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An Edge-Fog-Cloud Architecture of Streaming Analytics for Internet of Things Applications
1People in Motion Lab, University of New Brunswick, Fredericton, NB E3B 5A3, Canada. hcao3@unb.ca.
Abstract:
Exploring Internet of Things (IoT) data streams generated by smart cities means not only transforming data into better business decisions in a timely way but also generating long-term location intelligence for developing new forms of urban governance and organization policies. This paper proposes a new architecture based on the edge-fog-cloud continuum to analyze IoT data streams for delivering data-driven insights in a smart parking scenario.
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