Cost-Effectiveness Assessment of Internet of Things in Smart Cities
With the ongoing rapid urbanization of city regions and the growing need for (cost-)effective healthcare provision, governments need to address urban challenges with smart city interventions. In this context, impact assessment plays a key role in the decision-making process of assessing cost-effecti...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Oberta de Catalunya (UOC) |
| Repositorio: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/147663 |
| Acceso en línea: | http://hdl.handle.net/10609/147663 https://doi.org/10.3389/fdgth.2021.662874 |
| Access Level: | acceso abierto |
| Palabra clave: | IoT smart cities cost-effectiveness modeling evaluation ciutats intel·ligents rendibilitat modelatge avaluació ciudades inteligentes rentabilidad modelado evaluación |
| Sumario: | With the ongoing rapid urbanization of city regions and the growing need for (cost-)effective healthcare provision, governments need to address urban challenges with smart city interventions. In this context, impact assessment plays a key role in the decision-making process of assessing cost-effectiveness of Internet of Things–based health service applications in cities, as it identifies the interventions that can obtain the best results for citizens' health and well-being. We present a new methodology to evaluate smart city projects and interventions through the MAFEIP tool, a recent online tool for cost-effectiveness analysis that has been used extensively to test information and communications technology solutions for healthy aging. Resting on the principles of Markov models, the purpose of the MAFEIP tool is to estimate the outcomes of a large variety of social and technological innovations, by providing an early assessment of the likelihood of achieving anticipated impacts through interventions of choice. Thus, the analytical model suggested in this article provides smart city projects with an evidence-based assessment to improve their efficiency and effectivity, by comparing the costs and the efforts invested, with the corresponding results. |
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