| Title |
SMART: A process-oriented methodology for resilient smart cities |
| ID_Doc |
39459 |
| Authors |
Mourshed, M; Bucchiarone, A; Khandokar, F |
| Title |
SMART: A process-oriented methodology for resilient smart cities |
| Year |
2016 |
| Published |
|
| DOI |
|
| Abstract |
Cities are engines of economic prosperity and social development. Rapid urbanization and the impacts of climate change have resulted in increased vulnerabilities in cities. On the other hand, the increasing proliferation of connected devices and distributed monitoring of the environment around us has opened up an opportunity to transform the way we create and manage cities. Contextual evidence of performance, outcome and efficiency can now be readily collected at a higher resolution to aid multi-disciplinary and multi-objective decision-making, enabling optimal evolution of cities against the backdrop of constrained resources and intensified vulnerabilities. This paper first argues that distributed and ubiquitous monitoring is at the heart of smart cities. Insights can be inferred from the gathered data with potential for evidence-based decisions at the required spatial and temporal scales. The paper then discusses the development of a comprehensive but concise frameworks called DICES (data, insights, citizen, evidence and standards) for conceptualizing smart cities. The dimensions of DICES are then translated into a process oriented methodology called SMART (specify, monitor, analyze, resolve and transform) by formalizing key aspects of the smart city process. Generality and scalability of DICES and SMART are demonstrated through the development of REPRO, a risk-and evidence-based platform for resilient and optimal design of buildings and infrastructure in a smart city. |
| Author Keywords |
Smart city; resilience; smart city methodology; data-centric approach; SMART; DICES; Adaptable Services |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000392263700141 |
| WoS Category |
Engineering, Electrical & Electronic |
| Research Area |
Engineering |
| PDF |
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