Abstract

Smart cities frequently rely on vast sensor networks, such as traffic cameras and ventilation controllers. This requires that we rethink methods of spatial tessellation. As tessellation is becoming more dynamic, we often combine multiple tessellation methods and switch tessellation shapes frequently for different data collection and analytics. In this article, we review how tessellation works with the object and field geographic spatial models. To achieve the “smartness” within cities, this article introduces the dynamic tessellation approach as the initial solution. Key Words: big data, sensor network, smart city, spatial tessellation.

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