Carlos Manuel Rodrigues Machado Autonomic Ubiquitous Computing

The human ANS reflex arc was used as the inspiration of the capabilities required by the
low level components of an autonomic ubiquitous system. The reflex arc can execute an action
without the intervention of the human brain, resulting in a fast response time. The analogy also
specifies that the system low-level components need to be able to execute any basic function of the
system. This was achieved by providing the component with three main capabilities: event-driven
information, the transmission information in broadcast mode and configurable binding among
events and actions. These characteristics, linked to the ability to monitor the internal variables, of
devices allow them to be used in the upper system layers.
In order to test the concept proposed in this thesis, the Teleswitch device was built. This
development helped to clarify some technical aspects that need to be overcome to make its
implementation and possible deployment in a human environment. This device was also
implemented using hardware traditional communication technology, which simplifies the design,
resulting therefore in a low cost device. The usage of traditional technology means that it is not
necessary to adopt a state of the art communication interface in devices, showing that the
philosophy is the most important aspect in this ubiquitous system design.
In a ubiquitous system, the humans are a part of the system loop. In order to validate the
theory proposed in this thesis, a home environment was selected. A system was installed and
allowed the confirmation that the required capabilities presented earlier in this thesis were suitable
to the implementation of devices for this type of systems. The quality of the data that has been
acquired for a large period of time shows that the setup was appropriate. The captured data shows
the ability to infer the behaviour of the inhabitants, allowing the extraction of patterns of the
inhabitants during a year, as well as, during a day. The patterns presented show potential benefits
to the user as well to the optimization of the system functionality. In particular, it has been shown
that the energy economy in a home light system can be reduced 50%. The results reveal a relevant
aspect in today’s society concerning energy savings.
As sooner as the system installation and the capturing of events started, the focus of the
work of the thesis was the study of Artificial Intelligence. The AI is necessary to a system to be
adaptable to the patterns of the users, i.e., a context-awareness construction in order to create
useful applications that react to it. The Artificial Neural Networks (ANN) approach was selected,
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