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.
UR - http://www.scopus.com/inward/record.url?scp=84988591347&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-46131-1_23
DO - 10.1007/978-3-319-46131-1_23
M3 - Conference contribution
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 -