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Multiagent System | KB and Ontology | Control Strategies | Simulation Environment
· Multiagent System The
intelligence part of the ThinkHome system is implemented as a
multiagent system (MAS). MAS is a powerful logical methodology that
perfectly fullfill the requirements of complex scenarios from a
top-down approach, mainly in terms of distributed intelligence, for
providing encapsulation on a functional level and for natively
supporting communication among different system parts. In addition, the
use of the agent paradigm also brings along independent evolution,
exchange, and maintenance of the autonomous parts that are implemented
as agents. The use of well-defined interfaces helps to retain the
required autonomy and even permits a possible local distribution of
components. To the Multiagent System page...
· Knowledge Base and Ontology The
task of the knowledge base is to intelligently maintain all relevant
concepts that are considered to be influence factors in a smart home.
Thus, it stores details on users like their preferences and profiles,
current occupancy and activities (i.e., context), as well as schedules.
Likewise, also weather data and building conditions
are conceptualized mainly to enable dynamic optimizations.
Furthermore, the KB keeps information about the building: it integrates
data already collected during the architectural conception and
construction process of a building, in particular comprising data on the
building structure, building orientation, used materials, and related
properties of these items. It also stores information on all resources
(e.g., devices) that are available within the smart home, including
energy-related aspects. Viewed in a global context, the KB is the
foundation for the MAS and basically supports the system to infer the
most appropriate building control strategies, that is, those that are
most energy effcient and comfort oriented in the current situation.
Additionally, the KB functions as an abstraction layer of the underlying
Building Automation System (BAS). As it is not relevant for control
strategies to be aware of the concrete installations in the building,
but rather of the services they other, the KB provides a generic and
integrated view of the different devices, networks and related
functionalities to the higher system part. Taken together, this part of
the system represents the shared vocabulary used by the MAS for
execution of advanced control strategies. It is therefore fundamental in
grounding ThinkHome. To the Knowledge Base and Ontology page...
· Control Strategies The
control strategies supports the basis of the intelligent operation of a
ThinkHome building. They are responsible for the calculation of the
actions (switching commands, start/stop times and many other parameters)
that are executed by the underlying BAS. The control strategies are
implemented in a dedicated agent. Hence, they are embedded in the agent
framework (MAS) and can access all information that is available in
the system, either directly, by communication, or even by cooperation
with other agents. The control strategies are built over
artificial intelligence methods and algorithms in order to acquire
pervasive and context aware decision capabilities. In short, control
strategies face the resolution of specific "uses cases" and
applications taking advantage of the structure, resources and framework
established by the MAS and KB, and also submitted to the supervision of
the competent MAS agents. To the Control Strategies page...
· Simulation Environment Due
to the difficulties to evaluate experimental approaches in the built
environment, simulation is a suitable means for designing energy
efficient buildings and also for checking control strategies, the
application of artificial intelligence in BAS solutions and the
performance optimization of holistic concepts (like ThinkHome) as a
whole. In addition, simulation is not only a tool useful in
design or research phases, but a method available for advanced
holistic systems to make predictions and obtain foundations for the next
decision making. To the Simulation Environment page...
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