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.

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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

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Towards an AI-Driven Cyber-Physical System for Closed-Loop Control of Plant Diseases

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1 citations
Proceedings of the AAAI Symposium Series
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Towards an AI-Driven Cyber-Physical System for Closed-Loop Control of Plant Diseases

Abhisesh Silwal, Chang‐Tien Lu, Boris Alexander Vinatzer, George Kantor, S. Haque, Li Song, Xuemei Zhang, Thomas M Hadlock, Jacob Neice, Adwait Kaundanya
article en
1 citations

Abstract

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.

Proceedings of the AAAI Symposium SeriesVol. 4(1)
Carnegie Mellon University (US), Virginia Tech (US)
U.S. Department of Agriculture
Zero hunger
Openalex Percentile: Top 21%
Plant Virus Research Studies
0.60
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