| Title |
Stakeholder analysis for designing an urban air quality data governance ecosystem in smart cities |
| ID_Doc |
42201 |
| Authors |
Kaginalkar, A; Kumar, S; Gargava, P; Niyogi, D |
| Title |
Stakeholder analysis for designing an urban air quality data governance ecosystem in smart cities |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.uclim.2022.101403 |
| Abstract |
Cities, the world over, are fuelling economic growth. At the same time, rapid urbanization is a root cause of serious environmental damage. Recent WHO global air pollution guidelines high -light air pollution as a critical environmental threat along with climate change. To address these threats, smart cities and clean air programs are on a rise. In smart cities, data and Information and Communication Technologies (ICT) are major drivers of city transformations. The 4th Industrial Revolution (4IR) technologies such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cloud computing have the potential to accelerate these transformations toward urban resilience. However, the success of smart cities and clean air programs depends on cohesive multi-sector stakeholder contributions. This study conducted interdisciplinary participative stakeholder analysis to understand the data, and sectorial challenges, to outline the technological opportu-nities to facilitate clean air programs in Indian smart cities. The research highlights gaps due to siloed stakeholder operations, lack of data calibration, non-alignment of smart city and air quality management services, non-availability of health exposure data, and difficulty in translating sci-entific data into implementable actions. Stakeholders expressed potential 'fit for the purpose' use of IoT devices, satellites, smartphones, and mobility data augmented by AI methods in bridging these gaps. The analysis points toward a need to develop an easily accessible and ubiquitous urban data governance ecosystem enabling seamless cross-sector data exchanges to build trusting relationships among the stakeholders across the air quality management value chain |
| Author Keywords |
Smart city; Stakeholder analysis; Pollution management; Big data; Artificial intelligence; Urban computing |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000961372800001 |
| WoS Category |
Environmental Sciences; Meteorology & Atmospheric Sciences |
| Research Area |
Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences |
| PDF |
http://manuscript.elsevier.com/S2212095522003212/pdf/S2212095522003212.pdf
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