| 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 | |
| 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 |
| http://manuscript.elsevier.com/S2212095522003212/pdf/S2212095522003212.pdf |
Similar Articles
| ID | Score | Article |
|---|---|---|
39788
|
Kaginalkar, A; Kumar, S; Gargava, P; Niyogi, D Review of urban computing in air quality management as smart city service: An integrated IoT, AI, and cloud technology perspective(2021) | |
| 43462
|
Myeong, S; Shahzad, K Integrating Data-Based Strategies and Advanced Technologies with Efficient Air Pollution Management in Smart Cities(2021)Sustainability, 13, 13 | |
| 31554
|
Hui, CX; Dan, G; Alamri, S; Toghraie, D Greening smart cities: An investigation of the integration of urban natural resources and smart city technologies for promoting environmental sustainability(2023) | |
| 43212
|
Bui, L Breathing Smarter: A Critical Look at Representations of Air Quality Sensing Data Across Platforms and Publics(2015) | |
| 40961
|
Gerasopoulos, E; Bailey, J; Athanasopoulou, E; Speyer, O; Kocman, D; Raudner, A; Tsouni, A; Kontoes, H; Johansson, C; Georgiadis, C; Matthias, V; Kussul, N; Aquilino, M; Paasonen, P Earth observation: An integral part of a smart and sustainable city(2022) | |
| 79108
|
Allam, Z; Sharifi, A; Bibri, SE; Chabaud, D Emerging Trends and Knowledge Structures of Smart Urban Governance(2022)Sustainability, 14, 9 | |
| 79207
|
D'Amico, G; L'Abbate, P; Liao, WJ; Yigitcanlar, T; Ioppolo, G Understanding Sensor Cities: Insights from Technology Giant Company Driven Smart Urbanism Practices(2020)Sensors, 20, 16 | |
| 44349
|
Gracias, JS; Parnell, GS; Specking, E; Pohl, EA; Buchanan, R Smart Cities-A Structured Literature Review(2023)Smart Cities, 6, 4 | |
| 39622
|
Okonta, DE; Vukovic, V Smart cities software applications for sustainability and resilience(2024)Heliyon, 10, 12 | |
| 43710
|
Zheng, L; Kwok, WM; Aquaro, V; Qi, XY Digital Government, Smart Cities and Sustainable Development(2019) |