Agricultural Internet of Things and Decision Support for Precision Smart Farming. Editors: Annamaria Castrignano, Gabriele Buttafuoco, Raj Khosla, Abdul Mouazen, Dimitrios Moshou, Olivier Naud


Agricultural Internet of Things and Decision Support for Smart Farming reveals how a set of key enabling technologies (KET) related to agronomic management, remote and proximal sensing, data mining, decision-making and automation can be efficiently integrated in one system. Chapters cover how KETs enable real-time monitoring of soil conditions, determine real-time, site-specific requirements of crop systems, help develop a decision support system (DSS) aimed at maximizing the efficient use of resources, and provide planning for agronomic inputs differentiated in time and space. This book is ideal for researchers, academics, post-graduate students and practitioners who want to embrace new agricultural technologies.

Key Features

  • Presents the science behind smart technologies for agricultural management
  • Reveals the power of data science and how to extract meaningful insights from big data on what is most suitable based on individual time and space
  • Proves how advanced technologies used in agriculture practices can become site-specific, locally adaptive, operationally feasible and economically affordable

Table of Contents

1. Introduction
2. Monitoring
3. Data processing
4. Support to decision making
5. Smart action
6. Economic, environmental and societal impacts
7. Examples of smart precision farming worldwide

Chapter 4 – Support to decision-making

Olivier Naud, James Taylor, Lucio Colizzi, Rodolphe Giroudeau, Serge Guillaume, Eric Bourreau, Thomas Crestey, Bruno Tisseyre


Smart farming is about how emerging and evolving technologies support the farmer, and their professional network, in the management of production and of information related to production. Decision support is therefore a core concern. As decision support is actually about making the right decisions and undertaking the right action, it relates to precise functions. From these functions, three themes can be identified, which are developed in this chapter. The first theme concerns building information that can support decisions from spatial data. This includes defining the decision to be supported, including spatial scaling matters, identifying the knowledge management paradigm, the timeliness of decision and action and the criteria involved. The second theme is about optimization and planning. It includes concepts and methods that can be related to decisions taken during the nonproduction periods, such as strategical enterprise objectives and choices of tactics, as well as to decisions taken during the production cycle, which can be simple scheduling of operations or more complex choices aimed at adapting crop management to the specific characteristics of a given year. The third theme is about designing an information system for smart farming. This includes considering the production processes and making models of these and the general framework for design. It also includes elements related to implementation of proposed next-generation databases.