Nicklas, DanielaDanielaNicklas0000-0001-7012-6010Ackermann, LeonieLeonieAckermann0000-0002-3490-5452Das, DebasreeDebasreeDas0000-0003-0172-0280Amano, TatsuyaTatsuyaAmanoRizk, HamadaHamadaRizkYamaguchi, HirozumiHirozumiYamaguchi2026-01-072026-01-072026979-8-4007-1969-1https://fis.uni-bamberg.de/handle/uniba/112409This 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.engSmart CityCrowd MonitoringFederated Learningconferenceobject10.1145/3737611.3776621