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Ambient Intelligence
lot of energy. Therefore, research focuses on
energy efficient routing and communication pro-
tocols. A broad range of routing algorithms for
the commonly used communication stack IEEE
802.15.4, called ZigBee (Zhao & Guibas, 2004)
exist: AMRIS (Wu & Tay, 1999), SPIN (Kulik,
Heinzelman, & Balakrishnan, 2002), Directed
Diffusion (Intanagonwiwat, Govindan, & Estrin,
2000), Energy Aware Routing, Geographic Hash
Tables (Ratnasamy, et al., 2002) and Greedy Pe-
rimeter Stateless Routing (Karp & Kung, 2000).
Ambient Intelligence
(AmI) originated from the
field of smart and pervasive environments (Pent-
land, 1998), (Aarts & Marzano, 2003) and evolved
to an emerging paradigm for knowledge discovery.
Within the AmI community various definitions
exist, but there is a consensus that AmI refers
to systems which “… monitor and interact with
an environment populated by humans” (Bhatt &
Guesgen, 2009). AmI includes multi-disciplinary
fields within computer science, such as ubiquitous
computing, human-centric computer interac-
tion, mobile computing and cognitive sciences.
Such systems typically feature the following
characteristics:
(iii)
embedded,
(iii)
context aware,
(iii)
personalized,
(iv)
adaptive, and
(v)
anticipa-
tory. AmI applications can be separated into the
following three sub domains:
(iii)
assistance for
emergency treatment,
(iii)
assistance for autonomy
enhancement, and
(iii)
comfort features (Nehmer,
Becker, Karshmer, & Lamm, 2006). According
to (Nehmer, Becker, Karshmer, & Lamm, 2006),
emergency treatment, which aims at early predic-
tion and recovery from critical situations, can be
considered as the core functionality of every AmI
system. It covers detection, prediction, and preven-
tion of critical situations, such as heart attacks,
household accidents (fires, injuries, flooding),
strokes or sudden falls.
Smart Home
The term
smart home,
or
home automation
which
is synonymously used, originally referred to the
automation of office buildings, like automated
heating control, air conditioning or fire alarms
(Peine, 2009). Later theses concepts found their
way into private households to provide comfort
features, like automated light control, or safety
features, like burglar systems. The available data
from smart home sensor devices can also be used
for other purposes, like localizing the inhabitant
or extrapolating his physical condition from the
environmental situation. Such use cases can only
be realized, if a feasible amount of sensors and
some kind of intelligence unit that processes the
data are available.
The combination of data obtained from a smart
home with health data (for example, gained from
wearable sensors) can be used to make a mean-
ingful point, whether some critical situation is
actually happening. “Smart homes are a promising
and cost effective way to improve home care for
elderly and disabled persons in a non-obtrusive
way” (Chan, Campo, Esteve, & Fourniols, 2009).
Within this chapter the term smart home will be
used for referring to the sensory infrastructure
used for obtaining environmental information
from various devices (stove, television, light
switch sensors or room temperature sensors).
We do not distinguish in detail, if the perceived
data is transmitted by wired or wireless sensors.
Ambient Assisted Living
Currently, there exists no common definition for
Ambient Assisted Living
(AAL) within the scien-
tific community. AAL is usually used to outline
methods, concepts, devices, systems and services
that provide support for the daily life. In most
cases devices and services are based on context
and on the situation of the assisted person. AAL
mainly focuses on supporting elderly people or
people with special needs in their daily living
activities, but does also include younger and
healthy individuals who are interested in
lifestyle
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