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The Sensor Web: unpredictable, noisy and loaded with errors

Smeaton, Alan F. (2010) The Sensor Web: unpredictable, noisy and loaded with errors. In: WI/IAT 2010 - IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology, 1-3 September 2010, Toronto, Canada.

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Abstract

Classical information retrieval is based around a user having an information need, formulated as a query, and a system which matches the query against 'documents', retrieving those most likely to be relevant. In some applications there are challenges because the 'documents' are not discrete objects but highly inter-connected, and IR research has for decades developed models of the processes, devised novel ranking algorithms, and developed very elaborate benchmarking techniques for performance. But what if the information we need or seek is not neatly divided into documents, either discrete or inter-connected, but needs to be taken from a constant stream of data values, namely data from sensors. These sensors cover the physical sensors around us (environment, place, physical activities like traffic, weather, people movement, crowd gatherings like concerts and sports events) as well as the online sensors we have access to (blogs, tweets, etc.). Often termed the *sensor web*, this information source is characterised as being noisy, errorsome, unpredictable and dynamic, exactly like the real and the virtual worlds in which we live, work and play. In this presentation I introduce several diverse sensor web applications to show the breadth and pervasive nature of the sensor web and I then show some of the techniques which we use to manage the information which forms part of the sensor web.

Item Type:Conference or Workshop Item (Invited Talk)
Event Type:Conference
Refereed:No
Uncontrolled Keywords:sensor networks; innovation; data growth;
Subjects:Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Official URL:http://www.yorku.ca/wiiat10/
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:15676
Deposited On:02 Sep 2010 16:02 by Alan F. Smeaton. Last Modified 02 Sep 2010 16:02

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