Pervasive Data Science on the Edge

Lagerspetz, E. and Hamberg, J. and Li, X. and Flores, H. and Nurmi, P. and Davies, N. and Helal, S. (2019) Pervasive Data Science on the Edge. IEEE Pervasive Computing, 18 (3). pp. 40-48. ISSN 1536-1268

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Abstract

Proliferation of sensors into everyday environments is resulting in a connected world that generates large volumes of complex data. This data is opening new scientific and commercial investigations in fields such as pollution monitoring and patient health monitoring. Parallel to this development, deep learning has matured into a powerful analytics technique to support these investigations. However, computing and resource requirements of deep learning remain a challenge, often forcing analysis to be carried at remote third-party data centers. In this paper, we describe an alternative computing as a service model where available smart devices opportunistically form micro-data centers that can support deep learning-based investigations of data streams generated by sensors. Our model enables smart homes, smart buildings, smart offices, and other types of smart spaces to become providers of powerful computation as a service, enabling edge analytics, and other applications that require pervasive (in-space) decisioning.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Pervasive Computing
Additional Information:
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Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1706
Subjects:
ID Code:
140001
Deposited By:
Deposited On:
27 Jan 2020 14:45
Refereed?:
Yes
Published?:
Published
Last Modified:
25 Sep 2020 04:44