Towards Efficient and Secure Agricultural Information Collection Using a Multi-Robot System

This is an NSF-sponsored project (#1932300) on Secure Precision Agriculture (March 2020 – February 2023).

With the growing world population and diminishing agricultural lands, it becomes imperative to maximize crop yield by protecting crop health and mitigating against pests and diseases. Though there are decades-old practices still in place, there is also growing adoption of so-called precision agriculture solutions, which employ emerging technologies in sensing, automation, and analytics in daily farmland operations. As farmers gain real-time access to critical data (e.g., land and weather conditions) and can quickly share any untoward findings with others, farmland operations are morphing into full-fledged cyber-physical systems. To this end, this project seeks to develop, implement and evaluate a multi-robot agricultural information collection system that is autonomous, efficient and secure.

Principal Investigators

Dr. Ayan Dutta (UNF)Dr. Swapnoneel Roy (UNF)Dr. Patrick Kreidl (UNF)Dr. Ladislau Bölöni (UCF)


Mr. Cesar Castellon Escobar
(MS @ UNF)
Mr. Siavash Khodadadeh
(Ph.D. @ UCF)
Mr. Tamim Samman
(MS @ UNF)
Mr. James Spearman
(BS @ UNF)


Conference papers

  1. A. Dutta, O. P. Kreidl, and J. O’Kane, “Opportunistic Multi-robot Environmental Sampling via Decentralized Markov Decision Processes”, 15th International Symposium On Distributed Autonomous Robotics Systems (DARS), 2021.


  1. M. Pugliese, A. Flowers, M. Tapia, and O.P. Kreidl, “Garduino: Using Image Processing in Matlab to detect health in plants,” Annual Conference of the National Council on Undergraduate Research (NCUR2021), Apr 2021.


Dr. Ayan Dutta (Email: a dot dutta at unf dot edu)