@inproceedings{83de3d3875a248a5b66e94cb5671d46b,
title = "Deep Air-A Smart City AI Synthetic Data Digital Twin Solving the Scalability Data Problems",
abstract = "Cities are becoming data-driven, re-engineering their processes to adapt to dynamically changing needs. A.I. brings new capabilities, effectively enlarging the space of policy interventions that can be explored and applied. Therefore, new tools are needed to augment our capacity to traverse this space and find adequate policy interventions. Digital twins are revealing themselves as powerful tools for policy experimentation and exploration, allowing faster and more complete explorations while avoiding costly interventions. However, they face some problems, among them data availability and model scalability. We introduce a digital twin framework based on an A.I. and a synthetic data model on NO2 pollution as a proof-of-concept, showing that this approach is feasible for policy evaluation and (autonomous) intervention and solves the problems of data scarcity and model scalability while enabling city level Open Innovation.",
keywords = "Digital Twins, Digital twins and synthetic data, Smart City Policy, Synthetic data",
author = "Esteve Almirall and Davide Callegaro and Peter Bruins and Mar Santamar{\'i}a and Pablo Mart{\'i}nez and Ulises Cort{\'e}s",
note = "Publisher Copyright: {\textcopyright} 2022 The authors and IOS Press.; 24th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2022 ; Conference date: 19-10-2022 Through 21-10-2022",
year = "2022",
month = oct,
day = "17",
doi = "10.3233/FAIA220319",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "83--86",
editor = "Atia Cortes and Francisco Grimaldo and Tommaso Flaminio",
booktitle = "Artificial Intelligence Research and Development - Proceedings of the 24th International Conference of the Catalan Association for Artificial Intelligence",
}
