Internet-of-Things data aggregation using compressed sensing with side information

Evangelos Zimos, João F. C. Mota, Miguel Raul Dias Rodrigues, Nikos Deligiannis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

The Internet-of-Things (IoT) is the key enabling technology for transforming current urban environments into so-called Smart Cities. One of the goals behind making cities smarter is to provide a healthy environment that improves the citizens' quality of life and wellbeing. In this work, we introduce a novel data aggregation mechanism tailored to the application of large-scale air pollution monitoring with IoT devices. Our design exploits the intra- and inter-source correlations among air-pollution data using the framework of compressed sensing with side information. The proposed method delivers significant improvements in the data reconstruction quality with respect to the state of the art, even in the presence of noise when measuring and transmitting the data.

Original languageEnglish
Title of host publication2016 23rd International Conference on Telecommunications, ICT 2016
PublisherIEEE
ISBN (Electronic)9781509019908
DOIs
Publication statusPublished - Jun 2016
Event23rd International Conference on Telecommunications 2016 - Thessaloniki, Greece
Duration: 16 May 201618 May 2016

Conference

Conference23rd International Conference on Telecommunications 2016
Abbreviated titleICT 2016
CountryGreece
CityThessaloniki
Period16/05/1618/05/16

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Zimos, E., Mota, J. F. C., Rodrigues, M. R. D., & Deligiannis, N. (2016). Internet-of-Things data aggregation using compressed sensing with side information. In 2016 23rd International Conference on Telecommunications, ICT 2016 [7500418] IEEE. https://doi.org/10.1109/ICT.2016.7500418