Computational Intelligence - August 2014 - 85

Book
Review

Haibo He
University of Rhode Island,
Kingston, RI, USA

Intelligence for Embedded Systems:
A Methodological Approach, by
Cesare Alippi, (Springer, 2014 edition, March 2014, 307 pp.) ISBN:
978-3-319-05277-9.
Overview of the Book

t

he book Intelligence for Embedded
Systems: A Methodological Approach
by Cesare Alippi and published
by Springer addresses an existing gap in
the computational intelligence and
computer science literature.
Although we experience an increasingly pervasive presence of embedded
applications in our everyday life, such
that by 2020 it is predicted that each
person will possess between 5 and 10
embedded systems1, the presence of intelligence in current versions of embedded devices is generally very basic,
mostly confined to passive adaptation.
Embedded systems are characterized by
finite resources (e.g., cost, computational
power, memory and energy availability)
and operate in environments highly affected by uncertainty. Moreover, not uncommonly, faults and aging in the
hardware can intervene in the process
rendering the embedded algorithm ineffective for its designated purpose. Com-

1
Any system designed for an ad-hoc application is an
embedded system, e.g., the electronic control module
of our car, our mobile phone, the controllers in the
washing machine, etc.

Digital Object Identifier 10.1109/MCI.2014.2326104
Date of publication: 14 July 2014

1556-603x/14©2014ieee

putational intelligence can play a key
role here and its presence in embedded
applications is ever increasing, as evident
from inspecting recent published papers
that either directly or indirectly use embedded systems and applications. This
important book is unique since it provides a comprehensive methodological
framework that allows us to understand
those basic principles that permit computational intelligence techniques (mainly based on machine learning) to be
ported to embedded applications.
This book is a response to the important question of adopting a new computational paradigm as the methodological
basis for designing embedded systems with
sensor capabilities (e.g.,
pervasive computation,
Internet of Things and
cyber-physical systems).
The requirements of
this paradigm are to
control complexity, to
limit cost and energy
consumption, and to
provide adaptation and
cognition abilities thus
allowing the embedded
system to interact proactively with the real
world. With the latest
research methods and techniques presented, this book will pave the direction for a
new generation of intelligent systems capable of exploiting advances in digital architectures and in sensing technologies.
This is one of the most unique contributions and innovations of this book!

The Book's Content: Innovations in
Embedded Systems

This book comprises 10 chapters,
coherently organized in a systematic
manner to present the core aspects and
advancements of intelligent embedded
systems. Specifically, the structure of the
book is organized as follows.
The chapter 'From Metrology to
Digital Data' introduces the basic concepts behind measuring techniques and
measurements, e.g., accuracy, resolution
and precision, and sheds light on the elements composing the measurement
chain (the transducer, the conditioning
stage, the analog to digital converter, the
estimation module).
Since measurements are
often affected by uncertainty, the mechanisms
yielding uncertainty
that corrupt the measured data are investigated. This analysis sets
the basis for the subsequent propagation of
uncertainty within any
computational chain as
well as introduces constraints on accuracy for
the resultant embedded
application.
The chapter 'Uncertainty, Information and Learning
Mechanisms' introduces the most prevalent forms of uncertainty encountered
with digital embedded systems and
formalizes the processes by which uncertainty propagates within the computational flow. We have uncertainty in

august 2014 | ieee Computational intelligenCe magazine

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Table of Contents for the Digital Edition of Computational Intelligence - August 2014

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