Edge-enabled smart agriculture framework: Integrating IoT, lightweight deep learning, and agentic AI for context-aware farming

Smart farming in connectivity-limited, energy-sensitive environments demands on-device perception and decision-making to reduce latency and cloud dependence. This article proposes an edge-enabled smart agriculture framework that integrates lightweight deep learning, rule-based agentic AI, and Intern...

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Hlavní autoři:	Muhammad Usman Tariq, Sheikh Muhammad Saqib, Tehseen Mazhar, Muhammad Amir Khan, Tariq Shahzad, Habib Hamam
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2025-12-01
Edice:	Results in Engineering
Témata:	Agentic AI Edge computing Internet of things (IoT) Low-power deep learning Precision farming Smart agriculture
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S2590123025033973
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