| Title |
Data-Driven Solutions in Smart Cities: The case of Covid-19 |
| ID_Doc |
44196 |
| Authors |
Petrovic, NN; Dimovski, V; Peterlin, J; Mesko, M; Roblek, V |
| Title |
Data-Driven Solutions in Smart Cities: The case of Covid-19 |
| Year |
2021 |
| Published |
|
| DOI |
10.1145/3442442.3453469 |
| Abstract |
This paper aims to give a systemic vision about the data-driven mobile applications in urban data management processes, which is essential to ensure a sustainable smart city ecosystem for what is needed to ensure diversification between stakeholders and data sources. The realization of sustainable data-driven smart solutions based on an urban data platform that will enable citizen wellbeing in the smart city is needed to develop data-driven applications. In this paper, we present five case study mobile applications developed using AppSheet and Google Apps Script technologies to prevent the spread of COVID-19 and provide support to (potentially) infected citizens. Several aspects relevant to coronavirus pandemic are considered: quick COVID-19 patient assessment based on user-provided symptoms integrated with contact tracing; volunteer help during quarantine; UAV-based COVID-19 outdoor safety surveillance; test scheduling and AR-based pharmacy shop assistant. |
| Author Keywords |
Smart cities; Covid-19; systems thinking; mobile applications; knowledge management; augmented reality |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000749534900110 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Interdisciplinary Applications; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
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