Collaborative services for Crowd Safety systems across the Edge-Cloud Computing Continuum
Abstract
Crowd or mass gatherings at various venues such as entertainment events or transportation systems are faced by individuals on a daily basis. Crowd management for largescale planned events is essential, and depends on behavioural and mathematical modelling to understand how crowds move in different scenarios. In this paper, we propose the creation of a set of collaborative and services, the CrowdMesh platform, to allow for processing, analysis, and sharing of crowd monitoring datasets constructed over the Edge-Cloud Continuum. Comprehensive tools and best practices are needed to ensure that analysis pipelines are robust, and that results can be replicated.
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