Advancing sustainable and green agriculture with AI and IoT: Trends, challenges, and future directions

The agricultural sector contributes significantly to the economic development of nations worldwide. Owing to the population explosion, agriculture must address the complex challenges to meet the growing food demand while safeguarding natural and environmental sustainability. With limited farming land, water scarcity, soil degradation, and climate variability, it is essential to develop innovative, smart methods for sustainable agriculture. This article presents an in-depth analysis of the role of the Internet of Things, sensor networks, and UAVs in sustainable farming. Additionally, the article covers the integration of machine learning, artificial intelligence, computer vision, and deep learning that has transformed traditional practices into sustainable agricultural practices at every stage. The literature paper explores different agricultural applications, including smart irrigation, crop phenotyping, smart greenhouse, crop monitoring, quality assessment, yield prediction, and disease detection, thus covering about eighty seven research articles. The present study provides interconnected and valuable knowledge about smart and sustainable agriculture by integrating varied technologies in multiple agriculture domains instead of specific domains or technologies. Compared to many existing surveys emphasizing smart solutions, the innovation of the present article lies in its focus on sustainability, long-term resilience, resource optimization, and environmental conservation. • Study reviews 87 articles on sustainable smart farming. • Focuses on long-term resilience and environmental conservation.