| Title |
Designing a smart city sustainability assessment information system based on the adapted SULPiTER methodology |
| ID_Doc |
38476 |
| Authors |
Zhameshova, A; Sadykova, G; Alimzhanov, Y; Gorodnichev, M; Mansurova, A; Nugumanova, A; Perepelkin, V; Lebedev, D |
| Title |
Designing a smart city sustainability assessment information system based on the adapted SULPiTER methodology |
| Year |
2024 |
| Published |
Journal Of Infrastructure Policy And Development, 8, 4 |
| DOI |
10.24294/jipd.v8i4.3106 |
| Abstract |
Increasing number of smart cities, the rise of technology and urban population engagement in urban management, and the scarcity of open data for evaluating sustainable urban development determines the necessity of developing new sustainability assessment approaches. This study uses passive crowdsourcing together with the adapted SULPiTER (Sustainable Urban Logistics Planning to Enhance Regional freight transport) methodology to assess the sustainable development of smart cities. The proposed methodology considers economic, environmental, social, transport, communication factors and residents' satisfaction with the urban environment. The SULPiTER relies on experts in selection of relevant factors and determining their contribution to the value of a sustainability indicator. We propose an alternative approach based on automated data gathering and processing. To implement it, we build an information service around a formal knowledge base that accumulates alternative workflows for estimation of indicators and allows for automatic comparison of alternatives and aggregation of their results. A system architecture was proposed and implemented with the Astana Opinion Mining service as its part that can be adjusted to collect opinions in various impact areas. The findings hold value for early identification of problems, and increasing planning and policies efficiency in sustainable urban development. |
| Author Keywords |
smart city; sustainable development; SULPiTER; passive crowdsourcing; opinion mining; intelligent system |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:001209446700020 |
| WoS Category |
Management |
| Research Area |
Business & Economics |
| PDF |
https://systems.enpress-publisher.com/index.php/jipd/article/download/3106/2546
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