Precision and digital agriculture: Broad applications of sensors, remote sensing and artificial intelligence in crop management: A review

Abstract

Digital agriculture and precision farming are innovative methods to farm that employ the newest technologies to get the most out of resources and boost crop yields. This review gives a full picture of how sensors, remote sensing platforms and artificial intelligence (AI) are used in precision crop management. We start with a brief history of precision farming and the work of the first individuals who performed it. The next portion of the review paper is about several types of sensors, such soil, plant and environmental sensors and how they provide correct information about the area. Next, its about how drones, satellites and planes can see things from far away. Review article will focus on how spectral images and LiDAR data are utilised to keep an eye on crops. Next, its talk about AI and machine learning methods, such neural networks, support vector machines, clustering and others, that are used to look at agricultural data to find diseases, predict yields and run machinery on their own. Finally, review talk about how these technologies may be employed in different crops and production systems, such irrigation, managing nutrients, controlling pests and weeds, estimating yields and making the harvest as good as it can be. The review article also talks about future developments, such as IoT connectivity, robots and cloud analytics, as well as problems, such as making data simpler to access and combine. The review shows that combining sensors, remote sensing and AI is starting a new era in crop management based on data that is good for the environment.