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Smart city article details

Title Using The Experience Sampling Method To Find The Pattern Of Individual Quality Of Life Perceptions
ID_Doc 60650
Authors Sasao T.; Tai M.; Suzuki K.; Warisawa S.; Deguchi A.
Year 2023
Published Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14036 LNCS
DOI http://dx.doi.org/10.1007/978-3-031-34668-2_17
Abstract In recent years, with the spread of smart cities, which comprehensively tackle the social experimentation and implementation of new technologies, countries worldwide are emphasizing the importance of development focusing on the well-being and quality of life (QoL) of citizens. One issue is that provider-driven projects in smart cities often need to push development forward in the minimum amount of time. If a project is carried out without fully determining whether the community and its citizens really need them, and if dialog with citizens is neglected, it is unlikely that useful services would be created. Therefore, to make human-centered improvements, we need a method to grasp whether the experiences of existing urban service and urban space help increase people’s QoL as well as the characteristics of people whose QoL increases versus those whose QoL does not. Therefore, this research aims to develop a tool named ActiveQoL-ESM for measuring the satisfaction of each daily activity based on the experience sampling method (ESM), a classical method for continuously collecting personal subjective data that significantly change dynamically during daily life. Moreover, we propose a method for evaluating urban service and spatial experiences and for analyzing how to improve these experiences from the data gathered through the ESM. Through an experiment using ActiveQoL-ESM, we find suitable evaluation methods for capturing individual QoL perceptions. We show it is possible that the methods could help clarify the meaning of the word “citizens,” not only from the attribute and personality data collected from the preliminary questionnaire but also from the contextual data gathered from Fitbit and smartphones. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Author Keywords citizen sensing; daily life; experience sampling method; human behavior; lifestyle; quality of life; smart city measures; urban evaluation


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