In the dynamic realm of agriculture, artificial intelligence (AI) and machine learning (ML) emerge as catalysts for unprecedented transformation and growth. The emergence of big data, Internet of Things (IoT) sensors, and advanced analytics has opened up new possibilities for farmers to collect and analyze data in real-time, make informed decisions, and increase efficiency. AI and ML are key enablers of data-driven farming, allowing farmers to use algorithms and predictive models to gain insights into crop health, soil quality, weather patterns, and more. Agriculture is an industry that is deeply rooted in tradition, but the landscape is rapidly changing with the emergence of new technologies.

Data-Driven Farming: Harnessing the Power of AI and Machine Learning in Agriculture is a comprehensive guide that explores how the latest advances in technology can help farmers make better decisions and maximize yields. It offers a detailed overview of the intersection of data, AI, and ML in agriculture and offers real-world examples and case studies that demonstrate how these tools can help farmers improve efficiency, reduce waste, and increase profitability. Exploring how AI and ML can be used to achieve sustainable and profitable farming practices, the book provides an introduction to the basics of data-driven farming, including an overview of the key concepts, tools, and technologies. It also discusses the challenges and opportunities facing farmers in today’s data-driven landscape. Covering such topics as crop monitoring, weather forecasting, pest management, and soil health management, the book focuses on analyzing data, predicting outcomes, and optimizing decision-making in a range of agricultural contexts.

Victor Galaz is Associate Professor in Political Science at the Stockholm Resilience Centre at Stockholm University, Sweden, and Program Director at the Beijer Institute of Ecological Economics at the Royal Swedish Academy of Sciences. His research explores the political and social dynamics of climate crises and systemic risks, and the influence of information technological change on a human-dominated planet. He is the author of Global Environmental Governance, Technology and Politics: The Anthropocene Gap (2015), co-author of Biosphere Code: A Manifesto for Algorithms in the Environment (2015), and editor of Global Challenges, Governance, and Complexity: Applications and Frontiers (2019).