International Conference · 2026

Challenges for Federated Crowd Management in Smart Cities

Daniela Nicklas , Leonie Ackermann , Debasree Das , Tatsuya Amano , Hamada Rizk , Hirozumi Yamaguchi

ICDCN 2026 Workshop: IWNDSC2026

Published Version (DOI)

DOI: 10.1145/3737611.3776621

Abstract

This paper addresses the issue of crowd management in smart cities, where effectively handling large groups is essential for ensuring safety and a positive experience for all. Although smart cities strive to use data for better decision-making, simply measuring crowds is not enough; cities must analyze and utilize this data intelligently. In this paper, we leverage the various experiences of two research groups in this area and present a vision that allows cities to easily establish crowd management platforms by transferring knowledge and insights from similar use cases in other cities.

Research Note

都市で大人数の群衆をうまくさばけるかどうかは、安全の確保にも来場者の体験にも直結します。スマートシティの取り組みではデータを意思決定に活かすことが掲げられていますが、群衆を測っただけでは足りず、そのデータをどう解析してどう使うかまで踏み込む必要があります。

この論文は、群衆マネジメントに取り組んできた二つの研究グループの経験を持ち寄り、都市が群衆マネジメントの基盤を立ち上げやすくするための構想を示したものです。中心にある考え方は、ある都市で似た事例からすでに得られている知見やモデルを、別の都市へ移して使えるようにするというもので、都市ごとにゼロから作り直す必要をなくすことを狙っています。

ここでいう連合的（federated）というのは、各都市が自分のデータを手元に置いたまま、学習の成果や知見の側を共有するという考え方で、データの持ち出しに制約がある行政のデータを扱ううえで現実的な形になります。技術的な課題と組織的な課題の双方を整理し、今後取り組むべき論点を提示しています。

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