Development of Real-Time Smart City Mapping Utilizing Game Engines

Abstract

Game engines are ideal platforms to generate and visualize digital twins of smart cities in real time. The real-time mapping of a smart city faces two challenges: (1) streaming data from Internet of Things (IoT) devices, (2) rendering a high-throughput and heterogeneous digital twin. Current game engine infrastructure is not built to handle the influx of real time data streams from a diverse array of IoT devices, nor can they render a real-time dynamic mesh streamed from a scanning device such as a LIDAR. As meshes are the basic framework needed to render digital twin objects that represent their real word counterparts and real time IoT streams are necessary for modeling an accurate digital twin, both of these issues must be resolved in order to use game engines to create a digital twin of a smart city. In this paper, we propose a networking infrastructure capable of handling a wide variety of IoT devices and a novel mesh rendering algorithm. Additionally, we provide a quantitative error analysis. Experimental results show that the proposed streaming method and rendering algorithm could enable a game engine to efficiently generate a digital twin of a smart city.