wilamowski-b-m-irwin-j-d-industrial-communication-systems-2011

26-12 Industrial Communication Systems
in Europe and the United States, elderly people will soon constitute a major part of the population. One
main target of AAL is to allow them to live an independent life in their familiar surroundings, which
would otherwise not be possible without certain support. This support shall be delivered by a multitude
of home automation services that are designed for assisting the inhabitants to live longer and at higher
quality in their homes. Because of the target user group of AAL systems, several special requirements
emerge. Most important, systems have to become usable also for technically not versed people. Therefore,
an intuitive user interface to act as a mediator between system and user is of prime importance. Also,
the necessary interaction shall be kept to a minimum. This demands that AAL systems are capable of
self-learning. Through the use of a network of sensors and actuators, and with occasional user inputs,
the system shall be able to perceive the environment, predict (desired) user actions, and perform actions
to alleviate the burdens of daily tasks and provide additional measures of safety, security, and comfort.
For example, systems could detect users leaving the home and thereupon automatically turn off miscellaneous
electronic equipment, appliances, and lights, reduce temperature set points, and activate the
alarm system. Another possible application is to detect if a person has collapsed on the floor by means of
motion and pressure sensors as well as built-in logic and set off an emergency call for help.
The “smartness” in home automation needed for modern applications such as AAL benefits greatly
from the concepts presented by ambient intelligence (AmI) and context awareness. Context-aware
devices can sense and react based on the state of their environment. Information gained includes
location, physical properties (e.g., temperature), and information on ongoing processes and infrastructure,
available in the surrounding environment and the device itself. Senses are applied against
a rule-set that is based on the user’s profile and preferences and generates responses. Therefore, a
context-aware device such as a smartphone may “understand” that its bearer has arrived home and,
based upon its understanding of the user’s location and the environmental settings the user prefers at
the time, decide to illuminate the area and turn on the stereo through commands to the home’s infrastructure
(i.e., in this case the home automation network). The keystone of this automation approach
is proper pattern recognition of routine tasks, for example, learning and predicting user tasks. This
learning can be accomplished by exploitation of mechanisms originating in artificial intelligence, for
example, neural networks or fuzzy control.
Another benefit of home automation is increased energy efficiency and energy conservation. Energy
consumption throughout the world has been steadily increasing over the past half-century, and now
has become an urgent topic for mankind and thus politics. Efficiency of energy use is the primary purchase
reason behind new appliances—especially Energy Star certified appliances—and also behind new
miscellaneous electrical loads. Conservation of energy is a much broader topic that combines modern
building technologies (e.g., insulation, energy-saving lightbulbs) with improvement in the inhabitant’s
behavior toward more energy-efficient ways of going about daily tasks. In the latter case, support from
HAS can be expected. Through automatic metering (smart metering) of the energy consumption and
visualization of the data, users become aware of their consumption and can now actively change their
behavior toward acting more sustainably. The feedback is given in real-time, and may be more or less
abstract (e.g., numerically displaying kilowatt-hours and currency compared to feedback in the form of
dynamic color changes from green to red), therefore always adapting to the user’s needs.
HAS also offer perspectives to use energy more efficiently. On the one hand, this is possible through
context awareness (e.g., turn off the lights in currently not occupied rooms). On the other hand, automation
systems allow tasks to be executed at times when they are most energy efficient. An example
is to turn the heating on as late as possible yet reaching a predefined temperature at a defined point
of time. This becomes only possible with the system being aware of inside and outside temperatures,
weather, time of the year, and building inertia to name just a few. This information is accumulated and
exploited by the automation system to provide better control while guaranteeing optimum comfort for
the user. Other energy-aware approaches include “smart thermostats” that can automatically reduce the
temperature when energy is expensive to generate, as well as “smart appliances” that wait until energy
is inexpensive to start operation (e.g., a dishwasher starting its program when energy costs less).
© 2011 by Taylor and Francis Group, LLC