CPS: Small: Collaborative Research: RUI: Towards Efficient and Secure Agricultural Information Collection Using a Multi-Robot System
Lead PI:
Ladislau Boloni
Abstract

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.

This project led by the University of North Florida (UNF) and supported by the University of Central Florida (UCF) has two main goals: (i) develop and implement novel information collection techniques for autonomous mobile robots that collect, store and share data in an efficient yet secure manner using blockchain,and (ii)and to train undergraduate and graduate students to conduct basic and applied research while closely working with local farmland partners in north-east Florida. Current technologies already use robots for agricultural purposes, but they typically have a high maintenance cost and do not necessarily consider issues related to security and data integrity. The primary objective is to design and deploy a set of autonomous robots that communicate wirelessly and navigate through planned paths in order to collect valuable data. This project will also consider the threat of security attacks by which collected data can be corrupted; seeking new distributed blockchain-based consensus protocols that mitigate the adversarial influence of such attacks. This project also contains a significant research and education component leveraging the leadership of UNF in the context of a primarily undergraduate institution (RUI). Being predominantly an undergraduate institution, there is a lack of opportunity for pursuing higher degrees in the Jacksonville area. This project aligns with an established Memorandum of Understanding (MoU) between UNF and UCF to provide a conduit for computing/engineering students to pursue M.S. degrees at UNF that feed seamlessly into Ph.D. programs at UCF. Students will benefit from the new robotics course to be developed at UNF and the ones being offered at UCF. Research progress will be showcased via technical workshops at both institutions to be held annually. Developed solutions are expected to transfer to other cyber-physical system applications, including search and rescue, patrolling, advanced manufacturing, among others. Most broadly, this project will raise awareness among today's teenagers and young adults of the impending agricultural crisis if worldwide food production falls even further behind meeting demands of an increasing global population.
 

Ladislau Boloni
Lotzi Bölöni is a Professor of Computer Science at the University of Central Florida. He is a co-director of the AI Things Laboratory. He has secondary joint appointments in the Dept. of Electrical and Computer Engineering, at the UCF Center for Research in Computer Vision (CRCV) and the UCF Cluster for Disability, Aging and Technology. He received a PhD and MSc degree from the Computer Sciences Department of Purdue University and BSc in Computer Engineering from the Technical University of Cluj-Napoca, Romania. He held visiting researcher positions at Computer and Automation Research Institute of the Hungarian Academy of Sciences, University of Rome ``La Sapienza'', Imperial College of London and KTH Royal Institute of Technology, Stockholm, Sweden. He is a senior member of IEEE, senior member of the ACM, member of AAAI and the Upsilon Pi Epsilon honorary society.
Performance Period: 03/01/2020 - 02/29/2024
Institution: University of Central Florida
Sponsor: National Science Foundation
Award Number: 1931767