Overview:
Wireless sensor networks (WSN) consist of small devices (e.g. sensor
nodes) with low cost (typically $1 - $20), low power (resulting in a long
battery and shelf life), low data rate (up to approx. 250 KB/s or 2% the speed
of Wi-Fi) and low processing capabilities (based on embedded 8/16-bit systems).
WSNs are typically ad-hoc (there is no fixed
infrastructure) and isolated (there is no reference to the Internet or any
other network).
This technology is increasingly used in diverse areas like patient
monitoring (i.e. wireless biosignal monitoring), residential / commercial
control (i.e. ambient temperature/humidity measurement), industrial control
(i.e. remote machine monitoring), environmental monitoring (i.e. pH of a
waterway) and smart grid systems (i.e. advanced meters).
The WSN market is gaining momentum with 100s of millions of sensor nodes
to be deployed world-wide over the next 10 years. One of the most important
drivers for this development relates to increasing energy costs / environmental
concerns and subsequent massive worldwide investment in smart grid technology
in its broadest sense. Sensor networks have a key role to play in this
initiative, from improved building and environmental monitoring to smart
metering. Data centres (DC) consume 3% of global energy and this is predicted
to increase significantly with evolution of cloud computing. A gain in energy
efficiency in DC energy consumption will translate into significant savings.
Other drivers include the medical domain where there is growing need for better
ambulatory patient monitoring at home or in step-down facilities and more
general company savings through better asset management.
Security of these networks, however, is critical. End users do not want
their health data being exposed, while manufacturers must comply with
legislation regarding privacy such as HIPAA (Health Insurance Portability and
Accountability Act). Similarly, in the energy domain broad security concerns
within the evolving smart grid represent a key challenge to its success and
sensor security is one aspect of this. OSNA will look into these issues and
provide an authentication solution for such networks.
Researchers:
Jonathan Hanley, Fanie Meiring, Hugh Melvin, Michael Schukat
Received Funding:
Enterprise Ireland Commercialisation+ Funding
(Estimated) Duration:
09/11 – 08/13
Overview:
This research deals with the problem of multi robot exploration and
object recognition. We propose a system to accurately map an environment and to
model and classify objects within the environment. Our research is intended to
be of use in the development of service robots to carry out tasks in domestic
or industrial environments.
To model an environment
accurately, we aim to utilise the ability of robots to accurately recognize and
localise each other. A consistent map is thus achieved by maintaining visual
contact between robots, with different robots assigned roles of explorer and
observer. While maintaining contact between some team members, the team as a
whole spreads out, exploring the environment as efficiently as possible.
To accurately model an objects
appearance requires that sensory information be combined from different
orientations. Our proposed coordination technique thus instructs team members
to navigate around objects and gather as much information about them as
possible. This information can be used to calculate the shape of the object and
to model its appearance. For service robots to manipulate or move objects, the
objects 3D shape must be known. To this end, our proposed coordination approach
will facilitate the implementation of shape from silhouette. Objects shapes are
determined by obtaining the silhouette or outline contour from different
orientations, and fusing these to form a bounding hull. To classify a known
object, our coordination approach will gather as much information about the
object as is necessary to determine the objects identity with sufficient
certainty. To reduce uncertainty, the views of an object that best discriminate
between the objects possible matching identities are observed.
Researchers:
Declan O’Beirne, Michael Schukat
Received Funding:
IRCSET Ph.D. Scholarship
(Estimated) Duration:
Completion in 2012
Overview:
Approximately one-third of all independently living elderly people are
not compliant with their drug therapy. This lack of medication management results
either in undermedication or overmedication, causing unnecessary and often
serious health risks.
So far care schemes and retrospective assessment procedures have been the
only applicable solution to tackle this problem, but with the increasing aging
of the population and cost constraints in the health sector other more (cost-)
effective methods must be introduced.
This
project deals with a computer-assisted screening and management service that
allows health care providers and drug-treated individuals
to tackle this issue.
Researchers:
Michael Schukat, Tim Meagh, et al.
Received Funding:
(Estimated) Duration:
Ongoing
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