The project unites Florida Atlantic University, Kansas State University and Purdue University to develop FogAg, an edge and fog computing framework that delivers real-time, multi-layer sensing and analytics on how water and nitrogen together shape crop growth and yield across varied conditions.
Agriculture must boost production while conserving resources, yet water and nitrogen mismanagement can depress yields and pollute through runoff and waste. Many current smart farming tools cannot capture or react to these intertwined stresses with the timeliness and spatial precision farmers require.
FogAg is designed to close that gap by merging advances in edge and fog computing, cyber-physical systems and multi-modal sensing to generate actionable insights into plant-soil dynamics. The research spans architecture, sensing, machine learning and predictive modeling to interpret field data and recommend responses in near real time.
"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 system centers on a three-tier cyber-physical architecture spanning IoT devices, fog nodes and cloud servers for distributed processing and rapid analytics. Neuro-Sense, a reconfigurable platform, underpins energy-efficient signal and image processing to handle changing in-field workloads.
A multi-modal sensing suite will pair an economical LED-based multispectral imaging setup with a near-infrared point measurement sensor and a frequency response-based dielectric soil sensor. Together they capture conditions above, below and within the canopy for a comprehensive view of crop and 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.
For data processing, the team will use advanced machine learning, including a highly efficient convolutional neural network accelerator to parse image and sensor streams. Outputs will feed tree-based predictive models that fuse real-time and historical data to generate site-specific, variable-rate prescriptions for irrigation and fertilizer, boosting productivity while curbing input waste.
By integrating real-time water and nitrogen management, FogAg targets lower production costs and a reduced nitrogen footprint, with environmental benefits from less runoff and pollution. The framework's spatial and temporal scalability positions it for use from large industrial farms to urban and peri-urban operations.
"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."
Educational plans embed project outcomes into undergraduate and graduate curricula, preparing students to apply smart agriculture technologies. Co-investigators include Michell L. Neilsen, Ph.D.; Naiqian Zhang, Ph.D.; Paul Armstrong, Ph.D.; and Rachel L.V. Cott, Ph.D., at Kansas State University, and Ignacio Ciampitti, Ph.D., at Purdue University, ensuring both technical rigor and agronomic relevance.
Related Links
Florida Atlantic University
Farming Today - Suppliers and Technology
| Subscribe Free To Our Daily Newsletters |
| Subscribe Free To Our Daily Newsletters |
