Generating a Map of Well-being Regions Using Multi-scale Moving Direction Entropy on Mobile Sensors

Authors

  • Yukio Ohsawa School of Engineering, The University of Tokyo, Tokyo 113-8656 Japan
  • Sae Kondo School of Engineering, Mie University, 1577 Kurimamachiya-Cho, Tsu, Mie 514-8507 Japan Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan
  • Yi Sun School of Engineering, The University of Tokyo, Tokyo 113-8656 Japan
  • Kaira Sekiguchi School of Engineering, The University of Tokyo, Tokyo 113-8656 Japan

DOI:

https://doi.org/10.1609/aaaiss.v3i1.31242

Keywords:

Impact of GenAI on Social and Individual Well-being

Abstract

The well-being of individuals in a crowd is interpreted as a product of individuals crossing over from heterogeneous communities, via interactions with other crowds. Here, the index moving-direction entropy corresponding to the diversity of the moving directions of individuals is introduced to represent such an inter-community crossover and extended with multiscale scopes. Multiscale moving direction entropies, composed of various geographical mesh sizes to compute the index values, are used to capture the flow and interaction of information owing to human movements from/to various crowds. The generated map of high values of multiscale moving direction entropy was visualized, where the peaks coincided significantly with the preference of people to live in each region.

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Published

2024-05-20

Issue

Section

Impact of GenAI on Social and Individual Well-being