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Challenges for Federated Crowd Management in Smart Cities
Nicklas, Daniela; Ackermann, Leonie; Das, Debasree; u. a. (2026): Challenges for Federated Crowd Management in Smart Cities, in: Keiichi Yasumoto, Idit Keidar, Hirozumi Yamaguchi, u. a. (Hrsg.), ICDCN Companion ’26: Companion Proceedings of the 27th International Conference on Distributed Computing and Networking, New York: Association for Computing Machinery, S. 126–131, doi: 10.1145/3737611.3776621.
Faculty/Chair:
Author: ;  ;  ;  ;  ; 
Title of the compilation:
ICDCN Companion '26: Companion Proceedings of the 27th International Conference on Distributed Computing and Networking
Editors:
Conference:
27th International Conference on Distributed Computing and Networking, January 6 - 9, 2026 ; Nara
Publisher Information:
Year of publication:
2026
Pages:
ISBN:
979-8-4007-1969-1
Language:
English
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.
Keywords: ;  ; 
Smart City
Crowd Monitoring
Federated Learning
Peer Reviewed:
Yes:
International Distribution:
Yes:
Open Access Journal:
Yes:
Type:
Conferenceobject
Activation date:
January 7, 2026
Versioning
Question on publication
Permalink
https://fis.uni-bamberg.de/handle/uniba/112409