Abstract
Smart agriculture is transforming traditional farming by integrating advanced
sensor-based systems, intelligent control technologies, and sustainable energy solutions
to meet the growing global demand for food while reducing environmental impact. This
review presents a comprehensive analysis of recent innovations in smart agriculture, focusing on the deployment of IoT-based sensors, wireless communication protocols, energy
harvesting methods, and automated irrigation and fertilization systems. Furthermore, the
paper explores the role of artificial intelligence (AI), machine learning (ML), computer
vision, and big data analytics in monitoring and managing key agricultural parameters
such as crop health, pest and disease detection, soil conditions, and water usage. Special attention is given to decision-support systems, precision agriculture techniques, and
the application of remote and proximal sensing technologies like hyper-spectral imaging,
thermal imaging, and NDVI-based indices. By evaluating the benefits, limitations, and
emerging trends of these technologies, this review aims to provide insights into how smart
agriculture can enhance productivity, resource efficiency, and sustainability in modern
farming systems. The findings serve as a valuable reference for researchers, practitioners,
and policymakers working towards sustainable agricultural innovation.
