Agentic AI Framework to Automate Traditional Farming for Smart Agriculture
Muhammad Murad; Muhammad Ahmed; Nizam ul din; Muhammad Farrukh Shahid; Shahbaz Siddiqui; Daniel Byers; Muhammad Hassan Tanveer; Razvan C. Voicu · 2026 · AgriEngineering
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Artificial intelligence (AI) shows great promise for transforming the agriculture sector and can enable the development of many modern farming practices over conventional methods. Nowadays, AI agents and agentic AI have attained popularity due to their autonomous structure and working mechanism. This research work proposes an agentic AI framework that integrates multiple agents developed for farming land to promote climate-smart agriculture and support United Nations (UN) sustainable development goals (SDGs). The developed structure has four agents: Agent A for monitoring soil properties, Agen
Abstract by Muhammad Murad; Muhammad Ahmed; Nizam ul din; Muhammad Farrukh Shahid; Shahbaz Siddiqui; Daniel Byers; Muhammad Hassan Tanveer; Razvan C. Voicu, AgriEngineering (2026) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.3390/agriengineering8010008