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Information and Communication Technologies for Agriculture-Theme II: Data (Hardcover, 1st ed. 2022)
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Information and Communication Technologies for Agriculture-Theme II: Data (Hardcover, 1st ed. 2022)
Series: Springer Optimization and Its Applications, 183
Expected to ship within 12 - 17 working days
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This volume is the second (II) of four under the main themes of
Digitizing Agriculture and Information and Communication
Technologies (ICT). The four volumes cover rapidly developing
processes including Sensors (I), Data (II), Decision (III), and
Actions (IV). Volumes are related to 'digital transformation"
within agricultural production and provision systems, and in the
context of Smart Farming Technology and Knowledge-based
Agriculture. Content spans broadly from data mining and
visualization to big data analytics and decision making, alongside
with the sustainability aspects stemming from the digital
transformation of farming. The four volumes comprise the outcome of
the 12th EFITA Congress, also incorporating chapters that
originated from select presentations of the Congress. The first
part of this book (II) focuses on data technologies in relation to
agriculture and presents three key points in data management,
namely, data collection, data fusion, and their uses in machine
learning and artificial intelligent technologies. Part 2 is devoted
to the integration of these technologies in agricultural production
processes by presenting specific applications in the domain. Part 3
examines the added value of data management within agricultural
products value chain. The book provides an exceptional reference
for those researching and working in or adjacent to agricultural
production, including engineers in machine learning and AI,
operations management, decision analysis, information analysis, to
name just a few. Specific advances covered in the volume: Big data
management from heterogenous sources Data mining within large data
sets Data fusion and visualization IoT based management systems
Data Knowledge Management for converting data into valuable
information Metadata and data standards for expanding knowledge
through different data platforms AI - based image processing for
agricultural systems Data - based agricultural business Machine
learning application in agricultural products value chain
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