The Center for Education and Research in Information Assurance and Security (CERIAS)

The Center for Education and Research in
Information Assurance and Security (CERIAS)
Center for Education and Research in Information Assurance and Security

Cyber-Physical-Collaborative Agricultural Robotic Systems for Food Security

Research Areas: Cyber-Physical Systems

Principal Investigator: Shimon Nof

Food security is an essential challenge for society, especially in the face of climate change and increasing world population. The food security challenge is addressed by this project, which aims to develop (1) cyber-collaborative design and control algorithms and protocols for agricultural robotic systems (ARS); (2) Hubs of Collaborative Intelligence (HUB-CIs) for harmonizing intelligence flows. The ARS is designed to monitor, detect, and respond to different types of plant stresses to ensure reliable quality and productivity. This ARS cyber-physical system involves various agents: human farmers and farm workers, agricultural scientists and experts, agricultural autonomous robots and drones, and cyber-physical environments, including sensors, vision-systems, and AI. These agents must collaborate intelligently to overcome agricultural production and crops' unstructured and ever-changing conditions.

This project addresses the challenges of food security and real-time AI-based cyber-physical robotic automation. In a new phase of this project, we develop computational models for harmonizing telerobotic and human control/decision-making with agricultural robots and drones, and fruit harvesters.

Personnel

Other PIs: Avital Bechar Yang Tao

Other Faculty: Puwadol (Oak) Dusadeerungsikul, Praditya Ajidarma

Students: Churchill Sandana, Vivek Sangani

Representative Publications

  • Dusadeerungsikul, P. O., & Nof, S. Y.,  “A collaborative control protocol for agricultural robot routing with online adaptation.” Computers & Industrial Eng., 135, 2019, 456-66.

     

  • Dusadeerungsikul, P. O., & Nof, S. Y. (2024). Precision agriculture with AI-based responsive monitoring algorithm. International Journal of Production Economics, 271, 109204.

     

  • Dusadeerungsikul, O.P., Nof, S.Y., Cyber Collaborative Algorithms and Protocols: Optimizing Agricultural Robotics. Springer Series on Automation, Collaboration, and E-Services (ACES), Vol.15, 2024.

  • Wang, D., Vinson, R., Holmes, M., Seibel, G., Bechar, A., Nof, S.Y., Tao, Y., “Early Detection of Tomato Spotted Wilt Virus by Hyperspectral Imaging and Outlier Removal Auxiliary Classifier Generative Adversarial Nets (OR-AC-GAN),” Nature-Scientific Reports, 9(1), 2019, 4377.

Keywords: crop disease monitoring and detection, cyber-collaborative agricultural robots, disease treatment, food security