Agentic AI for smart and sustainable precision agriculture
The results confirm the feasibility and effectiveness of integrating AAI with federated learning for intelligent precision agriculture. A SWOT analysis highlights the strengths of the proposed approach, along with deployment challenges and constraints. Overall, this study establishes a roadmap for future research, emphasizing sustainable intelligent farming systems.
Authors
- Parvathaneni Naga Srinivasu (ORCID: https://orcid.org/0000-0001-9247-9132)
- Aruna Pavate (ORCID: https://orcid.org/0000-0002-3387-0905)
- Muhammad Fazal Ijaz (ORCID: https://orcid.org/0000-0002-9381-5801)
- J. Isabelle Choi (ORCID: https://orcid.org/0009-0005-2534-5886)
- G. JayaLakshmi
- Jana Shafi
Institutions
- Gachon University (KR)
- Prince Sattam Bin Abdulaziz University (SA)
- Siddhartha University (NP)
- Theologische Hochschule Chur (CH)
- Torrens University Australia (AU)
- Higher Education Academy (GB)
- Amrita Vishwa Vidyapeetham (IN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2026-01-14
- DOI
- https://doi.org/10.3389/fpls.2025.1706428
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00