Type: Book

Smart farms Improving data-driven decision making in agriculture


Professor Claus Sørensen is a Senior Scientist in the Department of Electrical and Computer Engineering at Aarhus University, Denmark. He is internationally renowned for his research on analysing data flows in farming operations to optimise resource use. He is winner of outstanding paper awards from the European Society of Agricultural Engineers (EurAgEng) and the journal Biosystems Engineering. He is past President of EurAgEng and current Workgroup Coordinator of the International Commission of Agricultural and Biosystems Engineering (CIGR). He has participated in a number of EU research projects such as Internet of Food and Farms 2020, FutureFarm and SmartAgriFood2 and has been a member of the scientific committees for conferences organised by the European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) as well as other biosystems engineering conferences.



Publication date:

26 March 2024

Length of book:

300 pages

ISBN-13: 9781801463829

Hardback - £140.00
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The agricultural sector remains under increasing pressure to reduce its environmental impact and consequent contribution to climate change, whilst also producing enough food to feed a rapidly growing population. With the variety and volume of data, coupled with the advanced methods for data processing, a new era of digital agriculture is emerging as a possible solution to this monumental challenge.

Smart farms: improving data-driven decision making in agriculture provides a comprehensive review of the recent advances in gathering and analysing data as a means of improving farm sustainability, productivity and profitability. The book discusses the evolution of farm information management systems, highlighting current trends and challenges, as well as methods of data acquisition and analysis, including the use of artificial intelligence.

Key features

  • Provides a detailed overview of the recent trends in farm information management systems, including their evolution and role in improving farmer decision making
  • Considers the range of data mining techniques used in decision support systems, such as artificial neural networks and support vector machines
  • Includes a selection of case studies which explore the use of decision support systems in optimising farm management and productivity

What others are saying...

“Although digital agriculture is gaining momentum with the advent of smart tools and intelligent farm equipment, the application of artificial intelligence to agriculture strongly relies on the quality and quantity of data acquired from the crops. In this new book, Professor Sørensen has focused on a key point for a successful digitization of the farm; the practical execution of data-driven solutions, and to do so, he has brought together an outstanding team of recognized agricultural scientists and engineers. This collection will be valuable to agricultural researchers, industry developers, farm practitioners, students, and many other professionals committed to push the agriculture of the 21st Century into a sustainable activity.” (Francisco Rovira-Más, Professor of Digital Agriculture, Universitat Politècnica de València, Spain)

Table of contents

Part 1 General

  • 1.Trends in farm management systems (FMIS): Liisa Pesonen, MTT Agri-Food Research, Finland
  • 2.Improving farm production planning information systems: Thiago Romanelli, University of Sao Paulo, Brazil
  • 3.Key issues in incorporating proximal and remote sensor data into farm decision making: Fatima Baptista, University of Evora, Portugal
  • 4.AgriSemantics: developments in improving data interoperability to support applications such as farm information management/decision support systems: Miel Hostens, Utrecht University, The Netherlands
  • 5.Using data mining techniques for decision support in agriculture: support vector machines: Caicong Wu, China Agricultural University, China

Part 2 Case studies

  • 6.Developing decision support systems for irrigation/water management on farms: Fedro Zazueta, University of Florida, USA
  • 7.Advances in crop disease forecasting models: Nathaniel Newlands, Summerland Research and Development Centre, Science and Technology Branch, Agriculture and Agri-Food Canada, Canada
  • 8.Smart Farming in extensive livestock production: the Australian experience: David Lamb, University of New England/Food Agility CRC, Australia