Page 14 - Artificial Intelligence for the Internet of Everything

CHAPTER 1

Introduction

†
‡
†
W.F. Lawless*, Ranjeev Mittu , Donald A. Sofge , Ira S. Moskowitz ,
Stephen Russell §
*
Departments of Math & Psychology, Paine College, Augusta, GA, United States
†
Information Management & Decision Architectures Branch (CODE 5580), Information Technology
Division, U.S. Naval Research Laboratory, Washington, DC, United States
‡
Distributed Autonomous Systems Group, Code 5514, Navy Center for Applied Research in Artificial
Intelligence, U.S. Naval Research Laboratory, Washington, DC, United States
§
Battlefield Information Processing Branch, Computational Information Sciences Directorate, Army Research
Laboratory, Adelphi, MD, United States
1.1 INTRODUCTION: IOE: IOT, IOBT,
AND IOIT—BACKGROUND AND OVERVIEW
The Internet of Everything (IoE) generalizes machine-to-machine (M2M)
communications for the Internet of Things (IoT) to form an even more
complex system that also encompasses people, robots, and machines. From
Chambers (2014), IoE connects:

people, data, process and things. It is revolutionizing the way we do business, trans-
forming communication, job creation, education and healthcare across the globe.
… by 2020, more than 5 billion people will be connected, not to mention 50 billion
things. … [With IoE] [p]eople get better access to education, healthcare and other
opportunities to improve their lives and have better experiences. Governments can
improve how they serve their citizens and businesses can use the information they
get from all these new connections to make better decisions, be more productive
and innovate faster.
From a recent view of IoE, IoT is “all about connecting objects to the net-
work and enabling them to collect and share data” (Munro, 2017). With the
approach of IoT in everyday life (Gasior & Yang, 2013), on battlefields—
Internet of Battlefield Things (IoBT), in the medical arena—Internet of
Medical Things (IoMT), distributed with sensory networks and cyber-
physical systems, and even with device-level intelligence—Internet of
Intelligent Things (IoIT) comes a number of issues identified by Moskowitz
(2017), which are the explosion of data (e.g., cross-compatible systems;
storage locations); security challenges (e.g., adversarial resilience, data exfil-
tration, covert channels; enterprise protection; privacy); and self-* and auto-
nomic behaviors, and the risks to users, teams, enterprises, and institutions.

Artificial Intelligence for the Internet of Everything Copyright © 2019 Elsevier Inc.
https://doi.org/10.1016/B978-0-12-817636-8.00001-6 All rights reserved. 1