
Digital Twin is a new concept that consists of creating an up-to-date virtual asset in cyberspace which mimics the original physical asset in most of its aspects, ultimately to monitor, analyze, test, and optimize the physical asset. In this article, we investigate and discuss the use of the digital twin concept of the roads as a step toward realizing the dream of smart cities. To this end, we propose the deployment of a Digital Twin Box to the roads that is composed of a 360° camera and a set of IoT devices connected to a Single Onboard Computer. The Digital Twin Box creates a digital twin of the physical road asset by constantly sending real-time data to the edge/cloud, including the 360° live stream, GPS location, and measurements of the temperature and humidity. This data will be used for realtime monitoring and other purposes by displaying the live stream via head-mounted devices or using a 360° web-based player. Additionally, we perform an object detection process to extract all possible objects from the captured stream. For some specific objects (person and vehicle), an identification module and a tracking module are employed to identify the corresponding objects and keep track of all video frames where these objects appeared. The outcome of the latter step would be of utmost importance to many other services and domains such as national security. To show the viability of the proposed solution, we have implemented and conducted real-world experiments where we focus more on the detection and recognition processes. The achieved results show the effectiveness of the proposed solution in creating a digital twin of the roads, a step forward to enable self-driving vehicles as a crucial component of smart mobility, using the Digital Twin Box.
Monitoring, ta213, Object detection, Digital twin, Roads, Temperature distribution, Streaming media, Cloud computing, Temperature sensors, Real-time systems, Smart cities
Monitoring, ta213, Object detection, Digital twin, Roads, Temperature distribution, Streaming media, Cloud computing, Temperature sensors, Real-time systems, Smart cities
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