Towards an AI-Driven Cyber-Physical System for Closed-Loop Control of Plant Diseases
Plant diseases are a major biosecurity threat to food production and the bio-energy industry. Early detection and control of plant diseases can improve producers’ profitability and reduce environmental impacts from chemical inputs. We proposed to develop a cyber-physical system with three major components: an AI-driven imaging system for early stress detection, an autonomous robotic system to collect plant samples, and a sequencing pipeline to detect molecular signatures of pathogens for disease confirmation. This system is envisioned to control a detected disease by removing or pruning infected plants. This manuscript describes the major milestones achieved by this CPS project and provides a future perspective on disease control automation in agriculture.
Authors
- Abhisesh Silwal (ORCID: https://orcid.org/0000-0002-1710-6704)
- Chang‐Tien Lu (ORCID: https://orcid.org/0000-0003-3675-0199)
- Boris Alexander Vinatzer (ORCID: https://orcid.org/0000-0003-4612-225X)
- George Kantor (ORCID: https://orcid.org/0000-0001-7088-8533)
- S. Haque (ORCID: https://orcid.org/0009-0001-4010-6008)
- Li Song (ORCID: https://orcid.org/0000-0002-2724-5812)
- Xuemei Zhang (ORCID: https://orcid.org/0000-0002-3912-5295)
- Thomas M Hadlock
- Jacob Neice
- Adwait Kaundanya
Institutions
- Carnegie Mellon University (US)
- Virginia Tech (US)
Publication Details
- Journal
- Proceedings of the AAAI Symposium Series
- Published
- 2024-11-08
- DOI
- https://doi.org/10.1609/aaaiss.v4i1.31828
- Citations
- 1
- Primary Topic
- Plant Virus Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.60
Funders
- U.S. Department of Agriculture