Abstract

Food security is a crucial global need, threatened by population growth, climate change, and decreasing arable land. Data-driven agriculture is the most promising approach to solving these current and future problems by improving crop yields, reducing costs, and ensuring sustainability. As the number of smart sensors and machines on farms increases and a greater variety of data is used, farms will become increasingly data-driven, enabling the development of smart farming. This is possible, thanks to new technologies that enable massive data storage, such as cloud computing and Hadoop, in addition to processing and analysis through Big Data and machine learning. In this chapter, we explain some practical examples of their use. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.