Reproducible evaluation on our sequential states for social improvement
We define the purpose of this area to be individual freedom from constraints, allowing the individual to satisfy their own physical and mental needs while at the same time fulfilling the needs of others.
Most of the prior measuring methods of individual conditions systematized by subjective well-being in Japan and abroad are based on questionnaire-based evaluation methods. It has been proven to be useful and reliable for policymaking and other purposes. However, it is difficult to grasp the changes in the state of well-being due to external and internal factors in detail, and there is a bottleneck of ambiguity due to the lack of a quantitative method based on simple measurements. Therefore, it has not yet reached various industrial applications. On the other hand, many recent technologies in engineering, information science, biology, and other fields have developed measuring methods for the state of individuals and their surrounding environment with high temporal resolution and sensitivity from sensing data.
In this prioritized theme, research methods and knowledge from the humanities and social sciences, as well as analytical technologies such as sensing, machine learning, and artificial intelligence (AI), will be layered to develop technologies to measure the various well-being factors that affect individuals and to visualize their sequential changing states. In the future, these technologies will be applied to the real world, and efforts will be made to realize the evaluation and visualization of the dynamic well-being of individuals.
|<Adopted in FY2021> R&D Project Title
|Personal optimization of community-contributing activities driven by new-value IKIGAI
|Co-creation of individual and collective well-being: Measuring the states of spaces and communities to support individuals' optimization
|Development of technology to support children's well-being using information on physical functions and home networks
|Happiness evaluation by visual index using multimodal AI
|AIoT-based visualization of Ecological Well-being for future Health Management
|Personalized learning supported by brain features
Affiliation and job title should automatically appear from the information that a researcher registered with researchmap.
Data may be outdated or undocumented.
When there is not a connection via the internet, data are not displayed.