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RESEARCH FOCUS


The AIC sensor research is focused on investigating the issue of integrating sensors into pervasive communication systems as front-end information gatherers, with the aim of generating true context aware networks that bridge the digital and molecular worlds. The research strategy is to address the issues of how to configure chemical sensor and biosensor networks that are capable of long-term autonomous operation and suitable for massive scale up in terms of numbers employed.  In order to effectively collect, communicate and utilise the large quantities of sensor data generated by these networks, other AIC researchers are investigating middleware for sensor networks, content extraction from audio-visual information, modelling collaborative reasoners and next-generation personalization technologies. In addition, privacy and trust models are being designed into the infrastructure to ensure the appropriate use of the data generated.


RESEARCH THEMES


The activities of the AIC are primarily based on four investigator awards made by Science Foundation Ireland in 2003.

The four research awards cover the following areas:

A further cohesion award was granted to enable collaboration between the academic partners and industry partners.


Foundations of Ubiquitous Sensing

Principal Investigator: Professor Dermot Diamond

Sensor Networks looks at the issue of integrating sensors into pervasive communication systems as front-end information gatherers, with the aim of generating true 'context aware' networks that bridge the digital and molecular worlds. The research strategy is to address the issues of how to configure chemical sensors and biosensors that are capable of long term autonomous operation and suitable for massive scale up in terms of numbers employed.

Content Extraction from Audio Visual Information

Principal Investigator: Professor Alan F. Smeaton

Automatic and adaptive extraction of content from information in video and audio will allow far greater utilisation of that information than at present. We focus on automatic and semi-automatic approaches to video object segmentation, tracking and matching based on objects recognised in the video. Work on audio analysis develops computer-audition techniques for detecting and localising anomalous sounds that would be environment-dependent, for the purpose of indexing and retrieval. To bring these two strands together, adaptive media retrieval targets the research and development of techniques to support information retrieval from individual media including video, audio, text, etc., but also information retrieval across different media. In particular the work sought to address how to do this by utilising the user's context as an important parameter in retrieval.

Modelling Collaborative Reasoners

Principal Investigators: G.M.P. O’Hare and Professor Mark Keane

Modelling Collaborative Reasoners will examine distributed techniques for the management of highly dynamic, large-scale distributed systems made up of many different computational entities.

Specifically this work seeks to..

  • work on problems of collaborative reasoning systems that are fully scalable and not restricted by arbitrary limits associated with pre-existing hardware, users scale and complexity;
  • To develop a collaborative reasoning infrastructure that is fully supportive of ambient computing needs;
  • To develop a collaborative learning infrastructure that is able to learn how to communicate, co-operate and indeed compete;
  • To develop collaborative reasoning models that are able to collaboratively and proactively retrieve, analyse. manipulate , filter and monitor data sources.

Situated Personalization

Principal Investigators: Professor Barry Smyth

Situated Personalization focuses on the development of next-generation personalization technologies that are better able to recognize and respond to the information preferences and needs of individual users and groups of users.

In particular a unique feature of the proposed research hinges on the idea that personalization techniques can add value beyond the virtual world of the Internet, especially as our physical world becomes more and more instrumented with sensor and display technologies. This integration between sensor-based input, adaptive personalization and advanced display technologies provides a unique opportunity to explore the possibilities of such an augmented physical world.

In short, these developments provide an opportunity to investigate the concept of situated personalization whereby elements of our physical world actively sense and intelligently respond to our implicit and explicit interactions, our learned needs and our routine behaviours.


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