Information and Communication Technologies for Agriculture-Theme II: Data

This book is the second in a series of four on digitizing agriculture and information and communication technologies. It focuses on data technologies in relation to agriculture, including data management, data fusion, and their uses in machine learning and artificial intelligent technologies. It also examines the added value of data management within the agricultural products value chain and provides an exceptional reference for researchers and professionals working in or adjacent to agricultural production.

Format: Hardback
Length: 288 pages
Publication date: 18 March 2022
Publisher: Springer Nature Switzerland AG

This comprehensive volume, the second installment of a four-part series, delves into the dynamic realm of digitizing agriculture and information and communication technologies (ICT). Spanning four volumes, this series explores rapidly evolving processes such as sensors, data, decision-making, and actions, all integral to the realm of smart farming technology and knowledge-based agriculture.

The content of this volume encompasses a wide range of topics, from data mining and visualization to big data analytics and decision-making, while also addressing the sustainability implications arising from the digital transformation of farming. The four volumes collectively represent the outcomes of the 12th EFITA Congress, featuring chapters derived from select presentations at the event.

In the first part of this book, the focus shifts to data technologies in agriculture, presenting three key aspects of data management: data collection, data fusion, and their applications in machine learning and artificial intelligence technologies. Part 2 delves into the integration of these technologies into agricultural production processes, showcasing specific applications across various domains. Part 3 explores the value added by effective data management within the agricultural products value chain.

This book serves as an invaluable resource for researchers, practitioners, and professionals engaged in or adjacent to agricultural production. It caters to a diverse audience, including engineers specializing in machine learning and AI, operations management, decision analysis, information analysis, and many others. The volume encompasses specific advancements in big data management from heterogeneous sources, data mining within large data sets, data fusion and visualization, IoT-based management systems, data knowledge management for transforming data into valuable information, and more.

By presenting a holistic and interdisciplinary perspective, this volume contributes to the ongoing efforts to modernize agriculture and enhance its productivity, sustainability, and resilience in the face of evolving technological landscapes.

Weight: 623g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030841478
Edition number: 1st ed. 2022