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

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

doi:10.1109/ICT.2016.7500418

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 proceeding › Conference contribution

16 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 language	English
Title of host publication	2016 23rd International Conference on Telecommunications, ICT 2016
Publisher	IEEE
ISBN (Electronic)	9781509019908
DOIs	https://doi.org/10.1109/ICT.2016.7500418
Publication status	Published - Jun 2016
Event	23rd International Conference on Telecommunications 2016 - Thessaloniki, Greece Duration: 16 May 2016 → 18 May 2016

Conference

Conference	23rd International Conference on Telecommunications 2016
Abbreviated title	ICT 2016
Country/Territory	Greece
City	Thessaloniki
Period	16/05/16 → 18/05/16

ASJC Scopus subject areas

Computer Networks and Communications

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ICT.2016.7500418

Cite this

@inproceedings{49aa047a48f743f0bb295122750959b3,

title = "Internet-of-Things data aggregation using compressed sensing with side information",

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.",

author = "Evangelos Zimos and Mota, {Jo{\~a}o F. C.} and Rodrigues, {Miguel Raul Dias} and Nikos Deligiannis",

year = "2016",

month = jun,

doi = "10.1109/ICT.2016.7500418",

language = "English",

booktitle = "2016 23rd International Conference on Telecommunications, ICT 2016",

publisher = "IEEE",

address = "United States",

note = "23rd International Conference on Telecommunications 2016, ICT 2016 ; Conference date: 16-05-2016 Through 18-05-2016",

}

TY - GEN

T1 - Internet-of-Things data aggregation using compressed sensing with side information

AU - Zimos, Evangelos

AU - Mota, João F. C.

AU - Rodrigues, Miguel Raul Dias

AU - Deligiannis, Nikos

PY - 2016/6

Y1 - 2016/6

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84979223443&partnerID=8YFLogxK

U2 - 10.1109/ICT.2016.7500418

DO - 10.1109/ICT.2016.7500418

M3 - Conference contribution

AN - SCOPUS:84979223443

BT - 2016 23rd International Conference on Telecommunications, ICT 2016

PB - IEEE

T2 - 23rd International Conference on Telecommunications 2016

Y2 - 16 May 2016 through 18 May 2016

ER -

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

Abstract

Conference

ASJC Scopus subject areas

UN SDGs

Access to Document

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