TY - CHAP
T1 - QROWD—A Platform for Integrating Citizens in Smart City Data Analytics
AU - Ibáñez, Luis Daniel
AU - Maddalena, Eddy
AU - Gomer, Richard
AU - Simperl, Elena
AU - Zeni, Mattia
AU - Bignotti, Enrico
AU - Chenu-Abente, Ronald
AU - Giunchiglia, Fausto
AU - Westphal, Patrick
AU - Stadler, Claus
AU - Dziwis, Gordian
AU - Lehmann, Jens
AU - Yumusak, Semih
AU - Voigt, Martin
AU - Sanguino, Maria Angeles
AU - Villazán, Javier
AU - Ruiz, Ricardo
AU - Pariente-Lobo, Tomas
N1 - Funding Information:
Acknowledgements Research on this paper was supported by the QROWD project, part of the Horizon 2020 programme under grant agreement 732194. We also acknowledge the Smart City managers of the Municipality of Trento.
Funding Information:
Research on this paper was supported by the QROWD project, part of the Horizon 2020 programme under grant agreement 732194. We also acknowledge the Smart City managers of the Municipality of Trento.
Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/11/3
Y1 - 2023/11/3
N2 - Optimizing mobility services is one of the greatest challenges Smart Cities face in their efforts to improve residents’ wellbeing and reduce emissions. The advent of IoT has created unparalleled opportunities to collect large amounts of data about how people use transportation. This data could be used to ascertain the quality and reach of the services offered and to inform future policy—provided cities have the capabilities to process, curate, integrate and analyse the data effectively. At the same time, to be truly ‘Smart’, cities need to ensure that the data-driven decisions they make reflect the needs of their citizens, create feedback loops, and widen participation. In this chapter, we introduce QROWD, a data integration and analytics platform that seamlessly integrates multiple data sources alongside human, social and computational intelligence to build hybrid, automated data-centric workflows. By doing so, QROWD applications can take advantage of the best of both worlds: the accuracy and scale of machine computation, and the skills, knowledge and expertise of people. We present the architecture and main components of the platform, as well as its usage to realise two mobility use cases: estimating the modal split, which refers to trips people take that involve more than one type of transport, and urban auditing.
AB - Optimizing mobility services is one of the greatest challenges Smart Cities face in their efforts to improve residents’ wellbeing and reduce emissions. The advent of IoT has created unparalleled opportunities to collect large amounts of data about how people use transportation. This data could be used to ascertain the quality and reach of the services offered and to inform future policy—provided cities have the capabilities to process, curate, integrate and analyse the data effectively. At the same time, to be truly ‘Smart’, cities need to ensure that the data-driven decisions they make reflect the needs of their citizens, create feedback loops, and widen participation. In this chapter, we introduce QROWD, a data integration and analytics platform that seamlessly integrates multiple data sources alongside human, social and computational intelligence to build hybrid, automated data-centric workflows. By doing so, QROWD applications can take advantage of the best of both worlds: the accuracy and scale of machine computation, and the skills, knowledge and expertise of people. We present the architecture and main components of the platform, as well as its usage to realise two mobility use cases: estimating the modal split, which refers to trips people take that involve more than one type of transport, and urban auditing.
UR - http://www.scopus.com/inward/record.url?scp=85141858698&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-08815-5_16
DO - 10.1007/978-3-031-08815-5_16
M3 - Chapter
AN - SCOPUS:85141858698
T3 - Studies in Computational Intelligence
SP - 285
EP - 321
BT - Studies in Computational Intelligence
PB - Springer Science and Business Media Deutschland GmbH
ER -