for producers. There may also be environmental benefits such as lowering agriculture’s nitrogen footprint by minimizing runoff into surrounding ecosystems.
“This research epitomizes the kind of forward-thinking, impact-driven innovation at Florida Atlantic University,” said Stella Batalama, Ph.D., dean of the College of Engineering and Computer Science. “Professor Munir’s work is a great example of how engineering can lead transformative change in critical sectors like agriculture. The integration of smart technologies into farming practices not only addresses urgent global challenges around food security and sustainability but also reinforces our role as a leader in cross-disciplinary research with real-world impact.”
In addition to its technical goals, the FogAg project will integrate its findings into FAU’s undergraduate and graduate curricula so students can learn about smart agriculture technologies firsthand.
Munir’s collaborators include Michell L. Neilsen, Ph.D.; Naiqian Zhang, Ph.D.; Paul Armstrong, Ph.D.; Rachel L.V. Cott, Ph.D., all from Kansas State University; along with Ignacio Ciampitti, Ph.D., from Purdue University’s Department of Agronomy.
