Smart City Gnosys

Smart city article details

Title	Measuring Quality Of Walkable Urban Environment Through Experiential Modeling
ID_Doc	36583
Authors	Yamagata Y.; Yoshida T.; Yang P.P.J.; Chen H.; Murakami D.; Ilmola L.
Year	2020
Published	Urban Systems Design: Creating Sustainable Smart Cities in the Internet of Things Era
DOI	http://dx.doi.org/10.1016/B978-0-12-816055-8.00012-9
Abstract	Smart city design should have one ultimate goal; to improve the human well-being (or quality of life) of its inhabitants. National level planning of economy and societal structures has recently paid more attention to the well-being of citizens. In order to design for well-being and smart communities, it is important to not only understand the dimensions of well-being but also to develop easy to apply measurement methods for city planners. As the first step for creating well-being in smart communities, this study presents two concrete cases where we have measured well-being. These early attempts provide us with only narrow visibility of multidimensional well-being but prove to us that mart well-being measurement systems are possible—and useful—to build. A street imagery tool and an image assessment with a machine learning technique was used for evaluating streetscapes and perceptions of heat wave tweets in Kyojima district and in Tokyo, Japan. Finally, based on our experiences in these two cases, we summarize a measurement framework for a comprehensive multidata well-being assessment system. © 2020 Elsevier Inc. All rights reserved.
Author Keywords	Experiential modeling; Heat risk; Neural image assessment; Street images; Walkability; Well-being measurement

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