IEEE Consumer Electronics Magazine - July/August 2021 - 4

From the Editor's Desk
Internet-of-Agro-Things (IoAT) Makes
Smart Agriculture
Saraju P. Mohanty
University of North Texas
& I WELCOME ALL the readers to the fourth issue
of year 2021, the July 2021 issue, of the IEEE Consumer
Electronics Magazine (MCE).
I am pleased that the current issue is dedicated
to agriculture cyber-physical system (ACPS),
which makes smart agriculture. The issue
presents many articles covering various key
aspects of A-CPS or smart agriculture. In the July
2020 issue of MCE, we covered transportation
cyber-physical system (T-CPS). In the September
2020 issue, we presented many articles covering
various key aspects of healthcare CPS (H-CPS).
Other important CPS, such as energy CPS (ECPS)
making smart energy also deserves coverage.
MCE also has covered themes of smart cities
and smart villages like bigger concepts, which
are designed based on these individual smart
components.
STATE-OF-THE-ART OF SMART
AGRICULTURE
We have learnt from the past issues that
deployment of Internet-of-Things (IoT) in the
physical systems make cyber-physical-systems
(CPS), which then make a specific smart component.
A specific example, Internet-of-Medical-Things
(IoMT) makes healthcare CPS (HDigital
Object Identifier 10.1109/MCE.2021.3074775
Date ofcurrent version 10 June 2021.
CPS) leading to smart healthcare. In a similar
manner, we can define Internet-of-Agro-Things
(IoAT) makes agriculture CPS (A-CPS) leading
to smart agriculture. While IoT is a dynamic
network connecting " Things, " specific instances
like IoMT differ IoAT in terms of the
details such as types of sensors and network
connectivity. In the context of smart agriculture,
several questions including the following
are worth discussing: What is smart agriculture?
Why is it needed? What makes smart
agriculture possible?
Smart agriculture (also known as smart farming)
can be defined as an agriculture system that
uses information and communication technologies
(ICT) for maximizing crop growth with ever
reduced land area available for farming. The
predecessors of the smart agriculture digital
farming (DF), precision farming (PF), or precision
agriculture (PA), also aimed at the same
objective, i.e., to significantly increase crop production
and farming efficiency. In the A-CPS,
aggregation of data from sensors and their analytics
through artificial intelligence (AI) or
machine learning (ML) models to monitor various
parameters of agriculture, including the
environmental conditions, soil moisture, and
crop health, are key driver for smart agriculture.
The major features of the smart agriculture
include continuous monitoring, energy harvesting,
automatic irrigation, and disease prediction.
4
2162-2248 ß 2021 IEEE
Published by the IEEE Consumer Technology Society
IEEE Consumer Electronics Magazine
IEEE Consumer Electronics Magazine - July/August 2021

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