Intelligent Urban data monitoring for smart cities

Nikolaos Panagiotou; Nikolas Zygouras; Ioannis Katakis; Dimitrios Gunopulos; Nikos Zacheilas; Ioannis Boutsis; Vana Kalogeraki; Stephen Lynch; Brendan O’Brien

doi:10.1007/978-3-319-46131-1_23

Intelligent Urban data monitoring for smart cities

Nikolaos Panagiotou
, Nikolas Zygouras
, Ioannis Katakis
, Dimitrios Gunopulos
, Nikos Zacheilas
, Ioannis Boutsis
, Vana Kalogeraki
, Stephen Lynch
, Brendan O’Brien

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Urban data management is already an essential element of modern cities. The authorities can build on the variety of automatically generated information and develop intelligent services that improve citizens daily life, save environmental resources or aid in coping with emergencies. From a data mining perspective, urban data introduce a lot of challenges. Data volume, velocity and veracity are some obvious obstacles. However, there are even more issues of equal importance like data quality, resilience, privacy and security. In this paper we describe the development of a set of techniques and frameworks that aim at effective and efficient urban data management in real settings. To do this, we collaborated with the city of Dublin and worked on real problems and data. Our solutions were integrated in a system that was evaluated and is currently utilized by the city.

Original language	English
Title of host publication	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings
Editors	Björn Bringmann, Elisa Fromont, Nikolaj Tatti, Volker Tresp, Pauli Miettinen, Bettina Berendt, Gemma Garriga
Publisher	Springer Verlag
Pages	177-192
Number of pages	16
ISBN (Print)	9783319461304
DOIs	https://doi.org/10.1007/978-3-319-46131-1_23
Publication status	Published - 1 Jan 2016
Event	15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016 - Riva del Garda, Italy Duration: 19 Sept 2016 → 23 Sept 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9853 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016
Country/Territory	Italy
City	Riva del Garda
Period	19/09/16 → 23/09/16

UN SDGs

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

SDG 11 Sustainable Cities and Communities

Access to Document

10.1007/978-3-319-46131-1_23

Cite this

Panagiotou, N., Zygouras, N., Katakis, I., Gunopulos, D., Zacheilas, N., Boutsis, I., Kalogeraki, V., Lynch, S., & O’Brien, B. (2016). Intelligent Urban data monitoring for smart cities. In B. Bringmann, E. Fromont, N. Tatti, V. Tresp, P. Miettinen, B. Berendt, & G. Garriga (Eds.), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings (pp. 177-192). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9853 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46131-1_23

Panagiotou, Nikolaos ; Zygouras, Nikolas ; Katakis, Ioannis et al. / Intelligent Urban data monitoring for smart cities. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings. editor / Björn Bringmann ; Elisa Fromont ; Nikolaj Tatti ; Volker Tresp ; Pauli Miettinen ; Bettina Berendt ; Gemma Garriga. Springer Verlag, 2016. pp. 177-192 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Urban data management is already an essential element of modern cities. The authorities can build on the variety of automatically generated information and develop intelligent services that improve citizens daily life, save environmental resources or aid in coping with emergencies. From a data mining perspective, urban data introduce a lot of challenges. Data volume, velocity and veracity are some obvious obstacles. However, there are even more issues of equal importance like data quality, resilience, privacy and security. In this paper we describe the development of a set of techniques and frameworks that aim at effective and efficient urban data management in real settings. To do this, we collaborated with the city of Dublin and worked on real problems and data. Our solutions were integrated in a system that was evaluated and is currently utilized by the city.",

author = "Nikolaos Panagiotou and Nikolas Zygouras and Ioannis Katakis and Dimitrios Gunopulos and Nikos Zacheilas and Ioannis Boutsis and Vana Kalogeraki and Stephen Lynch and Brendan O{\textquoteright}Brien",

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booktitle = "Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings",

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Panagiotou, N, Zygouras, N, Katakis, I, Gunopulos, D, Zacheilas, N, Boutsis, I, Kalogeraki, V, Lynch, S & O’Brien, B 2016, Intelligent Urban data monitoring for smart cities. in B Bringmann, E Fromont, N Tatti, V Tresp, P Miettinen, B Berendt & G Garriga (eds), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9853 LNCS, Springer Verlag, pp. 177-192, 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016, Riva del Garda, Italy, 19/09/16. https://doi.org/10.1007/978-3-319-46131-1_23

Intelligent Urban data monitoring for smart cities. / Panagiotou, Nikolaos; Zygouras, Nikolas; Katakis, Ioannis et al.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings. ed. / Björn Bringmann; Elisa Fromont; Nikolaj Tatti; Volker Tresp; Pauli Miettinen; Bettina Berendt; Gemma Garriga. Springer Verlag, 2016. p. 177-192 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9853 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Intelligent Urban data monitoring for smart cities

AU - Panagiotou, Nikolaos

AU - Zygouras, Nikolas

AU - Katakis, Ioannis

AU - Gunopulos, Dimitrios

AU - Zacheilas, Nikos

AU - Boutsis, Ioannis

AU - Kalogeraki, Vana

AU - Lynch, Stephen

AU - O’Brien, Brendan

PY - 2016/1/1

Y1 - 2016/1/1

N2 - Urban data management is already an essential element of modern cities. The authorities can build on the variety of automatically generated information and develop intelligent services that improve citizens daily life, save environmental resources or aid in coping with emergencies. From a data mining perspective, urban data introduce a lot of challenges. Data volume, velocity and veracity are some obvious obstacles. However, there are even more issues of equal importance like data quality, resilience, privacy and security. In this paper we describe the development of a set of techniques and frameworks that aim at effective and efficient urban data management in real settings. To do this, we collaborated with the city of Dublin and worked on real problems and data. Our solutions were integrated in a system that was evaluated and is currently utilized by the city.

AB - Urban data management is already an essential element of modern cities. The authorities can build on the variety of automatically generated information and develop intelligent services that improve citizens daily life, save environmental resources or aid in coping with emergencies. From a data mining perspective, urban data introduce a lot of challenges. Data volume, velocity and veracity are some obvious obstacles. However, there are even more issues of equal importance like data quality, resilience, privacy and security. In this paper we describe the development of a set of techniques and frameworks that aim at effective and efficient urban data management in real settings. To do this, we collaborated with the city of Dublin and worked on real problems and data. Our solutions were integrated in a system that was evaluated and is currently utilized by the city.

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AN - SCOPUS:84988591347

SN - 9783319461304

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 177

EP - 192

BT - Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings

A2 - Bringmann, Björn

A2 - Fromont, Elisa

A2 - Tatti, Nikolaj

A2 - Tresp, Volker

A2 - Miettinen, Pauli

A2 - Berendt, Bettina

A2 - Garriga, Gemma

PB - Springer Verlag

T2 - 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016

Y2 - 19 September 2016 through 23 September 2016

ER -

Panagiotou N, Zygouras N, Katakis I, Gunopulos D, Zacheilas N, Boutsis I et al. Intelligent Urban data monitoring for smart cities. In Bringmann B, Fromont E, Tatti N, Tresp V, Miettinen P, Berendt B, Garriga G, editors, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings. Springer Verlag. 2016. p. 177-192. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46131-1_23

Intelligent Urban data monitoring for smart cities

Abstract

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UN SDGs

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