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Abstract

In this talk, I will look at the concept of edge mining --- data mining that takes place at the edge of a wireless sensor network. Initially, we want our sensor networks to be as flexible as possible but as the area matures, automating information extracting into continuous analytics and pushing such analytics to the edge or leaf nodes of a network can reduce the infrastructural cost of the sensor network and thus enable many applications that would otherwise be infeasible. The talk will be rooted in my experience with deploying wireless sensor nets and deriving meaningful information from the resultant data streams.


Biography

James Brusey received his BApSc with distinction and PhD from RMIT University in 1996 and 2003, respectively. His PhD won the Australian Computer Science Association award for Best Thesis in 2004. He has over 15 years experience in the IT industry, part of which was as an independent consultant. More recently, he has worked as a Senior Research Associate at Cambridge University’s Institute for Manufacturing with funding from the Auto-ID Center. Since 2007, James has worked as a Senior Lecturer at Coventry University in wireless sensor networks and a Senior Research Fellow of the Cogent Computing Applied Research Centre. During this period, he has helped to establish Cogent as a world class research centre with a broad portfolio of successful, industry-sponsored projects related to wireless sensor projects. In 2012, he was awarded a readership in Pervasive Computing.

His current research interests include exploring issues with the practical deployment of wireless sensor networks, thermal comfort in buildings and car cabins.