Cultivating Innovation: An In-Depth Exploration of IoT and AI in Smart Agriculture

Abstract

The integration of smart agriculture technologies, especially through the Internet of Things (IoT), machine learning (ML), and artificial intelligence (AI), has significantly transformed modern agriculture. Smart agriculture has enabled precision farming by optimizing irrigation, monitoring soil health, predicting yields, and efficiently managing resources. This article discusses recent advances in smart agriculture technologies, especially in rice production and drought forecasting. A systematic analysis of 08 research papers high lights the role of communication systems, predictive analytics, and deep learning in optimizing agricultural productivity. Results indicate that there are significant gaps in the assessment of socio-economic impacts, real-world field validation, and integration of multifunctional smart agriculture technologies. Furthermore, challenges such as high implementation costs, lack of farmer training, and limited access to the technology hinder widespread adoption. The paper concludes with recommendations for future research to improve the sustainability, efficiency,
and adoption of smart agriculture worldwide.