A Review of the Internet of Things and Deep Learning in Agriculture: A Smart Agriculture Prespective

Azeem Ayaz Mirani, Shah Zaman, Rozina Chohan, Saima Siraj, Shamshad Lakho

Abstract

The artificial intelligence revolution in smart agriculture raises many challenges and opportunities for researchers. The adoption of modern technologies in agriculture has led to very high results compared to the last few decades. IoT technologies in agriculture have brought many new trends in monitoring the status of crops that can lead to monitoring the real-time environment and parameters that directly impact crop yield. The weather, soil, and plant monitoring can determine the exact crucial conditions for crops. Deep learning methods help intelligent disease detection and classification from the learned image dataset. The sub-field of artificial intelligence (deep learning) can structure algorithms in layers to develop artificial neural network learning and make intelligent decisions. Deep transfer learning attempts to solve the problem of the learned model that performs a task and to modify the experimental model to solve another task. This study aims to review agriculture technologies related to the literature, applications, and challenges. IoT and deep learning from the agriculture perspective are the primary focus of this study.

 

Keywords: deep learning, smart agriculture, Internet of Things.

 

https://doi.org/10.55463/issn.1674-2974.50.10.18


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