Agricultural Internet of Things and Decision Support for Smart Farming - Chapter 1: Introduction to agricultural IoT

Elsevier, Agricultural Internet of Things and Decision Support for Precision Smart Farming, 2020, Pages 1-33
Lucio Colizzi, Danilo Caivano, Carmelo Ardito, Giuseppe Desolda, Annamaria Castrignanò, Maristella Matera, Raj Khosla, Dimitrios Moshou, Kun-Mean Hou, François Pinet, Jean-Pierre Chanet, Gao Hui, and Hongling Shi

Significant challenges will have to be overcome to achieve the level of agricultural productivity necessary to meet the predicted world demand for food, feed, fibre and fuel in 2050. Although agriculture has met significant challenges in the past, targeted increases in productivity will have to be made by 2050, in the face of stringent constraints including limited resources, less skilled labour, limited amount of arable land and changing climate, among others. Currently, agriculture production accounts for over 70% of freshwater consumption and unsustainable levels of chemical consumption for crop production. In the hyperconnected world, where people, computers and physical objects cooperate to solve complex tasks, a big amount of data and information rises rapidly and a critical aspect is to manage that knowledge to make the right decision at the right time and the right place. Also, farming has to become SMART adopting a new vision of the primary production sector where the development processes are based on the integration of information and communications technologies and Internet of Things technologies in a secure fashion to manage the rural assets and optimization of agronomic inputs such as water, fertilizer, agrochemical or soil tillage and to enhance input use efficiency, output or production and profitability in a sustainable manner. In this vision, the land becomes a substrate where different kinds of sensors could acquire heterogeneous data. Those sensors are connected in a sort of rural network in turn linked to the Internet network. The real-time streaming data are stored in complex database containing all the necessary knowledge about the land characteristics. Intelligent programmes connected with the knowledge base run to make real-time decisions, sending acting messages to the domotic back-end system or suggestions to the farmer.